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production-monitoring

Monitor containerized Python services on AWS EKS with Grafana, Prometheus, Loki, and OpenTelemetry.

6|1|Updated Apr 7, 2026
Search Tags:#observability#eks#grafana#prometheus#alerting#opentelemetry#loki
One-click install
npx skills add https://github.com/kmshihab7878/claude-code-setup --skill production-monitoring-kmshihab7878
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: production-monitoring
Source: https://github.com/kmshihab7878/claude-code-setup/tree/main/skills/production-monitoring
Command: npx skills add https://github.com/kmshihab7878/claude-code-setup --skill production-monitoring-kmshihab7878

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a turnkey monitoring stack for containerized Python services on AWS EKS, removing visibility gaps across metrics, logs, and traces so teams can detect, alert, and troubleshoot production incidents quickly.

Core Features & Use Cases

  • OpenTelemetry instrumentation: guidance for instrumenting FastAPI and other Python services and exporting OTLP spans and metrics.
  • Prometheus metrics & alerting: metric exposition patterns, PromQL examples for request rates, latency, and error rates, and alert rule templates for SLO breaches.
  • Loki logs & Grafana dashboards: centralized log aggregation with Loki and prebuilt Grafana dashboards to correlate logs, traces, and metrics.
  • SLO/SLI definitions: examples for availability and latency SLOs and how to measure them using Prometheus and histogram quantiles.
  • Use Cases: detect high error-rate regressions, monitor P99 latency across releases, and alert when agents or background tasks become stuck.

Quick Start

Instrument your FastAPI service with OpenTelemetry, expose Prometheus metrics, configure Prometheus to scrape the service, point Loki at your log streams, and import the Grafana dashboards to start visualizing SLIs and alerts.

Frequently Asked Questions about production-monitoring

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I monitor Python services on EKS using Prometheus and Grafana?▼

Monitor Python services on EKS by instrumenting them with OpenTelemetry, exposing Prometheus metrics, and importing prebuilt Grafana dashboards to visualize SLIs and alerts. This stack provides full visibility across metrics, logs, and traces.

How do I set up OpenTelemetry instrumentation for a FastAPI service?▼

Set up OpenTelemetry instrumentation for FastAPI by integrating the library to export OTLP spans and metrics. This enables distributed tracing and metric collection for your application before configuring scrape targets.

Can I use Loki for log aggregation alongside Prometheus metrics in Kubernetes?▼

Yes, Loki can be used for log aggregation alongside Prometheus metrics in Kubernetes. Point Loki at your log streams to centralize logs and correlate them with metrics and traces in Grafana dashboards.

How do I alert on SLO breaches using PromQL for request rate and latency?▼

Alert on SLO breaches by writing PromQL rules to calculate request rates, error rates, and histogram quantiles for latency. The stack provides alert rule templates to trigger notifications when service objectives are violated.

Does this observability stack work for both development and production environments?▼

Yes, this observability stack works across development and production environments. It applies to containerized Python services on AWS EKS to detect error-rate regressions and monitor P99 latency consistently throughout the deployment lifecycle.

What is the best way to correlate logs and traces with metrics for production incidents?▼

Correlate logs and traces with metrics by aggregating logs in Loki and visualizing them in Grafana. This approach allows teams to quickly troubleshoot production incidents by providing unified visibility across telemetry signals.

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