Open-source CAST AI alternatives

Koordinator is a scheduling system for Kubernetes clusters that mixes different kinds of workloads on the same nodes. It is built around quality-of-service levels, so latency-sensitive services such as microservices and web apps can share hardware with batch, big data and AI jobs without the batch work hurting their performance.

The project aims to improve resource utilization and deployment density while reducing interference between containers. It offers flexible scheduling policies that administrators can tune, and it is designed to be added to an existing cluster with little friction. Its topics highlight colocation, cost optimization and workload consolidation as the main goals.

Koordinator is written in Go, released under the Apache-2.0 licence, and installed into your own Kubernetes environment, with documentation and best-practice examples for co-located workloads on its website. It is aimed at platform and infrastructure teams who run large clusters and want to get more value from the nodes they already pay for.

Crane is a FinOps platform focused on cloud resource analytics and cost management within Kubernetes clusters. It targets platform and SRE teams who need to manage cloud spending without sacrificing application reliability, and it is recognized as a FinOps Certified Solution by the FinOps Foundation.

Its approach follows an understand, analyze, optimize flow: it provides cost insight into cloud assets and Kubernetes resources such as Deployments and StatefulSets, periodically analyzes cluster state to generate optimization recommendations through a pluggable recommendation framework covering things like workload resource sizing, replica counts and idle resources, and then offers functionality to act on those recommendations and reduce cost. A standout capability is EffectiveHorizontalPodAutoscaler, which supports prediction-driven autoscaling so applications can scale up ahead of a forecasted traffic peak and scale down gracefully afterward, alongside a load-aware scheduler that places pods based on actual node usage rather than only requested resources.

Crane ships exporters that collect cloud pricing and billing data and send it to monitoring systems such as Prometheus, and it supports multi-cloud pricing through pluggable cloud provider integrations. It is written in Go, runs on Kubernetes, and is released under the Apache-2.0 license, with a live dashboard demo available for evaluation.