Migrating off ELK is usually about the cost and operational burden of running Elasticsearch, and the trick is to preserve search and dashboards while you move.
Migrating from the Elastic/ELK Stack means moving your logs, and often metrics and APM, off Elasticsearch, Logstash and Kibana to a new platform, usually to cut the operational and storage cost of running Elasticsearch at scale, while preserving the search and dashboards teams rely on.
The ELK Stack is powerful and open, but running it at scale is a project in itself: Elasticsearch cluster management, shard and cardinality tuning, and storage that grows relentlessly with log volume, plus Logstash pipelines to maintain. For many teams the total cost of ownership, in infrastructure and engineering time, eventually outweighs the benefit of owning the stack. Migrations are usually driven by that operational and cost burden, not by any failing in ELK's search itself.
As with any observability migration, run in parallel rather than cutting over at once. Shift ingestion to OpenTelemetry: replace Logstash and Beats with an OpenTelemetry Collector or Fluent Bit shipping over OTLP, and dual-run so logs flow to both Elasticsearch and the new backend while you validate. Recreate the Kibana dashboards and saved searches teams depend on, confirm log-search parity for the queries that matter, and only then decommission the Elasticsearch cluster. Throughout, keep retention and compliance requirements intact so nothing that must be kept is lost.
Search and query parity is the main risk: Elasticsearch has its own query DSL, and you need to confirm the queries and dashboards teams rely on work on the new platform. Field mappings and index patterns have to be translated, dashboards rebuilt, and alerting migrated. Retention policies deserve special attention, since logs often carry compliance obligations. A migration is also a good moment to shed the noise you were paying to index, filtering low-value logs at the edge rather than carrying old habits into the new system.
| ELK component | Replacement |
|---|---|
| Elasticsearch | OpenTelemetry-native / open log store |
| Logstash and Beats | OpenTelemetry Collector or Fluent Bit |
| Kibana | Rebuilt dashboards on the new platform |
| Index patterns and mappings | Attributes and schema on the new store |
| Watcher alerts | Alerts in the new backend |
Ops Singularity is OpenTelemetry-native and stores telemetry at petabyte scale on open storage, so it is a natural destination for an ELK migration: move ingestion to OpenTelemetry, land the data on cost-efficient storage, and gain autonomous, governed resolution instead of just another place to search logs.
Usually because of the operational and storage cost of running Elasticsearch at scale, shard tuning, cluster management and growing storage, rather than any weakness in its search.
Run in parallel: ship logs to both Elasticsearch and the new backend via OpenTelemetry, validate query and dashboard parity, then decommission the cluster once the new platform matches.
The OpenTelemetry Collector, or Fluent Bit as a lightweight edge collector, both shipping over OTLP, replace Logstash and Beats for ingestion.
Ops Singularity turns open telemetry into autonomous, governed resolution. See it on your own stack.