Madhav's Blogs

Oct 16, 20267 min read84 views

What I Learned Running Real-Time Pipelines at Scale

For the past few years I've spent a significant portion of my time building and operating real-time event pipelines — systems that ingest millions of messages daily, process them through multiple serv

GCP for Engineers Who Know AWS: The Mental Model That Actually Helps
Oct 11, 20266 min read468 views
Deploying AI Workflows on Cloud Run: Latency, Cold Starts, and Scaling
Oct 8, 20266 min read43 views
Testing AI-Dependent Code: Mocking LLMs, Evaluating Outputs, and Avoiding Flaky Tests
Oct 5, 20266 min read71 views
Redis Patterns Every Backend Engineer Should Know
Oct 1, 20266 min read30 views

Prompt Versioning and Cost Control: Running LLMs Responsibly in Production
The monthly bill was ten times the estimate. Investigation took two hours. Three things were wrong. A retry loop was calling the model on every validation error — including schema mismatches that woul
Sep 29, 20266 min read53 views
Async AI Pipelines in FastAPI: Streaming, Queuing, and Long-Running Requests
The document extraction endpoint was synchronous. A request came in, the service sent the document to OpenAI, waited for the full response, parsed it, wrote to the database, and returned. Each request
Sep 27, 20265 min read5 views
GitHub Actions I Set Up on Every Project
Most engineers using GitHub Actions daily know how to write a basic workflow — checkout, install dependencies, run tests, deploy. That covers 80% of what they need. The other 20% is a set of features
Sep 21, 20266 min read48 views
When Terraform Gets Messy: Refactoring, Imports, and State Surgery
S01E06 of Terraform for Application Engineers
Sep 19, 20266 min read20 views
Terraform CI/CD: Plan on PR, Apply on Merge
S01E05 of Terraform for Application Engineers
Sep 15, 20265 min read18 views
Provisioning GCP Services with Terraform: Cloud Run, Pub/Sub, and Cloud SQL
S01E04 of Terraform for Application Engineers
Sep 13, 20266 min read10 views

Madhav's Blogs

Latest articles

What I Learned Running Real-Time Pipelines at Scale

GCP for Engineers Who Know AWS: The Mental Model That Actually Helps

Deploying AI Workflows on Cloud Run: Latency, Cold Starts, and Scaling

Testing AI-Dependent Code: Mocking LLMs, Evaluating Outputs, and Avoiding Flaky Tests

Redis Patterns Every Backend Engineer Should Know

Prompt Versioning and Cost Control: Running LLMs Responsibly in Production

Async AI Pipelines in FastAPI: Streaming, Queuing, and Long-Running Requests

GitHub Actions I Set Up on Every Project

When Terraform Gets Messy: Refactoring, Imports, and State Surgery

Terraform CI/CD: Plan on PR, Apply on Merge

Provisioning GCP Services with Terraform: Cloud Run, Pub/Sub, and Cloud SQL