InfoQ Homepage Cloud Computing Content on InfoQ
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A Practical Road to SaaS in Python
Armin Ronacher discusses his experiences building SaaS businesses on a Python technology stack from a security and scalability point of view, and what other technologies work well with Python.
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Dev to Prod in Five Minutes: Is Your Company Ready?
Carlos Leon gives first-hand practical advice for adopting containers and the changes required, and talks about the technical and cultural changes needed to move at the pace containers can offer.
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When Containers Attack!
Anne Currie dives deep into history: what the past can tell us about full stack engineers, popular tech platforms and the dangers of searching for the perfect technology.
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cgroupv2: Linux's New Unified Control Group System
Chris Down goes over design decisions and deviations for cgroupv2 compared to v1, pitfalls and caveats one may encounter when migrating to cgroupv2, and how Facebook is using cgroupv2.
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Continuous Delivery the Hard Way with Kubernetes
Luke Marsden assembles a CI/CD pipeline from scratch to Kubernetes using GitLab CE as an example. The talk is mostly demos.
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Deliver Docker Containers Continuously on AWS
Philipp Garbe discusses ECS and all other services needed to run containers in production, automatically deploying and scaling an ECS cluster and containerized applications.
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The Hitchhiker's Guide to Serverless JavaScript
Steve Faulkner discusses Bustle's entire serverless stack. He talks about the good, the bad, and the ugly, sharing real numbers from production systems.
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It's Microservices All the Way down
Ori Pekelam discusses the principles underlying a microservices architecture, the risks associated with it, topologies, ways of communication between services, deployment, and other considerations.
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Continuous Performance Testing
Mark Price talks about techniques for making performance testing a first-class citizen in a Continuous Delivery pipeline.
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Building Reliability in an Unreliable World
Greg Murphy describes how GameSparks has designed their platform to be tolerant of many things: unreliable and slow internet connectivity, cloud resources that can fail without warning, and more.
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Big Data Infrastructure @ LinkedIn
Shirshanka Das describes LinkedIn’s Big Data Infrastructure and its evolution through the years, including details on the motivation and architecture of Gobblin, Pinot and WhereHows.
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From Data Science to Production–Deploy, Scale, Enjoy
Sergii Khomenko introduces best practices in development, covers production deployments to the AWS stack, and using the serverless architecture for data applications.
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