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OpenStack

OpenStack is an open-source platform that provides a modular set of software components for building and managing infrastructure, including compute, , and networking resources, typically deployed as infrastructure-as-a-service (IaaS) in public, private, or hybrid environments. It enables the orchestration of large-scale data centers through application programming (APIs), command-line interfaces, and web-based dashboards, supporting virtual machines, bare-metal servers, and workloads. As one of the world's most active open-source projects, OpenStack emphasizes , , and community-driven development to deliver and fault management across diverse setups. Launched in July 2010 as a collaborative effort between Rackspace Hosting and , OpenStack combined Rackspace's Cloud Files storage technology with NASA's compute platform to create an open alternative to proprietary cloud systems. The project quickly gained momentum, leading to the formation of the OpenStack Foundation in 2012, which was renamed the Open Infrastructure Foundation in 2021 and joined the in 2025, to oversee its , trademark, and donations from over 1,000 member organizations. This nonprofit structure ensures vendor-neutral development, with biannual releases—such as the latest 2025.2 "Flamingo" version—introducing enhancements in areas like , , and with emerging technologies. At its core, OpenStack comprises interrelated projects that handle key cloud functions, including for compute provisioning and management of virtual machines or bare-metal instances, for networking services like virtual networks and load balancing, for block storage volumes, for object storage scalability, for identity and authentication, Glance for image management, and Horizon for the web-based dashboard. These components are designed to be composable, allowing operators to deploy customized stacks for specific needs, from to . With adoption spanning industries like , , and , OpenStack clouds manage over 40 million CPU cores globally as of 2025, supporting mission-critical workloads for organizations such as and .

Introduction

Definition and Purpose

OpenStack is a platform designed for building and managing public, private, and hybrid cloud environments, primarily providing (IaaS) capabilities. It functions as a cloud operating system that orchestrates large pools of compute, storage, and networking resources across data centers, enabling automated provisioning and management through application programming interfaces (). As an IaaS solution, OpenStack allows users to deploy virtual machines, containers, or bare-metal servers on demand, supporting scalable infrastructure for diverse workloads without reliance on proprietary hardware or software. The primary purpose of OpenStack is to empower organizations with greater over their infrastructure, facilitating the efficient allocation of resources to meet varying computational needs. It supports technologies for running multiple virtual instances on shared , for lightweight application deployment via orchestrators like , and bare-metal provisioning for high-performance, direct access. By abstracting underlying complexities, OpenStack enables rapid scaling from small deployments to enterprise-level operations, promoting cost-effective adoption across industries such as , , and . At its core, OpenStack embodies principles of modularity, interoperability, and community-driven development, allowing users to integrate or extend components as needed while ensuring compatibility with standard cloud APIs. The platform is licensed under the Apache License 2.0, which encourages broad collaboration and reuse without restrictive terms. This open governance model fosters innovation through contributions from a global developer community, aligning with its mission to create a ubiquitous, easy-to-use cloud computing platform that operates at any scale. OpenStack was initiated in 2010 as a joint project between Rackspace Hosting and NASA to address the need for flexible, open cloud infrastructure.

Key Features and Architecture Overview

OpenStack employs a modular composed of independent services that collaborate to deliver (IaaS) capabilities. Each service handles a specific function, such as , compute, networking, or , and they communicate primarily through RESTful APIs for external interactions, while internal coordination occurs via a shared message queue like (an AMQP broker) and a persistent database such as or to maintain state and facilitate asynchronous processing. This design enables , allowing operators to deploy, scale, or upgrade individual services without affecting the entire system. Key features of OpenStack include its emphasis on through horizontal scaling, where additional nodes can be added to handle increased workloads without ; multi-tenancy support via projects (tenant isolation boundaries) and to securely segregate resources among users or organizations; and with multiple hypervisors, including KVM, XenServer, and , to accommodate diverse hardware environments. Additionally, the platform's are highly extensible, permitting developers to integrate plugins or extensions to tailor functionality for specific use cases. In a typical high-level workflow, users first authenticate against the Keystone identity service to obtain tokens, then request compute instances via , networking configurations through , and persistent storage with , all orchestrated through calls. Management and monitoring are facilitated by the Horizon dashboard, providing a web-based interface for administrative tasks. The open-source nature of OpenStack drives significant benefits, including cost savings by eliminating licensing fees and leveraging community-driven development, vendor neutrality to avoid lock-in through standardized supported by over 1,100 contributors, and extensive customization options for deploying private or hybrid clouds tailored to enterprise needs.

History

Founding and Early Years

OpenStack was founded in 2010 through a collaboration between Rackspace Hosting and , with the project officially announced on July 21 at the Open Source Convention (OSCON) in . The initiative combined 's compute-focused Nebula platform, developed since 2008 to enable scalable internal for hosting high-resolution scientific data independently of proprietary vendors, with Rackspace's Cloud Files system. This merger aimed to create a unified, open-source infrastructure-as-a-service (IaaS) platform as an alternative to proprietary clouds like , addressing the need for vendor-neutral, scalable solutions that could support both public and private cloud deployments. The early motivations were driven by 's desire for cost-effective, flexible computing resources inspired by large-scale infrastructures like Google's, and Rackspace's goal to open-source its cloud backend for broader innovation and to avoid ecosystem lock-in. The project's initial development culminated in the Austin release on October 21, 2010, which served as a proof-of-concept integrating the core compute service—derived from —for managing s and the object storage service from Rackspace. This early version focused on basic orchestration of compute and storage resources but lacked full stability and additional features. Building on this foundation, the Bexar release arrived on February 3, 2011, introducing the first integrated set of core components including , , and the new Glance image service for registering and retrieving images, thereby enhancing support for enterprise-scale deployments and improving overall usability. These releases established OpenStack's modular architecture, emphasizing interoperability and extensibility under the Apache 2.0 license. Key early contributors included engineers from NASA's team, working through contractors like Anso Labs, and Rackspace developers who drove the initial code contributions. As momentum built, companies such as , , , and others joined as supporters around the Bexar release, providing networking expertise, hardware integrations, and community resources to accelerate development. By 2012, to promote sustainable, independent growth amid rising participation from over 150 organizations, OpenStack transitioned governance to the OpenStack Foundation, a non-profit entity formally established in September 2012 with initial funding of $10 million to oversee project direction, trademarks, and events.

Release History

OpenStack follows a biannual release cycle, with new versions typically launching in April and October each year, a pattern established since the project's early days in 2010. This six-month cadence allows for iterative development, stable point releases within each series, and support for skip-level upgrades in recent "SLURP" releases. Initially, releases were named using alphabetical codenames inspired by locations in and later broader North American places, starting with Austin in 2010 and progressing through names like Diablo in 2011 and in 2013. In 2023, the naming convention shifted to a year-based format combined with thematic codenames, such as 2023.1 , to avoid cycling back through the alphabet while maintaining memorable identifiers. Early releases laid the foundation for core services. The Diablo release in September 2011 marked the first integration of Keystone, the identity service, enabling unified authentication across components and requiring additional configuration for services like Glance. By the Grizzly release in April 2013, OpenStack had expanded to include enhanced networking and orchestration capabilities, setting the stage for broader ecosystem growth. The project's structure evolved significantly in 2014 with the adoption of the "Big Tent" governance model during the Kilo release cycle, which decentralized development by allowing diverse teams to contribute under a unified umbrella rather than a strict set of integrated projects. In recent years, releases have emphasized performance, integration, and emerging workloads. The 2024.1 Caracal release in April 2024 introduced improvements like centralized database caching by default and deprecation of legacy drivers such as , enhancing scalability for large deployments. The 2025.1 release in April 2025 focused on security enhancements, including improvements in Ironic such as validation for requests and support for bootc deploy . The latest release as of November 2025, 2025.2 Flamingo from October 2025, addresses by dropping support for outdated Python versions like 3.9 and adds features for , such as libvirt driver support for launching instances with memory encryption to protect guest . OpenStack versions enter phased support after their initial release: a "Maintained" period of approximately 18 months, followed by an "Unmaintained" phase where critical bug fixes may continue if community interest and support persist, until End of Life. SLURP releases receive extended support to facilitate skip-level upgrades. For example, the 2025.1 series is projected to reach Unmaintained status in October 2026. Over time, the OpenStack ecosystem has grown substantially, evolving from approximately 13 core integrated projects around 2014 to over 50 official projects under the model by 2025, encompassing areas like and . This expansion includes influences such as the integration of Ceilometer's capabilities with Monasca for advanced , through projects like Ceilosca, which facilitate data publishing and migration to more scalable solutions. The focus remains on stability, with ongoing deprecations to reduce complexity while prioritizing high-impact features.

Notable Deployments

OpenStack's inaugural deployments emerged shortly after its inception in , with NASA's platform serving as an internal environment for the agency's research needs, leveraging early code that formed the basis of the compute service. This setup demonstrated OpenStack's potential for scalable, on-demand resources within a context. In parallel, Rackspace integrated OpenStack components into its infrastructure, launching production public cloud services powered by the platform in 2012, which enabled customers to access and compute capabilities without proprietary lock-in. Large-scale implementations have since highlighted OpenStack's robustness in enterprise environments. Walmart Labs deployed OpenStack for its private cloud in support of e-commerce operations, scaling beyond one million CPU cores by 2025 to handle massive data processing and application workloads with improved reliability and security. Similarly, AT&T adopted OpenStack starting in 2014 to underpin network function virtualization (NFV) in telecommunications, expanding from initial sites to over 20 data centers by 2016, facilitating agile service delivery and integration with 5G infrastructure. In the financial sector, institutions like American Express and Wells Fargo have leveraged OpenStack for secure, compliant cloud infrastructures, enabling rapid scaling for transaction processing and data analytics. Recent deployments underscore ongoing evolution and global adoption. operates one of the largest public OpenStack-based clouds, providing scalable compute, storage, and networking to millions of users worldwide, with continuous updates aligning to recent releases for enhanced performance and security. CERN's research cloud, initiated around 2013, has grown to over 300,000 cores across multi-region cells, supporting petabyte-scale data storage for experiments and . As of 2025, global OpenStack deployments exceed 55 million production cores, with many handling petabytes of object and block storage across thousands of nodes, often requiring custom integrations for in multi-tenant setups. These examples illustrate how operators overcome challenges like networking complexity and upgrade compatibility through tailored configurations, ensuring resilient operations at massive scales.

