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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchA move from on-premises systems to Amazon EKS works best when release checks happen before deployment and production evidence remains connected across the migration boundary. AWS DevOps Agent can review and test changes in a preview release-management capability, investigate configured production systems—including EKS clusters through read-only access—and use recurring incident patterns to inform later release checks. What it sees depends on the integrations and permissions your team configures.
How do I connect on-premises context to an EKS migration?
Plan the agent’s visibility around the systems your team already uses, rather than assuming it has universal access to on-premises hosts. AWS describes integrations with observability, ticketing, chat, webhooks, and private MCP servers. These connections can bring relevant telemetry and operational context together with AWS-side information.
AWS lists CloudWatch, Datadog, Dynatrace, Grafana, New Relic, and Splunk as telemetry options, and ServiceNow, PagerDuty, and Slack among ticketing and chat integrations. Available integrations and what they expose depend on configuration and permissions. See AWS’s integrations and knowledge guide, its production operations guide, and the AWS DevOps Agent FAQs.
Before relying on the agent during a migration, map the systems that hold the evidence needed to understand a service: monitoring, logs and traces, alerting, tickets, source changes, and deployment history. Connect the relevant sources, then confirm that the configured integrations expose the services and signals the team needs. An integration is a visibility path, not proof that every dependency or host is automatically discoverable.
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How do I validate an EKS release before it reaches production?
AWS labels release management a preview capability. Its documented workflow can review code changes, assess dependency risks and standards or practices, run builds and tests in a verification environment, and run QA tests in an integration environment. Teams can invoke release workflows from IDEs, pull or merge requests, CI/CD, or chat; the exact checks depend on the workflow and environments configured. AWS describes this lifecycle in Working with DevOps Agent.
- Choose the delivery point. Decide whether a review should be initiated from a pull or merge request, an IDE, a pipeline, or chat, and connect the relevant workflow.
- Make the validation environment representative. Configure the verification and integration environments where builds, tests, and QA checks will run. The documented capability does not establish a universal test suite or guarantee a particular depth of coverage.
- Use findings as a release input. Review flagged dependencies, standards, build or test outcomes, and QA results alongside the team’s normal release criteria. Treat the agent as a validation aid, not as an automatic production approval.
For an on-premises-to-EKS transition, the practical aim is to bring relevant migration risks into the same review path as code changes: for example, risks the team has observed in production can inform what the release workflow checks. The scope of any such check depends on the connected sources and configured process.
Can AWS DevOps Agent investigate a private EKS cluster?
Yes. AWS documents access to public and private EKS clusters. An administrator must configure an EKS authentication mode that includes the EKS API and create an IAM access entry for the Agent Space role. AWS says any number of EKS clusters can be connected to the same Agent Space. Access can be cluster-wide or restricted to namespaces.
The documented boundary is read-only: the agent can use kubectl to inspect Kubernetes resources, pod logs, events, and node health, but cannot create, modify, or delete cluster resources. AWS’s setup instructions reference the managed AmazonAIOpsAssistantPolicy for the EKS access entry. Review the current AWS EKS access setup and your role and cluster permissions before connecting a cluster.
Read-only investigation can help gather evidence without granting the agent authority to remediate a workload by changing cluster state. It does not remove the need to configure the right scope: namespace restrictions can limit which workloads are visible to the investigation.
Why might Kubernetes API throttling be hard to spot?
“Throttling” can describe different bottlenecks, and a quiet application dashboard does not by itself identify which one is occurring. When requests slow or fail, separate at least these possibilities:
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- AWS DevOps Agent service concurrency limits: these constrain how many agent operations can run at once; they are not Kubernetes API server limits.
- Kubernetes API server or API Priority and Fairness behavior: control-plane request load and priority-level concurrency can affect Kubernetes API requests.
- Application or dependency rate limits: an application or an external service may reject or delay requests under its own throttling policy.
AWS’s quotas page lists default concurrent-operation limits per Agent Space. Unless otherwise specified, quotas are Region-specific; some are adjustable, and AWS says a quota increase can take hours to days and is not granted immediately. Check the current regional quota before planning capacity.
| Agent Space operation | Default concurrent limit | What it limits |
|---|---|---|
| Incident investigations | 3 | Concurrent investigations by AWS DevOps Agent |
| On-demand chat invocations | 10 | Concurrent on-demand chat invocations |
| Release readiness reviews | 4 | Concurrent release readiness reviews |
These are service concurrency quotas, not Kubernetes API throttling thresholds. Values are the defaults listed on the AWS DevOps Agent quotas page, accessed October 5, 2026; check that page for current Region-specific limits and adjustment options.
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An AWS Containers Blog walkthrough illustrates how an EKS control-plane investigation can correlate CloudWatch metrics, EKS audit logs, CloudTrail, pod logs, and cluster state. In that example, AWS attributed a performance issue to request load and priority-level concurrency saturation. It is an example investigation, not a benchmark or evidence that every throttling issue will be detected or have the same cause. See Diagnose Kubernetes Control Plane Performance Issues with AWS DevOps Agent.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How do I capture an EKS incident before evidence disappears?
Connect the alerting and operational systems that hold the incident trail, then trigger an investigation from a connected alerting source, a webhook, or a manual request. AWS describes production investigations that correlate metrics, logs, traces, code changes, and deployment history through an application topology built from connected accounts and integrations.
That correlation can help an investigator relate a symptom to a recent deployment or code change and inspect the associated EKS evidence, such as pod logs, events, and node health, when the required access is configured. It does not guarantee that every relevant signal is available: a missing integration, insufficient permission, or unconnected dependency limits the context. AWS’s production operations guide describes the investigation workflow and trigger options.
For incident capture, the operational value is preserving related evidence in one investigation rather than relying only on a single alert or an application-level symptom. The investigation is evidence gathering and diagnosis; EKS access remains read-only.
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How can production incidents improve later release checks?
AWS describes a feedback loop from operations to release readiness. Incident patterns can inform recommendations; a recommendation can be turned into an agent-ready implementation specification; and topology information can contribute to dependency analysis in later reviews. The intent is to make recurring production lessons usable in future development and release workflows, not to treat every incident as an automatically approved code change.
AWS says production-prevention evaluations run weekly by default and can also be run manually. Recommendations may cover observability, infrastructure, governance, and code optimization. Teams can review the findings, decide which changes belong in their standards or tests, and then incorporate suitable checks into the release workflow. See AWS’s proactive incident prevention guide.
This closes the migration loop: connect the operational sources that span on-premises and EKS, validate changes before release, use configured read-only access to investigate production evidence, and convert useful recurring findings into deliberate future guardrails. AWS’s published workflow describes capabilities and examples, not an independently established reduction in incidents, release defects, or mean time to resolution.
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