Editor's Note: This is the second in a series of posts describing how we improved productivity at scale—both in terms of lines of code and number of engineers—at LinkedIn. In our first post of the #ProductivityAtScale series, we shared details on how we improved build time by 400%. This post covers how we continue to improve productivity with Gradle build cache....
Developer Productivity Articles
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- Topics:
- Developer Productivity,
- gradle
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When adopting a new language at scale, there are many different factors to consider because things can change dramatically. For many, choosing a language can arguably rely on personal preference, but at LinkedIn, we have a Foundation team tasked with evaluating the impact of such fundamental technical decisions. Recently, we underwent the process of evaluating...
- Topics:
- Developer Productivity,
- Android,
- Mobile
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Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more. Pinot uses Apache Helix for managing cluster resources and Apache Zookeeper to store metadata. Pinot has wide adoption at LinkedIn, ranging from internal...
- Topics:
- scale,
- Developer Productivity,
- Pinot,
- infrastructure
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With over 630 million members, the LinkedIn platform delivers thousands of features that individually serve and store large amounts of...
- Topics:
- scale,
- infrastructure,
- Developer Productivity
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Co-authors: Joel Young, Bee-Chung Chen, Bo Long, Marius Seritan, and Priyanka Gariba The rate at which artificial intelligence (AI)...
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At LinkedIn, when our engineers create software, there is often a need to leverage some of the great work done by the open source...
- Topics:
- Developer Productivity,
- Developer Experience,
- tools,
- Code