Optimization
We track 15 posts about Optimization from 13 engineering blogs. Most active: SitePoint, Cloudflare, Facebook. Latest post: Oct 13, 2026.
Companies writing about Optimization
Recent posts
Beyond Faster Load Times: Practical Web Performance Optimization for Modern Applications (opens on the source site)
null Continue reading Beyond Faster Load Times: Practical Web Performance Optimization for Modern Applications on SitePoint.
Prioritize your messages at scale with the Twilio Traffic Optimization Engine (opens on the source site)
Twilio ·
The Traffic Optimization Engine is a suite of products working across networks, senders, geography, and use cases to provide messaging deliverability at scale.
Saving another 100TB of RAM with math (and Rust) (opens on the source site)
Cloudflare's global network is immense but not limitless. As we look for small ways to trim our resource usage, we sometimes get lucky and we can cut significantly more. Here’s how we reduced one of our Pingora-based service's RAM usage with statistics.
AGENTS.md Optimization: Cut Token Waste with Automated Linting (opens on the source site)
Learn how to optimize AGENTS.md files and implement automated context linting to reduce token waste across autonomous coding agent sessions. Continue reading AGENTS.md Optimization: Cut Token Waste with Automated Linting on SitePoint.
How we saved 100 terabytes of memory by optimizing 1.1.1.1’s DNS cache (opens on the source site)
Five Rust-level memory optimizations to the DNS cache layout of Big Pineapple cut per-entry memory by 56%, freeing approximately 100 TB of memory across Cloudflare's fleet.
Exploring Hierarchical Interest Representation For Meta Ads Deep Funnel Optimization (opens on the source site)
Facebook ·
Hierarchical Interest Representation is a research area for Meta Ads. We’re exploring an upstream representation layer over the universe of Ads entities – users, advertisers, products, services – learning unified embeddings that connect users’ inferred interests with the breadth of what advertisers offer in their deep funnel ads. The innovations in Hierarchical Interest Representation are [...] Read More... The post Exploring Hierarchical Interest Representation For Meta Ads Deep Funnel Optimization appeared first on Engineering at Meta.
How we used DSPy to turn AI evaluations into better responses in Dash chat (opens on the source site)
Dropbox ·
We used DSPy to improve LLM judges and optimize our chat experience, creating an evaluation-driven feedback loop that produced better outputs.
Why 100% GPU Util Wasn’t Enough (opens on the source site)
Badoo ·
A practical loop for optimizing GPU inference without guessingIt wasn’t an incident. That made it interesting.A few days after a cloud migration, one of our highest-traffic ML services looked healthy. Traffic was flowing. Latency was fine. The rollout had gone the way you want these things to go: boringly.And yet a Slack thread started anyway.Not because anything was broken. Because something had become easier to see.On-prem, GPU efficiency tends to get folded into bigger conversations: capacity planning, hardware timelines, headroom for the next model. In the cloud, the same question…
Lyft’s Feature Store: Architecture, Optimization, and Evolution (opens on the source site)
Lyft ·
Written by Rohan Varshney, with support from Devon Mittow & Janice Lee.This article expands upon a presentation from the Feature Store Summit 2025, which can be viewed in full here. There is also another video available on the evolution of Lyft’s Feature Store from DE4AI 2024.Introduction and Core PurposeLyft’s Feature Store stands as a core infrastructural pillar within its Data Platform organization, designed to optimize the management and deployment of Machine Learning (ML) features at massive scale. Its primary objective is to centralize feature engineering efforts, guaranteeing…
Scaling recommendations service at OLX (opens on the source site)
OLX ·
Optimizing FastAPI at Scale: Lessons from OLX’s Recommendation PlatformPhoto by Rosy KoIn distributed systems, there is a motto that says ‘you are as slow as your slowest tasks’. In Python, thanks to the notorious Global Interpreter Lock (GIL), this issue is amplified: ‘your slowest task will make every other task slower’. In this article, I’ll walk you through the optimizations we made to scale a FastAPI service that now handles tens of thousands of requests per second, achieving a p99 latency under 10ms.IntroductionOLX is a global online marketplace that enables users to buy and sell goods…
MySQL Query Optimization with Releem (opens on the source site)
Introduction In this article, I’m going to show you how to optimize the queries executed by a Spring application running on MySQL using Releem. For a short introduction about Releem, check out this previous article, in which I explained how to set up Releem to collect metrics from your MySQL database. Spring Petclinic application The application under test is going to be the well-known Spring Petclinic that we are going to run using the MySQL profile: After starting the application, we are going to run the petclinic_test_plan.jmx JMeter test plan that is... Read More The post MySQL Query…
Aequitas Flow step-by-step: a Fair ML optimization framework (opens on the source site)
Feedzai ·
By Sérgio Jesus, Inês Silva, Pedro Saleiro, Hugo Ferreira, Pedro BizarroIn this blog post we will visit Aequitas Flow, an Open-Source framework designed to run complete and standardized experiments of Fair ML algorithms. We encourage you to try Aequitas Flow with the Google Colab Notebooks, which are available in the project’s GitHub repository.This blog post is based on the paper by Sérgio Jesus, Pedro Saleiro, Inês Silva, Beatriz M. Jorge, Rita P. Ribeiro, João Gama, Pedro Bizarro, and Rayid Ghani.Table of Contents:1. What is Aequitas Flow?- 1.1. For Practitioners selecting a model- 1.2.…
Android Large Screen Optimization (opens on the source site)
Large Screen Devices - The New Frontier SoundCloud large screen optimized Recently, the Android team at SoundCloud took on a project to…
Make your reports faster : Beginner’s guide to Tableau Optimization (opens on the source site)
Grofers ·
Make your reports faster: A beginner’s guide to Tableau OptimisationIn today’s world, given the pace at which data operates, we need a tool that can help us to generate reports faster and bring out insights within milliseconds. In order to solve this challenge, several companies have started utilising a few Business Intelligence (BI) tools such as Tableau/Power BI/Superset/Looker/Qlikview, etc. We at Blinkit have also moved away from the traditional way of reporting via spreadsheets to a more scalable and robust tool — Tableau.Earlier, we had no single source of truth for metrics; it took a…
Doctrine ORM Hydration Performance Optimization (opens on the source site)
PRE-REQUISITE: Please note that this article explains complexity in internal ORM operations with the Big-O notation. Consider reading this article, if you are not familiar with the Big-O syntax. What is hydration? Doctrine ORM, like most ORMs, is performing a process called Hydration when converting database results into objects. This process usually involves reading a record from a database result and then converting the column values into an object's properties. Here is a little pseudo-code snippet that shows what a mapper is actually doing under the hood: reflectionFields(); foreach…
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