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Why Errors and Saturation Matter More Than You Think - Part 2
Master cloud-native observability. Learn the essential monitoring metrics, to keep your distributed systems reliable and fast.
What CIOs Actually Expect From Technology Leaders But Rarely Say
CIOs want leaders who make value observable, reliability deliberate, governance executable, and talent development systematic tech...
The Green Dashboard Lie: Why Your AI System Is Failing in Ways You Can't See
Traditional monitoring tells you if your AI system is running. It tells you nothing about whether it's working. This piece introdu...
From webrtc-internals Dump Files to Production Monitoring: A Practical Migration...
Manual webrtc-internals dump files don't scale past a handful of beta testers. This guide walks through a real bug scenario compar...
Your AI Model Can Fail Quietly While Every Dashboard Stays Green
Traditional monitoring misses what breaks AI models. Here’s how to track drift, data quality, and model behavior in production.
We Track Changes and Decisions. We Don’t Track Intent - and AI Makes It Worse.
We’ve built systems that perfectly track what changed (Git) and why decisions were made (ADRs), but we still fail to capture inten...
What Firmware Execution Patterns Reveal: Detecting Anomalies in EDK2 Using Runti...
One misconfigured PCD turned a 2-second boot into a 17.5-second one. It took runtime heat maps across multiple runs to find it.
Monitoring Essential Metrics for Cloud Native Systems - Part 1
Dashboards don’t make systems observable. True monitoring requires the right signals: latency, traffic, errors, and saturation. Th...
When AI Agents Fail, Who Owns the Fallout?
In the world of security and DevOps, AI agents are being pushed from demos into production quickly. When an AI agent fails, it can...
Hybrid Observability Unifies Metrics, Logs, Traces, and Data Into a Single Pane...
Too many tools, too many blind spots. Hybrid observability brings all signals into one view faster fixes, less noise, no lock-in.
Why Observability Needs an AI On-Call Engineer
Modern observability tools detect outages quickly but rarely explain their root causes. Engineers still spend hours correlating da...
Prompt Injection Still Beats Production LLMs
Three things we learned running a two-stage SFT+GRPO safety fine-tuning pipeline on Ministral-3B (single H200, 7.5 hours, 8,344 pr...