Development and Governance

Development Process

OpenStack's development follows a structured, time-based release cycle consisting of six-month periods, during which projects coordinate milestones leading to synchronized releases of core components. This approach ensures predictable timelines, with planning initiated at the Project Teams Gathering (PTG), a biannual event held at the start of each cycle to facilitate cross-team discussions on priorities, blueprints, and cross-project dependencies. Code changes are managed through Gerrit, a web-based code review system that enforces peer review before merging patches into repositories. Continuous integration and delivery are handled by Zuul, which gates changes based on automated testing pipelines, while Launchpad serves as the primary bug tracking system. The contribution model emphasizes inclusivity under the "" structure adopted in December 2014, which allows a wide array of projects to join the OpenStack as long as they align with goals, fostering diversity in functionality from infrastructure to specialized extensions. An upstream-first policy guides integrations, prioritizing contributions to OpenStack's mainline repositories over downstream forks to ensure broad compatibility and rapid propagation of improvements across deployments. This model encourages external developers and vendors to submit patches directly, with oversight ensuring alignment, though detailed decision-making bodies are covered elsewhere. Development relies on the OpenDev infrastructure for hosting repositories, enabling collaborative across projects. Testing environments are provisioned using DevStack, a set of scripts for rapid deployment of development clouds, often automated with playbooks for reproducible setups. The codebase is primarily written in , leveraging its ecosystem for rapid prototyping and integration. Quality assurance is integral, with every project required to maintain unit and integration tests run via Zuul's CI pipelines to validate functionality before merging. API compatibility is verified using , an integration testing suite that simulates end-to-end scenarios across services. Features targeted for removal must first be deprecated, with a policy mandating at least one full release cycle (six months) of warnings and migration guidance before obsolescence, extendable to multiple cycles for significant elements to minimize disruption. In 2025, development practices have increasingly emphasized , exemplified by the Flamingo release (2025.2), which focused on reducing through refactoring and performance optimizations to promote long-term . Community discussions at events like the Gerrit User Summit have explored AI-assisted code reviews to enhance efficiency, aligning with broader open-source trends for tool integration in workflows.

Governance Model

OpenStack is governed by the Open Infrastructure Foundation, a non-profit organization that rebranded from the OpenStack Foundation in 2021 to reflect its broader support for open infrastructure projects while maintaining OpenStack as its flagship initiative. In March 2025, the Open Infrastructure Foundation joined the as a member foundation to amplify , providing access to additional resources and a global community of over 110,000 individuals across 187 countries. The foundation ensures the project's legal protection, financial sustainability, and operational infrastructure, allowing the community to focus on technical development. This structure evolved from the project's origins as a collaboration between Rackspace and in 2010, expanding to involve thousands of contributors from over 500 organizations by 2025, emphasizing collaborative and inclusive decision-making. The governance model features two primary bodies: the Board of Directors and the Technical Committee (TC). The Board of Directors handles strategic oversight, budget allocation, and foundation operations, comprising appointed representatives from platinum sponsors (such as Ericsson, Huawei, and Rackspace), elected gold sponsor delegates (including Canonical and Red Hat), and individually elected directors to ensure diverse representation. Platinum and gold sponsorships provide core funding through annual commitments, enabling the foundation to support community events and development efforts. The Board also enforces anti-trust compliance across all activities to maintain fair competition and open collaboration. The manages , including defining the project scope, overseeing the lifecycle of OpenStack components (from inception to graduation or archiving), and refining the overall model to prioritize needs and merit. Elected annually by active contributors, the TC delegates day-to-day management to individual project teams, each led by a Project Team Lead (PTL) responsible for releases, roadmaps, and contributions within their domain. This delegated approach fosters autonomy while ensuring alignment with OpenStack's guiding principles of and . Since 2020, the former User Committee has been integrated into the TC to better incorporate operator and end- feedback, enhancing user-centric priorities through mechanisms like annual user surveys that guide feature development and . Additional structures support global engagement and inclusivity, including the Ambassador Program, which recruits community leaders to promote OpenStack adoption, mentor local user groups, and facilitate outreach in underrepresented regions. The foundation promotes inclusivity via policies such as inclusive language guidelines, aiming to create a welcoming environment for diverse contributors and address barriers to participation. Funding sustains these efforts through sponsorship tiers, donations, and revenue from events like the OpenInfra Summit.

Community Involvement

The OpenStack community comprises thousands of individual contributors and organizations collaborating globally to advance . Participants hail from diverse backgrounds and regions, with ambassadors representing countries including the , , , , , and , among others. Special Interest Groups (SIGs) enhance this diversity by addressing region-specific needs, such as the APAC SIG for collaboration and the Telco SIG for applications. Community members engage through various channels, including IRC discussions on networks like OFTC in channels such as #openstack and #openstack-dev, mailing lists like openstack-discuss for asynchronous communication, and online forums for broader queries. Key events foster in-person and virtual participation, including the Project Team Gathering (PTG) for cross-project planning and Open Infrastructure Summits for knowledge sharing and networking. programs, coordinated via the OpenStack mentoring team, pair newcomers with experienced contributors to guide initial involvement in code reviews and project tasks. Contributions span bug fixes, documentation improvements, and development of plugins or extensions, enabling participants to address real-world needs in cloud operations. Top contributors receive recognition through the OpenStack Hall of Fame, which highlights individuals based on commit volume and impact. In 2025, diversity initiatives emphasized outreach to underrepresented groups, including women and minorities in tech, through targeted workshops and inclusive event policies. The community's efforts have driven significant innovations, such as the 2018 spin-off of StarlingX, an platform built on OpenStack components for distributed environments. Translation initiatives, led by the (I18n) team, support non-English documentation in languages like , , and , broadening accessibility worldwide. The OpenStack codebase surpasses 50 million lines of code, reflecting the scale of collaborative development. The 2025 OpenStack User Survey reported high engagement.

Components

Compute Service (Nova)

The OpenStack Compute service, known as , serves as the core orchestration layer for managing instances in an OpenStack cloud environment. It handles the provisioning, scheduling, and lifecycle operations of compute resources across a of hypervisors, enabling users to create, scale, and maintain servers . Nova abstracts the underlying hardware, providing a unified for administrators and users to deploy workloads while ensuring efficient resource utilization and . Nova's primary functionality revolves around scheduling and managing instances on hypervisors, including support for advanced operations such as to move running instances between hosts without downtime, resizing to adjust resource allocations like CPU and , and evacuation to relocate instances from failed hosts during or outages. These capabilities allow for seamless workload mobility and recovery, with supported on compatible hypervisors through block migration or shared storage configurations. Resizing operations enable dynamic of instance flavors, while evacuation ensures continuity by rebuilding instances on healthy nodes using the original image and configuration. The service exposes key RESTful APIs for instance management, including endpoints to create new servers via POST requests specifying flavor, image, and network details; start stopped instances using action payloads like os-start; stop running instances with os-stop; and delete instances through DELETE requests on the server resource. Since the release in 2018, Nova integrates with the Placement service to track and allocate resources more accurately, using Placement's inventory and usage APIs to inform scheduling decisions and prevent overcommitment. Nova supports multiple hypervisors, with KVM as the primary and most fully featured option for Linux-based environments, alongside for enterprise integrations and for compatibility. These hypervisors enable core operations like on KVM (for x86, , and s390x architectures) and VMware, as well as resizing across all listed drivers. The service employs a conductor , where the nova-conductor component acts as a central for database operations, insulating compute nodes from direct database access to enhance , , and in multi-tenant setups. In the 2025 Flamingo release, introduced enhancements for , including support for AMD Secure Encrypted – Encrypted State (SEV-ES) via the libvirt driver, which extends memory to CPU states for improved isolation. This builds on prior AMD SEV capabilities, allowing users to enable encrypted instances through image properties like hw_mem_encryption_model=amd-sev-es. While TDX integration remains under community discussion for future upstream support, the SEV-ES addition strengthens 's role in secure, hardware-encrypted . For configuration, Nova uses cells to scale deployments across geographic regions or large clusters, with Cells v2 providing logical sharding via separate databases, message queues, and conductors per while maintaining a global database for cross-cell visibility. This setup supports horizontal by allowing independent of compute hosts within each . The scheduler employs filters and weighers to select optimal hosts, such as the RAMWeigher for prioritizing available memory and CPUWeigher for vCPU allocation, configurable via weights in nova.conf to balance loads based on overcommit ratios. Nova briefly references networking requirements for instance attachment but defers detailed connectivity to the Neutron service.

