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The 350 KB Hidden in Our XML Layouts
Meesho

Solving an AAPT2 Auto-Versioning Mystery The discovery APK size is a core performance metric for us. We track it continuously, investigate regressions, and regularly inspect what is actually shipped, not only what exists in source control. That habit led us to an unusual…

Lens: Give Your Entire Team X-Ray Vision Into Your Android App
PhonePe

Lens lets your team see what is happening inside a running mobile app—from a normal web browser. You Know This Bug, Right? It is Friday afternoon. QA tells you that the profile screen is blank after login. You open the same app, follow the same steps, and everything works. The…

Holding Revamp Went Live. Then Reality Check Hit Hard
Groww

Introduction In the previous article, we shared how we redesigned Holdings retrieval to eliminate unnecessary work. The architecture looked solid, and the rollout was ready. Then we deployed it. With millions of users accessing Holdings every day, the rollout looked healthy…

CI Doesn’t Need On-Demand: Moving Our Build Pipelines to Spot Instances
Razorpay

Contributors: Guptaanuj CI/CD pipelines have always had a money-vs-stability problem. Run on-demand AWS instances and your build infrastructure is rock solid, expensive, and predictable. Run on spot instances and your costs drop 70–90%, but AWS can pull the rug with 2 minutes of…

LLMs for Relevance: Automating High-Quality Product Relevance Labeling in Flipkart Search
Flipkart

Amey Patil , Shreya Malani· November 2025 Every product you see on a Flipkart search results page is there because a system decided it was relevant to what you typed. But how do we know those decisions are good? Someone — or something — has to look at a query and a product and…

blog.flipkart.tech
Refusing the Haystack: How Groww’s Cyber Defence Team Scales Detection and Response
Groww

There’s a version of a security operations centre that exists mainly to be pointed at. It ingests every log it can reach, lights up a wall of dashboards, and staffs a rotation around the clock so that, if anyone asks, the answer is “yes, someone is watching.” It satisfies an…

TraceMind: Automating the Chaos of Crash Debugging
PhonePe

The Debugging Dilemma: Why TraceMind? In a complex mobile ecosystem, debugging a single production crash is rarely a straightforward task. Historically, developers at PhonePe faced a fragmented landscape of data points. When a crash alert hit, an engineer would often spend…

Freshworks migration journey from Cassandra to Scylla
Freshworks

by Vigneshkumar Ak Background & Motivation Freshworks offers a suite of applications across customer support, ITSM, and CRM . Some of the Freshwork’s Platform applications rely on distributed databases to handle high throughput and low-latency workloads at scale . For a long…

Building a Custom Documentation Engine: How Freshworks Scaled 2,500+ Pages Across 6 Products with…
Freshworks

Building a Custom Documentation Engine: How Freshworks Scaled 2,500+ Pages Across 6 Products with Markdoc and Next.js When off-the-shelf solutions couldn’t handle our multi-product, multi-version documentation needs, we built our own. Here’s what we learned — and why it was…

The Inner Loop Is Solved. The Outer Loop Is Yours.
Meesho

Agents now write most of our code, and the panic about what that means for engineers is aimed at exactly the wrong half of the job. A mental model I keep coming back to, what it says about the engineer we are all becoming, and why the engineers with the most to gain are the ones…

Journey of an Ad Request: The Hidden Engineering
JioHotstar

Advertising is a key source of revenue in most businesses. It certainly forms a key pillar for JioHotstar. There is so much technology hidden under the surface. In this blog, we will cover some of the complexity that gets unlocked when we render an ad on our content. Every…

Decoding Customer Value: pLTV Models for India’s Quick Commerce Delivery Wars — part 1
Swiggy

Author: Jayshmi A Special thanks to soumyajyoti banerjee , Meghana Negi, Shaik Masihullah, Akash Deep for their contributions throughout this project and Sunil Rathee for his guidance. The counterintuitive story of how 350+ carefully engineered features + a simple MLP matched…

DE Dost: Teaching Machines to Be a Friend on the Last Mile
Swiggy

Building Swiggy’s AI onboarding companion for delivery executives, where accuracy alone wasn’t enough and mentorship had to scale.For a new Delivery Executive (DE) joining Swiggy, the experience is often overwhelming, throwing a world of SOPs, incentive structures, zone…

How We Made All Swiggy Apps Operations AI-Native
Swiggy

Engineering across all Swiggy Apps has always had a simple problem with a very large surface area: we ship fast, but every release, every production signal, and every operational review touches too many systems. For a single release manager or on-call engineer, the day could…

From Gatekeeper to Strategic Catalyst: How GenAI is Transforming Compliance at PhonePe
PhonePe

India is undergoing a massive digital transformation, and at the heart of this revolution is PhonePe, enabling seamless payments and financial services for over 700 million registered users across Bharat. When you build at this kind of population scale, handling millions of…

How We Refresh Razorpay's Data Warehouse 10x Faster with Graphs and Indexes
Razorpay

Contributors: Utkarsh Koppikar Rohan Background Razorpay provides the payment infrastructure for millions of merchants globally. Behind every payment, settlement, and refund is a microservices architecture where each service owns its own database. While this keeps services…

Improving the Efficiency of Rendering User Holdings
Groww

Introduction At 9:15 AM IST, the opening bell rings on the Indian stock market — and millions of investors reach for the same screen. Within seconds, millions of investors open the Holdings page. They want to know how overnight news has impacted their stocks, whether they’re in…