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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, pod NotReady, or SLO guardrail breach
  • 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.

Get Started

Metrics Sources

Attune works with multiple metrics backends. One source is configured per policy:

Backend Guide Use case
Prometheus (+ Thanos, Mimir, VictoriaMetrics) Prometheus Setup Default for most clusters; auto-discovery available
Datadog Datadog Setup Teams already using Datadog for Kubernetes monitoring
CloudWatch Container Insights CloudWatch Setup EKS clusters using AWS-native observability

Reference