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Elasticsearch is a distributed, RESTful search and analytics engine capable of addressing a growing number of use cases. As part of the Elastic Stack, it is used for log and event data analysis, full-text search, security intelligence, business analytics, and operational intelligence use cases.
The ElasticsearchIndexingLatencyHigh alert indicates that indexing operations are taking longer than expected. This can significantly affect data ingestion rates, leading to delays in data availability for search and analysis.
When the ElasticsearchIndexingLatencyHigh alert is triggered, it suggests that the time taken for indexing documents into Elasticsearch is exceeding the predefined threshold. This can be due to several factors, including resource bottlenecks, inefficient indexing configurations, or insufficient cluster capacity.
High indexing latency can lead to delayed data availability, impacting real-time data processing and analysis. It can also cause increased load on the cluster, affecting overall performance.
Review and optimize your indexing settings to ensure efficient data ingestion. Consider the following adjustments:
PUT /your_index/_settings
{
"index": {
"refresh_interval": "30s"
}
}
Learn more about index refresh interval.
Ensure that your Elasticsearch cluster has sufficient resources. Monitor CPU, memory, and disk I/O usage. Use the following command to check cluster health:
GET /_cluster/health
Consider scaling your cluster if resource usage is consistently high. Refer to the Elasticsearch Cluster Health documentation for more details.
Evaluate your cluster's capacity to handle the current indexing load. If necessary, add more nodes to distribute the load effectively. Use the following command to add a new node:
PUT /_cluster/settings
{
"persistent": {
"cluster.routing.allocation.enable": "all"
}
}
For more information on scaling your cluster, visit the Elasticsearch Scalability guide.
Addressing the ElasticsearchIndexingLatencyHigh alert involves optimizing indexing settings, monitoring resource usage, and ensuring adequate cluster capacity. By following these steps, you can improve indexing performance and maintain efficient data ingestion rates.
(Perfect for DevOps & SREs)
(Perfect for DevOps & SREs)