
Edge Computing vs Cloud Computing: When to Process Data Closer to the Source
A practical comparison of edge and cloud computing: architectures, use cases, trade-offs, and how to decide where your workloads should run.
Deep-dive technical articles on cloud architecture, networking, security, databases, and infrastructure. Written by practitioners who build and scale production systems.

A practical comparison of edge and cloud computing: architectures, use cases, trade-offs, and how to decide where your workloads should run.

A practitioner's guide to GitOps: how to use Git as the single source of truth for infrastructure and application deployment with ArgoCD and Flux.

The real challenges of running agentic AI systems in production: non-determinism, token cost spirals, observability gaps, and how to solve them.

How to build production-ready LLM inference infrastructure: GPU selection, model serving frameworks, batching strategies, and cost optimization for AI workloads.

A practitioner's guide to FinOps: how engineering teams can take control of cloud costs without sacrificing velocity or innovation.

How OpenTelemetry works, why distributed tracing is different from logging and metrics, and how to instrument your services without drowning in overhead and noise.

SQL and NoSQL databases are not interchangeable. A principal architect with twenty years of database experience explains the real differences and when to use each.

RBAC breaks down at scale. Learn how Google Zanzibar's relationship-based model works, how OpenFGA and SpiceDB implement it, and when your app needs a dedicated authorization service.

Mainframe to cloud migration strategies that actually work: emulation, rewriting, and hybrid approaches, plus hard lessons from migrating COBOL and z/OS workloads.

A practical guide to vector databases for AI applications: when to use pgvector vs dedicated vector DBs, how ANN indexing works, and what I've learned shipping RAG systems in production.

DuckDB runs in-process like SQLite but handles analytical queries that would choke most data warehouses. Here's how it works, where it excels, and where it breaks down.

Sorting algorithms explained with real implementations, from bubble sort through Timsort. Big O complexity analysis and when algorithm choice actually matters in production.
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