Monitoring and Optimization Examples for Our Elasticsearch Cluster
1. Monitoring Cluster Health
Let’s Optimize the index settings for the “logs” index in the Elasticsearch cluster to improve indexing and search performance.
GET /_cluster/health
2. Optimizing Index Settings (for “sample_index”)
Let’s optimize the index settings for the “sample_index” index, we can increase the number of primary shards to 5 and set the refresh interval to 30 seconds
PUT /sample_index/_settings
{
"settings": {
"number_of_shards": 5,
"refresh_interval": "30s"
}
}
3. Monitoring Node Metrics
To monitor node metrics such as CPU usage, memory usage, disk usage, and network throughput for all nodes in the cluster, we can use the _cat/nodes
API with the v
parameter to display the metrics in a tabular format.
GET /_cat/nodes?v
4. Monitoring Indexing Performance
To monitor indexing throughput, latency, and errors for an index named sample_index
, we can use the _cat/indices
API with the v
parameter to display detailed information about the index.
GET /_cat/indices/sample_index?v
5. Monitoring Search Performance
To execute a search query that matches all documents in the sample_index
index, we can use the _search
endpoint with a match_all
query.
GET /sample_index/_search
{
"query": {
"match_all": {}
}
}
6. Monitoring Shard Allocation
To retrieve information about the shards of the sample_index
index, we can use the _cat/shards
endpoint.
GET /_cat/shards/sample_index?v
Monitoring and Optimizing Your Elasticsearch Cluster
Monitoring and optimizing an Elasticsearch cluster is essential to ensure its performance, stability and reliability. By regularly monitoring various metrics and applying optimization techniques we can identify and address potential issues, improve efficiency and maximize the capabilities of our cluster.
In this article, we will explore the importance of monitoring and optimization in Elasticsearch also discuss key metrics to track and provide examples and outputs to help beginners understand the process.