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Oracle Enterprise Manager

Oracle Enterprise Manager (OEM) is Oracle's comprehensive management platform that delivers centralized monitoring, administration, and lifecycle management functionality for Oracle databases, engineered systems, , applications, and infrastructure across on-premises, cloud, hybrid, and multicloud environments. Originally introduced in the as a tool for database administration, OEM has evolved into a full suite supporting heterogeneous environments, including non-Oracle technologies, with key components such as the Oracle Management Server, Console, and Intelligent Agents facilitating distributed management. The platform enables administrators to optimize , ensure , and control costs through features like automated , performance diagnostics, and provisioning. Core capabilities of OEM include database performance management for tuning and troubleshooting instances; engineered systems management for and other ; enterprise monitoring with a single for end-to-end visibility; middleware and application management for Oracle Fusion Middleware and third-party apps; and security and compliance tools featuring intelligent threat detection and remediation. Recent advancements in version 24ai, released in 2024, incorporate AI-driven insights and Zero Downtime Patching to enable updates without service interruptions. Earlier iterations, such as OEM 11g Grid Control (2010) and Cloud Control 12c/13c, expanded support for , adoption, and IT resource optimization.

Overview

Purpose and Scope

Oracle Enterprise Manager (OEM) is a web-based suite of tools providing centralized management for databases, , applications, , and services across data centers and multicloud environments. As a modern, AI-powered platform, it enables IT teams to monitor, manage, and optimize both and non-Oracle technologies, including third-party infrastructure through extensible plug-ins that add support for diverse targets without requiring full software upgrades. The core objectives of OEM focus on proactive to detect issues early, automated for routine tasks like patching and provisioning, optimization through diagnostics and recommendations, and enforcement to meet and regulatory standards in on-premise, , and multicloud setups. These goals support scalable operations, reducing and enhancing for large-scale deployments. Inception in 1996 as a basic tool for administration, OEM has expanded its scope from database-centric to a comprehensive enterprise platform, now incorporating AI-driven features in releases like 24ai for advanced and . High-level components such as agents for target and the Oracle Management Service (OMS) as the central console facilitate this broad coverage.

Key Benefits and Use Cases

Oracle Enterprise Manager delivers significant benefits by leveraging to minimize downtime, with organizations reporting up to 40% reductions in unplanned outages through proactive issue resolution. Automated provisioning features further drive cost savings, achieving up to 60% lower operational expenses and reducing provisioning cycle times by 99% in some deployments, from days to minutes. It provides unified visibility across hybrid environments, enabling seamless of on-premises, private cloud, and public cloud resources from a single console. Additionally, it enhances posture through centralized credential , automated assessments, and compliance monitoring to mitigate risks across the IT stack. In enterprise scenarios, Oracle Enterprise Manager excels at managing large-scale Oracle Database fleets, particularly in financial services where it supports compliance by handling over 1,200 instances and reducing incidents by fivefold for regulatory adherence. For performance optimization, it monitors and tunes Exadata engineered systems, providing graphical insights into hardware and software components to ensure high availability and efficiency in mission-critical workloads. It also facilitates hybrid cloud migrations, such as shifting workloads between Oracle Cloud Infrastructure (OCI) and AWS, by offering tools for zero-downtime transitions and multicloud oversight. The platform scales to support thousands of targets per deployment, accommodating petabyte-scale in expansive environments without proportional increases in administrative overhead. In digital transformation efforts, it enables self-service portals that empower teams to provision and manage resources autonomously, accelerating database delivery across hybrid setups. These capabilities, including AI-driven , contribute to overall operational agility.

Historical Development

Early Releases (1996-2006)

Oracle Enterprise Manager (OEM) was launched in 1996 with Oracle7 Release 7.3, providing a graphical user interface (GUI)-based tool for database administration that leveraged Java applets to deliver an intuitive console for managing Oracle databases. This initial release marked a shift from command-line tools to a visual platform, enabling administrators to perform tasks such as backup, recovery, and performance monitoring directly through the OEM Console. Key releases during this period expanded OEM's capabilities significantly. Version 2.0, released in 1998, introduced a web-based interface, allowing users to launch the console applet from a browser and access management functions remotely without requiring a dedicated client installation. The Oracle9i release in 2001 brought the first agent-based architecture, incorporating Oracle Intelligent Agents on managed nodes to enable remote monitoring and distributed task execution across heterogeneous environments. By the Oracle 10g release in 2003, OEM extended support to application server management, integrating tools for configuring and monitoring Oracle Application Server components alongside database operations. Core features introduced in these early versions included basic alerting mechanisms to notify administrators of threshold violations, performance tuning wizards that guided optimization of SQL queries and database parameters, and management capabilities through the OEM Console for creating, altering, and viewing database objects. These elements formed the foundation of OEM's role as an integrated framework, emphasizing ease of use for routine administrative tasks. However, these releases had notable limitations, primarily focusing on single-instance database environments without support for emerging paradigms, and relying on CORBA () for inter-component communication, which could introduce scalability challenges in larger deployments. This set the stage for subsequent evolutions toward multi-instance and scalable architectures.

