We model a supply chain in Neo4j using Apache Spark to load data, NetworkX to identify critical nodes, and Cypher to find alternative routes after a disruption.
We eliminated per-record Python-side Protobuf parsing and JVM-to-Python crossings by letting Flink's native Protobuf format decode records directly into typed columns.
By combining Quarkus Flow, LangChain4j, MCP tools, and AGENTS.md, developers can construct deterministic, tool-augmented, and enterprise-governed AI agent loops.
A zero-trust framework for cloud migrations, grounded in real enterprise deployment lessons. Perimeter security doesn't hold up once workloads move to the cloud.
One cron line breaks once you have more than one server. Learn to design a distributed job scheduler that runs each job once, survives crashes, and retries.
RAG cuts chatbot hallucinations by grounding answers in retrieved source data, not model memory. Retrieval quality and evaluation matter more than model size.
RFC 10008's new QUERY method is safe and cacheable like GET but carries content like POST. This article explains the spec and runs it on Quarkus today.
I built six AI visibility tools without a traditional backend, using one Cloudflare Worker to solve CORS while all scoring logic runs client-side in the browser.
A launch traffic spike hit cold-loaded LLM containers; shared-memory crashes and KV-cache OOMs taught us why GPU autoscaling needs warm floors, not reactive scaling.
A direct CNN benchmark on CIFAR-10 shows TensorFlow and PyTorch achieve identical accuracy (~68%). Choose TensorFlow for production and PyTorch for flexibility.