Skip to main content

Oracle Enterprise Manager 13c Release 5 Announced

Oracle announced the availability of Oracle Enterprise Manager 13c Release 5.

Oracle Enterprise Manager (EM) is the flagship management product for the Oracle stack.

Features include:

- Hyper-scale observability & management: A single EM deployment can scale up to monitor and manage millions of targets. In addition to hyper scalability, EM provides smart features and approaches to manage at scale including Dynamic Groups, Monitoring Templates, Event Compression, and more. You cannot practically manage large environments without utilizing such features.

- Integrated full-stack management: EM provides in-depth management of the entire Oracle stack. We call this application-to-SSD monitoring and management – covering packaged applications such as E-Business Suite, PeopleSoft, and Siebel, custom-built apps, middle tier/application server, database, operating system, and virtual infrastructure.

- EM also provides comprehensive support for Oracle Engineered Systems such as Oracle Exadata, Oracle Database Appliance (ODA), Zero Data Loss Recovery Appliance (ZDLRA), and Private Cloud Appliance (PCA)—supporting integrated hardware and software monitoring and management of these systems as well as lifecycle management of the databases running on Exadata, PCA, and ODA.

- Hybrid Cloud Management: With this new release of Enterprise Manager, you can manage targets running anywhere, on-premises, or in the cloud. You don’t need to learn or deploy new tools. Your existing best practices, scripts and jobs can be applied to cloud resources just like on-premises resources. Specifically, for Oracle Cloud Infrastructure (OCI) resources, EM understands the native cloud APIs for management operations and leverages them to provide a seamless experience. If you are using or are considering using Oracle Cloud databases, you can comprehensively manage them with EM.

- EM Hybrid Database-as-a-Service now supports self-service provisioning across on-premises and OCI (VM, Baremetal, Exadata Cloud Service and Exadata Cloud@Customer) and provides self-service governance tools for effective cloud resource utilization.

- Database Migration Workbench provides a complete platform to help DBAs move databases between on-premises and OCI. This workbench helps you plan the migration, performs pre-requisite checks to make sure that migration can occur successfully, then selects the best data movement technology (e.g., Data Pump, RMAN, etc.) based on the source and target choices, such as database versions and type of database, and then executes the actual migration plan. Post-migration, it uses the SQL Performance Analyzer feature to make sure your workload on the migrated platform will perform well. If any performance regressions are detected, it reports them to you so that you can take proactive actions before opening up the database for end-users.

- OCI bridge is a new feature you can think of that as a connection from EM to Oracle Cloud. The bridge is used to copy data from the EM repository and the targets it manages to the designated OCI object store, where it is accessed by OCI services such as Logging Analytics and Operations Insights. These cloud services provide deep analytics and identify data patterns which can help prevent outages and achieve better application and database performance regardless of where your databases are deployed.

Oracle EM also delivers several new capabilities in this release that will enable better operations automation:

- Smart Event Compression automatically groups multiple separate but related events into a single incident. For example, when a host goes down, the resulting availability events on the host and all targets on that host will be automatically compressed into a single incident. Working with a smaller set of actionable incidents enables Operations teams to better triage, respond, and manage incidents.

- Dynamic Runbooks speed up incident resolution by encapsulating subject matter expertise for diagnosing and resolving incidents into actionable Runbook procedures in EM. In this release, these teams can create these runbook procedures directly inside EM. This allows teams to encapsulate in EM their operational expertise in diagnosing and resolving incidents. When an incident is raised, IT Ops teams have easy access to the appropriate runbook, and can quickly execute the specified procedures. These procedures can dynamically invoke metric charts or execute an SQL or an OS command. This promotes more consistent and faster incident response times, and reduces overall Mean-Time-To-Recovery (MTTR).

- In the area of performance management, Oracle introduced a new feature called Automatic Workload Analysis. With this feature, EM constantly compares the current database performance with the baseline workload, and any divergence from this baseline is highlighted on the database home page. Examples of changes highlighted include:
* Regressed SQL statements and their quantified impact on the workload
* Reasons for regression, e.g., plan changes, increased I/O, CPU, etc.
* New SQL statements and their impact

A number of new enhancements improve the self-diagnostics capabilities of EM and provide proactive health monitoring of the various EM subsystems:

- New Job Diagnostics dashboards drill down into the performance and real-time status of the jobs running in or blocking the system. This includes what jobs are being retried, what job queues are blocked and why.

- Compliance standards for maintaining the health of EM sites with sizing recommendations for Oracle Management Service (OMS) and EM Repository, based on workloads running on the system.

- Oracle is making EM patching simpler and more agile. In this release, they consolidated the distributed agent patches into one single system patch for an agent. The agent system patch will include the Agent Platform and Agent Plug-in patches in one bundle. The benefits of using Agent System Patch are reduced overhead and greater agility for staying current with agent patches.

