Hour Usage Tracking

When running Cosmic Frog models and other jobs on the Optilogic platform, cloud resources are used. Usage of these resources is billed based on the billing factor of the resource used for the job. Each Optilogic customer has an amount of cloud compute hours included in their Master License Agreement (MLA). Users may want to check how many of these hours have been used up and in this documentation 2 ways to do so will be covered. In the last section we will touch on how to best track hours at the team/company level.

Option 1: Account > Usage

The first option for hours tracking that will be covered is through the Usage tab in the user’s Account:

1. On the Optilogic platform, open the drop-down menu by clicking on the down arrow to the right of your username, and then click on the first option in the menu: Account.
2. Click on the Usage tab, the tab farthest right.
3. Configure the period you want to see the usage for by using the following options:
   1. Group By: select the time periods you want to sum the usage hours up to. Options are: Total, Day, Week, Month, Year.
   2. Time Window Preset: select the timeframe you want to see the usage hours for. Options are: Week to Date, Month to Date, Year to Date, and Custom.
   3. Start and End: for the Time Window Presets of Week to Date, Month to Date, and Year to Date these are automatically filled out. For the Time Window Preset of Custom, user can manually enter the start and end dates of the timeframe for which the usage hours will be shown.
4. Based on the timeframe set as described under the previous bullet point, the Total Billed Compute Time will be shown here.
5. Bar charts for the time periods configured under bullet 3 (in this screenshot grouped by months) are shown here. When hovering over a bar in a chart, the number of hours will pop up.
   1. The dark green bar on the left indicates the sum of the billed compute time of the jobs that were run during that period.
   2. The lighter green bar in the middle indicates the sum of the compute time of the jobs that were run during that period.
   3. The blue bar indicates the sum of the total RAM (in gigabytes) used for the jobs that were run during that period.
6. The table at the bottom shows the sums of the compute time, billed compute time, CPU cores, and RAM for the entire configured timeframe and for the individual time periods within that timeframe.
7. User has the option to export this data, either to CSV format or to the Excel .xlsx format by clicking on these buttons.

If a user is asked by their manager to report the hours they have used on the Optilogic platform, they can go here and use the Custom Time Window Preset option to align the start and end date of the reporting period with the dates of the MLA. They can then report back the number shown as the Total Billed Compute Time (box 4 in the above screenshot).

Option 2: Run Manager

Through the Run Manager application on the Optilogic platform, user can also analyze their jobs run, including retrieving the Total Billed Compute Time:

1. On the Optilogic platform, go to the Run Manager in the list of applications on the left-hand side of the screen. Should you not see it there, click on the icon with the 3 dots to show all applications; the Run Manager should become visible then.
2. Along the top of the list of jobs run there is an option to View Charts, which will be covered next.
3. Another option is to download information of the jobs to a CSV format file. This will be covered a bit further below too.

After clicking on the View Charts icon, a screen similar to the following screenshot will be shown:

1. The View Charts icon now has changed to a View Jobs List icon to allow user to go back to the list view.
2. In the first part of the charts section, some overall statistics are listed:
   1. First, the number of jobs that did not complete successfully (status = Error), that ran to completion successfully (status = Done), and that were cancelled (status = Cancelled) are listed.
   2. Next, the Total Compute Time and Total Billed Compute Time are listed. The total billed compute time is calculated based on the time the job took and the Billing Factor of the resource used for the job.
3. The title of the chart, here it is Job Counts by Status. There are 3 options for showing the job counts, click on the following icons to toggle between them:
   1. Show Jobs by Resource Size.
   2. Show Jobs by Tag.
   3. Show Jobs by Status (the default, shown in blue when active).
4. Click on this i-icon to see guidance on how to pan and zoom within the chart.
5. Here the bar for the week of July 15-22 shows that there were 15 jobs with status = Error (did not complete successfully), 37 with status = Done (did complete successfully), and no jobs with status = Cancelled during this week.
6. At the bottom of the chart user can toggle all status types on or off simultaneously by clicking on Toggle All. The individual statuses can also be toggled on or off by clicking on them.
7. The types of Jobs included in the statistics and chart can be filtered by clicking on the Type filter drop-down. The following 4 types of jobs exist, and each can be included or excluded: Scenario, Model Run, Python, and Utility.
8. When clicking the Download button, user can choose to either Download All Jobs or Download Current Filtered Jobs. When downloading, the jobs are saved to a jobs.csv file which will look similar to this screenshot:

If a user needs to report their hours used on the Optilogic platform, they can download this jobs.csv file and:

1. Filter columns B-D to align the dates of jobs included to the period of the MLA.
2. Sum column G billedComputeTime to get the Total Billed Compute Time for the filtered date range and report this number back.

Individual & Team/Company Level Tracking

Currently, only tracking of usage hours at the individual user level is available as described above. To get total team or company usage, a manager can ask their users to use 1 of the above 2 methods to report their Total Billed Compute Time and the manager can then add these up to get the total used hours so far. Tracking at the team/company level is planned to be made available on the Optilogic platform later in 2024.