Elasticsearch – Scalability and Multitenancy [slides]
Last week I gave a talk in a local tech group about my experience with Elasticsearch at LogSentinel, and how we achieve multitenancy and scalability.
Obviously, the topic of scalability is huge and it can’t be fully covered in 45 minutes, but I tried presenting the main aspects from the application perspective (I entirely skipped the Ops perspective, as it was a developer audience). The list of resources at the end of the slides show some of the sources of my “research” on the topic, which I recommend going through.
Below are the slides (the talk was not in English):
I hope it’s a useful intro to the topic and the main conclusion is – it’s counterintuitive if you are used to relational databases, and some internals (shards, Lucene segments) “leak” through the abstractions to influence the application design (as per the law of leaky abstractions).
Last week I gave a talk in a local tech group about my experience with Elasticsearch at LogSentinel, and how we achieve multitenancy and scalability.
Obviously, the topic of scalability is huge and it can’t be fully covered in 45 minutes, but I tried presenting the main aspects from the application perspective (I entirely skipped the Ops perspective, as it was a developer audience). The list of resources at the end of the slides show some of the sources of my “research” on the topic, which I recommend going through.
Below are the slides (the talk was not in English):
I hope it’s a useful intro to the topic and the main conclusion is – it’s counterintuitive if you are used to relational databases, and some internals (shards, Lucene segments) “leak” through the abstractions to influence the application design (as per the law of leaky abstractions).