Networking Service (Neutron)

The OpenStack Networking service, known as , provides "networking as a service" by delivering API-driven connectivity between interface devices, such as virtual network interface cards (vNICs) managed by other OpenStack services like . It enables users to create and manage virtual networks, ensuring isolation and connectivity for cloud workloads without requiring direct configuration. Neutron abstracts the underlying physical network infrastructure, supporting both provider and tenant networks to facilitate scalable, multi-tenant environments. Neutron's core functionality includes managing virtual networks, subnets, routers, and load balancers through a RESTful API, allowing administrators to define addressing, routing, and balancing policies. The Modular Layer 2 (ML2) plugin serves as the extensible framework for this, supporting diverse Layer 2 technologies via type drivers (e.g., VLAN, VXLAN, GRE) and mechanism drivers, which enables simultaneous use of multiple networking backends without monolithic configurations. This modularity promotes extensibility, as new drivers can be added dynamically to accommodate evolving infrastructure needs. Key features encompass Floating IPs, which provide external, routable addresses mapped to internal instance IPs for public access, and security groups that enforce firewall rules at the instance level using iptables or similar mechanisms to control inbound and outbound traffic. Additionally, Distributed Virtual Routing (DVR) enhances scalability by distributing router functions across compute nodes, reducing bottlenecks at central network nodes and supporting high-availability through mechanisms like VRRP for SNAT traffic. Neutron integrates with common drivers such as (OVS) for software-defined L2 switching and Linux Bridge for simpler bridging, both configurable via ML2 mechanism drivers to handle overlay networks and port binding. For advanced SDN capabilities, it supports integrations with controllers like OpenDaylight through dedicated ML2 drivers and plugins, enabling centralized policy management and service function chaining in complex topologies. Another prominent integration is with Open Virtual Network (OVN), an extension of OVS that provides distributed logical routing and switching, often used as an ML2/OVN mechanism driver for efficient north-south and handling. The service exposes REST APIs for operations like creating ports, binding them to instances in , and managing attachments, with endpoints such as /v2.0/ports for port lifecycle management. The OVS agent, running on compute and network nodes, implements switching by configuring flows in the OVS database, ensuring seamless between virtual ports and physical underlays. In the 2025.1 Epoxy release, Neutron introduced enhancements to (QoS) policies, including bandwidth limiting rules for OVN logical switch ports using TC commands and prioritization of floating IP rules over router gateways, benefiting telco use cases with improved traffic control on localnet ports. Other updates include support for QinQ VLAN transparency via 802.1ad in ML2/OVN and a new metadata_path extension for distributed retrieval using OVS, alongside quota engine refinements for resource usage checks. These changes build on capabilities, though legacy prefix delegation via was deprecated in the L3 agent to streamline configurations.

Block Storage Service (Cinder)

The Block Storage service, known as , enables the provisioning and management of persistent block storage volumes that can be attached to instances in OpenStack, providing scalable storage independent of the compute lifecycle. It supports operations such as creating volumes of specified sizes, attaching and detaching them to instances via protocols like or , and managing snapshots for or backups to . Unlike solutions, Cinder delivers block-level access suitable for file systems or on . Cinder integrates with various storage backends through a modular driver architecture, allowing administrators to configure multiple backends simultaneously for diverse workload needs. Examples include the LVM driver for local , the Ceph driver for distributed block storage, and drivers such as those for VMAX, XtremIO, or Unity arrays that support enterprise features. Volume types further enhance flexibility by defining performance characteristics, such as SSD for high or HDD for cost-effective capacity, using quality-of-service (QoS) specifications like read/write limits. The driver architecture employs a model where each backend is defined in the cinder.conf file under sections like [backend1] with enabled_backends listing multiple options, enabling the scheduler to route requests based on availability and type matching. Cinder exposes its capabilities through a RESTful API for volume operations, including endpoints for creating, listing, updating, and deleting volumes, as well as managing attachments and snapshots, with microversioning to support evolving features without breaking compatibility. Key features include at-rest encryption using keys managed by the Barbican service or LUKS for protecting sensitive data on volumes, multi-attach capability for read/write sharing across multiple instances (supported on compatible backends like Ceph or certain SANs for clustered applications), and consistency groups that coordinate crash-consistent snapshots across multiple volumes to maintain application-level integrity, such as for Oracle databases or other transactional workloads. In the 2025.2 Flamingo release, introduced enhancements to NVMe-oF support, including NVMe-TCP protocol integration in drivers like PowerMax for higher-speed, low-latency storage access, along with in-use expansion for NVMe namespaces and improved architecture for secure volume migrations. These updates build on prior capabilities to better accommodate modern environments.

Identity Service (Keystone)

The OpenStack Identity service, known as , serves as the central and framework for the OpenStack cloud platform, enabling secure access to other services through client , , and distributed multi-tenant via the Identity v3. It manages users by assigning unique identifiers and credentials within domains, supports group memberships, and handles (MFA) for enhanced security. Projects act as hierarchical containers for resources, allowing users to be scoped to specific projects or domains, while roles define permissions such as "member" or "admin" that are assigned at the project or domain level to enforce . Keystone facilitates federated identity management, allowing integration with external identity providers using protocols like SAML and , which enables across multiple systems and persists attributes such as group memberships for federated users. For broader integrations, it supports backend connections to directory services including LDAP and , permitting centralized user management without duplicating identities in OpenStack. Scoping mechanisms allow tokens to be limited to specific domains, projects, or even system-wide for administrative tasks, ensuring granular control over resource access in multi-tenant environments. The in Keystone maintains a dynamic list of available OpenStack services and their endpoints, such as the public for the Compute service () at "http://controller:8774/v2.1", which clients retrieve during to discover and interact with other components. relies on token-based mechanisms, where unscoped or scoped tokens (using for secure, non-persistent encryption or UUID for legacy compatibility) are issued upon successful login and validated for subsequent requests, with expiration and revocation features to maintain . Authorization in Keystone employs role-based access control (RBAC), where permissions are defined in configurable policy files—typically named "policy.json"—that specify rules for actions like creating users or listing projects based on assigned roles. Trusts extend this by providing a model, allowing a trustor to grant a trustee specific roles within a project scope without sharing passwords, supporting impersonation and time-limited access for automated workflows or service-to-service interactions.

Image Service (Glance)

The Image Service in OpenStack, commonly referred to as Glance, enables users to discover, register, and retrieve (VM) images through a centralized repository. It manages the lifecycle of these images by providing secure storage, metadata tracking, and delivery mechanisms, ensuring efficient access for other OpenStack components. Glance operates as a standalone service but integrates seamlessly with the broader ecosystem, such as supplying bootable images to the Compute Service for instance provisioning. At its core, Glance handles the storage and retrieval of VM images in common formats like QCOW2 for QEMU copy-on-write disks, ISO for optical media, and for unstructured . This flexibility allows administrators to upload pre-built operating system images or custom disk snapshots. The service supports multiple backends for image persistence, including local file systems for simple deployments, for scalable distributed storage, and HTTP for remote access without direct backend management. These backends decouple image data from , enabling resilient operations across diverse environments. Metadata in Glance enriches images with descriptive properties, such as the operating system type (e.g., or Windows) and CPU architecture (e.g., x86_64 or ). This information aids in discovery and compatibility checks during deployment. For security, Glance incorporates image signing, which uses digital signatures and asymmetric cryptography to validate image and upon upload or retrieval; administrators configure public keys to enforce , preventing tampering in untrusted networks. Glance features a metadata definitions catalog, introduced in the Juno release, that standardizes schemas for image properties across the OpenStack community. This catalog organizes into namespaces containing objects and primitive-typed properties (e.g., strings, integers), with examples including requirements like minimum CPU cores or allocation defined via prefixes such as "hw_". property management is handled through API-driven creation, updates, and deletions, restricted to administrators since the release, ensuring consistent usage for resources like images while supporting . The service exposes RESTful APIs under version 2 for core operations, including uploading images via PUT requests to /v2/images/{image_id}/file and downloading them through GET endpoints, with support for partial retrievals. To optimize performance, Glance implements caching on API servers, storing frequently accessed images locally to reduce backend load and improve response times in high-traffic deployments. The Task API further enhances usability by managing asynchronous operations, such as image imports or format conversions, allowing clients to poll for status updates without blocking. In 2025 releases, Glance received enhancements like content inspection during uploads to verify format adherence (e.g., ensuring QCOW2 integrity) and configurable safety checks for disk images, alongside support for the x-openstack-image-size header in upload endpoints to validate data sizes proactively. These updates bolster reliability for VM workflows, while the existing container format enables basic support for container images as archives, positioning Glance as a versatile registry option.

Object Storage Service (Swift)

The Object Storage Service () in OpenStack provides a distributed system for storing and retrieving as objects within containers, enabling scalable management of large volumes of files, backups, and media without the need for a traditional . Objects are flat blobs that can include , and containers serve as logical groupings similar to directories but without nesting support. This design supports multi-tenancy through account isolation, making it suitable for cloud environments handling petabytes of across commodity hardware. Swift employs a ring-based to determine data placement and ensure even distribution across storage nodes, where the ring maps partitions of to devices using zones for and replicas for . By default, is replicated three times to achieve and , though administrators can configure storage policies for alternative levels. Erasure coding is also supported as an efficient alternative to full replication, encoding into fragments that allow from a subset, reducing storage overhead while maintaining against failures. For large objects exceeding the single-upload of 5 (configurable), Swift supports static large objects up to effectively unlimited sizes through manifest files linking segmented uploads, with practical limits often set around 1 TB for performance reasons. The service exposes both Swift-native RESTful and S3-compatible endpoints via a gateway, allowing operations such as creating, listing, updating, and deleting accounts, , and objects using standard HTTP methods like PUT, GET, POST, HEAD, and DELETE. Account-level operations include management and listing with support via parameters like and marker, while and object handling enables prefix-based filtering, versioning, and . Unlike block storage services that provide persistent volumes for virtual machines, Swift focuses on scalable, API-driven access to without direct semantics. Swift's proxy server enhances functionality, including via temporary URLs that grant time-limited access to objects without requiring ongoing credentials, generated using HMAC-SHA1 signatures with secret keys stored at the account level. Additionally, the static allows containers to serve static directly, specifying index and error pages for hosting simple sites. In the 2025.2 Flamingo release, improvements to the S3 gateway include support for AWS and multiple algorithms (e.g., CRC32C, SHA256), boosting performance for hybrid cloud integrations and large-scale uploads. The extensible format now accommodates over 65,536 devices, facilitating deployments in expansive or multi-region environments.

