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Important

The SingleStore 9.1 release candidate (RC) gives you the opportunity to preview, evaluate, and provide feedback on new and upcoming features prior to their general availability. In the interim, SingleStore 9.0 is recommended for production workloads, which can later be upgraded to SingleStore 9.1.

Active Workload Monitoring

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Active Workload Monitoring enables you to analyze query behavior during a specific time period by comparing metrics at the start and end of the recording window.

How it Works

  1. Cumulative Metrics view (mv_activities_extended_cumulative) contains a cumulative collection of query metrics gathered since the system started. The metrics include total CPU time, memory used, I/O, etc., for each query.

  2. Start a Snapshot (T₁): when you click Record the system takes a snapshot of the cumulative metrics at that specific time (T₁).

  3. End Snapshot (T₂): when you stop recording, a second snapshot is taken (T₂).

  4. Delta Calculation: the system calculates the difference (T₂ - T₁) in metrics for each query that was running or completed during the recording window.

  5. Result - the delta provides metrics specific to the recording period, such as:

    • CPU utilization during the recording window.

    • Number of query executions.

    • Memory consumed.

Total CPU Percentage Metric

This metric is intended for comparison purposes and is not an absolute measure of CPU capacity used.

It is the query’s CPU time during the recording window divided by the recording duration, expressed as a percentage on a single-core basis, so it is useful for comparing queries but not for measuring cluster-wide CPU utilization.

The formula it uses is: (sum(cpu time) / recording time)*100.

A key detail is that this calculation is always based on one CPU core, regardless of how many cores the cluster has.

This means values can be greater than 100%. For example, if you record for 10 seconds and a query accumulates 87 seconds of CPU time, the metric shows about 870%.

This does not mean the query used 8.7× the cluster’s total CPU capacity. It means the query consumed CPU time equal to 8.7 times the duration of the recording window, potentially across parallel work.

What this Metric is Useful For

  • Comparing queries to see which ones are more CPU-intensive relative to others running or completed during the recording time.

  • Ranking queries by CPU usage during a given recording period.

What this Metric Does Not Represent

  • It does not show CPU percentage relative to cluster’s total CPU capacity.

  • It does not tell you how close your cluster is to hitting CPU limits.

This metric should not be used to calculate overall CPU utilization of your cluster.

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Verification instructions

Note: You must install cosign to verify the authenticity of the SingleStore file.

Use the following steps to verify the authenticity of singlestoredb-server, singlestoredb-toolbox, singlestoredb-studio, and singlestore-client SingleStore files that have been downloaded.

You may perform the following steps on any computer that can run cosign, such as the main deployment host of the cluster.

  1. (Optional) Run the following command to view the associated signature files.

    curl undefined

  2. Download the signature file from the SingleStore release server.

    • Option 1: Click the Download Signature button next to the SingleStore file.

    • Option 2: Copy and paste the following URL into the address bar of your browser and save the signature file.

    • Option 3: Run the following command to download the signature file.

      curl -O undefined

  3. After the signature file has been downloaded, run the following command to verify the authenticity of the SingleStore file.

    echo -n undefined |
        cosign verify-blob --certificate-oidc-issuer https://oidc.eks.us-east-1.amazonaws.com/id/CCDCDBA1379A5596AB5B2E46DCA385BC \
          --certificate-identity https://kubernetes.io/namespaces/freya-production/serviceaccounts/job-worker \
          --bundle undefined \
          --new-bundle-format -
    Verified OK

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