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Helm provides native support for managing versioned releases, allowing easy rollback in case of issues. Option A is correct because the helm rollback <release_name> <revision> command reverts the deployment to a previously known stable release without requiring a redeployment from scratch. This ensures fast recovery and minimizes downtime after a faulty upgrade.

Option B (helm upgrade --force) attempts to reapply an upgrade but does not restore the previous version. Option C (helm template) only renders Kubernetes manifests from charts and does not affect running releases. Option D (helm uninstall) removes the release entirely, which is not suitable for quick recovery.

Rollback functionality is essential in platform engineering for resilience and rapid mitigation of production issues. By using helm rollback, teams align with best practices for safe, controlled release management in Kubernetes environments.

--- CNCF Helm Documentation

--- CNCF Platforms Whitepaper

--- Cloud Native Platform Engineering Study Guide

The best way for platform teams to support data scientists is by enabling easy access to specialized AI/ML workflows, tools, and compute resources. Option C is correct because it empowers data scientists to experiment, train, and deploy models without worrying about the complexities of infrastructure setup. This aligns with platform engineering's principle of self-service with guardrails.

Option A (integrating into standard CI/CD) may help, but AI/ML workflows often require specialized tools like MLflow, Kubeflow, or TensorFlow pipelines. Option B (strict quotas) ensures stability but does not improve usability or productivity. Option D (UI-driven execution only) restricts flexibility and reduces the ability of data scientists to adapt workflows to evolving needs.

By offering AI/ML-specific workflows as golden paths within an Internal Developer Platform (IDP), platform teams improve developer experience for data scientists, accelerate innovation, and ensure compliance and governance.

--- CNCF Platforms Whitepaper

--- CNCF Platform Engineering Maturity Model

--- Cloud Native Platform Engineering Study Guide