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OPENFAAS
Serverless functions made simple on Kubernetes
MIT
ABOUT
Serving ML models and glue jobs as always-on services wastes cluster capacity and turns every endpoint into an ops burden. OpenFaaS lets teams wrap any container as a function with a single HTTP contract, then scale replicas up from zero on demand and back down when idle. Templates, secrets, and a watchdog process keep language choice and GPU images intact while giving inference, webhooks, and batch triggers a uniform deploy path.
INTEGRATION GUIDE
1. Deploy GPU or CPU model-serving functions that scale to zero between inference requests
2. Wrap preprocessing, embedding, and postprocessing steps as independent functions in an ML pipeline
3. Expose webhook handlers that trigger dataset ingest or retraining jobs without a standing service
4. Package Python, Go, or custom container functions with one CLI for mixed-language AI backends
5. Run event-driven batch scoring on Kubernetes with autoscaling based on queue depth or HTTP load
TAGS
serverlesskubernetesfunctionsfaascontainersmlopsscale-to-zero