VictoriaMetrics is a fast, cost-effective, and scalable time-series database designed for high-performance monitoring and observability. It is widely used for storing and querying metrics data, providing a robust solution for handling large volumes of time-series data efficiently.
One common issue users may encounter with VictoriaMetrics is high CPU usage. This symptom manifests as increased CPU consumption on the server running VictoriaMetrics, potentially leading to degraded performance or resource exhaustion.
Complex queries that involve large datasets or intricate calculations can significantly increase CPU load. These queries may include multiple joins, aggregations, or filters that require substantial computational resources.
VictoriaMetrics is designed to handle high ingestion rates, but if the rate exceeds the allocated resources, it can lead to increased CPU usage. This is particularly true if the data is not pre-processed or if there are spikes in data volume.
Running VictoriaMetrics on a server with insufficient CPU resources can also cause high CPU usage. This is often observed when the server is shared with other resource-intensive applications.
Review and optimize your queries to reduce their complexity. Use query optimization techniques such as reducing the number of time series scanned, using appropriate time ranges, and avoiding unnecessary aggregations.
Consider reducing the ingestion rate by pre-aggregating data before sending it to VictoriaMetrics. You can also use rate limiting to control the flow of data into the database.
If possible, allocate more CPU resources to the server running VictoriaMetrics. This can be done by upgrading the server hardware or adjusting resource allocation in a virtualized environment.
Enable query caching to reduce the computational load on the CPU. VictoriaMetrics supports caching of query results, which can significantly improve performance for frequently executed queries. Refer to the caching documentation for more details.
By understanding the root causes of high CPU usage in VictoriaMetrics and implementing the suggested solutions, you can optimize the performance of your time-series database. Regular monitoring and adjustments based on workload changes will help maintain efficient operation.
Let Dr. Droid create custom investigation plans for your infrastructure.
Book Demo
