InfoQ Homepage Use Cases Content on InfoQ
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Robust Foundation for Data Pipelines at Scale - Lessons from Netflix
Jun He and Harrington Joseph share their experiences of building and operating the orchestration platform for Netflix’s big data ecosystem.
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Data Mesh in the Real World: Lessons Learnt from the Financial Markets
Tareq Abedrabbo shares how CMC Markets has gone through a transformation to take advantage of the new technologies, the architectural choices made and some of the challenges faced.
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Netflix Networking: Beating the Speed of Light with Intelligent Request Routing
Sergey Fedorov discusses how to build the Internet latency map, using network protocols and edge infrastructure, and how to use a data-driven approach to evolve your client-server interactions.
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Production Infrastructure Cloning++: Reliability and Repeatability
JD Palomino discusses how they have developed a cloud and product-agnostic infrastructure pipeline to handle extra steps and custom configuration, with no special exceptions.
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Safe and Fast Deploys at Planet Scale
Mathias Schwarz discusses the software management, scalability used by Uber, and the need to have these done automatically by software.
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Change Data Capture for Distributed Databases @Netflix
Raghuram Onti Srinivasan covers the challenges associated with capturing CDC events from Cassandra, discussing the Flink ecosystem and the use of RocksDB.
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Paving the Road to Production
Graham Jenson shares his experience of creating "paved roads" and deploying pipelines at Coinbase for the past five years, and what the advantages of doing that are.
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The More You Know: a Guide to Understanding Your Systems
Tyler Wells shares how Twilio developed a template that enables them to understand their systems better, identify critical metrics to watch, and how to use Chaos Engineering to verify it all.
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Let Devs Be Devs: Abstracting away Compliance and Reliability to Accelerate Modern Cloud Deployments
Rahul Arya shares how they built a platform to abstract away compliance, make reliability with Chaos Engineering completely self-serve, and enable developers to ship code faster.
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Lessons from Incident Management and Postmortems at Atlassian
Jim Severino shares what worked (and didn't work) in incident management and post-mortems for Atlassian.
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Identifying Hidden Dependencies
Liz Fong-Jones discusses some of the manual experiments they ran at Honeycomb, the bugs discovered in some automatic replacement tools, and what steps they took for continuously running experiments.
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Chaos Engineering: the Path to Reliability
Kolton Andrus shares examples of what works, what doesn’t, and what the future holds in using Chaos Engineering to build reliability in a system.
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