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Platform Engineering Copilot

Platform changes with a known blast radius.

A cloud and platform engineering assistant for Kubernetes, Terraform and OpenTofu, CI/CD, GitOps, IAM, networking, observability, and SRE. It reviews the manifests, plans, and logs you share and proposes the smallest reversible change.

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01 — The product

What is Platform Engineering Copilot?

Platform Engineering Copilot helps you design, review, troubleshoot, and operate cloud platforms. It covers architecture, Kubernetes, infrastructure as code, delivery, identity and networking, supply-chain security, reliability, cost and capacity, migrations, and internal developer platforms.

It’s aimed at platform, infrastructure, and SRE engineers, and at teams working out how much platform they actually need.

It starts from the simplest architecture that meets the requirement. It won’t add Kubernetes, a service mesh, or multi-cloud without a concrete reason. Every high-risk change gets a confirmed target, a preview where possible, an approval boundary, and a rollback or forward-fix path.

02 — Real workflow

Pods restart in a loop during a database slowdown

The problem

Latency on a shared database rose and the API deployment started restarting. The restarts made the outage worse.

Probe config and pod eventsyaml
livenessProbe:
  httpGet: { path: /healthz/deps, port: 8080 }
  periodSeconds: 5
  failureThreshold: 2

Events:
  Warning  Unhealthy  Liveness probe failed: HTTP probe failed with statuscode: 503
  Normal   Killing    Container api failed liveness probe, will be restarted
  Warning  BackOff    Back-off restarting failed container api

How Platform Engineering Copilot approaches it

  1. 1Finds the first failing boundary. The liveness probe calls a dependency check, so a slow database triggers restarts.
  2. 2Asks only for the evidence that separates likely causes, such as previous container logs and termination reasons, and has you save it before anything else restarts.
  3. 3Suggests reversible containment, such as pausing or rolling back the rollout, instead of deleting pods or scaling blindly.
  4. 4Splits the startup, liveness, and readiness probes and moves the dependency check to readiness. It then defines validation signals and a rollback trigger.

Expected result

An incident write-up that runs from most likely cause to decisive check, containment, permanent fix, and validation. It includes corrected probe YAML.

Illustrative workflow. It doesn’t depict a real session, system, or result.

03 — Areas of expertise

Where it helps

  • Terraform and OpenTofu

    Reviews plans by create, update, replace, and destroy, plus backend, version constraints, and drift. Never bypasses state locks or calls an apply safe without plan evidence.

  • Delivery and supply chain

    Traces commit to build, artifact digest, promotion, and controller sync. Covers signatures, provenance, and SBOMs, and confirms live state after a rollback instead of assuming it.

  • SLOs and observability

    SLIs drawn from user-visible behavior, error budgets, and alerts with owners and runbooks. OpenTelemetry-based traces, metrics, and logs without high-cardinality or secret-bearing labels.

  • Identity and least privilege

    Maps principal, resource, and action, credential lifetime, and workload identity federation. Reviews Kubernetes RBAC and pod privileges, and requires scope and approval for IAM or network changes.

04 — Working with Platform Engineering Copilot

What to provide and what to expect

Share

  • Kubernetes manifests, events, and describe output
  • Terraform or OpenTofu code and plan output
  • CI/CD or GitOps pipeline definitions
  • Incident timeline, logs, and dashboards
  • SLOs, constraints, and cloud provider details

Expect

  • Most likely cause, decisive check, containment, fix, and validation
  • Architecture recommendations with trade-offs and a validation plan
  • Focused Terraform or OpenTofu, Kubernetes YAML, or pipeline config
  • Change plans with rollback triggers and post-change monitoring

It can’t inspect cloud accounts, run kubectl or Terraform, change IAM or networking, or deploy workloads on its own. It reviews what you share and won’t invent resource IDs or test results.