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Partial script not running while deployment
Hi All, I am deploying a windows VM in Azure using terraform and want to install some software while deployment so I thought about PS script extension. Things are working fine for me however ENV variables is not getting added though If I will run this script in the system after deployment then everything is right. Can anyone suggest me why only ENV variable is not getting set. you can read the script here, https://raw.githubusercontent.com/INGourav/Azure-Resources/master/azbastionsetup01.ps1 <# Script to install chocolatey on the windows system and install some apps that is needed for Azure Author : - Gourav Kumar Reach Me : - email address removed for privacy reasons Version : - 1.0.1 #> Set-ExecutionPolicy Bypass -Scope Process -Force; New-Item -Path 'C:\Temp\terraform_1.2.4_windows_amd64' -ItemType Directory # setting env vars $path = (Get-Item -Path Env:\Path).Value Start-Sleep -Seconds 5; $newpath = $path + 'C:\Temp\terraform_1.2.4_windows_amd64' Start-Sleep -Seconds 5; Set-Item -Path Env:\Path -Value $newpath # Installation of Terraform on the machine Invoke-WebRequest 'https://releases.hashicorp.com/terraform/1.2.4/terraform_1.2.4_windows_amd64.zip' -OutFile C:\temp\terraform_1.2.4_windows_amd64.zip -Verbose Start-Sleep -Seconds 5; Expand-Archive C:\temp\terraform_1.2.4_windows_amd64.zip C:\temp\terraform_1.2.4_windows_amd64 -Verbose -Force Start-Sleep -Seconds 5; [System.Net.ServicePointManager]::SecurityProtocol = [System.Net.ServicePointManager]::SecurityProtocol -bor 3072; Invoke-Expression ((New-Object System.Net.WebClient).DownloadString('https://community.chocolatey.org/install.ps1')) -Verbose Start-Sleep -Seconds 5; # Installation of apps (Pycharm, vscode, git, and drwaio) choco install pycharm -y --force; Start-Sleep -Seconds 5; choco install vscode -y --force; Start-Sleep -Seconds 5; choco install git -y --force; Start-Sleep -Seconds 5; choco install drawio -y --force; Start-Sleep -Seconds 5; The code that I am using to deploy resources is as follows, provider "azurerm" { features {} } data "azurerm_subnet" "vmsnet" { name = "vm_subnet" virtual_network_name = "az_test" resource_group_name = "poc" } resource "azurerm_resource_group" "vmrg" { name = "tfvmtestrg" location = "uk south" } resource "azurerm_network_interface" "az_vm_nic" { location = "uk south" name = "tfvmtestnic" resource_group_name = azurerm_resource_group.vmrg.name ip_configuration { name = "internal" private_ip_address_allocation = "Dynamic" subnet_id = data.azurerm_subnet.vmsnet.id } } resource "azurerm_windows_virtual_machine" "az_vm_win" { admin_password = "tfvmtestrgrtetghcgh" admin_username = "tfvmtestrg" location = "uk south" name = "tfvmtestvm" network_interface_ids = [azurerm_network_interface.az_vm_nic.id] resource_group_name = azurerm_resource_group.vmrg.name size = "Standard_D2s_v3" os_disk { caching = "ReadWrite" storage_account_type = "Standard_LRS" } source_image_reference { publisher = "MicrosoftWindowsServer" offer = "WindowsServer" sku = "2022-Datacenter" version = "latest" } } resource "azurerm_virtual_machine_extension" "vmext" { name = azurerm_windows_virtual_machine.az_vm_win.name virtual_machine_id = azurerm_windows_virtual_machine.az_vm_win.id publisher = "Microsoft.Compute" type = "CustomScriptExtension" type_handler_version = "1.10" ### THIS PART IS ALL NEEDED, INCLUDING THE WEIRD SETTINGS BIT. settings = <<SETTINGS { "commandToExecute": "powershell -ExecutionPolicy Unrestricted -File azbastionsetup01.ps1", "fileUris": ["https://raw.githubusercontent.com/INGourav/Azure-Resources/master/azbastionsetup01.ps1"] } SETTINGS }
Azure Machine Learning compute cluster - avoid using docker?
Hello, I would like to use an Azure Machine Learning Compute Cluster as a compute target but do not want it to containerize my project. Is there a way to deactivate this "feature" ? The main reasons behind this request is that : I already set up a docker-compose file that is used to specify 3 containers for Apache Airflow and want to avoid a Docker-in-Docker situation. Especially that I already tried to do so but failed so far. I prefer not to use a Compute Instance as it is tied to an Azure account which is not ideal for automation purposes. Thanks in advance.
