Are you tired of querying Prometheus multiple times for different metrics in Grafana? Do you want to optimize your dashboard’s performance and reduce the load on your Prometheus server? Look no further! In this article, we’ll show you how to query Prometheus only once for multiple queries in Grafana, and take your dashboard’s performance to the next level.
What’s the Problem with Multiple Queries?
When you create a dashboard in Grafana, each panel queries Prometheus separately for the required metrics. This can lead to multiple queries being sent to Prometheus, which can cause performance issues and increase the load on your server.
The Consequences of Multiple Queries
- Slow dashboard loading times
- Increased load on your Prometheus server
- Potential errors and timeouts
- Inefficient use of resources
The Solution: Using the `union` Function
The `union` function in Prometheus allows you to combine multiple queries into a single query. This reduces the number of requests sent to Prometheus, improving performance and reducing load.
Syntax and Examples
union( query1, query2, ... )
For example, let’s say you want to query Prometheus for the CPU usage and memory usage of multiple servers. Instead of sending two separate queries, you can use the `union` function like this:
union(
sum(cpu_usage{instance=~"server1|server2"}),
sum(memory_usage{instance=~"server1|server2"})
)
Using the `union` Function in Grafana
To use the `union` function in Grafana, you’ll need to create a new Prometheus data source and modify the query syntax.
Step 1: Create a New Prometheus Data Source
In your Grafana dashboard, click on the gear icon in the top right corner and select “Data Sources”. Then, click on “New” and select “Prometheus” as the data source type.
Step 2: Modify the Query Syntax
In the “Query” field, enter the following syntax:
union(
${__range_query('1h', 'now', '1h')}(sum(cpu_usage{instance=~"${instance}"})),
${__range_query('1h', 'now', '1h')}(sum(memory_usage{instance=~"${instance}"}))
)
Step 3: Configure the Query Options
In the “Query Options” section, set the “Format” to “Table” and the “Show” to “All values”. This will allow you to display the results in a table format.
Step 4: Add the Query to Your Dashboard
Click on the “Add” button to add the query to your dashboard. Then, select the “Table” visualization and configure the display options as needed.
Optimizing Your Query
To optimize your query, make sure to use the following best practices:
Use Aggregations
Use aggregations such as `sum`, `avg`, and `max` to reduce the amount of data returned by Prometheus.
Use Labels Wisely
Use labels to filter and group your data. This will reduce the amount of data returned by Prometheus and improve performance.
Use the `__range_query` Function
The `__range_query` function allows you to specify a time range for your query. This can help reduce the amount of data returned by Prometheus and improve performance.
Common Use Cases
The `union` function is particularly useful in the following scenarios:
Multiple Metric Queries
When you need to query multiple metrics for the same instance or label, the `union` function can help reduce the number of queries sent to Prometheus.
Multi-Dimensional Data
When you need to query data with multiple dimensions, such as time series data with multiple labels, the `union` function can help simplify your query and reduce the number of requests sent to Prometheus.
Conclusion
Querying Prometheus only once for multiple queries in Grafana is a game-changer for dashboard performance and optimization. By using the `union` function, you can reduce the number of requests sent to Prometheus, improve performance, and create more efficient dashboards. Remember to optimize your query using aggregations, labels, and the `__range_query` function, and apply this technique to common use cases such as multiple metric queries and multi-dimensional data.
| Best Practices | Description |
|---|---|
| Use Aggregations | Reduce data returned by Prometheus |
| Use Labels Wisely | Filter and group data |
| Use the `__range_query` Function | Specify a time range for your query |
Start optimizing your Grafana dashboard today and take your performance to the next level!
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Frequently Asked Question
Get the most out of your Grafana dashboards by optimizing your Prometheus queries! Here are the top 5 questions and answers on how to query Prometheus only once for multiple queries in Grafana.
Q1: What is the advantage of querying Prometheus only once for multiple queries in Grafana?
Querying Prometheus only once for multiple queries reduces the load on your Prometheus server, minimizing the risk of performance issues and allowing you to create more complex and dynamic dashboards!
Q2: How do I use the `batch` parameter in Prometheus to query multiple metrics at once?
In your Prometheus query, simply add the `batch` parameter with a comma-separated list of metrics, like this: `batch_requests{job=”my_job”, instance=”my_instance”}[5m], batch_errors{job=”my_job”, instance=”my_instance”}[5m]`. Easy peasy!
Q3: Can I use regex to filter multiple metrics in a single Prometheus query?
You bet! Use the ` =~` operator to filter metrics using regex patterns. For example: `my_metric{job=”my_job”, instance=”my_instance”, metric=~”requests|errors|latency”}[5m]`. This will fetch all metrics that match the regex pattern.
Q4: How do I use the `union` operator to combine multiple Prometheus queries into one?
The `union` operator is your friend! Use it to combine multiple queries, like this: `union(requests{job=”my_job”, instance=”my_instance”}[5m], errors{job=”my_job”, instance=”my_instance”}[5m], latency{job=”my_job”, instance=”my_instance”}[5m])`. This will return a single result set with all the metrics.
Q5: Are there any limitations to querying Prometheus only once for multiple queries in Grafana?
While querying Prometheus only once for multiple queries is a powerful optimization technique, be aware that it can lead to increased memory usage and slower query performance for very large datasets. Be mindful of your Prometheus server’s resources and adjust your queries accordingly.