Grid and Cloud Control Eras (2007-2021)

The Grid Control era of Oracle Enterprise Manager began with significant enhancements in 2007, building on the foundational 10g Release 2 framework to emphasize centralized management of distributed grid environments, including clusters and heterogeneous systems. Oracle Enterprise Manager 10g Grid Control Release 3 (10.2.0.3), released in March 2007, introduced improved support for managing clusters through automated discovery and provisioning capabilities, enabling administrators to handle large-scale Oracle deployments efficiently. A key advancement was the extensibility via plug-ins, which allowed monitoring of non-Oracle targets such as , BEA WebLogic, and , facilitating heterogeneous enterprise management without requiring separate tools. This release addressed early challenges in grid computing by providing to track changes across deployments and enforce compliance, reducing operational silos in multi-vendor data centers. Subsequent updates in 2007, including Release 4 (October 2007) and Release 5, further refined these capabilities with bug fixes and performance optimizations for larger environments, laying the groundwork for scalable across data centers. By 2010, Oracle Enterprise Manager 11g Control Release 1 (11.1.0.1), released in April 2010, enhanced scalability through simplified addition of Oracle Management Service (OMS) instances and support for up to thousands of targets, improving performance in high-volume setups. It introduced advanced (APM) features, such as JVM Diagnostics for real-time Java application monitoring and end-to-end request tracing integrated with , providing deeper insights into application dependencies and bottlenecks. Integration with Oracle Fusion Middleware 11g was strengthened, offering centralized navigation and context-sensitive management for components like SOA Suite and , which streamlined middleware administration in federated setups. support expanded with plug-ins for ESX Server, enabling monitoring of virtual machines and hosts alongside physical infrastructure to address growing adoption of virtualization technologies like . The transition to Cloud Control marked a pivotal shift toward cloud paradigms, with Oracle Enterprise Manager 12c Cloud Control Release 1 (12.1.0.1), released in 2011, rebranding the product to reflect its focus on hybrid . This version introduced provisioning through a dedicated portal, allowing authorized users to deploy databases, , and applications on demand while enforcing centralized policies for and , thus balancing with in private environments. Federated across data centers was bolstered with dynamic resource tracking and lifecycle automation, supporting multitenant architectures and integration with for engineered systems. For environments, plug-ins for Oracle Big Data Appliance and Hadoop distributions enabled monitoring of clusters, , and , tackling challenges in distributed . By 2021, Oracle Enterprise Manager Cloud Control 13c Release 5 (13.5.0.0), released on April 27, 2021, culminated this era with advanced for predictive insights and multicloud support, allowing unified management of on-premises, , and third-party clouds like AWS and without multiple consoles. Features included operational for in application performance and resource utilization, enhancing APM with in logs and metrics to preempt issues in complex environments. Integration with Fusion Middleware evolved to support containerized deployments, while and handling matured with automated patching for VMware-integrated setups and for Hadoop/ ecosystems, addressing complexities. These developments provided a robust for subsequent AI-driven enhancements in later versions.

AI-Driven Modern Versions (2022-Present)

