AEM Integration with Apache Solr: A Complete Technical Guide

Adobe Experience Manager (AEM) is a popular enterprise CMS. Integrating AEM with Apache Solr brings distributed indexing, advanced query features, and improved relevancy for large content platforms. This article walks through architecture choices, integration methods, configuration steps, sample code, and production best practices.

Why choose Solr for AEM?

• Scalability — SolrCloud supports sharding and replication for large datasets.
• Rich query features — faceting, boosting, spellcheck, suggestions.
• Performance — optimized for high read loads and complex queries.
• Custom scoring — advanced relevancy tuning for enterprise use cases.

Architecture overview

A typical integration places Solr as the external search engine while AEM remains the content source. Content authored and published in AEM is indexed in Solr. The front-end queries Solr for search results and displays them in AEM components or SPA layers.

Author/Publisher AEM  -->  Indexing Pipeline  -->  Solr (SolrCloud)
Front-end (AEM/Public) <-- --="" api="" ervice="" search=""> Solr

Common integration methods

1. Replication Agent / Push-based indexing

Configure a custom replication agent in AEM that sends content to Solr whenever a page is activated. This is a pragmatic approach that hooks into existing authoring workflows.

2. Sling Event Listeners / OSGi Service

Implement an OSGi service or Sling event listener that reacts to resource changes and sends JSON documents to Solr. Provides fine-grained control and transformation logic.

3. Pull-based indexing (REST / Data Import Handler)

Expose a REST endpoint from AEM and configure Solr to pull content on a schedule. Simpler to implement but less real-time.

Solr schema — fields to include

Create a Solr core/collection (e.g. aem-index) and define fields that reflect AEM content model:

• id — unique identifier (recommend using the content path)
• title, content, description
• path — AEM page or resource path
• last_modified — for incremental indexing
• tags, type, author — for faceting/filtering

Example: Simple Sling Servlet to index one page

Paste this into an OSGi-enabled servlet in AEM (simplified example — production code needs error handling and batching):

@SlingServlet(paths = "/bin/solr/index")
public class SolrIndexServlet extends SlingSafeMethodsServlet {
    @Override
    protected void doGet(SlingHttpServletRequest request, SlingHttpServletResponse response)
            throws ServletException, IOException {
        String path = request.getParameter("path");
        Resource resource = request.getResourceResolver().getResource(path);

        String title = resource.getValueMap().get("jcr:title", "");
        String content = resource.getValueMap().get("jcr:description", "");

        SolrInputDocument doc = new SolrInputDocument();
        doc.addField("id", path);
        doc.addField("title", title);
        doc.addField("content", content);

        SolrClient solr = new HttpSolrClient.Builder("http://localhost:8983/solr/aem-index").build();
        solr.add(doc);
        solr.commit();
    }
}

Querying Solr from AEM

Use the SolrJ client or HTTP APIs inside a custom AEM service to run queries and return structured results to front-end components.

SolrQuery query = new SolrQuery();
query.setQuery("content:experience");
query.addFacetField("type");
QueryResponse resp = solrClient.query(query);

Best practices for production

• Use SolrCloud (collections, shards, replicas) for HA and scale.
• Design your indexing pipeline for incremental updates (use last_modified).
• Index ACLs or implement a permissions filter so search results respect AEM security.
• Monitor Solr with metrics and alerts (Prometheus/Grafana + logs).
• Implement retries and buffering — network failures between AEM and Solr are common and should be handled gracefully.
• Plan for schema evolution and reindexing strategies.

Note: This guide provides a technical overview and starter code. For enterprise-grade implementations, consider batching, bulk-index workflows, schema management automation, and security auditing.

Conclusion

Integrating AEM with Solr opens powerful search capabilities for enterprise content platforms. Whether using push-based replication, an OSGi indexing service, or a mixed approach, the key is designing a reliable pipeline for indexing and a robust query layer for your front-end.