This article was written by Swapnik Ghike, Software Engineer LinkedIn and posted at the LinkedIn Engineering Blog.
High-performance applications form the backbone of the modern web. At LinkedIn, a number of internal high-throughput services cater to thousands of user requests per second. For optimal user experience, it is very important to serve these requests with low latency.
For example, a product our members use regularly is the Feed – a constantly updating list of professional activities and content. Examples of various feeds across LinkedIn include those in company pages, school pages, and most importantly – the homepage feed. The underlying feed data platform that indexes these updates from various entities in our economic graph (members, companies, groups, etc.) has to serve relevant updates with high throughput and low latency.
For taking these types of high-throughput, low-latency Java applications to production, developers have to ensure consistent performance at every stage of the application development cycle. Determining optimal Garbage Collection (GC) settings is critical to achieve these metrics.
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