Argo Workflows

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Coverage Matrix

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Argo Workflows Overview

Argo Workflows is a Kubernetes-native workflow engine that uses CRDs to define multi-step processes as directed acyclic graphs. It’s widely adopted for automating CI/CD pipelines, ML tasks, and data processing at scale. By offloading orchestration logic onto Kubernetes, Argo Workflows simplifies operational overhead. Its design allows dynamic scaling, native container isolation, and extensive integration with CNCF projects. As a CNCF graduated project, it adheres to cloud-native best practices for performance and reliability.

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Chkk Coverage

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Curated Release Notes

Staying on top of Argo Workflows release changes is critical, especially since Argo does not strictly adhere to semantic versioning and even minor releases may introduce breaking changes. Chkk curates the upstream Argo Workflows release notes into an actionable summary for your team. This means you’ll see highlights of new features, critical bug fixes, security patches, and any breaking changes or deprecations that could affect your workflows. This flags new features, critical fixes, or removed APIs that could impact your workflow executions.

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Preflight & Postflight Checks

Upgrading Argo Workflows can be risky without thorough validation. Chkk performs automated preflight checks to ensure your environment is ready for the new version. After the upgrade, postflight checks confirm that the Argo Workflows controller and related components are healthy and functioning. Chkk will verify that the new controller pod is running with the expected version, all CRDs have been upgraded successfully, and existing workflows (including any cron schedules) continue to run without errors.

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Version Recommendations

Chkk continuously monitors Argo Workflows release cycles and support timelines to help you stay on a safe version. The Argo project maintains active support only for the most recent two minor releases, which means running an older version could leave you without patches or security fixes. Chkk keeps track of when your current Argo Workflows version is approaching end-of-life. It will alert you if you’re on an outdated release stream and recommend a target version to upgrade to that is both stable and compatible with your Kubernetes cluster.

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Upgrade Templates

To simplify the upgrade process, Chkk provides Upgrade Templates for Argo Workflows. For in-place upgrades, Chkk walks you through each step in the sequence: applying CRD updates, upgrading the controller deployment, and restarting the Argo server/UI if present. For a blue-green upgrade, Chkk helps you deploy a new instance of Argo Workflows (a “green” controller) alongside the old (“blue”) one. The goal is to run the old and new versions in parallel, allowing you to gradually direct non-critical workflows to the new controller and observe results. Once the new version is proven stable (i.e., workflows are running successfully under the new controller), you can promote it to replace the old version for all workflows. In both scenarios, Chkk’s templates build safety checks and rollback procedures at each stage.

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Preverification

One of Chkk’s most powerful features is the ability to simulate an Argo Workflows upgrade in a digital twin environment before it goes to the production cluster. Chkk runs an isolated instance that mirrors your cluster’s Argo Workflows setup - including the same version of Kubernetes and similar Argo configurations - and then applies the upgrade there first. During this simulation, Chkk checks for any compatibility problems. By catching CRD conflicts, performance regressions, or logic changes in this sandbox environment, Chkk ensures you only proceed with the real upgrade once you have certainty that it will succeed.

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Supported Packages

It has built-in support for deployments via Helm charts, Kustomize overlays, or plain Kubernetes YAML manifests. Upon connecting to your cluster, Chkk auto-detects the installation method and tracks the current Argo Workflows version and manifest source. It preserves custom configurations, images, and private registry references within your workflows.

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Common Operational Considerations

• Workflow Execution Performance: Large, concurrent workflow runs can overload the Kubernetes API and the workflow controller. Offloading logs and status, plus careful resource tuning, helps maintain stability at scale.
• CRD Scaling & Persistence: High-volume or resource-intensive workflows can surpass etcd capacity and cause performance issues. Persisting workflow data to an external database ensures smooth operation under heavy loads.
• Version Mismatches: Using different releases of the controller, UI, and CLI can lead to incompatible API calls and random failures. Align all components to the same supported version to avoid unexpected errors.
• RBAC in Multi-Tenant Clusters: Multi-team environments often need isolation through separate namespaces and controllers. Clear roles, permissions, and namespace boundaries prevent unauthorized access or workflow overlap.
• Namespace & Template Best Practices: Duplicating workflow definitions in multiple namespaces can lead to version drift. Reusing standardized templates and storing them in a central repository keeps definitions consistent.
• Workflow Failures from Dependency Changes: Shifts in external services or system settings can break previously functional tasks. Monitoring upstream dependencies and updating workflow steps accordingly prevents unplanned downtime.

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Additional Resources

• Argo Workflows Documentation
• Argo Workflows Releases