Oracle Enterprise Manager transitioned toward integration beginning with enhancements in the 13c release updates around 2022, introducing initial capabilities to proactively identify unusual patterns in system performance and resource utilization. This built on the multicloud foundations of prior Cloud Control versions, extending monitoring to hybrid environments with early -driven insights for faster issue resolution. By 2024, the platform underwent a significant and evolution with the release of Oracle Enterprise Manager 24ai Release 1 in December 2024, positioning it as a fully -powered solution for Oracle databases, engineered systems, and hybrid deployments. Key updates in 2025 further advanced the platform's AI capabilities, including 24ai Update 3, released in July 2025, which introduced the Database Fleet Page for enterprise-wide visibility into database health and performance metrics, alongside AWR monitoring for standby databases to ensure comprehensive coverage in high-availability setups. Additionally, Zero Downtime Patching was announced in May 2025, enabling seamless application of release updates to the Oracle Management Service without interrupting monitoring or management operations, thereby supporting continuous availability in production environments. As of November 2025, the latest update is 24ai Release 1 Update 5, released in September 2025, providing ongoing patches and stability improvements. These enhancements addressed gaps in post-2021 coverage by emphasizing AI's role in managing modern hybrid clouds, where disparate on-premises and cloud resources require unified, intelligent oversight. Central to the AI-driven features in these modern versions is AI-powered SQL tuning, which leverages up to 25 months of historical performance data from Automatic Workload Repository (AWR) snapshots to provide deeper insights and recommendations for query optimization. Predictive employs models to forecast resource needs, identify over- or under-provisioned systems, and support seasonal workload trends across infrastructures. Furthermore, with the Autonomous Health Framework allows for automated diagnostics and proactive management of engineered systems, using AI to detect and resolve potential issues before they impact operations. These capabilities collectively enable organizations to modernize database and cloud management with reduced manual intervention and enhanced scalability.

Core Architecture and Components

Management Agents and Oracle Management Service

Oracle Management Agents are lightweight processes deployed on managed hosts to monitor , collect performance metrics, and execute administrative tasks such as starting or stopping . These agents act as proxies between the hosts and the central , identifying , detecting issues like high CPU usage, and pushing collected data to the Management Service (OMS). In Enterprise Manager 24ai, Remote Agents were introduced as a new type that enables remote monitoring and management of , such as , from dedicated hosts, supporting through agent pools. Communication occurs via HTTP or protocols, with recommended for secure, encrypted transmission and using SSL. Agents primarily operate in a push model, proactively uploading metrics and status information at configured intervals, though they can respond to pull requests for specific data. The Oracle Management Service (OMS) serves as the middle-tier application in the Enterprise Manager , built on to orchestrate agent interactions, process incoming data, and facilitate management operations across the enterprise. In 24ai, the OMS adopts a multi-container-based , enabling zero-downtime updates and improved . It handles agent registrations, job dispatching and execution, event processing, alerting, and user authentication, consolidating metrics from distributed agents for centralized analysis. The OMS is designed for , supporting deployments with thousands of agents and through clustering and load balancing configurations. For instance, configurations can accommodate large environments with multiple OMS instances managing up to millions of overall as of 2025. In the architecture flow, Management Agents gather data from monitored hosts and , then push it to the OMS over secure channels; the OMS processes this information, applies rules for alerts and , and stores it in the Management Repository for persistence and querying. A key feature is the framework, which allows extension of capabilities for or third-party by deploying modular plug-ins to both OMS and agents, enabling metric collection, alerting, and without core system upgrades. Over time, the communication and mechanisms in Enterprise Manager have evolved; early releases like 9i relied on CORBA standards for and third-party tool , while modern versions such as 24ai leverage for efficient, web-based interactions and extensibility. This shift supports contemporary cloud-native and hybrid environments with improved performance and security.

Repository Database and Console Interface

The Repository Database serves as the centralized data storage backbone for Oracle Enterprise Manager, implemented as a dedicated instance that houses configuration details, performance metrics, monitoring alerts, and historical data collected across managed environments. This repository utilizes the SYSMAN schema as its primary structure, which encapsulates all , information, and operational records essential for Manager's functionality. In large-scale deployments, the repository supports table partitioning to optimize query performance and manage data growth, enabling efficient aggregation of metrics by time intervals such as hourly or daily to reduce storage overhead while maintaining accessibility. Key schemas within the include SYSMAN for core management and the MGMT$ family of views, which facilitate querying of , metrics, and incident without direct to underlying tables, ensuring controlled and performant retrieval for administrative tasks. strategies for the emphasize the use of Recovery Manager (RMAN), which provides automated, incremental backups of the database to safeguard against loss and support , integrated directly through Enterprise Manager's scheduling capabilities. The Console Interface, known as the EM Console, is a web-based that enables administrators to interact with the repository data through intuitive visualizations and controls. It features customizable dashboards for real-time overviews of system health, topology views to map relationships between managed targets such as and hosts, and navigation tools for drilling down into specific metrics or incidents. Access to the console is governed by role-based security, providing fine-grained privileges through predefined roles like EMDADMIN, which grants full administrative control over operations and console features, while other roles limit scope to or basic to enforce least-privilege principles. In Oracle Enterprise Manager 24ai, the console has evolved to incorporate AI-driven visualizations, such as predictive analytics dashboards and natural language query interfaces like "Ask EM," enhancing user interaction with repository data through generative AI for faster insights and automated recommendations.

