A practical framework for tracking attribution, setting budgets, and circuit-breaking spending on LLM in your CI/CD pipeline by using an OpenTelemetry implementation.
This comprehensive technical guide breaks down the essential architectural, storage, and integration patterns required to scale enterprise big data platforms.
RAG pipelines are getting more and more popular with vector search at the core of them. However, vector search might not be just enough for high-quality retrieval.
No, but its role has fundamentally changed. Here is what I have seen work, after building data platforms at enterprise scale across multiple industries.
Throughput-based load balancing breaks down when streaming messages have heterogeneous processing costs — the fix is balancing on actual per-partition resource usage.
This article details a resilient pseudo-labeling architecture. It combines Redis ingestion, Matryoshka embeddings, XGBoost to neutralize self-training confirmation bias.
Many MVPs get too big because teams treat several user-facing systems and vendor-dependent workflows as one app instead of planning one complete path first.
AI models do not fail due to bad coding; they fail due to an upstream change in the input. Combine contracts with circuit breakers to stop bad data from entering models.
Jakarta EE 12 introduces the Data Age of Enterprise Java with Jakarta Query, improved data access, and a unified model for cloud-native and polyglot systems.
AI agents have access, move at machine speed, and raise no alarms. Your DLP was built for humans — by the time it flags risk, the data is already gone.