Dashboard (Horizon)

Horizon serves as the canonical web-based dashboard for OpenStack, offering a graphical user interface that enables administrators and users to interact with core cloud services such as compute, networking, and storage. Built on the Django web framework with dynamic elements powered by AngularJS, it provides role-based access through distinct panels tailored for project users and cloud administrators. This interface abstracts the complexity of underlying APIs, allowing seamless management of OpenStack resources without direct command-line interaction. The dashboard's functionality centers on modular panels that organize access to specific services. For project users, the Project panel includes sections for launching and managing compute instances via , configuring networks and subnets through , and handling block storage volumes with . Administrators access the Admin panel for system-wide oversight, including user management, quota settings, and service health monitoring across the deployment. These panels support provisioning, where users can create and scale resources like virtual machines, snapshots, and floating IP addresses directly from the browser. Customization in Horizon is facilitated through a architecture that allows extensions without modifying the core codebase. Developers can create Django-based to add new panels or modules for interactive features, enabling tailored integrations such as third-party service dashboards. Theming options permit branding adjustments, including custom logos, color schemes via CSS overrides, and site branding text configurable in local_settings.py. is supported natively through Django's translation framework, allowing multi-language interfaces by setting locale preferences and providing gettext_lazy strings for UI elements. Integration with other OpenStack components is core to Horizon's design, with serving as the mandatory identity backend for and . Upon login, users are authenticated via Keystone's token-based system, after which Horizon acts as an proxy, forwarding requests to services like Glance for image management or for while enforcing policy rules. This proxy model ensures secure, centralized access without exposing service endpoints directly to end-users. Key features include comprehensive monitoring dashboards that display resource utilization, such as instance metrics and traffic overviews, drawn from integrated data. capabilities extend to workflow orchestration, where users can initiate templates for automated deployments, though detailed template management occurs via dedicated service interfaces. Since the release in 2015, Horizon has incorporated Bootstrap standards to ensure responsive design across devices, adapting layouts for tablets and mobiles. In the 2025.2 release, enhancements added detail views for user credentials in the panel, including generation for two-factor authentication setup, and enabled non-admin users to perform cold migrations on instances.

Orchestration Service (Heat)

The Orchestration service, known as , enables the provisioning and management of complex cloud applications in OpenStack through declarative templates. It orchestrates multiple OpenStack resources, such as compute instances, networks, and storage, by executing calls based on user-defined specifications. Heat's design emphasizes and , allowing operators to define entire application stacks in a single template file, which can be version-controlled and deployed consistently across environments. Heat primarily uses the Orchestration (HOT) format, a native YAML-based specification that supports advanced OpenStack-specific features. HOT templates are compatible with syntax, enabling users familiar with that ecosystem to adapt existing templates with minimal changes, though HOT extends beyond CFN capabilities for deeper OpenStack integration. A defines sections like parameters for customization, resources for OpenStack components, and outputs for post-deployment results. represent the runtime instantiation of a template, grouping related resources logically and managing their lifecycle as a unit; for example, a stack might provision a by combining servers, load balancers, and databases. Heat integrates with core OpenStack services through resource plugins, which map template declarations to API interactions. For instance, the OS::Nova::Server resource plugin creates compute instances via , while OS::Neutron::Net handles virtual networks through . These plugins ensure ordered deployment by resolving dependencies, such as attaching a volume to a server only after the server is active. Autoscaling is supported via the OS::Heat::AutoScalingGroup resource, which dynamically adjusts instance counts based on metrics from the service (Ceilometer), such as CPU utilization thresholds, to maintain application performance under varying loads. The service exposes a RESTful API for stack operations, allowing programmatic control over creation, updates, and deletion. Stack creation involves a request to /v1/{tenant_id}/stacks with the template and parameters, returning a unique stack ID upon success. Updates use PUT or to /v1/{tenant_id}/stacks/{stack_name}/{stack_id}, enabling modifications like resources without full redeployment. Deletion via DELETE removes the stack and its dependencies, ensuring cleanup. Wait conditions, implemented through OS::Heat::WaitCondition resources, handle asynchronous dependencies by pausing stack creation until external signals (e.g., from user scripts) confirm readiness, using handles like OS::Heat::WaitConditionHandle for signaling. Key features include software configuration management, where OS::Heat::SoftwareConfig resources define post-boot scripts or configurations delivered via config drives or metadata services, supporting tools like cloud-init for automated setup. Cross-stack references allow templates to import attributes from other stacks using the get_resource , facilitating modular designs where one stack outputs (e.g., a network ID) are consumed by another.

Workflow Service (Mistral)

The Workflow Service, known as , is an OpenStack component designed to orchestrate and automate complex processes across resources by defining workflows as directed acyclic graphs (DAGs) of interconnected tasks. It enables users to model computations involving multiple steps, such as provisioning or software deployments, without requiring custom , by leveraging a YAML-based (DSL). Mistral manages workflow state, execution order, parallelism, synchronization, and recovery, making it suitable for distributed systems operations. At its core, supports task actions defined using YAQL for query-like expressions (e.g., <% $.vm_name %> to reference input data) and Jinja2 templating (e.g., {{ _.vm_id }} for runtime variables), facilitating data flow between tasks. Workflows can be structured in several types: direct workflows execute tasks sequentially via explicit transitions like on-success or on-error; reverse workflows rely on dependency declarations (using the requires attribute) to determine execution order backward from a target task; and advanced constructs include branches via fork-join patterns (with join types such as all, numeric, or one for synchronization) and loops using with-items to iterate over collections, such as creating multiple virtual machines. Additionally, workflows can be triggered periodically using syntax for scheduled automation or via event-based mechanisms. Mistral exposes a RESTful API (v2) for defining, validating, and executing workflows, including endpoints for workbooks (containers for multiple workflows), individual workflows, actions, executions, tasks, and action executions, with support for filtering, pagination, and state management (e.g., SUCCESS, ERROR, RUNNING). It integrates with the Orchestration Service () through dedicated Heat resources like OS::Mistral::Workflow, allowing Heat templates to create, run, and monitor Mistral workflows for enhanced application . Key features include robust error handling via on-error transitions and on-complete handlers that execute regardless of outcomes, as well as configurable retry policies (e.g., specifying count, delay, and break-on conditions) to ensure reliability. Workflow definitions adhere to version 2 of the DSL, introduced in 2014, which provides and structured updates. Unlike resource-focused orchestration in , specializes in sequential and conditional task automation, enabling fine-grained control over cross-service interactions in OpenStack environments.

Telemetry Service (Ceilometer)

The Service, known as Ceilometer, is an OpenStack component responsible for gathering and processing resource utilization data across the cloud infrastructure, enabling capabilities such as billing, monitoring, and scalability analysis. It operates by collecting metering data through a combination of active polling and passive notification listening, normalizing the information into standardized samples that capture metrics like over time. This service supports multi-tenant environments by associating data with specific projects and users, ensuring secure and isolated access to telemetry information. Ceilometer's core functionality revolves around polling agents that periodically query OpenStack services for metering data. The ceilometer-agent-compute runs on nodes to collect instance-specific metrics, such as CPU utilization in hours (cpu), memory usage (memory.usage), and disk I/O (disk.read.bytes). Similarly, the ceilometer-agent-central handles non-instance resources from a central location, including network bandwidth metrics like incoming and outgoing bytes (network.incoming.bytes, network.outgoing.bytes). These agents use configurable namespaces to target specific pollsters, which define the metrics to retrieve, and forward the resulting samples to a storage backend for persistence. Samples are typically stored in a time-series database, with serving as the recommended backend since the Mitaka release in 2016, offering efficient indexing and querying for large-scale deployments. For alarm management, Ceilometer provides the foundational data that enables threshold-based notifications, integrating seamlessly with the Aodh service to evaluate conditions and trigger actions like scaling or alerts. Users can define alarms on Ceilometer meters, such as notifying when CPU usage exceeds 80% over a specified period, with Aodh handling the evaluation logic and execution. This integration allows for automated responses without direct modification to Ceilometer's collection mechanisms. Data flow in Ceilometer is orchestrated through pipelines, which couple data sources—such as polling results or service notifications—with transformation rules and output sinks. Notification handling occurs via the (AMQP), where the ceilometer-agent-notification consumes messages from OpenStack services (e.g., or ) over the message bus, extracts relevant metering or event details, and applies pipeline transformations before publishing to storage like . Pipelines support multiple sinks for redundancy, such as logging or external systems, and can filter or aggregate data to reduce overhead. Key features include event sinking, where Ceilometer captures discrete events like instance creation or deletion from notifications, storing them alongside meters for comprehensive auditing and analysis. The service is highly extensible, allowing operators to define custom meters by implementing new pollsters in or notification handlers, which can target specialized resources without altering core components. For instance, custom meters might track application-specific metrics by hooking into service notifications. In its evolution, Ceilometer has incorporated influences from Monasca for enhanced monitoring since the Victoria release in 2020, introducing a dedicated publisher that sends metrics directly to Monasca instances for advanced analytics and scalability. By 2025, in the 2025.2 (Flamingo) release, further improvements include parallel execution of pollsters via configurable threads to boost performance in large clusters, along with new metrics for volume pools and exporter enhancements with TLS support, reflecting a continued emphasis on scalable, integrated .

Database Service (Trove)

provides Database as a Service (DBaaS) within OpenStack, enabling users to provision, manage, and scale relational and databases without directly handling underlying infrastructure. It automates tasks such as deployment, configuration, backups, and monitoring, running entirely on OpenStack components like for compute and for storage. Designed for multi-tenant cloud environments, supports databases including , , , and , allowing operators to offer self-service database instances to tenants. The core functionality relies on guest agents deployed within database instances, which execute management operations via a messaging bus. For and , guest agents handle tasks like creating read replicas through replication, performing full and incremental backups to storage, and basic clustering setups where supported. guest agents similarly manage backups and support replica sets for , using containers to isolate the database engine from the host OS. These agents implement datastore-specific APIs, ensuring compatibility with OpenStack's resource and mechanisms. Trove exposes a RESTful API for instance lifecycle management, including creation via POST to /v1.0/{project_id}/instances with parameters for flavor, volume size, and datastore version, and resizing through POST actions for flavor or volume adjustments. Datastore versions are managed via GET requests to list available datastores (e.g., MySQL) and their versions (e.g., 5.7, 8.0), with admin-only POST for registering new versions. Backups are created via POST to /v1.0/{project_id}/backups, supporting incremental strategies, while read replicas are provisioned by specifying replica_of in instance creation requests. Key features include read replicas for offloading query loads in and (via replication APIs like promote-to-replica-source), high availability through mechanisms such as ejecting replica sources, and clustering support for replica sets. Integration with enables secure handling of secrets, such as AES-256 keys for backups stored in , by configuring to use Barbican workflows instead of proprietary ones. Configuration groups allow tenant-specific parameter tuning without direct agent access. While effective for multi-tenant deployments with quotas like 10 instances per tenant, has limitations in handling massive-scale production (OLTP) workloads, prioritizing ease of management over extreme available in self-hosted databases. In contrast to big data cluster management in , Trove targets traditional structured data stores. The 2025.2 (Flamingo) release expanded support to newer versions, including 8.0 and 8.4, 16 and 17, and 11.4 and 11.8, enhancing compatibility with modern database features.

