{"categories":[{"label":"Distributed Computing","url":"https://skillfed.io/packages/category/system-distributed-computing"}],"enrichment":{"capability":"Integrates Dagster data pipeline orchestration with Kubernetes, enabling declarative asset management and orchestration on k8s infrastructure.","skillfed_tags":["kubernetes","orchestration","data-pipelines"],"use_cases":["Run Dagster asset jobs on Kubernetes clusters instead of local or single-machine executors.","Scale data pipeline execution across multiple k8s nodes for parallel asset computation.","Deploy Dagster in containerized environments where k8s is the standard orchestration layer.","Isolate asset execution in separate k8s pods for resource control and fault isolation.","Integrate Dagster with existing k8s-based data infrastructure and CI/CD pipelines."],"what_it_does":"dagster-k8s is a Dagster integration that runs Dagster asset definitions and jobs on Kubernetes infrastructure. It bridges Dagster's declarative asset model\u2014where you define data pipelines as Python functions\u2014with Kubernetes' container orchestration, allowing you to scale asset execution across a k8s cluster. The package depends on dagster (the core orchestrator), google-auth (for credential handling), and kubernetes (the Python client library), and is designed for teams deploying Dagster in containerized environments.\n\nThe integration lets you configure how your assets run on k8s with resource specifications and executor settings. It is part of the broader Dagster ecosystem, which provides observability, lineage tracking, and a web UI for monitoring asset health and dependencies. This is most useful when your data infrastructure already runs on Kubernetes or when you need the scalability and isolation that k8s provides.","worth_installing":"Yes, if you are already using Dagster and deploying on Kubernetes. The package is actively maintained with no known vulnerabilities and low install friction. It is the standard way to run Dagster jobs on k8s. Install only if you have a running k8s cluster and need Dagster's orchestration on that infrastructure; otherwise, use Dagster's local or other executor options."},"id":"dagster-k8s","links":{"html":"https://skillfed.io/packages/dagster-k8s","md":"https://skillfed.io/packages/dagster-k8s.md","pypi":"https://pypi.org/project/dagster-k8s/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-07","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"dagster-k8s","python_support":"supports_current","summary":"A Dagster integration for k8s"},"popularity":{"monthly_downloads":5871063,"position":2020,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.29.17"}