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RSS feedMarch 2024
Support for Ubuntu 20.04 LTS for Batch pools will be retired on 23 April 2025
Target retirement date: April 24, 2025
End of life announcement for Ubuntu 20.04 LTS support for Azure Batch pools on 23 April 2025
Default Internet outbound access for Simplified node communication Batch pools without public IP addresses will be retired on 30 September 2025
Target retirement date: October 01, 2025
End of life announcement for default Internet outbound access for Simplified node communication Batch pools without public IP addresses on 30 September 2025
September 2023
Support for select marketplace images for Batch pools will be retired
Target retirement date: January 10, 2024
End of life announcement for select marketplace images for Batch pools
Azure Batch pool list usage metrics API will be retired on 30 September 2024
Target retirement date: October 01, 2024
End of Life Announcement of Azure Batch Pool List Usage Metrics API on 30 September 2024
Azure Batch CLI extensions will be retired on 30 September 2024
Target retirement date: October 01, 2024
End of Life Announcement of Azure Batch CLI Extensions on 30 September 2024
Azure Batch task authentication token will be retired on 30 September 2024
Target retirement date: October 01, 2024
End of life announcement of Azure Batch task authentication token on 30 September 2024
March 2023
Batch custom image pools using VHD or managed images will be retired on 31 March 2026
Target retirement date: April 01, 2026
Transition custom image pools use images from Azure Compute Gallery
Batch Service in select regions will be retired on 31 March 2026
Target retirement date: April 01, 2026
Migrate your Batch workloads before 31 March 2026 to other regions where Azure Batch will continue to be available.
Select Batch Pool autoscale service-defined variables will be retired on 31st March, 2024
Target retirement date: April 01, 2026
Remove references in your autoscale formula for the service-defined variables
Azure Batch classic compute node communication model will be retired on 31st March, 2026
Target retirement date: April 01, 2026
Transition Batch pools to the Simplified compute node communication model
October 2022
Azure Batch Certificates will be retired on 29 February 2024
Target retirement date: March 01, 2024
Retirement Notice: Transition to Azure Key Vault before 29 February 2024.
Azure Batch pools without public IP addresses (classic) will be retired on 31 March, 2023
Target retirement date: April 01, 2023
Retirement notice: Transition to Simplified compute node communication pools without public IP addresses by 31 March, 2023
September 2022
Azure Batch Low Priority VMs will be retired on 30 September 2025
Target retirement date: October 01, 2025
Retirement Notice: Transition to Azure Batch Spot VMs before 30 September 2025.
Azure Batch Job/Pool Lifetime Statistics API will be retired on 30 April 2023
Target retirement date: May 01, 2023
Retirement Notice: Stop using Batch Job/Pool Lifetime Statistics API by 30 April 2023.
Azure Batch TLS 1.0/1.1 will be retired on 31 March 2023
Target retirement date: April 01, 2023
Retirement notice: Transition to Azure Batch TLS 1.2 by 31 March 2023.
October 2017
Azure Batch AI Service
Azure Batch AI Preview is now available. Azure Batch AI Preview helps you train and test deep learning and other machine learning models using GPU and CPU clusters.
July 2017
Azure Batch updates
Application packages can be used with VirtualMachineConfiguration pools, new metrics are available for low-priority VMs, and new template and file transfer capabilities are available in the Azure CLI for Batch.
May 2017
Azure Batch Rendering Service
Azure Batch Rendering accelerates large scale rendering jobs to deliver results to our customers faster.
Azure Batch AI Training for deep learning models
Azure Batch AI Training, a new addition to Azure Batch which will target data scientists and AI researchers, as well as those who train and test deep learning and other AI models, will soon be available. Users will specify their job requirements and the path to model and data and Batch will take care of provisioning a cluster and running the jobs.
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