Primary Functionality

Monitoring and Diagnostics

Oracle Enterprise Manager provides robust monitoring capabilities through its Management Agents, which collect performance and health metrics from targets such as databases, hosts, and applications. These agents gather data on key indicators like CPU utilization, I/O throughput, and memory usage at configurable intervals, enabling real-time visibility into system performance. Thresholds are defined for these metrics to detect deviations, where warning or critical levels trigger events when values exceed specified limits, such as high CPU load surpassing 80% for sustained periods. Blackouts allow administrators to temporarily suspend metric collection and alerting on selected targets during planned maintenance, preventing false alarms from routine operations like patching. Each target type supports a comprehensive set of over 100 default metrics out-of-the-box, covering aspects from hardware utilization to application-specific behaviors, with the option to extend via custom metric templates. Diagnostics in Oracle Enterprise Manager center on , where events and violations are automatically grouped into incidents for streamlined troubleshooting. The tool integrates diagnostic packs, such as the Diagnostics Pack for , which provides automated analysis tools including and historical for issues like excessive CPU usage. is facilitated by the Automatic Database Diagnostic Monitor (ADDM), an embedded engine that periodically evaluates database snapshots to identify bottlenecks, such as inefficient SQL statements or , and suggests corrective actions. Alerting mechanisms ensure timely notifications by routing incidents via , SNMP traps, or custom scripts when thresholds are breached. policies automatically increase incident priority and notify additional recipients or integrate with external ticketing systems, such as opening helpdesk tickets, based on severity and response time. In Oracle Enterprise Manager 24ai, AI enhancements introduce machine learning-based anomaly detection that identifies unusual patterns in metrics without requiring manual threshold configuration, improving proactive issue resolution through embedded AI/ML models.

Administration and Automation

Oracle Enterprise Manager provides robust administration capabilities that streamline database maintenance tasks, including patch management, which automates the application of updates and upgrades across Oracle databases and engineered systems to ensure security and performance. In version 24ai (released in 2024), Zero Downtime Patching enables updates to the Oracle Management Service and Repository without interrupting operations, minimizing service disruptions. Patch management in Enterprise Manager uses tools like the Patch Advisor to recommend and deploy patches, supporting both single-instance and clustered environments through guided workflows that minimize downtime. Backup and recovery orchestration is facilitated via integration with Oracle Recovery Manager (RMAN), allowing administrators to schedule, monitor, and execute backups while coordinating recovery operations across multiple targets from a centralized console. Schema comparisons enable the identification of differences in database object definitions between baselines, databases, or schemas, helping administrators detect configuration drifts and ensure consistency. Wizards for database cloning simplify the creation of full clones or pluggable databases, supporting methods like RMAN backups or snap clones for rapid provisioning without extensive manual intervention. Building on monitoring alerts from diagnostics, administration features in Enterprise Manager automate responses to identified issues, such as triggering deployments or actions based on predefined thresholds. Automation is enhanced through the Enterprise Manager Command Line Interface (EMCLI), a scripting tool that allows users to perform operations like target and deployment via command-line verbs or scripts, enabling integration with external automation . Provisioning and deployment packs, part of the lifecycle , facilitate rapid by automating the mass deployment of software stacks, , or applications across hosts, using procedures that ensure repeatable and reliable setups. Job scheduling supports complex workflows with dependencies, allowing administrators to define sequences where jobs execute only after prerequisites are met, such as running a before a clone operation. The Application Management Pack extends these capabilities for end-to-end lifecycle management of , including deployment, patching, and configuration, while supporting idempotent operations that allow procedures to be executed multiple times without unintended side effects. These automation features contribute to significant reductions in manual tasks; for instance, the Provisioning and Automation Pack reduces labor-intensive activities like software . Automated checks, integrated into workflows, further minimize manual verification efforts by proactively validating configurations against standards.