Azure premium functions - Zero deployment down time
Hello, This is something I am not sure of. Does Azure premium function provide zero downtime deployment by default. In theory there is at least one premium function always up and running, so the new version is deployed as a new instance and the old one is killed after its ongoing request are completed is that even possible. I know we can use deployment slots. I am just wondering if premium functions has this feature by default(not needing to use deployment slot) as there is at least one instance always running. I know we can use deployment slots to achieve this.Boosting Performance with the Latest Generations of Virtual Machines in Azure
Microsoft Azure recently announced the availability of the new generation of VMs (v6)—including the Dl/Dv6 (general purpose) and El/Ev6 (memory-optimized) series. These VMs are powered by the latest Intel Xeon processors and are engineered to deliver: Up to 30% higher per-core performance compared to previous generations. Greater scalability, with options of up to 128 vCPUs (Dv6) and 192 vCPUs (Ev6). Significant enhancements in CPU cache (up to 5× larger), memory bandwidth, and NVMe-enabled storage. Improved security with features like Intel® Total Memory Encryption (TME) and enhanced networking via the new Microsoft Azure Network Adaptor (MANA). By Microsoft Evaluated Virtual Machines and Geekbench Results The table below summarizes the configuration and Geekbench results for the two VMs we tested. VM1 represents a previous-generation machine with more vCPUs and memory, while VM2 is from the new Dld e6 series, showing superior performance despite having fewer vCPUs. VM1 features VM1 - D16S V5 (16 Vcpus - 64GB RAM) VM1 - D16S V5 (16 Vcpus - 64GB RAM) VM2 features VM2 - D16ls v6 (16 Vcpus - 32GB RAM) VM2 - D16ls v6 (16 Vcpus - 32GB RAM) Key Observations: Single-Core Performance: VM2 scores 2013 compared to VM1’s 1570, a 28.2% improvement. This demonstrates that even with half the vCPUs, the new Dld e6 series provides significantly better performance per core. Multi-Core Performance: Despite having fewer cores, VM2 achieves a multi-core score of 12,566 versus 9,454 for VM1, showing a 32.9% increase in performance. VM 1 VM 2 Enhanced Throughput in Specific Workloads: File Compression: 1909 MB/s (VM2) vs. 1654 MB/s (VM1) – a 15.4% improvement. Object Detection: 2851 images/s (VM2) vs. 1592 images/s (VM1) – a remarkable 79.2% improvement. Ray Tracing: 1798 Kpixels/s (VM2) vs. 1512 Kpixels/s (VM1) – an 18.9% boost. These results reflect the significant advancements enabled by the new generation of Intel processors. Score VM 1 VM 1 VM 1 Score VM 2 VM 2 VM 2 Evolution of Hardware in Azure: From Ice Lake-SP to Emerald Rapids Technical Specifications of the Processors Evaluated Understanding the dramatic performance improvements begins with a look at the processor specifications: Intel Xeon Platinum 8370C (Ice Lake-SP) Architecture: Ice Lake-SP Base Frequency: 2.79 GHz Max Frequency: 3.5 GHz L3 Cache: 48 MB Supported Instructions: AVX-512, VNNI, DL Boost VM 1 Intel Xeon Platinum 8573C (Emerald Rapids) Architecture: Emerald Rapids Base Frequency: 2.3 GHz Max Frequency: 4.2 GHz L3 Cache: 260 MB Supported Instructions: AVX-512, AMX, VNNI, DL Boost VM 2 Impact on Performance Cache Size Increase: The jump from 48 MB to 260 MB of L3 cache is a key factor. A larger cache reduces dependency on RAM accesses, thereby lowering latency and significantly boosting performance in memory-intensive workloads such as AI, big data, and scientific simulations. Enhanced Frequency Dynamics: While the base frequency of the Emerald Rapids processor is slightly lower, its higher maximum frequency (4.2 GHz vs. 3.5 GHz) means that under load, performance-critical tasks can benefit from this burst capability. Advanced Instruction Support: The introduction of AMX (Advanced Matrix Extensions) in Emerald Rapids, along with the robust AVX-512 support, optimizes the execution of complex mathematical and AI workloads. Efficiency Gains: These processors also offer improved energy efficiency, reducing the energy consumed per compute unit. This efficiency translates into lower operational costs and a more sustainable cloud environment. Beyond Our Tests: Overview of the New v6 Series While our tests focused on the Dld e6 series, Azure’s new v6 generation includes several families designed for different workloads: 1. Dlsv6 and Dldsv6-series Segment: General purpose with NVMe local storage (where applicable) vCPUs Range: 2 – 128 Memory: 4 – 256 GiB Local Disk: Up to 7,040 GiB (Dldsv6) Highlights: 5× increased CPU cache (up to 300 MB) and higher network bandwidth (up to 54 Gbps) 2. Dsv6 and Ddsv6-series Segment: General purpose