Elasticsearch Technology Intelligence

What is Elasticsearch?

Elasticsearch is a distributed, RESTful search and analytics engine built on Apache Lucene. It provides real-time search, analysis, and storage capabilities at scale, making it the core of the Elastic Stack (formerly ELK Stack) for logging, monitoring, and security analytics.

Created by Shay Banon in 2010, Elasticsearch was designed from the ground up as a distributed system. Its JSON-based document storage, powerful query DSL, and horizontal scaling have made it the most popular enterprise search engine. Elastic NV provides commercial support and develops the Elastic Stack including Kibana for visualization, Logstash and Beats for data collection, and various security and observability solutions.

Key Features

Search Capabilities

• Full-Text Search: Relevance-ranked text search
• Fuzzy Search: Match despite typos and variations
• Autocomplete: Search-as-you-type suggestions
• Aggregations: Analytics and faceted search
• Geo Search: Location-based queries
• Vector Search: KNN for similarity and ML embeddings

Distributed Architecture

• Horizontal Scaling: Add nodes to increase capacity
• Sharding: Distribute data across nodes
• Replication: Automatic replica management
• Cluster Coordination: Automatic master election

Data Management

• Dynamic Mapping: Auto-detect field types
• Index Templates: Configure mappings for new indices
• Index Lifecycle: Automate rollover and deletion
• Snapshot/Restore: Backup to object storage

API and Query DSL

• RESTful JSON APIs
• SQL query support
• Painless scripting language
• Bulk operations for high throughput

Use Cases

Log and Event Analytics

Organizations centralize logs from applications, servers, and containers in Elasticsearch. Combined with Kibana dashboards, teams analyze patterns, troubleshoot issues, and monitor system health in real-time.

Application Search

E-commerce sites, content platforms, and applications power their search with Elasticsearch. Features like autocomplete, typo tolerance, and relevance tuning create superior search experiences.

Security Analytics (SIEM)

Security teams use Elasticsearch for security information and event management. Threat detection rules, anomaly detection, and incident investigation benefit from fast search across security events.

Infrastructure Monitoring

DevOps teams monitor infrastructure metrics and traces with Elasticsearch. The ability to correlate logs, metrics, and APM data provides observability across distributed systems.

Business Analytics

Companies analyze business data in near real-time. Aggregations across millions of records power dashboards showing sales trends, user behavior, and operational metrics.

Geospatial Applications

Location-based services use Elasticsearch geo features. Store finders, delivery radius search, and geographic filtering leverage built-in geospatial capabilities.

Code Examples

Index Document

curl -X POST "localhost:9200/products/_doc/1" -H 'Content-Type: application/json' -d'
{
    "name": "Wireless Headphones",
    "description": "Premium noise-canceling wireless headphones",
    "price": 299.99,
    "category": "electronics",
    "tags": ["audio", "wireless", "premium"],
    "in_stock": true
}'

Search Query DSL

{
    "query": {
        "bool": {
            "must": [
                { "match": { "description": "wireless headphones" } }
            ],
            "filter": [
                { "range": { "price": { "lte": 500 } } },
                { "term": { "in_stock": true } }
            ]
        }
    },
    "aggs": {
        "categories": {
            "terms": { "field": "category.keyword" }
        },
        "avg_price": {
            "avg": { "field": "price" }
        }
    },
    "highlight": {
        "fields": { "description": {} }
    }
}

Node.js Client

const { Client } = require('@elastic/elasticsearch');
const client = new Client({ node: 'http://localhost:9200' });

// Search products
const result = await client.search({
    index: 'products',
    body: {
        query: {
            multi_match: {
                query: 'wireless audio',
                fields: ['name^2', 'description', 'tags']
            }
        }
    }
});

result.hits.hits.forEach(hit => {
    console.log(hit._source.name, hit._score);
});

Index Mapping

{
    "mappings": {
        "properties": {
            "name": { "type": "text", "analyzer": "english" },
            "price": { "type": "float" },
            "category": { "type": "keyword" },
            "location": { "type": "geo_point" },
            "created_at": { "type": "date" }
        }
    }
}

Elastic Stack and Deployment

Elastic Stack Components

• Kibana: Visualization and dashboard platform
• Logstash: Data processing pipeline
• Beats: Lightweight data shippers
• APM: Application performance monitoring
• Fleet: Centralized agent management

Deployment Options

• Elastic Cloud: Official managed service
• Self-Managed: On-premises or cloud VMs
• Amazon OpenSearch: AWS managed fork
• Kubernetes: ECK operator for orchestration

Licensing

• Basic: Free core features
• Gold/Platinum/Enterprise: Additional security, ML, support
• SSPL: License change from Apache 2.0 in 2021
• OpenSearch: Apache 2.0 licensed fork

Comparison

• vs Solr: Elasticsearch easier clustering, Solr more mature
• vs OpenSearch: Same origin, Elasticsearch more features
• vs Splunk: Elasticsearch open source, Splunk more polished

Best Practices

• Size shards appropriately (10-50GB)
• Use index lifecycle management
• Configure dedicated master nodes
• Monitor cluster health continuously