Prometheus 2.37: Native Histograms and Performance Advances

Introduction

Prometheus 2.37, released on June 1, 2022, delivers significant improvements to native histogram support, query performance enhancements, and better remote write capabilities. This release strengthens Prometheus’s position as the de facto standard for Kubernetes metrics collection and monitoring.

In practical terms, this one matters most if you’ve hit the usual trade-off in clusters with lots of services: you want richer latency distributions (histograms), but you don’t want to pay for it in storage churn, query timeouts, or remote-write backpressure. Prometheus 2.37 aims to make “more detail” feel less like “more pain” when you scale out.

Native Histogram Improvements

• Histogram storage optimizations provide more efficient storage and querying of high-cardinality histogram data.
• Sparse histograms enable efficient representation of distributions with many zero buckets.
• Query functions expansion includes new functions for histogram analysis and aggregation.
• Backward compatibility ensures existing histogram metrics continue to work without changes.

Query Performance Enhancements

1. Query engine optimizations reduce latency for complex PromQL queries, especially those involving large time ranges.
2. Index improvements accelerate label and series lookups, improving query response times.
3. Memory management enhancements reduce memory usage during query execution.
4. Concurrent query handling improves throughput for high-query-load scenarios.

Remote Write Enhancements

• Queue management improvements provide better backpressure handling and retry logic for remote storage backends.
• Sharding enhancements enable more efficient distribution of metrics across remote write endpoints.
• Compression support reduces bandwidth usage for remote write operations.
• Error handling improvements provide better recovery from transient remote storage failures.

Kubernetes Integration

• Service discovery improvements enhance automatic discovery of Kubernetes resources.
• Label management enhancements provide better handling of Kubernetes label changes.
• Scrape configuration improvements simplify setup for complex Kubernetes deployments.
• RBAC support enables secure metric collection with service accounts.

Operational Improvements

• Alerting refinements improve alert evaluation performance and reduce false positives.
• Recording rules optimizations reduce evaluation overhead for frequently used queries.
• Configuration validation provides better error messages for misconfigured scrape jobs.
• Documentation expansion includes comprehensive guides for common monitoring scenarios.

Getting Started

kubectl create namespace monitoring
kubectl apply -n monitoring -f https://raw.githubusercontent.com/prometheus-operator/prometheus-operator/v0.60.0/example/prometheus-operator-crd/monitoring.coreos.com_prometheuses.yaml

Configure Prometheus with native histograms:

apiVersion: v1
kind: ConfigMap
metadata:
  name: prometheus-config
data:
  prometheus.yml: |
    global:
      scrape_interval: 15s
    scrape_configs:
    - job_name: 'kubernetes-pods'
      kubernetes_sd_configs:
      - role: pod

Summary

Prometheus 2.37 continues to evolve as the foundation of Kubernetes observability, providing teams with powerful metrics collection and querying capabilities.