Migrate from Kibana to OpenObserve

If you're running Kibana on top of Elasticsearch for log exploration and dashboards and want to move to OpenObserve, this guide walks you through moving your dashboards and visualizations. The OpenObserve Dashboard Migrator converts Kibana saved-object exports into OpenObserve dashboards automatically, translating Lucene and KQL queries to SQL.

Kibana is a visualization layer over Elasticsearch, so migrating it has two independent parts:

1. The data — move your Elasticsearch data into OpenObserve streams. This is a standard ingestion task (OpenTelemetry Collector, Filebeat, Logstash, or Fluent Bit) and has nothing to do with the dashboard work.
2. The dashboards and visualizations — convert your saved objects into OpenObserve dashboards. This is what the Dashboard Migrator automates.

Table of Contents

1. Overview — why migrate and what changes
2. Migrating Dashboards & Visualizations — convert Kibana saved objects with the Dashboard Migrator

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Why Migrate?

Kibana is a capable visualization tool, but running it means operating the whole Elastic stack — and most of that cost is spent on things you don't get visibility value from.

License and vendor lock-in

Elasticsearch and Kibana are licensed under the SSPL, which is restrictive for teams offering Elasticsearch as a service. The query language (Lucene/KQL), the saved-object export format, and the aggregation DSL are all Elastic-specific.

OpenObserve is open source and speaks open protocols (OpenTelemetry, Prometheus Remote Write, Loki Push API, plain JSON), and queries your data with SQL — a language your team already knows.

Operational cost

The Elastic stack is heavyweight: a JVM per node with large heap allocation, separate Elasticsearch, Kibana, and (usually) Logstash or Beats deployments, and careful index/shard lifecycle management. OpenObserve is a single binary (or Helm chart) that stores data as Apache Parquet on object storage — up to 140x more efficient — with no JVM, no index management, and no shard tuning.

Storage cost

Elasticsearch keeps every field indexed by default, which balloons disk usage and memory. OpenObserve stores raw events as Parquet columns and indexes only what you tell it to, so the same data costs a fraction of the disk.

What OpenObserve Changes

Before You Start

Before migrating, export a snapshot of what you have:

• Dashboards and visualizations: in Kibana, go to Stack Management → Saved Objects and export everything (or the dashboards you actually use) as an .ndjson file. This is the input to the Dashboard Migrator.
• Index patterns: note which index patterns your visualizations reference — the migrator maps these to OpenObserve streams.
• Data sources: confirm how data reaches Elasticsearch today (Beats, Logstash, Fluent Bit, application SDKs), so you can repoint it at OpenObserve.

Set Up OpenObserve

Before migrating, get OpenObserve running:

Next Steps

• Migrating Dashboards & Visualizations — convert Kibana saved objects with the Dashboard Migrator
• OpenObserve Ingestion — get your logs, metrics, and traces into OpenObserve

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