Practical DevOps, Cloud, AI & Linux engineering guides
GitLab's New Rate Limits: What to Fix Before Oct 19
GitLab is capping unauthenticated API calls at 60 an hour starting October 19, and the preview windows land before most teams will have noticed.
Most read
- 01How to Reduce Datadog Costs Without Losing CoverageCloud · 2,102 views
- 02OpenTelemetry Collector Pipelines: Real Configs That Survived ProductionDevOps · 2,047 views
- 03Azure DevOps Best Practices in 2026: Build Pipelines You Can TrustDevOps · 1,061 views
- 04
- 05A Pragmatic Multi-Region Strategy for Small TeamsCloud · 946 views
Topics
Latest Articles
View All →
Deep Dive: Model Serving Observability Stack
We had Datadog for app metrics, Loki for logs, and zero useful insight into what our LLM service was actually doing. Here's the observability stack we built specifically for model serving.
Practical Guide: Incident Response for Platform Teams
Platform teams own the systems that EVERY service depends on. Our incident response playbook for when the foundation cracks.
Practical Guide: Infrastructure Drift Detection Workflow
We had three months of slow drift between our Terraform code and AWS reality. Here's the daily-cron + Slack workflow that closed the gap.
Fine-tuning Large Language Models: A Practical Guide
Learn how to fine-tune LLMs like Llama 2, Mistral, and GPT models for your specific use case. Includes LoRA, QLoRA, and full fine-tuning techniques.
Infrastructure as Code: Terraform vs Pulumi vs Ansible
Compare Terraform, Pulumi, and Ansible for Infrastructure as Code. Learn when to use each tool and how they complement each other in modern DevOps workflows.
Linux System Monitoring with Prometheus and Grafana
Set up comprehensive Linux system monitoring using Prometheus and Grafana. Monitor CPU, memory, disk, network, and application metrics with beautiful dashboards.
AWS Cost Optimization: The Discipline That Actually Sticks
The initial cleanup is the easy part. The savings that last come from tagging, per-team budgets, and a monthly review, not a one-time audit.
Building Production-Ready AI Applications with LangChain and Docker
We deploy LangChain apps in Docker on Kubernetes. The patterns that work, the LangChain-specific gotchas, and what we'd build differently next time.
Practical Guide: Linux Performance Baseline Methodology
When everything seems "slow," a baseline gives you something to measure against. The capture-and-compare workflow we use on every Linux host.
Kubernetes Autoscaling: HPA vs VPA vs Cluster Autoscaler
HPA, VPA, and Cluster Autoscaler / Karpenter solve overlapping problems badly when you don't understand which one owns what. The mental model that keeps them from fighting.
Orchestrating AI Agents on Kubernetes
We run a fleet of LLM agents on Kubernetes. They're stateful, bursty, and expensive — none of which K8s defaults are good at. Here's what we changed.
eBPF: The Future of Kernel Observability
We replaced three kernel-level monitoring tools with a small set of eBPF programs. What it bought us, what it cost, and where we still use the old stuff.