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.
Jakarta Query unifies queries across Jakarta Persistence, Data, and NoSQL, with common and relational levels to simplify polyglot persistence in EE 12 M2.
Migrating legacy monolithic systems to the cloud is risky. Here is a proven pattern for automating regression testing at scale by replaying production traffic.
Cloud cost is a distributed systems failure mode. This article explains how to make it observable, prevent waste, and manage spend as an operational metric.
This article explains how to build a self-healing observability system with AWS Bedrock AgentCore using AI agents to analyze and remediate infrastructure issues.
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.
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.
H100 GPUs are best for flexibility, fast iteration, and custom CUDA work. TPU v5p wins on GCP for large-scale LLM training with better cost efficiency and scaling.
Cloud systems drift when exceptions accumulate, and decisions lose connection to original objectives. Clear requirements and early security design prevent sprawl.
Modify URI-based API versioning to use date-based versions, easing operations, ensuring immutability, and also separating core logic from API responses.