Big Data Processing (Sahara)

Sahara, OpenStack's Data Processing service, enables users to provision and manage scalable big data clusters for frameworks such as and directly on OpenStack infrastructure. It simplifies the deployment of data-intensive applications by abstracting the underlying cloud resources, allowing operators to define cluster configurations through reusable templates that specify hardware requirements, software versions, and scaling policies. These templates support the creation of node groups for master, worker, and client roles, ensuring efficient across OpenStack's compute and services. Sahara integrates seamlessly with other OpenStack components for data handling, using Swift for object storage to manage job binaries, libraries, and input/output data, while leveraging Cinder for persistent block storage to back HDFS volumes in Hadoop clusters. This allows clusters to access large-scale data without manual configuration, treating Swift objects as HDFS-compatible inputs for processing tasks. Plugins extend Sahara's functionality to support specific distributions, including the Vanilla plugin for pure Apache Hadoop and Spark installations, the Cloudera plugin for Manager-orchestrated environments, and the Hortonworks (now part of Cloudera) plugin for HDP-based setups. These plugins handle version-specific image requirements and automate the installation of framework components upon cluster launch. The service exposes a RESTful for core operations, including cluster creation, , and node group , with support for autoscaling based on predefined policies that adjust worker dynamically in response to workload demands. A key feature is Elastic Data Processing (), which facilitates the submission and execution of batch jobs such as workflows or applications, including configurations for main files, input datasets from , and output handling. Users can monitor job progress and results through the or Horizon integration, enabling iterative without direct cluster access. Although remained functional through the early 2020s with ongoing support for up to version 3.1 in its plugins, the project saw reduced emphasis as container-based alternatives like Magnum gained traction for modern workloads. In May 2024, the OpenStack Technical Committee retired due to sustained inactivity, archiving its repositories and removing integrations from dependent projects like . No further updates, including potential Spark 3.5 integrations, were pursued post-retirement.

Bare Metal Provisioning (Ironic)

OpenStack Ironic is the bare metal provisioning service that enables the management and deployment of physical servers within an OpenStack cloud environment, treating them similarly to without the overhead of . It supports heterogeneous fleets by providing a unified interface for provisioning, allowing operators to enroll nodes, discover their capabilities, and deploy operating systems directly onto bare metal. Ironic integrates with other OpenStack services such as for compute orchestration, for networking, Glance for images, and for temporary storage during deployment. The core functionality of Ironic revolves around standard protocols for hardware control, including PXE for the deployment agent and IPMI or for of server baseboard management controllers (BMCs). It offers drivers and hardware types like the ipmi type, which uses ipmitool for power control and sensor monitoring, and the redfish type, which leverages the standard for modern servers from vendors such as , HPE, and to handle tasks like updates and virtual media mounting. These drivers enable automated power operations, console access, and secure boot processes across diverse hardware. Ironic integrates deeply with Nova through a dedicated hypervisor driver, allowing users to launch instances on bare metal s using the same as virtual instances, with scheduling based on node capabilities and resource classes. Before deployment, Ironic performs a process to prepare , which includes automated steps like disk wiping, updates, and reconfiguration, or manual steps for custom actions, ensuring nodes are in a consistent . introspection, handled via the Ironic Inspector service, automatically discovers node properties such as CPU count, memory, and storage details by a temporary over PXE, populating resource traits for better scheduling. Key features include support for RAID configuration, where operators can define logical volume arrays (e.g., for mirroring or for striping with parity) using JSON schemas applied during cleaning or deployment via the CLI or , compatible with both hardware and software controllers. Multi-tenancy is achieved through integration, isolating tenant traffic on VLANs or other overlays while sharing the provisioning network, enabling secure, segmented bare metal deployments without physical network reconfiguration. Ironic exposes a RESTful for core operations, such as enrolling nodes with POST /v1/nodes (specifying driver and interfaces) and managing power states via PUT /v1/nodes/{node_ident}/states/power for on/off/ actions, supporting asynchronous workflows and detailed state tracking. In the 2025.2 Flamingo release, Ironic enhances support for accelerator devices, adding compatibility with NVIDIA A10, A40, L40S, and L20 GPUs, along with fixes for accurate re-introspection of removed accelerators, better enabling AI and high-performance computing workloads on bare metal.

Messaging Service (Zaqar)

Zaqar is OpenStack's multi-tenant cloud messaging and notification service, designed to enable developers to send messages between components of SaaS and mobile applications using a scalable queuing system. It combines concepts from Amazon's Simple Queue Service (SQS) with additional features tailored for cloud environments, providing a firewall-friendly interface without requiring broker provisioning. The service supports high availability, fault tolerance, and low-latency operations through a distributed architecture that avoids single points of failure. At its core, Zaqar manages queues that operate in a first-in, first-out (FIFO) manner, allowing producers to push messages and consumers to pull them asynchronously. This decoupling of applications facilitates reliable communication patterns, such as task distribution and event broadcasting. Subscriptions extend queue functionality by enabling fanout delivery to multiple endpoints, including email, webhooks, and WebSocket connections, which notify subscribers when new messages arrive. For instance, in workflow orchestration, Zaqar can decouple Heat processes by queuing events that trigger subsequent actions in Mistral workflows. Zaqar supports multiple storage backends to handle varying workloads, with as the recommended option for its robust document storage capabilities and for high-throughput scenarios via in-memory operations. Pooling mechanisms distribute messages across backend instances to ensure and performance under heavy loads, such as processing thousands of messages per second. The service's include a RESTful HTTP for standard operations and a for persistent, real-time connections, with support for claims that allow workers to reserve messages for processing and acknowledge receipt by deletion or release. Key features include time-to-live (TTL) settings for messages and queues, which automatically expire content after a specified duration to manage and prevent accumulation. Metadata tagging allows users to attach custom key-value pairs to queues and messages, aiding in , filtering, and search within large-scale deployments. These capabilities make Zaqar suitable for use cases like notifying guest agents in virtual machines or resource state changes across OpenStack services.

Shared File System Service (Manila)

The OpenStack Shared File Systems service, known as , enables users to provision and manage shared file systems that can be accessed concurrently by multiple virtual machine instances or containers. It abstracts the underlying storage infrastructure, allowing administrators to integrate various back-end file systems while providing a unified interface for end users. Manila supports standard protocols such as NFS and CIFS, facilitating integration with existing enterprise environments and applications that rely on POSIX-compliant . Manila's functionality centers on creating, managing, and accessing file shares through pluggable drivers that connect to diverse back ends. Notable drivers include the driver, which leverages systems for high-performance NFS and CIFS shares, and the CephFS driver, which utilizes Ceph's distributed file system for scalable, resilient . These drivers handle share provisioning, ensuring compatibility with multi-tenant environments by isolating shares per project. Share types in Manila support access modes like ReadWriteMany (RWX), which allows multiple pods in to read and write to the same share simultaneously, making it ideal for stateful applications in containerized workloads. Additional features include share snapshots for point-in-time backups and restores, as well as quotas to enforce limits on shares and snapshots per project, preventing resource overuse. The service exposes a RESTful for operations such as creating shares, defining access rules, and managing share networks. Users can specify share types, sizes, and protocols via calls, with access rules controlling permissions for specific clients or ranges. This is versioned at 2.x and integrates with OpenStack's identity service for . Security in Manila incorporates for in NFS environments, enabling secure, ticket-based access without transmitting passwords over the network. Export policies further enhance control by defining which clients can mount shares and with what permissions, such as read-only or read-write, at the driver level. In the 2025.1 release, received updates including the ability to modify access rule levels dynamically (e.g., from read-only to read-write) and improvements to driver capabilities, such as enhanced provisioning in the driver to avoid high-availability takeover issues and better capacity reporting in the CephFS driver for scheduler optimization. GlusterFS remains a supported driver for distributed file systems, with ongoing compatibility for edge deployments through its native handling.

DNS Service (Designate)

OpenStack Designate is a multi-tenant DNS-as-a-Service (DNSaaS) component that enables users and operators to manage DNS zones, records, and names within OpenStack clouds through a standardized integrated with . It orchestrates DNS data propagation to backend servers, supporting scalable, access to authoritative DNS services in a technology-agnostic manner. Designate separates handling, , data persistence, and backend interactions to ensure reliability and multi-tenancy, allowing cloud tenants to provision DNS resources without direct access to underlying DNS . At its core, Designate manages and recordsets to organize DNS , where each represents a owned by a specific and includes default SOA and recordsets upon creation. Administrators configure pools of DNS servers to handle , grouping namespace servers for efficient and load across multiple backends. Supported backend resolvers include BIND9, which uses the rndc utility for remote creation and deletion, and , integrated via its for secondary management and record updates. The pluggable of the Pool Manager divides servers by type and capacity, enabling operators to expand DNS capacity by adding more servers to pools without disrupting service. This setup ensures that updates, such as adding A, CNAME, or records, are persisted in a central database and asynchronously propagated to designated backend pools by worker processes. Designate integrates seamlessly with the Networking service () through hooks that automatically generate DNS recordsets for floating IP addresses, simplifying name resolution for cloud resources. For instance, when a floating IP is assigned to a , Designate can create a corresponding PTR or A record in a specified , with updates triggered on IP association or disassociation. This integration builds on Neutron's IP management to provide resolution, distinct from Neutron's internal DNS handling for fixed IPs. The service exposes a v2 REST API for core operations, including creating, listing, updating, and deleting zones and recordsets, with endpoints like /v2/zones for zone management secured by Keystone tokens. Additionally, the MiniDNS (MDNS) component facilitates metadata service interactions by notifying backend DNS servers of zone changes, using protocols to propagate updates efficiently to hosts and ports. Zone transfers and imports further support interoperability, allowing ownership changes between projects via secure keys. Key features include support for hierarchical zones, where subdomains can be delegated as child zones under parent domains for organized namespace management across tenants. is enforced at the level to prevent abuse, configurable via settings that cap requests per interval, such as limiting zone creations to protect backend resources. In the 2025.2 release, enhancements like SVCB and record types were added to expand supported DNS resource types, improving capabilities.

