# Building a Custom Metrics Exporter for Kubernetes

Publisher-attributed story with a reviewed brief or permitted publisher paragraph. The original publisher is responsible for the linked reporting.

- Publisher: Kubernetes
- Category: Infrastructure
- Original publication time: 2026-07-14T18:00:00Z
- First observed by NexusTechWire: 2026-10-01T15:54:35Z
- Original source: https://kubernetes.io/blog/2026/07/14/custom-metrics-exporter-kubernetes/
- NexusTechWire record: https://nexustechwire.com/news/news-695b8d5359717af83252

## From the publisher

Kubernetes ships with built-in awareness of CPU and memory, but most real-world scaling decisions depend on signals that live entirely outside that narrow window: how many messages are waiting in a queue, how long the last batch job took, how many active WebSocket connections a pod is holding. When the built-in metrics are not enough, a metrics exporter bridges that gap. This post walks through writing one from scratch, packaging it as a container, and wiring it into a cluster so that Prometheus — and ultimately the HorizontalPodAutoscaler — can consume it. What a metrics exporter actually does An exporter is a small HTTP server with a single responsibility: expose application state as text on a /metrics endpoint. Prometheus scrapes that endpoint on a regular interval, stores the time-series data, and makes it available for queries, alerts, and autoscaling rules.

Source license: [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). Publisher excerpt shortened and converted to plain text. Original source license applies.

Read the full original: [Kubernetes](https://kubernetes.io/blog/2026/07/14/custom-metrics-exporter-kubernetes/)

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