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Hands-on guides to AI infrastructure, MLOps, models, and shipping to production.

Learn how technology startups can implement efficient DevOps automation with CI/CD pipelines, containerisation, infrastructure as code, and observability to ship faster and scale confidently.

A deep dive into NVIDIA DGX OS, the purpose-built operating system for AI workloads. Learn what it includes, how it differs from standard Ubuntu, and whether your team needs it.
Battle-tested database backup strategies for MySQL and PostgreSQL in production. Covers physical and logical backups, PITR, WAL archiving, automated scheduling, cloud storage, and disaster recovery across AWS, Azure, GCP, and k3s.
A support-friendly, SRE-ready overview of Couchbase Server rolling upgrades under the Couchbase Autonomous Operator (CAO), using spec.paused to gate swap-rebalance one node at a time—so you can stabilize, validate health, and keep rollback options open.
Complete guide to running Couchbase Server in high availability production environments with XDCR multi-region replication, Couchbase Autonomous Operator on Kubernetes, across AWS, Azure, GCP, and bare metal k3s with Rancher.

Should you run AI workloads in the cloud or invest in on-premise hardware? We break down the total cost of ownership, data sovereignty, latency, scalability, and hybrid approaches to help you decide.
Workstation take on Claude Opus 5 on Amazon Bedrock: agentic coding, long-running agents, 1M context, ZDR by default, and how teams should adopt it.
Choose the right Claude model tier: Haiku for fast routing, Sonnet for daily work, Opus for complex agentic coding, and Fable 5 for long-horizon autonomy. Includes a token-budget router blueprint.