GraphQL was good at a time, then it simmered off. Is GraphQL about to make a comeback because of AI? Will GraphQL be able to serve better for AI Agents?
In this article, I will be introducing a pipeline designed to identify sensitive data columns before masking steps and improve the efficiency of the data masking process.
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.
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.
AI agents don't break your API rules; they expose the ones you never enforced. This article covers five gateway-level controls that bring autonomous agents under control.
Single-layer AI guardrails hit a 40% false-positive rate. My five-layer architecture on live AWS achieved 94% accuracy and 0% false negatives on destructive operations.
This guide demonstrates exchanging an AWS SigV4 Request for a GCP access token to enable secure, zero-trust communication between clouds using MultiCloudJ.
Deploy a production-ready Spring Boot microservice on AWS Fargate with Docker, ECS, ALB health checks, private subnets, secrets, CI/CD, and autoscaling.
Azure AI Foundry turns RAG setup from a week of manual plumbing into an afternoon of configuration — but access control, security, and cost planning are still on you.