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Attune

Safe, in-place Kubernetes pod resource right-sizing. VPA done right.

Attune is a Kubernetes operator that automatically right-sizes pod resource requests and limits using In-Place Pod Resize (beta in Kubernetes 1.33+, alpha with feature gate in 1.32). In-place by default, optional eviction fallback for infeasible resizes, and no HPA conflicts.

The Problem

Average Kubernetes CPU utilization is 8%. That means 92% of the compute you're paying for is idle. Industry-wide, this adds up to $44.5 billion in projected cloud waste (Harness 2025), and 70% of organizations cite overprovisioning as their #1 cost driver (CNCF 2023).

The existing tool for this, VPA, evicts pods to resize them. It conflicts with HPA, causes cascading failures, and fewer than 1% of teams run it fully automated (ScaleOps 2026). Recommendation-only tools like Goldilocks show you the numbers but leave you with hundreds of YAML edits that sit in the backlog for months.

Kubernetes 1.33 changed this by graduating In-Place Pod Resize to beta (enabled by default). The foundation for non-disruptive right-sizing now exists. Attune is the operator built to use it.

How It's Different

VPA Goldilocks Attune
Resize method Evicts pods No resize (recommend only) In-place (no restarts)
HPA compatible No (death spirals) N/A Yes (adjusts base, not %)
Safety Minimal guardrails N/A Graduated rollout + auto-revert
Algorithm Backward-looking histograms VPA recommender Time-of-day-aware + burst detection
Production path <1% use automated N/A Observe, Recommend, Canary, Auto

Who Is This For?

  • Platform teams managing dozens of namespaces where developers set resource requests once and never look at them again.
  • FinOps teams that need concrete dollar estimates per workload and a safe path from "we know it's overprovisioned" to "it's fixed."
  • SREs running latency-sensitive services where pod restarts during peak traffic are not an option.
  • Anyone running HPA who has been told "VPA and HPA don't mix."

Key Features

  • In-place resize via the Kubernetes 1.32+ /resize subresource
  • Graduated rollout: Observe, Recommend, OneShot, Canary, Auto
  • Auto-revert on OOMKill, CPU throttle, restart spikes, or pod NotReady
  • HPA coexistence without death spirals
  • Confidence scaling for sparse data
  • Time-of-day awareness for bursty workloads
  • Mandatory bounds (no unbounded recommendations)

Estimate your savings with the interactive calculator, or read Why Attune? for the full story.

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