{"id":183,"date":"2020-12-01T17:00:00","date_gmt":"2020-12-01T17:00:00","guid":{"rendered":"https:\/\/fde.cat\/index.php\/2020\/12\/01\/from-lambda-to-lambda-less-lessons-learned\/"},"modified":"2021-02-02T13:45:34","modified_gmt":"2021-02-02T13:45:34","slug":"from-lambda-to-lambda-less-lessons-learned","status":"publish","type":"post","link":"https:\/\/fde.cat\/index.php\/2020\/12\/01\/from-lambda-to-lambda-less-lessons-learned\/","title":{"rendered":"From Lambda to Lambda-less: Lessons learned"},"content":{"rendered":"
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Co-authors: Xiang Zhang<\/a> and Jingyu Zhu<\/a><\/i><\/p>\n

Introduction<\/h2>\n

The Lambda architecture<\/a> has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods. But it also has some drawbacks, such as complexity and additional development\/operational overheads. One of our features for Premium members on LinkedIn, Who Viewed Your Profile<\/a> (WVYP), relied on a Lambda architecture for some time. The backend system supporting this feature had gone through a few architectural iterations in the past years: it started as a Kafka client processing a single Kafka topic, and eventually evolved to a Lambda architecture with more complicated processing logic. However, in an effort to pursue faster product iteration and lower operational overheads, we recently underwent a transition to make it Lambda-less. In this blog post, we\u2019ll share some of the lessons learned in operating this system in the Lambda architecture, the decisions made in transitioning to Lambda-less, and the shifts necessary to undergo this transition.<\/p>\n

How the system works<\/h2>\n

The WVYP system relies on a number of different input sources to provide members with an up-to-date record of who most recently viewed their profile. These details include:\u00a0<\/p>\n