Building a Cloud-Native Search Platform: Solr-to-Elasticsearch Migration for a Global Enterprise
Client
A global professional services firm modernized its search capabilities by migrating from Solr to Elasticsearch v8.16.1 on a cloud-native ECK Operator v3.0.0 deployment within Google Kubernetes Engine (GKE).
Project Context
The client sought to modernize its search platform by migrating from legacy Solr to the Elastic Stack. The new setup was deployed on Google Kubernetes Engine (GKE) using the ECK Operator v3.0.0, enabling a cloud-native and scalable environment. The project focused on delivering production-grade security, scalability, and observability, along with a smooth, reliable migration of all data from Solr to Elasticsearch.
Project Objectives
- Establish a new, best-practices ECK setup from scratch for all environments.
- Data Migration: Migrate all data from Solr to Elasticsearch using custom scripts, while also optimizing search workloads.
Challenges
- Seamless migration of complex, high-volume data from legacy Solr to Elasticsearch.
- Deployment of the new cloud-native search cluster on GKE using Elastic Stack.
- Ensuring production-grade security, performance, and reliability from day one.
Solution
- Deployed ECK v3.0.0 with Elasticsearch v8.16.1 on GKE (3 master, 3 hot, 3 cold nodes).
- Used custom Python scripts to execute seamless Solr-to-Elasticsearch data transfer.
- Configured Snapshot/Restoration workflows to safeguard all migrated data.
- Designed production security model: RBAC and Field/Document-Level Security.
- Implemented Stack Monitoring, slow logs, ILM tuning, and autoscaling recommendations.