vCPUs Range: 2 – 128 Memory: Up to 512 GiB Local Disk: Up to 7,040 GiB in Ddsv6 Highlights: Up to 30% improved performance over the previous Dv5 generation and Azure Boost for enhanced IOPS and network performance 3. Esv6 and Edsv6-series Segment: Memory-optimized vCPUs Range: 2 – 192* (with larger sizes available in Q2) Memory: Up to 1.8 TiB (1832 GiB) Local Disk: Up to 10,560 GiB in Edsv6 Highlights: Ideal for in-memory analytics, relational databases, and enterprise applications requiring vast amounts of RAM Note: Sizes with higher vCPUs and memory (e.g., E128/E192) will be generally available in Q2 of this year. Key Innovations in the v6 Generation Increased CPU Cache: Up to 5× more cache (from 60 MB to 300 MB) dramatically improves data access speeds. NVMe for Storage: Enhanced local and remote storage performance, with up to 3× more IOPS locally and the capability to reach 400k IOPS remotely via Azure Boost. Azure Boost: Delivers higher throughput (up to 12 GB/s remote disk throughput) and improved network bandwidth (up to 200 Gbps for larger sizes). Microsoft Azure Network Adaptor (MANA): Provides improved network stability and performance for both Windows and Linux environments. Intel® Total Memory Encryption (TME): Enhances data security by encrypting the system memory. Scalability: Options ranging from 128 vCPUs/512 GiB RAM in the Dv6 family to 192 vCPUs/1.8 TiB RAM in the Ev6 family. Performance Gains: Benchmarks and internal tests (such as SPEC CPU Integer) indicate improvements of 15%–30% across various workloads including web applications, databases, analytics, and generative AI tasks. My personal perspective and point of view The new Azure v6 VMs mark a significant advancement in cloud computing performance, scalability, and security. Our Geekbench tests clearly show that the Dld e6 series—powered by the latest Intel Xeon Platinum 8573C (Emerald Rapids)—delivers up to 30% better performance than previous-generation machines with more resources. Coupled with the hardware evolution from Ice Lake-SP to Emerald Rapids—which brings a dramatic increase in cache size, improved frequency dynamics, and advanced instruction support—the new v6 generation sets a new standard for high-performance workloads. Whether you’re running critical enterprise applications, data-intensive analytics, or next-generation AI models, the enhanced capabilities of these VMs offer significant benefits in performance, efficiency, and cost-effectiveness. References and Further Reading: Microsoft’s official announcement: Azure Dld e6 VMs Internal tests performed with Geekbench 6.4.0 (AVX2) in the Germany West Central Azure region.Experience with Automanage Machine Configuration
Hi, I am experimenting with Automanage Machine Configuration and find the overall experience and documentation very poor. I am wondering if there are others who have experience with automanage and can point me towards additional documentation. I have built an example implementation which I am using as my lab setup: https://github.com/JelleBroekhuijsen/azure-automanage-example What I am experiencing is that the compliance-state reporting seems to be very inconsistent. Sometimes these sample configurations reports everything being compliant while maybe 30 minutes later the same configuration is marked as incompliant (while the VM is observably in a compliant state). Additionally, there seems to be no option to get support or report issues with the GuestConfiguration-extension (for Windows) or the GuestConfiguration PowerShell module. For instance, in my experimenting with the module I found that calling the PackageManagement DSC resource from within a configuration leads to a conflict with the embedded PackageManagement module in the windows extension. I found a workaround for this, but I have no way to report this issue.
Azure Function to unzip blob to specific blob folder
If this is not the right group to post this, please let me know. I am not much of a developer but have a need to extract a ZIP file that resides in a Blob Container into the same container in a specific folder, I would like that folder to be named the same of the zip filename. I have found several Azure Function blobs that use the new file blob trigger but all of them simply extract all the files in a specific container. I cannot for the life of me figure out how to tell it to save it in a specific folder and how to get it to pull the name of the file to name that folder. Does anyone have a template or code they would be willing to share with me? The reason I need this is due to the fact that Power Automate's "extract to ***" connectors have a limit of 100 files in the zip. Of course my zip files have just over 100 files in them......
