InfoQ Homepage Scalability Content on InfoQ
-
Futures and Promises: Lessons in Concurrency Learned at Tumblr
Blake Matheny discusses the current status of Tumblr, its evolution and lessons learned along the way, 3 types of concurrency -Macro, Mecro and Micro-, and Motherboy –a dashboard system-.
-
Embracing Concurrency at Scale
Justin Sheehy discusses designing reliable distributed systems that can scale in order to deal with concurrency problems and the tradeoffs required by such systems.
-
Event Processing at Massive Scale
Uri Cohen discusses several types of queues with their pros and cons used in financial and trading industries for highly parallelized data processing.
-
Scalable Internet Architectures
Theo Schlossnagle presents several architectural design principles useful for building scalable systems starting from the networking up to the application layer.
-
Architecture at Scale at ESPN
Manny Pelarinos presents ESPN’s overall and core service architecture, the data ingest process, the custom CMS and template language used, and how live scores and personalization work.
-
Storm: Distributed and Fault-tolerant Real-time Computation
Nathan Marz discusses Storm concepts –streams, spouts, bolts, topologies-, explaining how to use Storms’ Clojure DSL for real-time stream processing, distributed RPS and continuous computations.
-
Reliability Engineering Matters, Except When It Doesn't
Michael Nygard shares essential Reliability Engineering techniques that can keep systems from falling apart, but the discipline has some limitations to be considered.
-
Above the Clouds: Introducing Akka
Jonas Bonér introduces Akka, a JVM platform that wants to address the complex problems of concurrency, scalability and fault tolerance using Actors, STM and self-healing from crashes.
-
Get Satisfaction Uses Ruby on Rails and Cloud Computing Platform to Achieve Scalability and Reliability
Thor Muller presents how Get Satisfaction managed to reliably scale their Ruby on Rails-based customer community platform using Agile, TDD, BDD, and by deploying their framework in the cloud.
-
Scaling with MongoDB
Roger Bodamer provides advice on scaling out MongoDB using replica sets and auto-sharding, plus tips for database deployment and scaling use cases.
-
Being Elastic - Evolving Programming for the Cloud
Randy Shoup discusses the cloud programming model, covering topics such as state/statelessness, distribution, workload partitioning, cost and resource metering, automation, and deployment strategies.
-
Embracing Concurrency At Scale
Justin Sheehy explains the principles behind concurrent distributed systems: no global state, no ACID but rather BASE, no RPC but protocols over APIs, prepare for failure, degradation, measurement.