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Overview

Reports

The Reports module provides a consolidated and exportable view of HPC usage across different dimensions like Project, Clusters, Queues, and Users. Admins can leverage this section to analyze and download usage data for auditing, cost management, and performance tracking.

  1. Go to the Reports tab from the left-hand navigation.

  2. Use the following global filters at the top of the page to narrow down report results:

    Report Global Filter

    • Provider – Select the cloud provider (e.g., AWS).
    • Project – Select the project name.
    • Account – Choose the cloud account.
    • Region – Select the cloud region (e.g., us-east-1, ap-south-1).
    • Cluster – Choose the cluster(s) to report on.
    • Duration – Specify the time window (e.g., 01-May-2025 to 13-May-2025).

    The refresh button at the top right corner is used to reset all filters and refresh the page view.

Report Types Overview

Reports Page

There are four main categories of reports available, each serving a distinct purpose:

  1. Resource Consumption Report:
    Provides insights into how HPC resources (CPU, memory, GPU, etc.) are utilized across projects, clusters, queues, and users. Useful for identifying over- or under-utilization patterns.
    (See Resource Consumption Report).

  2. Job Execution Report:
    Captures detailed information on job performance — including job count, runtime and success/failure rates. Ideal for workload analysis and performance tuning.
    (See Job Execution Report)

  3. Budget and Cost Report:
    Breaks down costs by project, cluster, queue, user, job and workstation against allocated budgets. Helps track spending and detect anomalies or budget overruns.
    (See Budget and Cost Report)

  4. Consolidated Cost Report:
    Aggregates cost data from multiple dimensions (provider, account, cluster, user, etc.) into a single view. Enables comprehensive financial reporting and cross-account analysis.
    (See Consolidated Cost Report)

By using the Reports, admins gain precise visibility into HPC consumption trends across projects, clusters, queues, and users aiding in optimization and resource governance.