The Latest

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

Oracle Enterprise Manager 13c Release 5 Announced

Oracle announced the availability of Oracle Enterprise Manager 13c Release 5.

Oracle Enterprise Manager (EM) is the flagship management product for the Oracle stack.

Features include:

- Hyper-scale observability & management: A single EM deployment can scale up to monitor and manage millions of targets. In addition to hyper scalability, EM provides smart features and approaches to manage at scale including Dynamic Groups, Monitoring Templates, Event Compression, and more. You cannot practically manage large environments without utilizing such features.

- Integrated full-stack management: EM provides in-depth management of the entire Oracle stack. We call this application-to-SSD monitoring and management – covering packaged applications such as E-Business Suite, PeopleSoft, and Siebel, custom-built apps, middle tier/application server, database, operating system, and virtual infrastructure.

- EM also provides comprehensive support for Oracle Engineered Systems such as Oracle Exadata, Oracle Database Appliance (ODA), Zero Data Loss Recovery Appliance (ZDLRA), and Private Cloud Appliance (PCA)—supporting integrated hardware and software monitoring and management of these systems as well as lifecycle management of the databases running on Exadata, PCA, and ODA.

- Hybrid Cloud Management: With this new release of Enterprise Manager, you can manage targets running anywhere, on-premises, or in the cloud. You don’t need to learn or deploy new tools. Your existing best practices, scripts and jobs can be applied to cloud resources just like on-premises resources. Specifically, for Oracle Cloud Infrastructure (OCI) resources, EM understands the native cloud APIs for management operations and leverages them to provide a seamless experience. If you are using or are considering using Oracle Cloud databases, you can comprehensively manage them with EM.

- EM Hybrid Database-as-a-Service now supports self-service provisioning across on-premises and OCI (VM, Baremetal, Exadata Cloud Service and Exadata Cloud@Customer) and provides self-service governance tools for effective cloud resource utilization.

- Database Migration Workbench provides a complete platform to help DBAs move databases between on-premises and OCI. This workbench helps you plan the migration, performs pre-requisite checks to make sure that migration can occur successfully, then selects the best data movement technology (e.g., Data Pump, RMAN, etc.) based on the source and target choices, such as database versions and type of database, and then executes the actual migration plan. Post-migration, it uses the SQL Performance Analyzer feature to make sure your workload on the migrated platform will perform well. If any performance regressions are detected, it reports them to you so that you can take proactive actions before opening up the database for end-users.

- OCI bridge is a new feature you can think of that as a connection from EM to Oracle Cloud. The bridge is used to copy data from the EM repository and the targets it manages to the designated OCI object store, where it is accessed by OCI services such as Logging Analytics and Operations Insights. These cloud services provide deep analytics and identify data patterns which can help prevent outages and achieve better application and database performance regardless of where your databases are deployed.

Oracle EM also delivers several new capabilities in this release that will enable better operations automation:

- Smart Event Compression automatically groups multiple separate but related events into a single incident. For example, when a host goes down, the resulting availability events on the host and all targets on that host will be automatically compressed into a single incident. Working with a smaller set of actionable incidents enables Operations teams to better triage, respond, and manage incidents.

- Dynamic Runbooks speed up incident resolution by encapsulating subject matter expertise for diagnosing and resolving incidents into actionable Runbook procedures in EM. In this release, these teams can create these runbook procedures directly inside EM. This allows teams to encapsulate in EM their operational expertise in diagnosing and resolving incidents. When an incident is raised, IT Ops teams have easy access to the appropriate runbook, and can quickly execute the specified procedures. These procedures can dynamically invoke metric charts or execute an SQL or an OS command. This promotes more consistent and faster incident response times, and reduces overall Mean-Time-To-Recovery (MTTR).

- In the area of performance management, Oracle introduced a new feature called Automatic Workload Analysis. With this feature, EM constantly compares the current database performance with the baseline workload, and any divergence from this baseline is highlighted on the database home page. Examples of changes highlighted include:
* Regressed SQL statements and their quantified impact on the workload
* Reasons for regression, e.g., plan changes, increased I/O, CPU, etc.
* New SQL statements and their impact

A number of new enhancements improve the self-diagnostics capabilities of EM and provide proactive health monitoring of the various EM subsystems:

- New Job Diagnostics dashboards drill down into the performance and real-time status of the jobs running in or blocking the system. This includes what jobs are being retried, what job queues are blocked and why.

- Compliance standards for maintaining the health of EM sites with sizing recommendations for Oracle Management Service (OMS) and EM Repository, based on workloads running on the system.

- Oracle is making EM patching simpler and more agile. In this release, they consolidated the distributed agent patches into one single system patch for an agent. The agent system patch will include the Agent Platform and Agent Plug-in patches in one bundle. The benefits of using Agent System Patch are reduced overhead and greater agility for staying current with agent patches.

The Latest

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...