Building a Production-Grade Observability Platform with LGTM Stack, DORA Metrics & SLOs
The article outlines the development of a production-grade observability platform using the open-source LGTM stack—Loki, Grafana, Tempo, and Prometheus—combined with DORA metrics and SLOs. The solution is deployed via a single Docker Compose command and emphasizes cost efficiency, data sovereignty, and infrastructure as code. It enables comprehensive monitoring, alerting, and performance analysis without reliance on proprietary tools.
- ▪The observability platform is built using the LGTM stack: Prometheus for metrics, Loki for logs, Tempo for traces, and Grafana for visualization.
- ▪DORA metrics, SLI/SLOs, and automated alerting to Slack are integrated to measure software delivery performance and reliability.
- ▪The entire stack is deployed using Docker Compose, runs on a single server, and avoids vendor lock-in with open standards like OpenTelemetry and Prometheus exposition format.
- ▪Self-hosting the LGTM stack reduces costs at scale and ensures sensitive data remains within internal infrastructure.
- ▪All configurations are code-driven with no manual UI setup, enabling full automation and reproducibility.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3898965) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Abraham Acha Posted on May 16 Building a Production-Grade Observability Platform with LGTM Stack, DORA Metrics & SLOs #devops #observability #prometheus #grafana GitHub Repository: https://github.com/AirFluke/meetmind-observability One command to deploy: docker compose up -d Introduction Modern software teams don't just need to know when something is down — they need to understand why it broke, how long users were affected, how fast they recovered, and whether their engineering…
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