InfoQ Homepage Scalability Content on InfoQ
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Stream Processing at Scale with Spring XD and Kafka
Marius Bogoevici demoes how to unleash the power of Kafka with Spring XD, by building a highly scalable data pipeline with RxJava and Kafka, using Spring XD as a platform.
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Data Driven Action: A Primer on Data Science
S Aerni, S Ramanujam and J Vawdrey present approaches and open source tools for wrangling and modeling massive datasets, scaling Java applications for NLP on MPP through PL/Java and much more.
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Create Elegant Builds at Scale with Gradle
Hans Dockter discusses how to solve the challenges of standardization, dependency management, multi-language builds, and automatic build infrastructure provisioning.
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LinkedIn's Active/Active Evolution
Erran Berger discusses how they scaled architecture at LinkedIn across multiple data centers.
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Don't Scale Agile. Descale Your Organization
Stuart Bargon discusses how to “descale” an organization, removing the extra weight and making it agile, showcasing the transformation of one of the oldest Australian public institutions.
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Orchestrating Containers with Terraform and Consul
Mitchell Hashimoto shows how Terraform and Consul can be used together to easily deploy and scale large-scale containerized workloads using container runtimes like Docker.
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Workers, Queues, and Cache
Jason McCreary takes a look at using background job processes, messaging queues, and cache to help an application scale.
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Scaling Stack Overflow: Keeping it Vertical by Obsessing Over Performance
David Fullerton shares some of the things the Stack Exchange tech team have learned along the way while scaling one of the top sites in the world primarily through vertical scaling.
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A Pragmatic Introduction to Multicore Synchronization
Samy Bahra discusses high performance multicore synchronization, scalability bottlenecks in multicore systems and memory models, and scalable locking and lock-less synchronization.
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Ground-up Introduction to In-memory Data
Viktor Gamov covers In-Memory technology, distributed data topologies, making in-memory reliable, scalable and durable, when to use NoSQL, and techniques for Big In-Memory Data.
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Elements of Scale
Ben Stopford examines tools, mechanisms and tradeoffs that allow a data architecture to scale, from disk formats to fully blown architectures for real-time storage, streaming and batch processing.
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Scaling Distributed Systems
Natalia Chechina outlines features of actor and functional programming models, and the reason these models attract so much interest in parallel, concurrent, and scaling world.
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