What’s new in Ankra

“Would this be cheaper somewhere else?” now has an answer built from your actual cluster rather than a pricing page. Compare Providers takes the node groups, control plane, volumes and load balancers you are really running and prices them on every provider Ankra can build on, side by side with today’s metered bill.

• Like-for-like matching keeps dedicated cores dedicated, so the figure is one you could actually move to rather than a best case built from shared vCPUs.
• Cheapest fit shows the other end of the range when shared cores are acceptable.
• Line by line - the bill is broken down by what drives it, so you can see which machine class is the reason and what changes if you move.

Find it under Cloud Cost on any cluster. The economics behind it are on the cost optimization page.

You can now try Ankra on a real, writable Kubernetes environment without connecting a cloud account, installing anything, or talking to us first.

• One click in the portal, or ankra cluster playground create from the terminal.
• Ready in about two minutes - four provisioning steps, and our timed run clocked it at eighty-two seconds.
• A starter app already live on its own hostname over HTTPS by the time you arrive.
• Real in every way that matters - kubectl works, nodes and pods are genuine, and stacks you deploy go through the same pipeline your production deploys use.

Nothing you build in it is playground dialect: the stacks are standard Helm charts and Kubernetes manifests, and they move to a cluster of your own unchanged.

Start one from the Playground page.

Every cluster ships with thousands of CVEs, and severity alone will not tell you which ones matter. The Security Center ranks them by evidence of real-world exploitation instead:

• CISA Known Exploited Vulnerabilities first - findings on the KEV catalogue surface above everything else, with their remediation deadlines.
• FIRST EPSS on every finding - the exploitation probability sits next to the CVSS score, so a critical nobody is exploiting stops outranking a high that everybody is.
• The fixed version, per occurrence - not “upgrade something”, but which image and which package version closes it.
• Scanner freshness per cluster - a cluster that stopped reporting three weeks ago cannot quietly look clean.

One command covers the whole fleet, and the same data is in the CLI, the portal and your AI tools:

ankra security overview
ankra security findings --known-exploited
ankra security finding <finding-id>
ankra security clusters

More on the Security Center, and on why findings are not decisions on the blog.

Build infrastructure agents from plain CI jobs and the Ankra CLI - no framework, no orchestration layer:

• PR review agent - validates cluster-definition changes against the live platform and comments on the PR with what will actually change, including live capacity headroom checks.
• Deploy watcher - ankra cluster apply --wait on merge, verifies rollout health, and posts a root cause to Slack when a deploy fails instead of a red X.
• Scheduled infra watcher - runs every 30 minutes, stays silent while healthy, posts to Slack only when something degrades.

ankra chat is one-shot and scriptable, with server-side access to cluster context: logs, events, manifests, and stack history. Read the guide.

Cursor is good at application code but loses context the moment a change crosses into Kubernetes, Helm, and CD pipelines. The Ankra CLI now works as an infrastructure subagent: Cursor delegates cluster-aware questions (“why is this pod crashing on staging?”) to ankra chat, which answers with grounded cluster state instead of guesses.

Includes llms.txt support on the docs site so agents can self-serve CLI usage. Read the setup guide.

AI agents at other companies have wiped real production databases this year. Ankra’s answer is architectural: the AI can only produce drafts. Every generated stack, values change, or fix lands as a draft with a full preview (what changes, what restarts, what depends on it), requires explicit human approval, and commits through GitOps with an audit trail and one-click rollback.

The AI gets the speed; Git keeps the authority. How it works.

Stacks are one object deployed to many clusters with different variables - so cloning production for local dev, QA review, or a client demo is a first-class operation, not a weekend of scripting. Works from OrbStack on a laptop to GitHub Actions to ephemeral staging clusters.

Read the 5-person-team walkthrough.