Co-authors: Susie Xia and Anant Rao LinkedIn serves more than 467 million members on a global computing infrastructure through hundreds of internal services. During processes such as new feature releases, capacity planning for traffic growth, and data center failover analysis, the following questions are raised frequently: “What is the maximum QPS (queries per...
Automation Articles
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- Topics:
- Performance,
- Resilience,
- Testing,
- Automation
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LinkedIn’s data center infrastructure has grown at a massive scale. Starting with one server setup, one cabinet at a time, we’re now powering on hundreds of servers at a time and seeing them come online automatically. You could call it “Zero Touch Provisioning” for systems. This evolution presented us with many challenges, however. This post will describe how...
- Topics:
- data center,
- Automation
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Around the end of 2012, LinkedIn decided to move away from retail data centers to wholesale ones that are built and maintained by LinkedIn. With exponential growth prospects we were already going to build multiple data centers in the coming few years. One major and time-consuming task of this operation is bringing up the application stack—which consists of over...
- Topics:
- Python,
- Automation,
- SRE
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LinkedIn’s API is the gateway used by numerous applications to access LinkedIn data, from simple third-party apps to large-scale...
- Topics:
- tools,
- Automation,
- SRE
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In ensuring site availability as you scale, you automate or you die. Making sure LinkedIn works properly for 364 million members...
- Topics:
- infrastructure,
- Automation,
- SRE
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A key point of frustration for many developers is a slow and inflexible release cycle. The slower the release cycle, harder it is for...
- Topics:
- Release Quality,
- Automation,
- developer happiness