VictoriaMetrics is a fast, cost-effective, and scalable time-series database and monitoring solution. It is designed to handle large volumes of data with high performance and efficiency, making it a popular choice for monitoring systems and applications.
Data ingestion lag in VictoriaMetrics is observed when there is a noticeable delay between the time data is sent to the database and when it becomes available for querying. This can impact real-time monitoring and analytics, leading to outdated insights.
One common cause of ingestion lag is the high volume of data being ingested, which can overwhelm the system's capacity to process and store data efficiently.
Network instability or bandwidth limitations can also contribute to delays in data transmission, resulting in ingestion lag.
If the system running VictoriaMetrics lacks adequate CPU or memory resources, it may struggle to keep up with data ingestion demands.
To handle higher data volumes, you can increase the number of ingestion workers. Adjust the following parameters:
--influx.maxLineSize=1048576
--influx.maxConcurrentInserts=16
These settings increase the maximum line size and the number of concurrent insert operations, respectively.
Check your network infrastructure to ensure there are no bottlenecks or instability issues. Consider upgrading your network bandwidth if necessary.
Ensure that the system running VictoriaMetrics has adequate CPU and memory resources. Monitor resource usage and scale up if needed.
For more detailed information on optimizing VictoriaMetrics performance, refer to the official documentation. You can also explore the VictoriaMetrics GitHub repository for community support and updates.
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