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What is Iter8?

Kubernetes release optimizer built for DevOps and MLOps teams.

What is an Iter8 experiment?

Iter8 experiments make it simple to collect performance and business metrics for apps and ML models, assess, compare and validate multiple app/ML model versions, safely rollout the winning version, and maximize business value in each release.

Experiment chart

Experiment charts are specialized Helm charts that contain reusable experiment templates. Iter8 combines experiment charts with user supplied values to generate runnable experiment.yaml files.

Iter8 Hub

Iter8 hub is a specific location within in the Iter8 GitHub repo that hosts several pre-packaged and reusable charts. These charts enable to you to launch powerful release optimization experiments in seconds. Their usage is described in depth in various Iter8 tutorials.

Features at a glance

  • Load testing with SLOs

    Iter8 experiments can generate requests for HTTP and gRPC services, collect built-in latency and error-related metrics, and validate SLOs.

  • A/B(/n) testing

    Grow your business with every release. Iter8 experiments can compare multiple versions based on business value and promote a winner.

  • Simple to use

    Get started with Iter8 in seconds using pre-packaged experiment charts. Run Iter8 experiments locally, inside Kubernetes, or inside your CI/CD/GitOps pipelines.

  • K8s app/serverless/ML frameworks

    Use with any app, serverless, or ML framework. Iter8 works with Kubernetes deployments, statefulsets, Knative services, KServe/Seldon ML deployments, or custom Kubernetes resource types.


Iter8 is primarily written in go and builds on a few awesome open source projects including:

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