kestra-io
- 5 skills
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- 1 day ago last updated
- ▌ Kestra Ops · kestra-ioOperate Kestra environments using kestractl for context setup, flow inspection, flow validation and deployment, execution monitoring, namespace operations, and namespace file management. Use when users request Kestra operational CLI tasks in dev, staging, or production.
- ▌ Kestra Flow · kestra-ioGenerate, modify, or debug Kestra Flow YAML by fetching the live flow schema and applying the same guardrails used by the Kestra AI Copilot. Use when users ask to create, write, update, or fix a Kestra flow.
- ▌ Migrate Kestra 2 · kestra-io bundleMigrate a Kestra 1.3 instance and its flows to Kestra 2.0: pre-flight audit with readiness report and complexity rating, server upgrade (database migrations, Docker/Helm), CLI-first flow migration with kestra-migrate, and guided rewrites of the patterns the CLI cannot automate (ForEach/ForEachItem → Loop, trigger conditions → when/dependsOn, pluginDefaults → Policies). Use when users want to upgrade or migrate to Kestra 2.0, ask if their instance is ready for 2.0, mention kestra-migrate or its warnings, or report flows failing to parse after a 2.0 upgrade. For migrations FROM other orchestrators (Airflow), use migrate-airflow-kestra instead.
- ▌ Kestra Flow Hardening · kestra-io bundleAudit one or more existing Kestra flows and add production-hardening controls — retries, timeouts, concurrency limits, error/finally/afterExecution handlers, SLAs, checks, and idempotency guards. Produces a severity-ranked findings report, then applies confirmed edits. Use when users ask to harden, audit, review, or make a flow more production-ready, resilient, or idempotent — not for authoring new flows (use kestra-flow).
- ▌ Migrate Airflow Kestra · kestra-ioMigrate an Airflow DAG to a production-ready Kestra flow. Extracts Python task logic into namespace files, maps DAG dependencies to Kestra tasks, and preserves parallel execution structure.