Deployment and Implementation

Installation and Configuration Processes

The installation of Oracle Enterprise Manager (EM) 24ai Release 1 begins with downloading the software from the Oracle Technology Network (OTN), available for x86-64 and Windows x86-64 platforms as self-extracting binaries or executables. Prerequisites include a certified operating system such as 8 or later, or or later, with sufficient hardware resources; for a small deployment, the Oracle Management Service (OMS) requires at least 4 CPU cores, 10 GB RAM, and 28 GB disk space, while the Management Repository database needs 19c Release Update 19.22 or later, configured as a pluggable database (PDB) or non-container database (non-CDB) with Oracle Text enabled for certain features. The installer includes JDK 1.8.0_431 and 12.2.1.4.0, eliminating the need for separate Java installations, though users must ensure the database parameters like _allow_insert_with_update_check=true are set. Running the EM Prerequisite Kit is recommended prior to installation to validate repository compatibility. Installation proceeds via the Universal Installer (OUI), launched by executing em24100_linux64.bin on or setup_em24100_win64.exe on Windows, requiring or administrator privileges. Two modes are available: simple for environments, limited to up to 30 with 2 agents and default settings; and advanced for , allowing of deployment (small: up to 999 and 99 agents; medium: 1,000–9,999 and 100–999 agents; large: 10,000+ and 1,000+ agents), plug-in selection, WebLogic credentials, database connection details (using or a non-SYS user with privileges), and locations. During advanced setup, users specify the home and agent base directory outside it, review assignments (customizable via staticports.ini), and execute scripts like allroot.sh on Unix systems post-; the process creates the OMS, deploys a default agent on the host, and configures the repository schema. Post-installation configuration involves securing and starting the OMS using emctl secure oms and emctl start oms commands, verifying status with emctl status oms, and deploying additional agents either manually via OUI or through the Enterprise Manager Command Line Interface (EMCLI). EMCLI, installed with EM, facilitates bulk operations such as syncing configurations (emcli sync) and discovering targets by adding hosts, databases, or other managed entities via commands like emcli add_target after with emcli login -username=sysman. Target discovery can also occur through the EM Console at the URL (default port range 7799–7809), where administrators promote the default agent and scan for resources. For , OMS clustering is configured post-installation using a Server Load Balancer (SLB) and additional OMS instances, following guidelines in the advanced configuration documentation, which includes setting up shared and mechanisms. Best practices emphasize matching to deployment size—for instance, allocating at least 10 GB for a small OMS to handle baseline loads—and configuring firewalls to open essential ports such as 4889–4898 for HTTP uploads to OMS, 1159 or 4899–4908 for HTTPS uploads, 3872 or 1830–1849 for agent uploads, and 7799–7809 for the HTTPS Console, ensuring no conflicts via tools like netstat. Sizing should also consider repository growth, with small deployments requiring 147 GB initial disk space. Common troubleshooting issues include repository connectivity failures, resolved by verifying the password, ensuring REMOTE_LOGIN_PASSWORDFILE is set to SHARED or EXCLUSIVE in the database, and confirming the password file (orapw<SID>) exists; logs in <ORACLE_HOME>/install/setupinfo.txt provide details on configuration assistant errors. Port conflicts can be addressed by customizing assignments during OUI or post-install via emctl, and prerequisite failures may require rerunning the Prerequisite Kit or adjusting database parameters. This initial setup enables integration with existing databases, as detailed in subsequent configuration steps.

Integration with Oracle and Third-Party Systems

Oracle Enterprise Manager (OEM) provides seamless integration with key Oracle technologies, enabling unified management across Oracle Cloud Infrastructure (OCI), Exadata engineered systems, and Fusion Applications. For OCI, OEM facilitates data transfer to OCI services like Object Storage and integrates with OCI Observability for enhanced monitoring and analytics, allowing users to upload management data directly from OEM to OCI for further processing. With Exadata, OEM offers specialized management packs that provide high-level integration for incident rules, notifications, and performance monitoring of Exadata Cloud systems, including database metrics and tuning capabilities. Integration with Oracle Fusion Applications is achieved through the Application Management Suite for Fusion Applications, which leverages OEM's framework to monitor and manage Fusion instances, including custom metrics, alerts, and service-level management. OEM extends its reach to third-party systems via plug-ins and connectors that support multi-cloud and heterogeneous environments. It includes plug-ins for monitoring resources on (AWS), , and Google Cloud, allowing discovery and management of Oracle databases deployed in these platforms. For container orchestration, OEM supports monitoring of environments, particularly for domains running on clusters, using agents to collect performance data. Additionally, OEM provides plug-ins for non-Oracle databases such as , enabling remote monitoring without requiring agents on every MySQL server. The Enterprise Manager (EMCLI) further enhances integrations by supporting API calls, permitting automation and connectivity with external tools for custom scripting and workflows. OEM utilizes standard protocols to connect with hardware and external systems, ensuring broad compatibility. It supports (SNMP) for integrating with third-party management consoles, sharing event data via SNMP traps, and extending monitoring to network devices and hardware. For database connectivity, OEM employs (JDBC) to interface with external databases, facilitating queries and data retrieval from non-Oracle sources. Federation capabilities allow OEM to integrate with tools like , where OEM metrics and logs can be forwarded to Splunk for advanced analytics and visualization, often configured through connectors that pull data from the OEM repository. In cloud scenarios, OEM enables comprehensive monitoring of databases running on AWS EC2 instances alongside on-premises or OCI resources. For instance, administrators can deploy OEM Management Agents on AWS EC2 to discover and monitor databases, collecting metrics on performance, availability, and compliance, while using the central OEM console for unified views and automated responses across the setup.

