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Job Manager release notesRSS

January 17, 2023
Job Manager v213

Fixes

  • Fixes a bug to allow both simple and scripted browser jobs to be recognized as browser jobs.

Job Manager v212

Improvements

  • Added additional logging to give insight on when new runtimes are pulled for use.

Job Manager v211

Improvements

  • Added some additional logging where our local runtime images are checked against the new images.

Job Manager v210

Improvements

  • Adds the type of monitor being staging for execution in key logs in our system.

Job Manager v209

Fixes

  • Reduces the amount of data pushed to SQS when running non-simple jobs.

November 10, 2022
Job Manager v208

Improvements

  • Adds upgraded logging functionality to include exceptions when they are thrown.

Job Manager v206

Fixes

  • Skipped querying for the instanceId if the Metadata field is disabled to avoid Server Side Request Forgery attacks that can leak information

November 3, 2022
Job Manager v204

Improvements

  • Largely improved the reduction in compute resources due to more efficient usage of each job manager
  • Added more detailed logging for when a job not found
  • Provided better logging around jobs coming off the parking log

Fixes

October 17, 2022
Job Manager v191

New Features

  • Changed the MAX_JOB_CAPACITY environment variable to HEAVYWEIGHT_WORKERS environment variable, which is the maximum number of heavyweight jobs that the job manager will run in parallel

Improvements

  • Updated the synthetics-utilities version we are using to 1.0.24

Fixes

  • Added better logging around the error message for not finding the runtimes
  • Fixed an NPE error about the ping-runtime could not be found after all the runtimes have been downloaded successfully
  • Replaced docker cpu quotas with docker cpu shares to ensure that unused capacity is not wasted

October 10, 2022
Job Manager v183

New Features

  • Added the ability to configure a CPU core limit for each runtime type

Improvements

  • Reduced CPU usage while the job manager is waiting for results from ephemeral runtimes by implementing a more efficient waiting algorithm

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