PostgreSQL Query Rewriting Techniques The previous articles in this series covered performance problems you fix by adding indexes, restructuring joins, or tuning memory. This one is about the queries where the plan is "fine" — every node is doing something reasonable — but the query itself is asking the wrong question, producing unnecessarily large intermediate results or forcing the planner dow
SQL is widely known for data querying and manipulation but systems do grow; data becomes larger; processes become repetitive and operations become sensitive. SQL has some features which enables it to be considered a fully fledged programming language. Some of the features which I discuss in this article are procedures, functions and transactions. Each of these concepts serve distinct purposes. Sto
Hi 👋, In this post we shall explore Bedrock's structured KB with this architecture: Upload CSVs to S3 > SNS Queue > Crawl data with Glue > Query with Redshift > Bedrock KB > Query with LLM. Let's do some of this with code. Let's get started. Clone the repo and switch to the project directory. git clone [email protected]:networkandcode/networkandcode.github.io.git cd structured-kb-demo/ Do a uv sync
Overview Let's get our hands dirty. This part covers the full setup and the actual demo: deploy PayLedger to both regions, wire up Route 53 failover, configure the Agent Space, inject three simultaneous faults, and walk through exactly what the agent found. Quick recap from Part 1: PayLedger is a demo payment ledger deployed to ap-southeast-1 (primary) and ap-northeast-1 (secondary) with Route 5
Overview I finished the DR Toolkit thinking I had covered the important parts of disaster recovery: runbooks, RTO/RPO targets, post-mortems. Then I mapped out the actual incident lifecycle and realized everything I built sits at the edges. The middle part (detecting the incident, correlating signals across regions, finding the root cause while the primary region is actively failing) was not cove
Subqueries vs. CTEs in SQL: A Practical Guide to Writing Cleaner, Smarter Queries Whether you're just getting comfortable with SQL or leveling up your data skills, two tools will come up again and again when working with complex queries: subqueries and Common Table Expressions (CTEs). They solve similar problems — breaking a complex query into manageable pieces — but they do it in different ways
Every observability vendor has bolted "AI" to their landing page. Half of those features are genuine improvements. The other half are autocomplete in a costume. After a few years of running these tools across enterprise estates, here is where AI-augmented SRE actually pays off, where it doesn't, and what we'd advise teams adopting it today. The single most defensible use case. A medium-sized estat
In a previous post, I explored Codd's connection trap in PostgreSQL and MongoDB — the classic pitfall where joining two independent many-to-many relationships through a shared attribute produces spurious combinations that look like facts but aren't. The example followed Codd's 1970 suppliers–parts–projects model: we know which suppliers supply which parts, and which projects use which parts, but j