Resource Indexing and Search (Searchlight)

Searchlight is an OpenStack project that provides indexing and search capabilities across various cloud resources, enabling high-performance, flexible querying and near real-time results through integration with . It allows users to perform advanced searches on resources such as compute instances, networks, and volumes without overloading individual service APIs, supporting multi-tenant environments by enforcing role-based access controls. The service listens for notifications from other OpenStack components, including Ceilometer for telemetry data, and indexes them asynchronously to maintain up-to-date resource representations. Core functionality revolves around resource plugins that map OpenStack entities to searchable indices, with built-in support for services like (compute) and (networking). These plugins process notifications via a listener service using Oslo Messaging over , enabling asynchronous indexing to handle scale without blocking other operations. Faceted search features allow filtering by attributes such as project ID, resource type, or status, providing aggregated results like counts or distributions for efficient navigation in large deployments. The API exposes a RESTful at a base like /v1/search, supporting Elasticsearch's Query DSL for SQL-like queries, including , wildcards, ranges, and . Queries require authentication via an X-Auth-Token header, with role-based access ensuring users see only owned or public resources; administrators can opt for cross-project searches using all_projects: true. (from and size parameters) and field selection enhance usability for large result sets. As the backend, handles distributed indexing and querying, with configuring it for security through network restrictions and tenant-isolated documents. integration provides visualization dashboards for exploring indexed data and facets. Introduced in the release (2015), reached maturity in the Mitaka cycle (2016) with stabilized plugins and API features. However, due to lack of maintainers and low adoption, the project was retired from OpenStack during the cycle (2021), with its repository archived and no further development.

Key Manager Service (Barbican)

The Key Manager service, known as , serves as OpenStack's primary facility for the secure storage, provisioning, and management of sensitive data, including symmetric and asymmetric keys, X.509 certificates, and arbitrary binary secrets. It enables operators to centralize secret handling across cloud deployments, reducing the risk of exposure through decentralized storage practices. By leveraging encrypted storage and access controls, Barbican ensures that secrets remain protected even in multi-tenant environments, supporting compliance with security standards such as those requiring key isolation. At its core, Barbican organizes secrets into containers, which act as logical groupings for multiple secret references, each optionally named for clarity. These containers facilitate structured management, such as bundling related keys and s for specific use cases like TLS configurations. For (PKI) operations, Barbican integrates with the Dogtag plugin, which leverages the Dogtag Key Recovery Authority () subsystem to securely store encrypted secrets using storage keys managed via software NSS databases or hardware security modules. This setup allows automated issuance and renewal while maintaining cryptographic isolation. Barbican exposes its capabilities through a RESTful , version 1.0 with support for microversions to enable backward-compatible enhancements. The Secrets API handles core operations, including creating new secrets via requests with payload (such as and bit length), listing available secrets with GET, and retrieving secret payloads separately to avoid unnecessary exposure of . Access to these resources is governed by Lists (ACLs), configurable via dedicated API endpoints that allow users or projects to grant read, write, or delete permissions on individual secrets or containers, ensuring fine-grained authorization beyond Keystone's project scoping. For backend storage, supports multiple plugins, including the Simple Crypto plugin for software-based encryption of secrets stored directly in its database and the plugin for integration with to offload to an external secure vault. Rotation policies enhance security by automating key refreshes; for instance, the Simple Crypto backend now supports key-encryption-key (KEK) rotation, where new symmetric keys can be generated and prioritized in configuration to re-encrypt project-specific keys without downtime. In the 2025.1 release, this feature was expanded to allow multiple KEKs, with the primary key used for new encryptions and others retained for decryption of legacy data. Barbican integrates with other OpenStack services through the Castellan library, an Oslo-based interface that abstracts key management operations and defaults to Barbican as its backend for fetching and storing secrets. This enables seamless adoption in components like Cinder for volume encryption keys, promoting a unified secrets ecosystem. As of the 2025.2 release, administrative tools were enhanced with commands to re-encrypt existing secrets using updated project keys, further streamlining maintenance in large-scale deployments.

Container Orchestration (Magnum)

Magnum is an OpenStack service designed to manage container orchestration engines (s), enabling the deployment and operation of containerized workloads as native resources within the cloud infrastructure. It abstracts the of setting up and maintaining COE clusters by providing a unified for provisioning hosts, configuring networking, and handling scaling operations. By leveraging pluggable drivers, Magnum supports multiple COEs, including as the primary engine, along with Docker Swarm and Mesos for alternative orchestration needs. The core functionality of Magnum revolves around COE drivers that define how clusters are instantiated and managed for each supported engine. For , the driver handles the creation of master and worker nodes, installation of necessary components like etcd and kubelet, and configuration of networking overlays such as or . Docker Swarm drivers focus on manager and worker node setups with built-in , while Mesos drivers enable framework-based scheduling for diverse workloads. Users define cluster specifications through ClusterTemplates, which specify labels like image ID, flavor, and network configurations to customize deployments across these COEs. Magnum exposes a RESTful API via the magnum-api service for comprehensive cluster lifecycle management, including creation, scaling, updates, and deletion. Cluster creation involves asynchronous operations initiated through commands like openstack coe cluster create, with scaling achieved via openstack coe cluster resize to add or remove nodes dynamically. Security features include support for pod security policies in , configurable through ClusterTemplate labels such as pod_security_policy to enforce admission controls and restrict privileged containers. Integration with other OpenStack services enhances Magnum's capabilities for robust deployments. It utilizes orchestration templates to provision underlying virtual or bare metal instances, automating the stacking of infrastructure resources like networks and volumes. For secure communications, Magnum integrates with to store and retrieve TLS , configurable via the cert_manager_type parameter in ClusterTemplates to enable x.509 key pairs or external certificate authorities. Key features of Magnum include auto-healing mechanisms to ensure cluster reliability, where failed nodes are automatically detected and replaced using the magnum-auto-healer daemon or ' Draino tool when enabled via the auto_healing_enabled label. Load balancing is facilitated through Neutron's Load Balancer (LBaaS), allowing external access to cluster services with the master-lb-enabled option provisioning dedicated load balancers for endpoints and ingress traffic. These features collectively support resilient, scalable container environments. In the 2025.2 Flamingo release, Magnum introduced a new credentials endpoint for rotating cluster credentials, supporting Application Credentials or Trusts to improve security hygiene without disrupting operations. Additionally, enhancements to certificate generation added subject key identifier extensions, enabling better authority key identification in cluster certificates. Magnum can also deploy container clusters on bare metal infrastructure provisioned via Ironic for high-performance workloads.

Root Cause Analysis (Vitrage)

Vitrage serves as OpenStack's (RCA) service, employing a graph-based approach to correlate and analyze alarms and events across the infrastructure, thereby identifying underlying causes of problems. It constructs an in-memory entity that maps physical and resources, such as compute instances, , and storage volumes, along with their interdependencies. This enables the service to propagate states and alarms through defined relationships, distinguishing between symptoms and root causes by evaluating correlations in . Central to Vitrage's functionality are configurable templates that define entity graphs, specifying nodes (e.g., vertices representing hosts or virtual machines) and edges (e.g., connections denoting dependencies like "hosted on" or "connected to"). These templates facilitate the modeling of complex infrastructure topologies and support the creation of inference rules for automated correlations. Notifications and data inputs are ingested from various sources, including telemetry metrics via the Aodh service, which interfaces with Ceilometer for alarm events. The applies algorithms, such as (BFS) and (DFS), to perform shortest path analysis between entities, highlighting potential causal chains. Vitrage exposes a REST for querying the entity graph, diagnosing issues, and retrieving RCA results, allowing operators to investigate specific alarms or entities programmatically. Key features include drill-down views that enable hierarchical exploration of graph substructures, from high-level overviews to granular details on affected components. For integrations, Vitrage includes panels in the Horizon for visual RCA workflows and supports datasource plugins for OpenStack services like , , , , and Aodh, as well as external tools such as , , and collectd. These plugins ensure seamless data collection and event propagation without requiring custom middleware. Originally introduced as an experimental project, Vitrage has achieved stable status within OpenStack's , with ongoing inclusion in release cycles up to the 2025.2 series, though it currently lacks an appointed project technical lead and requires maintainer contributions for further evolution.

