A clear-eyed breakdown of serverless costs — why they’re hidden, when they make sense, and how to choose between functions and containers before surprises hit your bill.
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.