Prometheus 1.0: Reliable Monitoring for Cloud-Native Systems

Introduction

Prometheus 1.0 signals stability for a pull‑based monitoring system that fits containers and microservices. With a multi‑dimensional data model and PromQL, it’s ideal for Kubernetes metrics.

Core Pieces

• PromQL for expressive queries and alert conditions.
• Exporters for common systems and a flexible client model.
• Alertmanager for routing and deduplication.
• Time-Series Storage: A custom TSDB with WAL, chunked segments, and retention flags to balance disk usage and query speed.

Kubernetes Fit

• Scrape targets discovered from the API.
• Label‑rich series map naturally to pods and namespaces.
• Node, kubelet, and service annotations determine which endpoints get scraped, making cluster metadata first-class labels.

scrape_configs:
- job_name: 'kubernetes-apiservers'
  kubernetes_sd_configs:
  - role: endpoints
  scheme: https
  tls_config:
    ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
  bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
  relabel_configs:
  - source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name]
    action: keep
    regex: default;kubernetes

Limitations in 1.0

• Alertmanager lacks native high-availability; run active/passive or accept brief gaps.
• Remote write/read is nascent—long-term storage needs Thanos/Cortex-style projects that will come later.
• Persistent volumes are required to survive pod restarts; emptyDir loses data between restarts.

Conclusion

Prometheus 1.0 is the monitoring backbone many Kubernetes users have been waiting for.