How Workday Search Built their Metrics Pipeline with the Elastic Stack

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After struggling to find a traditional database that could ingest large volumes of application metrics at an acceptable rate, Workday Search noticed that each of their already existing Elastic Stack deployments were able to process over 1 billion log events a week without issues. This talk will share how Workday Search expanded their deployment by implementing a robust, easy-to-use metrics processing pipeline.

Bo and Thomas will provide details on how they architected their pipeline, the scripts and frontend tools they use to visualize their data and proactively alert them to issues in production, as well as the metrics they look at to provide insight into usage patterns and facilitate intelligent product decisions.

Bodecker DellaMaria

Bo DellaMaria is a Software Engineer on the Workday Search team, where he focuses on developing microservices in Scala and optimizing Workday’s production Elasticsearch clusters. Originally from the suburbs of Chicago (go Cubs!), Bo studied Computer Engineering at the University of Illinois at Urbana-Champaign and came straight to San Francisco after school. Relevant to this conference, Bo also created an open source workshop to help others learn about Elasticsearch in a quick and fun manner.

Thomas Kim

Thomas Kim is a Principal Engineer at Workday, where he uses Elasticsearch to help build the microservices that power Workday Search. At Workday he spends his time pushing Elasticsearch to solve Workday’s multi-tenancy and security requirements. He has spent 15 years working in enterprise software, previously at Salesforce and Upshot Data, a small company he co-founded. He enjoys typeful functional programming in Scala and loves teaching it to new developers. Being a bandwagon Warriors fan makes his wife laugh.