Systems fail in the gaps between diagrams.
Core Routers investigates production failure modes in distributed systems and AI infrastructure: latency, contention, backpressure, retrieval quality, capacity, and the architecture decisions behind them.
Labs
Each lab starts with an operational failure or scaling question and ends with a decision a production team can actually use.
Why Your Backend Is Slow Even When CPU Looks Fine
A failure-oriented walkthrough of connection-pool saturation, database contention, queueing, and the misleading comfort of normal host-level CPU.
Kafka Under Load: When More Partitions Stop Helping
Partition count is a scaling mechanism, not a universal cure. This lab separates broker capacity, key skew, consumer concurrency, and rebalance overhead.
A RAG Demo Can Be Correct While the Production System Is Unreliable
A compact failure matrix for stale documents, retrieval misses, chunking errors, ranking drift, latency, and missing observability.
From evidence to intervention
The same diagnostic method can be applied to a live system without turning the engagement into an open-ended consulting project.
Production performance diagnostic
Trace latency, saturation, contention, retry amplification, and queueing across a backend path. Deliver a bottleneck map and prioritized remediation plan.
Distributed-system architecture review
Review Kafka, Cassandra, Java services, workload isolation, capacity assumptions, failure domains, and operational tradeoffs.
AI production-readiness review
Inspect retrieval quality, failure observability, latency, cost behavior, stale data, evaluation gaps, and production failure modes.