Use a query router for LLM analytics — Redshift (KPIs), OpenSearch (definition), Neptune (lineage), and Cache (repeats) — to improve accuracy, latency, and costs.
Jakarta Data in Jakarta EE 12 M2 extends the EE 11 repository model with stateful operations, unified querying, and SQL/NoSQL alignment for domain-centric data access.
Migrating legacy monolithic systems to the cloud is risky. Here is a proven pattern for automating regression testing at scale by replaying production traffic.
Learn context engineering to build better AI apps. This guide covers key techniques, practical examples, and resources to master this essential AI skill.
NetOps teams often face a skills gap when troubleshooting complex infrastructure. This article presents an automation pattern for an AI co-pilot for incident response.
MCP is production-ready for LLM-to-tool integration; A2A enables emerging multi-agent collaboration. They complement, not compete, and neither replaces Spark or Airflow.
Document extraction accuracy improves most when multiple independent sources with failure modes are combined, and values are selected based on weighted agreement.
Hashing detects tampering, but it doesn't prevent it. Here is an architectural pattern for securing business-critical files using Amazon QLDB and the Symbol Blockchain.
Learn the three production-proven Modern RAG architectures Basic, Agentic, and Multi-Agent RAG and how to choose the right one based on cost, complexity, and scale.
Combining direct path loading, parallelism, partitioning, index strategy, NOLOGGING, and tuned commits can reduce Oracle data load times by 70–90% in production.
Retrieval-Augmented Generation (RAG) optimization technique to reduce the number of tokens required to generate a response while maintaining response accuracy.
This article begins a series examining how identity functions in programmatic advertising, how audiences become addressable, and why common metrics fail.
BigID leverages agentic AI to move beyond traditional LLMs, enabling secure, autonomous data discovery, governance, and real-time decision-making at enterprise scale.
Proven techniques for production vector search, including when to use each one, how to combine them effectively, and trade-offs to understand before deployment.