Alarming Service (Aodh)

The Alarming service, known as Aodh, enables OpenStack users to define and manage alarms that trigger actions based on rules evaluated against or events, facilitating automated responses to changes. Aodh supports alarms, which compare values against specified thresholds using operators like greater than (gt) or less than (lt), and event alarms, which react to specific event patterns. Alarms can incorporate aggregation methods, such as mean or last value, over defined time periods to determine if conditions are met. A key functionality of Aodh is its support for composite alarms, which allow complex logic using operators to combine multiple sub-alarms—for instance, triggering only if both a CPU usage and a are exceeded simultaneously ({"and": [ALARM_1, ALARM_2]}) or if either is met ({"or": [ALARM_1, ALARM_2]}). Alarms follow a tri-state model for transitions: ok when the rule evaluates to false, alarm when true, and insufficient data when there are not enough datapoints for evaluation, ensuring reliable . Features include time constraints via cron-like repeat actions for periodic evaluations and severity levels such as low to prioritize responses. Aodh exposes a RESTful API for creating, listing, updating, and evaluating alarms, allowing programmatic management through endpoints like /v2/alarms. For actions, it supports webhooks that send HTTP/HTTPS notifications to external systems upon state changes, enabling integrations like autoscaling or notifications. The service relies on as its primary backend for metric storage and querying, using a declarative rule syntax to define conditions, including granularity periods and evaluation windows (e.g., 5-minute averages over 10 minutes). Originally forked from the alarming components of Ceilometer during the Liberty release in 2015, Aodh has evolved as a standalone project focused solely on alarm evaluation and actions. These alarms can briefly feed into root cause analysis systems like Vitrage for deeper diagnostics.

Compatibility and Integrations

API Compatibility with Other Clouds

OpenStack provides compatibility with Amazon Web Services (AWS) APIs primarily through its core compute and object storage services, enabling users to leverage familiar interfaces for easier adoption and hybrid cloud configurations. The Nova compute service integrates with the ec2-api project, which implements a standalone EC2-compatible API for managing virtual machine instances, security groups, and elastic block storage volumes. This allows tools and applications designed for AWS EC2 to interact with OpenStack infrastructure, though with certain constraints such as the absence of support for advanced features like spot instances, VPC peering, and dedicated hosts. For object storage, OpenStack's Swift service employs middleware such as s3api to emulate the AWS S3 , supporting core operations including bucket creation, object uploads, multipart uploads, and lists. This gateway facilitates seamless access to Swift containers using S3-compatible clients like the AWS CLI or SDKs, promoting without requiring changes to existing workflows. However, full parity is not achieved; unsupported S3 features encompass bucket notifications, lifecycle policies, object tagging, and analytics, limiting compatibility to fundamental functionalities as outlined in the official S3/Swift comparison matrix. These compatibility layers offer significant benefits for organizations migrating from clouds or building environments, as they reduce retraining needs and enable workload portability across AWS and OpenStack deployments. For instance, developers can test AWS-dependent applications against OpenStack using EC2 and S3 endpoints, streamlining transitions to clouds. Limitations persist due to architectural differences, with OpenStack's open-source prioritizing extensibility over exact replication of proprietary AWS features; middleware extensions from the library aid in request handling but do not bridge all gaps. In the 2025.2 Flamingo release, enhancements to Nova's —such as expanded and image in libvirt XML and the of the OVN in favor of the OVN agent—improve instance delivery for and .

Integrations with Emerging Technologies

OpenStack has integrated support for and workloads through its Compute service (), which enables the provisioning of GPU-accelerated instances via passthrough and virtual GPU (vGPU) technologies. This allows deployments to allocate physical GPUs hosted on hypervisors to virtual machines, facilitating tasks such as model and . For instance, 's virtual GPU feature supports GPUs, enabling multiple instances to share a single physical GPU while maintaining isolation for AI/ML applications. In the edge computing domain, OpenStack incorporates the StarlingX project, an official initiative designed as a fully integrated software for deploying edge clouds across one to 100 servers. StarlingX addresses distributed requirements by combining OpenStack services with for orchestration, supporting localized worker resources to ensure maximum responsiveness in low-latency environments like deployments. Complementing this, the Networking service () provides mechanisms such as SR-IOV for achieving near-line-rate speeds and reduced latency, which are critical for data processing at the edge. For telecommunications applications, OpenStack integrates with the Open Network Automation Platform (ONAP) to support (NFV), enabling the orchestration and deployment of virtual network functions across multiple OpenStack regions. This synergy allows service providers to manage distributed NFV clouds, incorporating features like service chaining for efficient VNF lifecycle management. Additionally, the project, launched in 2018 in collaboration with , , and , facilitates 5G core deployments by providing a declarative platform for bootstrapping OpenStack on , supporting container-native infrastructure for telco edge sites. On the security front, OpenStack advances through Nova and the Bare Metal service (Ironic), which support hardware-based trusted execution environments like AMD Secure Encrypted Virtualization (SEV) to protect instance memory from access. This enables secure and edge workloads by encrypting data in use. The Identity service () contributes to zero-trust architectures by enforcing fine-grained , , and delegation via trusts, assuming no inherent trust in users or devices. Looking ahead, OpenStack's is positioned for emerging paradigms, with ongoing enhancements in container orchestration via Magnum providing a foundation for potential future integrations in specialized computing domains. OpenStack also supports limited compatibility with through third-party tools and adapters, though not as mature as AWS integrations.

Ecosystem

Vendors and Commercial Support

Several major vendors offer commercial products, support, and services built around OpenStack, enabling enterprises to deploy and manage private clouds with enhanced reliability and scalability. provides the Red Hat OpenStack , an integrated solution that virtualizes resources from industry-standard to organize them into clouds, complete with enterprise-grade support and lifecycle management. delivers Charmed OpenStack, a distribution based on that uses charms for automated deployment and operations, including security patching and fully managed options for carrier-grade environments. Hardware vendors such as HPE and contribute through certified compatibility lists, ensuring their servers and storage systems integrate seamlessly with OpenStack distributions like those from and . Commercial offerings extend beyond software to include and hardware validation. Rackspace Technology provides Fanatical Support for OpenStack, a 24x7 service model that includes real-time monitoring, deployment assistance, and optimization for private cloud environments, often integrated with technologies. Certified hardware lists, maintained by ecosystem partners, validate components from vendors like HPE and for performance in OpenStack setups, reducing deployment risks. In terms of position, OpenStack services are projected to reach a of USD 30.11 billion by 2025, reflecting strong adoption in private infrastructures amid a broader private valued at USD 143.94 billion in 2024 and growing at 29.7% CAGR. Partnerships, such as Cisco's ACI integration with OpenStack, facilitate policy-driven networking automation, supporting dynamic requirements in versions like OpenStack Platform 17. Support models for OpenStack typically contrast community-driven assistance with paid enterprise options. Vendors like offer subscriptions with 4 years of production support and optional extended lifecycle coverage, ensuring updates and fixes. provides tiered enterprise support with guaranteed SLAs for deployment, operations, and upgrades, tailored to organizational needs. These paid models deliver proactive monitoring and dedicated expertise, surpassing open-source community forums in responsiveness and accountability. Recent trends indicate a post-2023 shift toward operator-focused services, emphasizing hybrid integrations with and workloads to address and in private clouds. This evolution supports seamless transitions for users from proprietary platforms, driven by cost pressures and demands.

Distributions and Appliances

OpenStack distributions provide pre-packaged, automated deployment options that simplify the installation and management of the cloud platform, often integrating tools like for orchestration. Canonical's Ubuntu OpenStack, for instance, leverages charms and MAAS (Metal-as-a-Service) for automated provisioning on Server, which powers over half of production deployments according to the 2024 OpenStack User Survey. This distribution supports the latest releases, including OpenStack 2025.1 (), through the Ubuntu Cloud Archive, enabling seamless updates via standard package management. Mirantis OpenStack for (MOSK) offers a Kubernetes-native approach, deploying OpenStack services as containers for enhanced scalability and resilience, with version 25.2 released in September 2025 incorporating optimizations and air-gapped support for enterprise environments. Red Hat's TripleO (OpenStack-on-OpenStack) enables self-deploying clouds using orchestration, integrated into OpenStack Platform for automated overcloud setups, though recent efforts focus on hybrid integrations with Container Platform. These distributions emphasize automation, with OpenStack-Ansible (OSA) providing role-based playbooks for deploying full environments on , , or , reducing manual configuration. OpenStack appliances extend this ease of use to and virtual formats, offering turnkey solutions for rapid deployment. OpenMetal delivers on-demand private clouds powered by OpenStack and Ceph , configurable in under a minute on bare metal , with built-in for compute and networking resources. Virtual appliances, such as Canonical's MicroStack or the community DevStack, facilitate testing by emulating full or single-node OpenStack environments on a workstation, pre-loaded with core services like and for development and proof-of-concept evaluations. Key features of these distributions and appliances include pre-configuration for specific releases, such as bundles that bundle validated components for 24.04 and , along with lifecycle management tools for upgrades and monitoring. They offer advantages like reduced setup time—often from days to hours—through certified integrations with hardware vendors and automated testing via Tempest validation. Wind River offers edge-focused appliances via its Cloud Platform, a distributed solution supporting OpenStack for telco and use cases, enabling secure, containerized deployments at the network edge; a 2025 partnership with aims to accelerate intelligent edge and cloud innovation for scalable infrastructure.

Challenges and Best Practices

Implementation and Installation Challenges

Implementing OpenStack presents several challenges, primarily due to its modular comprising numerous interconnected services that require precise coordination across multiple nodes. Multi-node deployments often encounter difficulties in synchronizing components like compute, networking, and services, leading to inconsistencies in configuration and . Additionally, management poses a significant hurdle, as OpenStack relies on a complex of packages and libraries that can result in version conflicts or "" during installation, particularly in environments with varying operating system distributions. Various installation methods cater to different use cases, from development testing to production environments. DevStack serves as a popular tool for developers, enabling a quick all-in-one setup on a single machine to evaluate features and contribute to the codebase; however, it is not recommended for production due to its focus on simplicity over stability. For single-node proof-of-concept deployments, Packstack—part of the RDO project—automates the installation of core OpenStack services on Red Hat-based systems using , though it frequently encounters issues like IP connectivity disruptions during setup. In production scenarios, Kolla-Ansible deploys OpenStack services within containers via playbooks, offering scalability and isolation while reducing host-level dependencies. TripleO, leveraging OpenStack's own tools like and Ironic, facilitates automated overcloud deployments on bare metal, making it suitable for large-scale, hardware-provisioned environments. Common issues during implementation include networking misconfigurations, such as incorrect bridge setups or rules that prevent inter-service communication, and inadequate database tuning for services like or , which can lead to performance bottlenecks under load. Hardware prerequisites for basic all-in-one deployments typically require at least 8 GB RAM, multiple CPU cores, and 20 GB storage to accommodate virtual machines and logs, with requirements increasing based on the number of services and increasing with load, with deviations often resulting in resource exhaustion. A market analysis indicated that 49% of organizations viewed installation complexity as a critical barrier to OpenStack , underscoring the need for specialized skills in overcoming these obstacles. To mitigate these challenges, best practices emphasize automation to streamline multi-node coordination and dependency resolution. Utilizing tools like for or TripleO for orchestrated deployments minimizes manual errors and ensures consistent setups across environments. Starting with well-defined microversions in configurations helps maintain compatibility during initial service integrations, while thorough pre-installation testing of and topologies is essential for reliability.

