Knative is an open-source platform that extends Kubernetes to provide a serverless, event-driven, and autoscaling environment for running containerized applications. It was originally created by Google and is now governed by the CNCF (Cloud Native Computing Foundation).
What is Knative?
- Knative adds a “serverless” layer on top of Kubernetes.
- It enables you to run your containerized workloads only when they’re needed, scaling them up or down (even to zero) automatically, in response to events or HTTP traffic.
- Designed to make deploying, running, and managing microservices and serverless functions easier, faster, and more resource-efficient.
Key Features
1. Serverless Workloads on Kubernetes
- Automatically scales apps up or down (even to zero) based on demand.
- No need to manage underlying servers or worry about idle resources.
2. Event-driven Applications
- Easily connect to event sources (Kafka, CloudEvents, etc.) and trigger workloads in response.
3. Simplified Deployment
- Simple, declarative YAML to deploy stateless services.
- Handles networking, routing, and traffic splitting for blue/green and canary deployments.
4. Autoscaling
- Supports HTTP-based scaling and concurrency-based scaling.
- Great for unpredictable or bursty workloads.
5. Integration with CI/CD
- Works with existing Kubernetes tools, pipelines, and other cloud-native technologies.
Core Components
- Knative Serving
- Deploy and manage serverless, stateless services.
- Supports autoscaling, revision tracking, and traffic splitting.
- Each deployment creates a “Revision” (version) for easy rollback/rollforward.
- Knative Eventing
- Build event-driven apps by connecting various event sources to services.
- Standardizes event formats and delivery.
Knative in MLOps and ML Serving
- Model Inference: Run ML model servers (like KFServing/KServe) that scale to zero when idle and auto-scale under load.
- On-demand workloads: Useful for data preprocessing, batch jobs, or ad-hoc inference.
Example: Deploying a Knative Service
apiVersion: serving.knative.dev/v1
kind: Service
metadata:
name: helloworld
spec:
template:
spec:
containers:
- image: gcr.io/knative-samples/helloworld-go
- Deploy with:
kubectl apply -f service.yaml
When to Use Knative?
- You want to minimize cloud costs by running workloads only when needed.
- You need auto-scaling for unpredictable, spiky, or infrequent workloads.
- You want to build event-driven architectures on Kubernetes.
- You’re building microservices that benefit from easy versioning and traffic management.
Knative vs. Other Tools
| Feature | Knative | K8s Deployments | AWS Lambda / GCP Cloud Functions |
|---|---|---|---|
| Platform | Kubernetes | Kubernetes | Vendor Cloud Only |
| Scale to Zero | Yes | No | Yes |
| Event-Driven | Yes (via Eventing) | No | Yes |
| Traffic Split | Yes | No | Yes |
| Language Support | Any (containerized) | Any | Limited |
Summary
Knative brings the benefits of serverless—autoscaling, event-driven execution, simple deployment—to any Kubernetes cluster, making it easier to run cost-efficient, scalable, and production-grade microservices or ML inference endpoints.