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1. Ensure that your HySDS cluster is up and running by logging into the MOZART instance and running:

   Code Block
   sds status

   If it is not running, run:

   Code Block
   sds start all

2. Configure the docker_matlab repo as a new job type for continuous integration and deployment
   

   Code Block
   sds ci add_job -b master https://github.com/aria-jpl/isce_stamps_processing.git s3

3. Navigate to your ci instance (e.g. http://<your-ci-instance>:8080) to validate that the jenkins job was configured. You should see your jenkins job named as "container-builder_<your repo name>_<branch>" (e.g. container-builder_gmanipon_hello_world_master).
   
   

   

   
   

4. Verify that the jenkins job runs to completion by manually scheduling a build. The jenkins job will build the docker image, publish it to your S3 code bucket, and register the job types into you HySDS cluster. Click on the green arrow and view the console output to validate.
   

5. Navigate to your grq instance (e.g. http://<your-grq-instance>/search) and select “STACK” under the dataset section of the ARIA Facet Search Menu. Then select the co-registered stack you would like as your input for PS time series.
   

   

6. Click on the "On-Demand" button. From the On-Demand screen, fill in the parameters as shown in the figure below (default values are shown in example) and click "Process Now":
   

   

   

   
   

   

   
   

7. Navigate to your mozart instance (e.g. http://<your-mozart-instance>/figaro)* to view your job. You can facet on it by looking for the "job-stamps:master" job-type along with your specific tag assigned to job. The job should go through the "Queued", "Started", and "Completed" states.
   
   

8. From your completed job, click on the "work directory" link to view the live work directory. It should look similar to the output shown below:
   

9. With the work directory, use ps_plot_app_linux (follow readme.txt in link) to create a time series of the StaMPS output. Enjoy!