DevOps
Monitoring and Logging: What to Track, How to Alert, and Tools That Work
Practical monitoring and logging advice from three decades of production operations. What metrics matter, how to build alerts that work, and tools I trust.
Observability
DevOps
Observability Pipelines: OpenTelemetry Collector, Cribl, and Taming the Telemetry Data Flood Before It Bankrupts You
How to build observability pipelines with the OpenTelemetry Collector, Cribl, and Vector to cut telemetry costs 60-80% without losing diagnostic visibility.
DevOps
Continuous Profiling in Production: Pyroscope, Parca, and Finding the CPU Hog You Never Knew You Had
Continuous profiling is the fourth pillar of observability most teams skip. Learn how Pyroscope, Parca, and eBPF-based profilers find CPU and memory bottlenecks that metrics and traces can't.
DevOps
The Cloud-Native Observability Stack: Prometheus, Loki, Grafana, and Tempo in Production
A deep-dive into building a production-grade observability stack with Prometheus, Loki, Grafana, and Tempo. Learn the architecture, scaling trade-offs, cardinality traps, and when the open-source stack beats a $40k/month SaaS bill.
Databases
ClickHouse for Real-Time Analytics: Architecture, Use Cases, and When to Use It
ClickHouse is a columnar database built for real-time analytics at absurd scale. Here's how it works, why it's faster than the alternatives, and where it fits in your data stack.
DevOps
SLOs, SLIs, and Error Budgets: The Reliability Framework That Actually Works
SLAs are for lawyers. SLOs are for engineers. Here's how to define meaningful service level objectives, measure them properly, and use error budgets to make smarter deployment decisions.
Networking
eBPF Explained: How It's Revolutionizing Cloud Networking and Observability
A practical guide to eBPF: how it works at the kernel level, why Cilium replaced iptables for Kubernetes networking, and how eBPF powers next-generation observability without sidecars.
DevOps
OpenTelemetry and Distributed Tracing: Making Sense of Microservice Chaos
How OpenTelemetry works, why distributed tracing is different from logging and metrics, and how to instrument your services without drowning in overhead and noise.
DevOps
AIOps Explained: How AI Is Changing Monitoring, Alerting, and Incident Response
AIOps applies machine learning to operations data to reduce alert noise, detect anomalies, and accelerate incident response. Here's what works in practice and what's still hype.