Decision Logs
Not tutorials. Real decisions, real trade-offs, real consequences.
Reading paths
What to decide before putting AI in charge of diagnosing your platform: where it helps, where it must not decide and what real investment it demands. The full article's conclusions, in 6 minutes.
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Automate diagnosis without delegating the truth: governed capabilities, deterministic evidence, and AI that interprets rather than decides.
How to combine them without multiplying calls, extending latency, or triggering cascading failures.
Read tail latency and relate percentiles to traffic volume and SLOs without being fooled by the average.
An operational method to go from an alert to a testable hypothesis with metrics, traces, and logs.
Latency isn't a technical metric: it's a P&L line item. Where the money bleeds and how to mitigate it with architecture.
Metrics, prediction models, vertical vs horizontal scaling and when to scale. The engineering of predicting before fighting fires.
They're not the same. Not interchangeable. Real differences, when you need each, and the most common anti-pattern.
The platform that moves global commerce. Internal architecture, real troubleshooting and lessons from banking environments.
When the JVM won't talk, dumps speak for it. Diagnosing deadlocks, memory leaks and concurrency issues.
If the incident repeats, the postmortem failed. Structure, blame-free culture and actionable items.
K8s isn't the answer to everything. Real decisions on resource limits, networking, storage and debugging.
Beyond the 99.9%. Active-active, failover, health checks, quorum and the decisions that matter.
Diagnosis is not intuition. It's method. A 5-step framework for diagnosing production incidents.
Why AI is really a set of functional models: LLMs, computer vision and generative models. Practical understanding for engineers.
A practical guide to modern architecture without falling for the hype. Real criteria for deciding when to split and when not to.
Essential patterns for production systems: Circuit Breaker, Retry, Timeout, Bulkhead and Fallbacks.
How to measure, design and manage latency budgets in critical platforms.
The difference between monitoring and observability. The 3 pillars for distributed systems.
Practical implementation of the Circuit Breaker pattern to prevent cascading failures in distributed architectures.
Understanding AWS, Azure and IBM Cloud through architectural patterns, not service names.