A new volume type has recently joined the Kubernetes ecosystem: the image volume. This feature promises to change how we manage static data and configurations.
Use a query router for LLM analytics — Redshift (KPIs), OpenSearch (definition), Neptune (lineage), and Cache (repeats) — to improve accuracy, latency, and costs.
GPU-as-a-Service makes it easier to share accelerators, but it also raises concerns about isolation and security. This introduces a secure Kubernetes architecture.
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.
This article discusses how to build a lightweight, distributed task queue using Python asyncio and Redis as a simpler alternative to Celery for I/O-bound workloads.
AI-driven development is outpacing security teams. This piece examines where AI-powered security actually help, where they fail, and how teams can use them responsibly.
Retrieval-Augmented Generation (RAG) is transforming enterprise AI by bridging the gap between general-purpose language models and organization-specific knowledge.
The blog introduces you to the four pillars of observability, AWS and Azure cloud-native services, and ROI to help in architects and engineer's quest for system clarity.
AI Agents perceive, reason, plan, and act autonomously using LLMs. This article breaks down the core components that power every agent and shows you how to build one.
Feature flags and safe rollouts with Azure App Configuration for large SPA teams, hands-on setup, core principles, TypeScript code for backend and frontend.