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2022-08-18 11:12:31 -04:00
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@@ -18,7 +18,7 @@ In this lab we will use the `forecast` command to forecast potential GitHub Acti
## Prepare for forecast
Before we can run the forecast we need to answer a few questions so we can construct the correct command.
1) What namespace do we want to run the forecast for? __valet. This is the only group in the demo GitLab instance.__
2) What is the date we want to start forecasting from? __08-02-2022. This is around but before the time the data was populated on our demo GitLab instance.__
2) What is the date we want to start forecasting from? __08-02-2022. This date is before the time the data was populated on our demo GitLab instance. In practice, this should be a date that will give you enough data to get a good understand of the typical usage. Too little data and the metrics might not give a accurrate picture__
3) Where do we want to store the results? __./tmp/forecast_reports. This can be any valid path on the system, but for simplicity it is recommend to use a directory in the root of the codespace workspace.__
## Perform a forecast
@@ -31,7 +31,7 @@ gh valet forecast gitlab --output-dir ./tmp/forecast_reports --namespace valet -
![forecast_output](https://user-images.githubusercontent.com/18723510/185232893-1ed46bca-f310-47dc-804c-40c13737f231.png)
## Review forecast report
Now we will open the forecast report and review the calculated metrics.
Open the forecast report and review the calculated metrics.
- From the codespace explorer pane find `./tmp/forecast_reports/forecast_report.md` and right-click, and select __Open Preview__.
![forecast_explorer](https://user-images.githubusercontent.com/18723510/185234641-948a551b-316f-4cce-9e7d-4c078ae11a04.png)
- The file should be similar to this.
@@ -104,7 +104,7 @@ Now we will open the forecast report and review the calculated metrics.
</details>
### Metrics
### Metric Definitions
| Name | Description |
| ----- | ----------- |
| Median | The __middle__ value |
@@ -112,9 +112,38 @@ Now we will open the forecast report and review the calculated metrics.
| Min | The lowest value |
| Max | The highest value |
### Sections
- `Total` shows the metrics using all of the known runners.
- `gitlab-runner` shows the metrics for the runners in the gitlab-runner group, if there were other groups they would show here under their own group heading.
### Total Section
- This section shows the metrics for all of the jobs run in projects in the `valet` group during the time between today and 08/02/2022.
## Total
- Job count: **57**
- Pipeline count: **15**
---
We can see we ran 15 pipelines that contained 57 jobs. The number of jobs is expected to be larger than pipelines because a pipeline is typically a collection of jobs. For example `basic-pipeline-example` contains 6 jobs
![basic-pipeline-jobs](https://user-images.githubusercontent.com/18723510/185423928-ec1b13b5-01fc-4e48-bbe5-0a77be7cecea.png)
- `Execution time` shows the metrics for the time a job took to ran. Looking closer we can see during our forecast timeframe the total job run time was 135 minutes with 90% of the jobs finishing under 7 minutes, and the longest job taking 10 minutes. The `min` is 0 because the quick job took less than a minute and was rounded down to 0.
- Execution time
- Total: **135 minutes**
- Median: **0 minutes**
- P90: **7 minutes**
- Min: **0 minutes**
- Max: **10 minutes**
- `Queue time` shows the metrics for how long jobs waited for a runner to be available.
- Queue time
- Median: **0 minutes**
- P90: **5 minutes**
- Min: **0 minutes**
- Max: **42 minutes**
- `Concurent jobs` show the metrics for how many jobs were run at the same time.
- Concurrent jobs
- Median: **0**
- P90: **0**
- Min: **0**
- Max: **9**
### Runner Section
- The data`gitlab-runner` shows the metrics for the runners in the gitlab-runner group, if there were other groups they would show here under their own group heading.
### TBD