Observability: Monitoring, Metrics, Prometheus & Grafana Guide

Observability is not optional in production systems.

If you are running:

  • Kubernetes clusters
  • AI model inference workloads
  • GPU infrastructure
  • APIs and microservices
  • Cloud-native systems

You need more than logs.

You need metrics, alerting, dashboards, and system visibility.

This pillar covers modern observability architecture with a focus on:

  • Prometheus monitoring
  • Grafana dashboards
  • Metrics collection
  • Alerting systems
  • Production monitoring patterns

Comments

Post a Comment

Popular posts from this blog

Gitflow Workflow overview

Another Gitflow Workflow overview: Steps, Alternatives, Pros & Cons https://dasroot.net/posts/2025/06/gitflow-overview-and-alternatives #Gitflow #git #devops Gitflow is a structured Git branching model designed to manage software development workflows with dedicated branches for features, releases, and hotfixes. It emphasizes **stable code in production**, **parallel development**, and **controlled release cycles**. While it offers robust version control and collaboration, its complexity and rigidity make it less suitable for agile or continuous deployment environments. Alternatives like **GitHub Flow** and **Trunk-Based Development** provide simpler, more flexible workflows.
Read more

UV - a New Python Package Project and Environment Manager. Here we provide it's short description, performance statistics, how to install it and it's main commands

https://www.glukhov.org/post/2025/06/uv-new-python-package-project-and-environment-manager/ Python uv (pronounced “you-vee”) is a modern, high-performance Python package and project manager written in Rust. It is designed as a drop-in replacement for traditional Python package management tools such as pip, pip-tools, virtualenv, pipx, and pyenv, aiming to simplify and accelerate Python development workflows uv is developed by Astral, the team behind the popular Python linter Ruff, and is designed to address common pain points in the Python ecosystem—such as slow installations, dependency conflicts, and complex environment management—by leveraging Rust’s performance and modern software architecture.
Read more