06-14, 14:00–14:40 (Europe/Berlin), Frannz Salon
Elasticsearch (or OpenSearch) clusters likely need to scale to adapt to changes in load. But autoscaling Elasticsearch isn't trivial: indices and shards need to be well sized and well balanced across nodes. Otherwise the cluster will have hotspots and scaling it further will be less and less efficient.
This talk focuses on two aspects:
- best practices around scaling Elasticsearch for logs and other time-series data
- how to apply them when deploying Elasticsearch on Kubernetes. In the process, a new (open-source) operator will be introduced (yes, there will be a demo!). This operator will autoscale Elasticsearch while keeping a good balance of load. It does so by changing the number of shards in the index template and rotating indices when the number of nodes changes.
The Search track is presented by OpenSource Connections
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Radu Gheorghe works mainly as a search consultant at Sematext, working with clients of all sizes on their Elasticsearch and Solr projects. He is also a trainer and does production support for both these search engines.
Sometimes he helps out with the development of Sematext Cloud (an observability SaaS), mostly when it comes to Elasticsearch and log shippers (e.g. Logstash, rsyslog...). He also writes on the Sematext blog or helps other publish new articles.
He co-authored a book (Elasticsearch in Action, Manning), recorded a video tutorial (Working with Elasticsearch, O'Reilly) and was a speaker at a number of conferences, such as Berlin Buzzwords, LuceneSolrRevolution (later Activate) and O'Reilly Velocity.
Ciprian Hacman works mainly as a DevOps/Software Engineer for polypoly, helping them and other clients modernize their infrastructure and migrate to Kubernetes.
He is also an open source project maintainer for kOps (Kubernetes Operations), etcd-manager, cloud-provider-aws and frequent contributor to other projects in the Kubernetes ecosystem.