Cloud Architecture
Agentic AI in Production: Scaling Challenges and Practical Solutions
The real challenges of running agentic AI systems in production: non-determinism, token cost spirals, observability gaps, and how to solve them.
Blog
Deep-dive technical articles on cloud architecture, networking, security, databases, and infrastructure. Written by practitioners who build and scale production systems.
Cloud Architecture
LLM Inference Infrastructure: A Practical Guide to Serving AI Models at Scale
How to build production-ready LLM inference infrastructure: GPU selection, model serving frameworks, batching strategies, and cost optimization for AI workloads.
Cloud Architecture
What is FinOps? Cloud Cost Optimization Explained for Engineers
A practitioner's guide to FinOps: how engineering teams can take control of cloud costs without sacrificing velocity or innovation.
DevOps
OpenTelemetry and Distributed Tracing: Making Sense of Microservice Chaos
How OpenTelemetry works, why distributed tracing is different from logging and metrics, and how to instrument your services without drowning in overhead and noise.
Databases
SQL vs NoSQL Databases: Architecture, Trade-offs, and Choosing the Right One
SQL and NoSQL databases are not interchangeable. A principal architect with 30 years of database experience explains the real differences and when to use each.
Cloud Migration
Mainframe to Cloud Migration: Strategies, Challenges, and Hard Lessons
Mainframe to cloud migration strategies that actually work: emulation, rewriting, and hybrid approaches, plus hard lessons from migrating COBOL and z/OS workloads.
Databases
Vector Databases Explained: pgvector, Pinecone, Weaviate and How to Choose
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.
Databases
DuckDB and Embedded OLAP: The Rise of In-Process Analytical Databases
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.
DevOps
Sorting Algorithms Explained: Implementations, Complexity, and When They Matter
Sorting algorithms explained with real implementations, from bubble sort through Timsort. Big O complexity analysis and when algorithm choice actually matters in production.
Security
Cloud Sovereignty and Data Residency: What It Actually Takes to Stay Compliant Across Borders
Data sovereignty is the fastest-growing constraint in enterprise cloud architecture. Here's how multinational companies architect around GDPR, DPDP, and conflicting national data laws without fragmenting their platform.
DevOps
AIOps Explained: How AI Is Changing Monitoring, Alerting, and Incident Response
AIOps applies machine learning to operations data to reduce alert noise, detect anomalies, and accelerate incident response. Here's what works in practice and what's still hype.
Data & Analytics
Data Observability: How to Know When Your Pipelines Are Lying to You
Data quality failures are silent and expensive. Data observability gives you the monitoring layer to detect when your pipelines are producing wrong data before the business finds out first.