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You're reading from  Vector Search for Practitioners with Elastic

Product typeBook
Published inNov 2023
PublisherPackt
ISBN-139781805121022
Edition1st Edition
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Authors (2):
Bahaaldine Azarmi
Bahaaldine Azarmi
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Bahaaldine Azarmi

Bahaaldine Azarmi, Global VP Customer Engineering at Elastic, guides companies as they leverage data architecture, distributed systems, machine learning, and generative AI. He leads the customer engineering team, focusing on cloud consumption, and is passionate about sharing knowledge to build and inspire a community skilled in AI.
Read more about Bahaaldine Azarmi

Jeff Vestal
Jeff Vestal
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Jeff Vestal

Jeff Vestal has a rich background spanning over a decade in financial trading firms and extensive experience with Elasticsearch. He offers a unique blend of operational acumen, engineering skills, and machine learning expertise. As a Principal Customer Enterprise Architect, he excels at crafting innovative solutions, leveraging Elasticsearch's advanced search capabilities, machine learning features, and generative AI integrations, adeptly guiding users to transform complex data challenges into actionable insights.
Read more about Jeff Vestal

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Summary

In this chapter, you hopefully have learned the end-to-end process of setting up log vectorization for your log analysis workload based on Elastic. One important point for you to decide on while doing this is whether you expand the log on write or on read, meaning preparing the data while ingesting it or expanding to the meaning of the raw log only when querying it. As you can appreciate, this is still an exploratory domain where applying vector search, or GenAI, to accelerate observability incident management workflow is just beginning to murmur. But you are now prepared with the necessary guidance to implement it as it grows.

In the next chapter, we will address another domain of application for vectors and semantic search—cybersecurity, where the requirements are pretty similar to observability in terms of data, but the workflow is quite different.

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Vector Search for Practitioners with Elastic
Published in: Nov 2023Publisher: PacktISBN-13: 9781805121022

Authors (2)

author image
Bahaaldine Azarmi

Bahaaldine Azarmi, Global VP Customer Engineering at Elastic, guides companies as they leverage data architecture, distributed systems, machine learning, and generative AI. He leads the customer engineering team, focusing on cloud consumption, and is passionate about sharing knowledge to build and inspire a community skilled in AI.
Read more about Bahaaldine Azarmi

author image
Jeff Vestal

Jeff Vestal has a rich background spanning over a decade in financial trading firms and extensive experience with Elasticsearch. He offers a unique blend of operational acumen, engineering skills, and machine learning expertise. As a Principal Customer Enterprise Architect, he excels at crafting innovative solutions, leveraging Elasticsearch's advanced search capabilities, machine learning features, and generative AI integrations, adeptly guiding users to transform complex data challenges into actionable insights.
Read more about Jeff Vestal