Operations 9 min read

How to Consolidate Monitoring for Multiple Elasticsearch Clusters with INFINI Console

The article analyzes the pain points of managing several Elasticsearch clusters separately, compares native Kibana, custom scripts, and commercial tools, and then walks through a practical implementation using the lightweight INFINI Console to achieve unified, version‑agnostic monitoring and alerting.

Mingyi World Elasticsearch
Mingyi World Elasticsearch
Mingyi World Elasticsearch
How to Consolidate Monitoring for Multiple Elasticsearch Clusters with INFINI Console

Problem Analysis: Pain Points of Multi‑Cluster Monitoring

When a company runs three to five Elasticsearch clusters for log analysis, search services, or testing, each cluster has its own nodes, indices, and health status. Managing them individually leads to scattered administration, low efficiency, version incompatibility (e.g., 6.x vs 8.x), lack of a unified view for key metrics, and slow incident response because each cluster must be checked one by one.

Solution Exploration: Available Options

1. Native Kibana Monitoring

Pros : Direct integration with Elasticsearch, simple configuration, strong data visualization.

Cons : Designed for a single cluster; multi‑cluster support requires Cross‑Cluster Search and has limited version compatibility. Deployment is heavyweight (hundreds of MB).

2. Custom Scripts + Monitoring Platform

Pros : Highly customizable; you can pull any metric you need.

Cons : High development and maintenance cost; you must handle version compatibility, data collection stability, and operational complexity.

3. Third‑Party Commercial Tools

Pros : Feature‑complete, out‑of‑the‑box, with vendor support.

Cons : Expensive, data must be sent to the vendor’s cloud (potential security concerns), and customization is limited. Small teams often cannot afford them.

4. INFINI Console

Pros : Lightweight (17 MB installer), supports all Elasticsearch versions (1.x‑8.x) and also OpenSearch/Easysearch, provides a unified view, alerting, and data migration, open‑source and free.

Cons : Community is relatively new; documentation and examples are still being expanded.

Compared with the other options, INFINI Console stands out for its light footprint, strong compatibility, and ease of use for small teams.

Implementation: Using INFINI Console

1. Install INFINI Console

INFINI Console is written in Go and can be deployed without external dependencies.

2. Register Clusters

After installation, click “Cluster Register” and add each cluster by providing its address (e.g., 192.168.1.100:9200) and optional credentials. Test the connection, then save. Repeat for all clusters.

3. Unified Dashboard

Overview : Top bar shows real‑time alert counts and health status (green, yellow, red) for all clusters.

Cluster List : “Cluster Management” displays node count, index count, JVM usage, and allows filtering by version or health.

4. Set Up Alerts

Navigate to “Alert Management”, create a rule such as “when a cluster health turns yellow, send a notification”. Supported channels include email, DingTalk, and WeChat; the author chose email, configured SMTP, and received a test alert within two seconds.

5. Data Exploration

Use “Data Explorer” (similar to Kibana’s Discover) to query documents across clusters without logging into each Kibana instance.

Conclusion: Value of INFINI Console

Unified Management : One interface for all clusters.

Strong Compatibility : Works with any Elasticsearch version and even OpenSearch/Easysearch.

Lightweight & Easy : 17 MB package, minutes to deploy, suitable for junior ops.

Practical Features : Monitoring, alerting, data exploration, all open‑source and free.

The tool is not perfect—advanced reporting may still be missing—but for the common need of multi‑cluster monitoring it is already sufficient.

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monitoringElasticsearchMulti-ClusterAlertingPrometheusKibanaINFINI Console
Mingyi World Elasticsearch
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Mingyi World Elasticsearch

The leading WeChat public account for Elasticsearch fundamentals, advanced topics, and hands‑on practice. Join us to dive deep into the ELK Stack (Elasticsearch, Logstash, Kibana, Beats).

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