Scaling Elasticsearch to petabytes and beyond: Tips for scaling storage, ingest, backup, and queries
We’ll discuss effectively scaling Elasticsearch clusters to petabytes and beyond using the latest features in Elasticsearch 6.x and 7.0.
We'll discuss Elasticsearch scaling best practices in four categories:
- scaling Elasticsearch storage
- scaling search queries
- scaling data ingestion
- scaling backups and recovery
From index lifecycle management (ILM) and frozen indices to improvements to cross-cluster search (CCS) and more, Elasticsearch has come a long way. We're excited to share these new features with you.
- Implementing a Hot-Warm-Cold Architecture with Index Lifecycle Management
- Creating frozen indices with the Elasticsearch Freeze index API
- Getting started with cross-cluster replication
- Want to try it for yourself? Take some of these features for a spin with a free trial of our Elasticsearch Service
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Jason Zucchetto is a member of the Product Management team and focuses on Elasticsearch. Prior to joining Elastic, Jason was an early employee at a popular open source database company. Jason has held several positions, ranging from Java architect, team lead, and company co-founder. Jason is passionate about distributed systems, financial technologies, and developer experiences.