Android × Monitoring
Android Monitoring, page 2
Android Monitoring articles 31–53 of 53
Fixing Performance Regressions Before They Happen
Angus Croll from Netflix reveals how his team slashed false performance alerts by 90% while catching more real regressions. The secret? They stopped using static thresholds entirely.
Nextdoor Notifications: Using ML to Keep Neighbors Informed
Karthik Jayasurya from Nextdoor reveals how they transformed notifications from random spam into personalized updates that neighbors actually want. The result? A 40% jump in engagement without sending more mess...
A Importância da Performance Para Apps Mobile
Victor Oliveira from Mercado Libre reveals a harsh truth: 53% of users uninstall apps due to performance issues. With 4.5 billion active Android and iOS devices worldwide, each performing differently, mobile pe...
A Saga of Improvement in Android App Performance (Part 2)
Tokopedia built an automated performance testing pipeline that catches regressions before they hit production. Here's how they measure every build, every night.
How We Improve Android App Performance (Part 1)
Tokopedia's Android team achieved a 40% improvement in app start time and page load speed. Here's the systematic approach that got them there.
Optimizing OpenTelemetry's Span Processor for High Throughput and Low Latency
DoorDash's OpenTelemetry adoption hit a wall: 72% CPU utilization versus 56% without tracing. That's a costly tax for observability.
Client Tracing: Understanding Mobile and Desktop Application Performance at Scale
"My app is slow" - every engineer's nightmare. Slack's mobile team was tired of hitting dead ends when debugging performance issues.
How Pinterest Leverages Honeycomb to Enhance CI Observability and Improve CI Build Stability
Pinterest sends 1 million CI build events to Honeycomb daily. Here's how they turned that data into a competitive advantage for mobile development.
Improve Reliability with Observability Tracing in Your CI/CD Pipeline
Walmart's engineering team reveals how observability tracing transformed their CI/CD pipeline reliability. The secret? Treating data requests like package tracking.
Introducing Pulse: Envoy Mobile's stats library
Jingwei Hao from Lyft reveals how real-time stats APIs caught a production crash spike at 9:55am, enabling engineers to ship a hotfix before most users even noticed the problem.
Logging And Alerting in Android Tokopedia
Hendry Setiadi from Tokopedia reveals how they built a custom logging system that catches production issues before users even notice. Firebase Crashlytics is great, but what if you need more?
Monitoring Android Codebase
Fajar Ulin Nuha from Tokopedia reveals how their 50+ Android engineers manage a codebase that changes so dramatically every single week that assumptions become dangerous. Their solution? Become data-driven deve...
Tracing at Slack: Thinking in Causal Graphs
Slack processes 8.5 billion spans daily, but their tracing system looks nothing like traditional distributed tracing. Here's why they rebuilt it from scratch.
How We Ensure Credible Analytics on Dropbox Mobile Apps
Marianna Budnikova from Dropbox reveals why your mobile analytics are probably lying to you. And it's costing you two weeks every time you get it wrong.
Ad Metrics Quality And Testing On Mobile
Maya Reddy from Pinterest reveals how their team eliminated last-minute P1 bugs by automating ad metrics testing. The shift from bi-weekly manual QA to continuous integration transformed their release confidenc...
Quality Assurance and Testing for Mobile Applications
Julio Zynger from SoundCloud reveals how they ship mobile releases every two weeks without breaking things. Their secret? A release train model that turns chaos into predictability.
Profilo: Understanding App Performance in the Wild
Meta's engineers were spending days or months debugging performance issues they couldn't reproduce in their device labs. Sound familiar?
Battery Instrumentation at Facebook
Facebook was flying blind on battery drain across a billion devices. User-facing battery percentage? Too noisy, too coarse, and deliberately inaccurate by design.
Mobile A/B Testing at Quora
Tommy MacWilliam from Quora reveals how they A/B test mobile UX without waiting weeks for App Store approval. The secret? A hybrid architecture that lets them iterate at web speed.
Mobile Performance: Tooling Infrastructure at Facebook
Facebook processes thousands of mobile code changes weekly. How do they catch performance regressions before users feel the pain?
Crittercism: Solving Mobile Performance Issues for One Billion Users | AWS Startups Blog
Crittercism handles more traffic than Google Search (50K vs 40K requests/second) with just 3 DevOps engineers. How do they pull this off?
Process Stats: Understanding How Your App Uses Memory
Dianne Hackborn from the Android framework team reveals a hidden tool that exposes exactly how your app behaves when users aren't looking. Most developers are flying blind on background memory usage.
Keeping Instagram Up with Over a Million New Users in Twelve Hours
Instagram's Android launch brought 1 million new users in 12 hours. Here's how their infrastructure team kept the lights on during hypergrowth.