A full walkthrough of how to set up Docker sandboxes on a local machine and how to run AI agents safely in YOLO mode without corrupting the host environment.
Choosing a base Linux image for containers is not just about the size. It is also about licensing, compatibility, update cadence, security posture, and support options.
Why environment variables leak, how Docker Swarm secrets work, when to use HashiCorp Vault, and building a layered approach to secrets in production containers.
Deploy and tune Apache Spark on AmpereOne M, with setup steps, cluster configs, and benchmarks showing gains vs Ampere Altra in performance and efficiency.
Hadoop on AmpereOne M shows improved throughput, scaling, and efficiency, with setup, tuning, and benchmark insights for optimizing big data workloads.
MCP gives Copilot a standard way to call tools (like SQLcl) without custom integrations. SQLcl runs locally and talks to Oracle; SQL MCP exposes an MCP server over stdio.
Kafka feeds the stream, Spark tracks progress via checkpoints, and Delta's transaction log ensures every event lands exactly once, even across failures and restarts.
A custom framework testing Oracle 26ai’s ability to convert natural language into SQL using the 22 TPC-H benchmark. With no prompt engineering, it achieves high accuracy.
Securely connect to a MongoDB DocumentDB replica set in Kubernetes using mongosh with credentials retrieved dynamically from Kubernetes secrets for direct access.
Many AI tools fail in production not because of model quality, but due to architectural decisions around retries, cost control, observability, and multi-tenant safety.
Queues hide overload. Without back-pressure, limits, and scaling, lag just grows until failure. Bound queues, alert on lag, fail fast, and plan capacity.
Tuning Java on Kubernetes (Arm64): align CPU/memory limits with JVM, use container-aware settings, optimize placement, and leverage OS tuning for better performance.