AWS CloudWatch Metrics and Alarms: Practical Observability
Build a meaningful CloudWatch setup with custom metrics, composite alarms, and dashboards that catch real incidents without paging on noise.
·4 min read · #aws#cloudwatch#metrics
#metrics
7 posts · page 1 of 1
DevOps Observability Stack Overview
A tour of the modern observability stack: metrics, logs, traces, and events. Learn how the pillars fit together and how to choose tooling without drowning in dashboards.
·4 min read · #devops#observability#metrics
Kubernetes Horizontal Pod Autoscaler Explained
Understand how HPA decides when to add or remove pods, the metrics it can scale on, and the tuning knobs that prevent flapping and runaway scaling.
·4 min read · #kubernetes#autoscaling#hpa
Confusion Matrix Deep Dive
A thorough look at the confusion matrix: how to read it, the metrics it produces, and how to use it to diagnose classifier behavior beyond a single accuracy number that often hides what is going wrong.
·4 min read · #machine learning#evaluation#confusion matrix
ML Precision Recall and F1 Explained
Decode precision, recall, F1, and accuracy with concrete intuition, threshold tuning, and PR vs ROC curve guidance for imbalanced data.
·5 min read · #ml#metrics#precision
RAG Evaluation Metrics Tutorial
Measure RAG quality with recall@k, MRR, context precision, faithfulness, and answer relevancy so you can iterate on data, not vibes.
·5 min read · #rag#evaluation#metrics
Test Coverage Metrics and Their Pitfalls
Line, branch, and mutation coverage explained. Learn what each metric tells you, what it hides, and how to use coverage without gaming it.
·4 min read · #testing#coverage#metrics