Advanced Capabilities

and Environment

Oracle Enterprise Manager (OEM) provides robust support for managing cloud environments through deep integration with (OCI), enabling seamless administration of autonomous databases. This integration allows users to deploy and monitor Autonomous Database instances directly from the OEM console, leveraging OCI's native APIs for automated provisioning and scaling. For instance, the Hybrid Database-as-a-Service (DBaaS) feature facilitates self-service deployment of autonomous databases on OCI, including virtual machines, bare metal, and Exadata configurations, ensuring consistent governance across cloud resources. In multicloud scenarios, OEM offers unified dashboards to monitor and manage Oracle databases hosted on AWS, , and (GCP), alongside OCI and on-premises targets. These dashboards provide a single pane of glass for visibility into performance metrics, configuration compliance, and resource utilization across heterogeneous environments, reducing operational silos. OEM 24ai enhances this with fleet-scale management capabilities, particularly for Exadata Cloud@Customer, where it supports centralized monitoring of hardware and software configurations across distributed deployments. For hybrid management, OEM delivers unified views of on-premises and cloud targets, allowing administrators to oversee mixed infrastructures without switching tools. The Database Migration Workbench streamlines migrations from on-premises databases to OCI, supporting methods like Data Pump, RMAN, and Zero Downtime Migration, with built-in assessment, execution, and post-migration validation. Key features include auto-scaling policies for dynamic resource adjustment in DBaaS setups and cost optimization analytics via metering, which tracks usage and generates reports to identify inefficiencies. Additionally, OEM supports containerized applications through plug-ins for environments, such as Oracle Container Engine for Kubernetes (OKE), enabling monitoring of WebLogic domains and other workloads in container-orchestrated setups.

AI-Powered Analytics and Security Features

Oracle Enterprise Manager (OEM) incorporates models for across key metrics, enabling proactive identification of unusual patterns in database and infrastructure performance. These models analyze telemetry data in , integrating with Stack Monitoring to cover resources like Prometheus-based services and OCI components such as Load Balancers and Block Storage. In OEM 24ai, SQL insights leverage historical Automatic Workload Repository (AWR) data retained for up to 25 months via the Operations Insights (OPSI) retention period, allowing administrators to visualize trends, wait events, and comparative analyses without relying on individual AWR reports. This facilitates root-cause analysis of suboptimally performing SQL statements using AI-driven recommendations from the SQL Tuning Advisor. Predictive forecasting for uses historical data to project resource needs, supporting proactive scaling in environments like Exadata Cloud. A notable advancement in OEM 24ai Release Update 4 (as of August 2025) is the "Ask EM" GenAI assistant, which enables queries for , diagnostics, and troubleshooting, enhancing user interaction with AI-powered . OEM's security features include vulnerability scanning through integration with the Database Security Assessment Tool (DBSAT) 4.0, which automates assessments across database estates to identify risks and sensitive data exposure at scale. Compliance reporting is enabled via prebuilt templates and standards for regulations such as GDPR and , utilizing the Audit Vault and (AVDF) for activity summaries, data privacy reports, and audit logs exportable in XML format. OEM adheres to Zero Trust principles through enforcement of least privilege, , and fine-grained access controls, complemented by support for (MFA) via and 2FA configurations for user logins. For Autonomous Databases, OEM automates security patching workflows using named credentials and Fleet Maintenance, ensuring timely application of updates without manual intervention while maintaining via TLS and SSH keys. In OEM 24ai, innovations include guided discovery for Autonomous Databases to monitor resource usage and integrate with Oracle Key Vault for credential management.

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