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
“We have failover.” That sounds reassuring. But when real failure hits… many systems still go down — hard. Why? Because failover is easy to configure — but extremely hard to make reliable at global scale. Here are the most common ways failover fails in production: RDS Multi-AZ enabled Kubernetes failover configured Looks good on paper. Reality: Takes minutes instead of seconds Gets stuc
Is your website throwing 502 errors whenever an external API starts lagging? It is a common engineering grind where slow dependencies choke your server and kill your response times. The fix is not adding more resources. It is about changing how you handle work. Stop making users wait for external processes to finish. Offload heavy tasks to background jobs and queues. Distinguish between workers
The Signal: The Legally Binding Hallucination The failure wasn't that the LLM hallucinated—it’s that it was allowed to speak directly to the customer and the database without a chaperone. When you give a non-deterministic guest unregulated access to your deterministic house, you are legally and financially responsible for the fire. We need to stop treating AI as an open-ended "chat" interface and
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
The on-call alert at 02:14 said auth_5xx_rate spiked from 0.01 to 31.4. Not a deploy window. Not a traffic spike. Just thirty-one percent of authenticated requests failing for ~four minutes, then back to baseline. The cause was a JWKS rotation on the issuer side. New keys came in. Old keys went out. Caches in our service didn't refresh fast enough. Tokens signed with the new key were rejected beca
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