rl_concurrency.md

Concurrency, Performance and Scalability

• The cost of async I/O, false assumptions and pride
• Microservices fault and latency tolerance using Netflix Hystrix
• The Image Optimization Technology that Serves Millions of Requests Per Day
• Google still loves disks, should you?
• Fundamentals of Apache Kafka
• Troubleshoot OutOfMemoryError: Unable to Create New Native Thread
• The Heard-Of Model: Computing in Distributed Systems with Benign Failures
• New Compilers Streamline Optimization and Enhance Code Conversion
• 10 Stack Benchmarking DOs and DON’Ts
• A Scalable System for Ingestion and Delivery of Timed Text
• Fastest code is the one not run: Part I – The cost of escaping strings
• Instructors’ Guide to Raft
• I/O matters.
• The design of RavenDB 4.0: You can’t see the map/reduce from all the trees
• Fastest code is the one not run: Part II – Memory management
• Eager Optimization Is The Enemy
• Google’s Transition from Single Datacenter, to Failover, to a Native Multihomed Architecture
• Performance and Scaling in Enterprise Systems
• Garbage Collection Logging: Which Time Matters to the Customer?
• Web Page Performance Death by a Thousand Tiny Cuts
• Production postmorterm: Houston, we have a problem
• A Journey Through How Zapier Automates Billions of Workflow Automation Tasks
• JLBH Examples 2 – Accounting for Coordinated Omission
• Performance Tuning Ideas for Apache Camel
• Java Caching Benchmarks 2016 – Part 1
• Swift Compilation Reporting at Tumblr
• Efficient binary serialization
• Performance & Usage at Instagram
• Locking in WebKit
• Performance Culture
• Fun async tricks for getting better performance
• Scaling NSQ to 750 Billion Messages
• Tools of the Trade for Performance and Load Testing
• How to Make C++ Code Run 90x Faster
• PostgreSQL Scalability: Towards Millions TPS
• A tale of troubleshooting database performance, with Cassandra and sysdig
• JLBH Examples 1 – Why Code Should be Benchmarked in Context
• Displaying Linux Memory
• Building nginx and Tarantool based services
• Is Your Computer Stable?
• Application data caching using SSDs
• High Performance Erlang – Finding Bottlenecks in a CouchDB Cluster #1
• Saving 13 Million Computational Minutes per Day with Flame Graphs
• TIL: clock skew exists
• What does Etsy’s architecture look like today?
• Understanding caching in Postgres – An in-depth guide
• Trie based routing
• Stack Overflow: The Architecture – 2016 Edition
• Egnyte Architecture: Lessons Learned in Building and Scaling a Multi Petabyte Distributed System
• The design of RavenDB 4.0: Replication from server side
• How does perf work? (in which we read the Linux kernel source)
• Logging yourself to death
• What’s the Difference Between BLOCKED, WAITING, And TIMED_WAITING?
• tcpdump is amazing
• Improving Kubernetes Scheduler Performance
• Introduction to Apache Kafka: Distributed Systems, Scalable Architecture, and Messaging Queues
• Mozilla Pushes the Web to New Levels as a Platform for Games
• Scaling to exabytes and beyond
• Creating a Heavy-Duty Balancer With Nginx and Lua
• Detecting Java Race Conditions With Tests, Part 1: Lost Updates
• Profiling in Erlang
• Distributed Consistency and Session Anomalies
• A Patreon Architecture Short
• How do you do capacity planning?
• Coupling in distributed systems
• System loads Web pages 34 percent faster by fetching files more effectively
• Pitfalls of the MyBatis Caches with Apache Ignite
• How Complex Systems Fail
• Solving Intractable Performance Problems Through Vertical Engineering
• An assignment framework for optimizing distributed systems operations on social networks
• The cost of routing in NancyFX
• Message Durability in ActiveMQ 5.x
• Optimal compression rate
• To Compress or Not to Compress, that was Uber’s Question
• Building an anycast network for our CDN
• jcmd: One JDK Command-Line Tool to Rule Them All
• Making asm.js/WebAssembly compilation more parallel in Firefox
• Python vs Copy on Write
• CDNs aren’t just for caching
• I conquered thread pools! For today, at least.
• Small intro to threads, race conditions and locking
• Malice or Stupidity or Inattention? Using Code Reviews to Find Backdoors
• From Node.js to Go
• Interpreting jstat’s Garbage Collection Events
• Understanding Consensus and Paxos in Distributed Systems
• JVM JIT optimization techniques
• The cost of routing
• How to Get Started With JMeter: Part 2 – Building Scripts and Running JMeter
• So You Wanna Go Fast?
• Performance Engineering with React (Part 1)
• Performance Tuning Apache Storm at Keen IO
• Go and Quasar: A Comparison of Style and Performance
• HTTP/HTTPS not working inside your VM? Wait for it.
• Using ltrace to debug a memory leak
• HotSpot Incremental Java Garbage Collector
• Debugging an API Performance Problem From the Real World
• Benchmarking Message Queue Latency
• Cache digests for HTTP/2 Push: lossy compression saves the day again
• Facebook’s new front-end server design delivers on performance without sucking up power
• Starving JMS Consumers in ActiveMQ
• The importance of a data format: Part VII – Final benchmarks
• Apache Spark as a Compiler: Joining a Billion Rows on your Laptop: A deep dive into the Tungsten Engine
• Understanding the Java Garbage Collection Log
• Prepare your distributed system, so you don’t lose money, when it fails
• Optimizing Distributed Actor Systems for Dynamic Interactive Services
• Checking HashMaps with MapClashInspector
• Instruction-level Multithreading to improve processor utilization
• A Beginner’s Guide to Addressing Concurrency Issues
• Load balancing or balancing on the edge of a cliff?
• Benchmarking Fleet Clusters With Rkt And Docker
• Measuring baseline costs
• The deadlock in the fairness assumption
• A workshop on strace & tcpdump
• Fast incremental sort
• Performance of green threads and why it matters
• The Go binary diet
• Autoscaling on Complex Telemetry
• Distributed Dask Arrays
• How We Monitor and Run Kafka At Scale
• When code is suspiciously fast: adventures in dead code elimination
• External API Caching with Varnish & Nginx
• The design of RavenDB 4.0: The implications of the blittable format
• I hate web bloat.
• Design of a Modern Cache
• How to run database integration tests 20 times faster
• How do low latency applications differ for regular applications?
• Structured Concurrency
• How we get high availability with Elasticsearch and Ruby on Rails
• Dive into React Native performance
• Preload: What Is It Good For?
• FairRide: Near-Optimal, Fair Cache Sharing
• Redis vs. Hazelcast – Radargun Puts Them to a Challenge
• Thread pools! How do I use them?
• Is reference counting slower than GC?
• A Short Note on Atomicity and Ordering
• Building a Translation Memory to Improve Machine Translation Coverage and Quality
• 9 Lessons Learned Scaling Hotjar’s Tech Architecture To Handle 21,875,000 Requests Per Hour
• How to avoid wasting megabytes of memory a few bytes at a time
• Profiling mysteries
• How Twitter Handles 3,000 Images Per Second
• Introducing Runway, a distributed systems design tool
• Memory Leaks and Resource Management in Swift and iOS
• How we implemented the video player in Mail.Ru Cloud
• Resilient ad serving at Twitter-scale
• The Platform Advantage of Amazon, Facebook, and Google
• How to derive business value from performance monitoring?
• Making GitLab Faster
• Fixing the Internet for Real Time Applications: Part II
• Writing a very fast cache service with millions of entries in Go
• Managing Mobile Performance Optimization
• Performance Tuning Ideas for Apache Camel