Knowing what actually breaks before you commit to the migration
ElasticsearchAmazon S3TerraformThe customer went into migration with a concrete list of the client upgrades and two feature redesigns required, rather than discovering them mid-cutover. Two workloads identified as poor migration ca…
Overview
A digital media platform wanted to move off a licensed Elasticsearch distribution to OpenSearch, but the estate had grown organically and nobody had a clear picture of which features were actually in use. AceMQ assessed feasibility, effort, and risk before any migration work started.
Challenge
The application estate used a mix of official Elasticsearch clients across several languages, and the newer client versions include a product check that refuses to talk to OpenSearch. Several teams had also built on features that diverge between the two projects, including specific machine learning jobs and a licensed alerting configuration. Without an inventory, the migration effort estimate was pure guesswork.
Environment
Elasticsearch clusters on AWS serving content search and log analytics, applications in Java, Python, and Node.js.
Approach
The assessment inventories every client library, plugin, index mapping feature, and query construct in use, then classifies each as compatible, requiring a client swap, or requiring redesign. We test the ambiguous cases against a real OpenSearch cluster rather than relying on compatibility matrices, and produce a phased migration plan with effort attached to each phase.
Solution
- 1Client library inventory across all application languages, flagging versions that will fail the product check
- 2Plugin and feature usage inventory covering alerting, anomaly detection, and any licensed-tier functionality in active use
- 3Query and mapping constructs tested against a live OpenSearch cluster to confirm behavior rather than assume it
- 4Index and snapshot compatibility path documented, including which snapshots can be restored directly and which need reindexing
- 5Phased migration plan with a dual-write or reindex strategy per workload and rollback criteria at each phase
- 6Cost and licensing comparison based on the customer's actual node counts and data volumes
Outcome
The customer went into migration with a concrete list of the client upgrades and two feature redesigns required, rather than discovering them mid-cutover. Two workloads identified as poor migration candidates were deliberately left in place, which removed the riskiest part of the original plan.
Technologies
ElasticsearchAmazon S3TerraformRelated Use Cases
OpenSearch Multi-Tenant Search Architecture Design
Consulting engagement to design tenant isolation, index strategy, and query governance for OpenSearch serving thousands of customer tenants.
OpenSearch Cluster Support for Regulated Workloads
24/7 enterprise support for OpenSearch clusters carrying regulated search and audit workloads, including security plugin and upgrade coverage.
Ready for a OpenSearch Health Check?
AceMQ's senior OpenSearch engineers have handled this exact type of engagement before. Whether you need architectural guidance, hands-on remediation, or an ongoing managed partnership, we're ready to help.