Engineering Blog
Real stories from production.
Incidents, failures, and how we're building autonomous SRE systems. No marketing. No fluff. Just engineering.
The Night Everything Broke: Why Traditional Monitoring Failed Us
At 2:13 AM, latency spiked. Dashboards were green minutes before. It took 3 engineers and 47 minutes to find a single exhausted DB connection pool. Here's what we learned.
How We Built AI Root Cause Analysis for Kubernetes
Root cause analysis isn't magic — it's correlation at scale. We explain the signal graph, anomaly scoring, and why LLMs alone aren't enough.
Auto-Remediation: Powerful, Dangerous, and Necessary
Giving AI the ability to execute commands in production is terrifying. Here's how we think about safety, approval gates, and when to pull the plug.
Understanding Blast Radius in Microservices (With Real Examples)
One service fails. Three others go down. You find out from users. Blast radius mapping is the missing layer in most observability stacks.
Alert Fatigue Is Killing SREs — Here's What Needs to Change
200 alerts per shift. 80% are noise. Engineers stop caring. This is the real cost of bad alerting — and it's not a tooling problem.
We Simulated 50 Production Failures — Here's What We Learned
Chaos engineering at scale. We ran 50 failure scenarios across a test cluster and measured detection time, root cause accuracy, and remediation success rate.
Inside Tagent: Architecture of an AI SRE System
How do you build a system that understands Kubernetes incidents? Signal ingestion, dependency graphs, AI correlation, and the remediation runtime — explained.