Upgrading and Long-Term Support

OpenStack upgrades typically employ rolling upgrade strategies to minimize , allowing services to be updated incrementally across nodes while maintaining overall availability. Tools like OpenStack-Ansible provide playbooks that facilitate these upgrades by automating the deployment of new versions on controller and compute nodes in sequence, ensuring that upgraded components can coexist with legacy ones during the transition. Database schema changes are managed through migrations, a SQLAlchemy-based tool integrated into projects such as and ; operators run commands like nova-manage db sync or neutron-db-manage upgrade heads to apply additive "expand" migrations online and contractive changes offline after halting relevant services. Key challenges in upgrades include ensuring microversion compatibility, where services like use microversions to support backward-compatible changes without breaking clients; during transitions, operators must configure upgrade levels in configuration files (e.g., [upgrade_levels] compute=auto in nova.conf) to pin RPC versions and avoid disruptions. Plugin breakages, particularly in Neutron's Modular Layer 2 (ML2) framework, can arise from incompatible driver updates or external networking components, requiring pre-upgrade testing of custom plugins to prevent service interruptions. OpenStack provides (LTS) through a standardized release model, where all stable branches receive approximately 18 months of active , including bug fixes and security updates, after which they enter an unmaintained phase with community-driven patches but no official releases. This applies uniformly across the 6-month release cycle, though community efforts may extend practical usability beyond formal support. Testing tools aid in validating upgrades: DevStack includes built-in upgrade checks via scripts that simulate version transitions in development environments, while , a dedicated CI harness, automates full upgrade paths between releases by stacking DevStack installs and exercising project-specific upgrade scripts to detect regressions. As of 2025, operators are advised to plan migrations toward the Flamingo (2025.2) release, which offers maintained support until an estimated end-of-life in April 2027, incorporating zero-downtime strategies such as live migrations for instances and phased service restarts to sustain operations during updates.

Documentation and Training

OpenStack's official documentation is hosted at docs.openstack.org, providing comprehensive resources including installation guides, operations and administration manuals, configuration references, and project-specific documentation for core services like Nova (compute), Neutron (networking), and Cinder (block storage). These materials cover deployment architectures, troubleshooting procedures, and API references that detail RESTful endpoints, authentication methods, and request/response formats for interacting with OpenStack services. Additionally, the documentation supports translations into more than 50 languages through community-driven efforts using platforms like Zanata and Launchpad, enabling global accessibility for non-English speakers, though completion rates vary by language. Despite these strengths, OpenStack documentation faces challenges related to fragmentation, as resources are distributed across individual project repositories rather than a centralized repository, requiring users to navigate multiple guides for integrated setups. Some sections, particularly those covering older releases prior to 2023, have been noted as outdated due to rapid project evolution outpacing updates, leading to discrepancies between documented configurations and current implementations. Training resources for OpenStack users and operators are available through the Open Infrastructure Foundation, which offers structured programs such as the University Partnership Program to integrate OpenStack into academic curricula and hands-on learning s. A key certification is the Certified OpenStack Administrator (), a vendor-neutral administered by the Open Infrastructure Foundation that validates skills in cloud operations, security, troubleshooting, and routine administration tasks like managing projects, networks, and instances; it requires at least six months of practical experience and consists of a 180-minute hands-on assessment in a live . Community-driven resources supplement formal training, including forums like ask.openstack.org for , IRC channels on the OFTC for real-time discussions (e.g., #openstack-general), and extensive tutorials covering topics from beginner introductions to advanced deployments. In 2025, efforts have emphasized enhanced interactivity in documentation tools, with integrations like Jupyter Notebooks explored for educational deployments on OpenStack to facilitate and experimentation. Improvements to documentation quality are guided by the OpenStack Documentation Contributor Guide, which outlines workflows for writing, reviewing, and building docs using RST conventions, ensuring consistency in , , and . The community conducts periodic reviews, including deprecation policies and bug tracking for documentation impacts, to maintain relevance, though formal annual audits are more commonly applied to security and compliance aspects rather than docs specifically.

Deployment Models and Use Cases

Private and Hybrid Cloud Deployments

OpenStack's cloud deployments provide organizations with complete control over their infrastructure, enabling strict adherence to regulatory requirements such as the General Data Protection Regulation (GDPR). By hosting data and applications on dedicated, on-premises resources, clouds eliminate the shared responsibilities inherent in public cloud models, simplifying efforts for sensitive workloads in sectors like finance and healthcare. For instance, has leveraged OpenStack to build a massive cloud environment, scaling to over 1 million compute cores to support internal retail operations while maintaining and operational agility. In hybrid cloud configurations, OpenStack facilitates seamless integration between private and public clouds through features like , which allows across multiple environments using protocols such as SAML or . This enables and resource access without duplicating user directories, supporting federated authentication between on-premises OpenStack deployments and external providers. Additionally, Swift's compatibility with the API ensures data portability, allowing objects to be transferred between private storage and public cloud services with minimal reconfiguration, thus avoiding . Architectural elements further enhance hybrid capabilities, including Nova's multi-region cells, which partition compute resources into isolated domains for geographic distribution while maintaining a unified surface for management. This setup supports scalability across data centers without compromising fault isolation. Neutron's VPN-as-a-Service (VPNaaS) complements this by provisioning secure tunnels for site-to-site connectivity, enabling private instances to communicate with public cloud resources as if on the same . These deployments offer key benefits, including cost optimization through efficient resource utilization in private environments and burst capacity to clouds during peak demands, such as seasonal workloads. Cloud bursting mechanisms allow automatic scaling to providers like AWS, maintaining performance without overprovisioning on-premises hardware. In 2025, surveys indicate growing adoption, with OpenStack deployments interacting with clouds like AWS to balance and flexibility.

Edge Computing and Telco Applications

OpenStack has emerged as a foundational platform for deployments, enabling low-latency processing closer to data sources in distributed environments. StarlingX, an open-source project under the Open Infrastructure Foundation, integrates OpenStack with to deliver a complete cloud optimized for demanding workloads at remote locations. This combination supports the orchestration of virtual machines and containers in resource-constrained settings, such as industrial or remote sensors, by providing scalable compute and management capabilities without relying on centralized data centers. For lightweight installations at the , Kolla facilitates containerized deployments of OpenStack services using , allowing operators to bootstrap minimal, efficient clusters on bare metal or virtual machines with reduced overhead compared to traditional setups. In telecommunications, OpenStack aligns with ETSI NFV standards through projects like Tacker, which implements a reference for managing virtual network functions (VNFs) in compliance with ETSI specifications for . This enables telcos to deploy and orchestrate VNFs on OpenStack-based infrastructure, with major vendors such as and leveraging it for their NFV platforms to virtualize core elements like EPC and IMS. Key features supporting these telco use cases include integration with Ceph for distributed , which provides scalable, resilient object, block, and file across edge nodes to handle high-throughput data from 5G traffic without single points of failure. Additionally, the Neutron networking service supports real-time capabilities for by enforcing quality-of-service policies on VNFs, enabling isolated networks with tailored and for diverse services like ultra-reliable low-latency communications. Practical deployments illustrate OpenStack's impact in and scenarios. In 2016, expanded its NFV infrastructure using OpenStack across multiple U.S. data centers, which continues to support core functions, integrating with SDN solutions for enhanced and scalability in mobile . For automotive applications, OpenStack powers in autonomous vehicles through multi-access (MEC) architectures, where it orchestrates resources for real-time data processing from vehicle sensors, as demonstrated in a 2019 proof-of-concept combining OpenStack with MANO for low-latency decision-making in self-driving systems. Looking to 2025, OpenStack's integration with ONAP advances orchestration for , allowing seamless multi-cloud management of VNFs and containerized network functions across environments.

Current Adoption and Market Trends

As of 2025, OpenStack has seen widespread adoption, with deployments exceeding 55 million cores in production worldwide, highlighting its scalability for large-scale infrastructures. Major organizations continue to leverage the , including , which operates over one million cores for its private needs; for telecommunications infrastructure; and for scientific computing. Verified usage spans more than 5,000 companies across various sectors, from and to and . The OpenStack services market is valued at approximately $30.11 billion in , reflecting robust demand for open-source solutions, and is projected to reach $120.72 billion by 2030 at a (CAGR) of 32%. It holds a leading position in the private segment, where organizations prioritize customization and vendor independence over public alternatives. Growth is particularly strong in the region, driven by telecommunications providers adopting OpenStack for and edge deployments to handle increasing data demands. Current trends emphasize integration with emerging technologies, including and , which are fueling a projected 20-30% year-over-year increase in deployments for distributed workloads. There is a notable shift toward hybrid models combining OpenStack with for container orchestration, addressing competition from Kubernetes-native platforms while enhancing scalability. Early results from the 2025 OpenStack User Survey indicate accelerating adoption across industries, with users reporting high satisfaction in flexibility and cost efficiency, alongside growing emphasis on sustainable operations through efficient resource management. , for example, uses OpenStack for testing space capsule flight software for the II mission. Looking ahead, experts anticipate OpenStack's sustained relevance in private and clouds, supported by ongoing innovations and its adaptability to AI-driven and applications, ensuring long-term viability amid evolving needs.