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Microsoft Azure

  1. Azure
  2. Azure Mindmap
  3. Azure Policy Best Practices
  4. Azure Cloud Adoption Framework CAF
  5. Azure Well-Architected Framework WAF
  6. CAF vs WAF
  7. Azure Landing Zones
  8. Azure Sandbox
  9. Azure Marketplace
  10. Microsoft REST API Guidelines
  11. Azure Quick Review
  12. New Features
  13. Blogs
  14. Azure Training and Certifications
  15. Azure Naming Convention
  16. Mission-critical Architecture on Azure
  17. Understand Azure Load Balancing
  18. Azure Load Testing
  19. Microsoft Linux Distribution CBL Mariner
  20. Azure Patterns
  21. ARM Templates
  22. DevTest
  23. Azure DevOps
    1. Azure DevOps vs GitHub Actions
    2. YAML Schema in DevOps Azure Pipelines
    3. Azure Pipeline Tasks
    4. Azure DevOps Snippets
  24. Azure AD and RBAC. Azure Tenant and Azure Subscription. Service Principal SPN. Microsoft Entra
    1. Register applications in Azure AD. Authenticate apps and services
    2. Azure AD Pen Testing
  25. Azure Arc. Azureโ€™s Hybrid And Multi-Cloud Platform. GitOps with Azure Arc
  26. Secure DevOps Kit for Azure
  27. Azure App Service
  28. Azure Application Gateway
  29. Azure Functions
  30. Azure Monitor managed service for Prometheus
  31. Mobile Apps
  32. Powershell
    1. Microsoft Graph PowerShell SDK
    2. Powershell repos
    3. Crescendo powershell module
    4. Secrets Management with Powershell
    5. Azure Resource Inventory
  33. Azure CLI. AZ CLI
  34. Azure Run Command
  35. IaC with PowerShell DSC Desired State Configuration
  36. Azure Bicep
  37. Azure Cross region Load Balancer
  38. Azure Traffic Manager
  39. Azure DNS
  40. Azure OpenVPN
  41. Azure Security
    1. Azure Microsoft Defender for Cloud
  42. Azure Virtual WAN. vWAN
  43. Data Ingestion. Azure Data Factory
  44. WinGet Windows Package Manager CLI
  45. Windows 11
  46. Azure API Management
  47. Azure Container Apps
  48. Azure Container Instances
  49. Azure Container Storage
  50. Windows Server Container Host
  51. Disaster Recovery
  52. Azure Samples (Boilerplates)
  53. Azure Healthcare Data Services
  54. Office 365
  55. Azure Books
  56. Azure OpenAI
  57. Windows Tools
  58. Azure Tools
  59. Images
  60. Videos
  61. Tweets

Azure Terraformer

Azure

Azure Mindmap

Azure Policy Best Practices

Azure Cloud Adoption Framework CAF

Azure Well-Architected Framework WAF

  • learn.microsoft.com: Azure Well-Architected Framework The Azure Well-Architected Framework (WAF) is a set of quality-driven tenets, architectural decision points, and review tools intended to help solution architects build a technical foundation for their workloads.
  • infoq.com: Microsoft Refreshes its Well-Architected Framework
  • azure.github.io: Azure Proactive Resiliency Library (APRL)
    • This library is built with the intention of being a staging area for guidance and recommendations that can be used by customers, partners and the field in Well-Architected Framework reliability engagements/assessments; with the intent of the guidance and recommendations being promoted, once tested and validated with customers and partners, into the official Well-Architected Framework documentation.
    • The library also contains supporting Azure Resource Graph (ARG) queries, and sometimes Azure PowerShell or Azure CLI scripts, that can help customers, partners and the field identify resources that may or may not be compliant with the guidance and recommendations. The intent for these queries, in the long-term, is to make them part of the Azure Advisor service.

CAF vs WAF

Azure Landing Zones

Azure Sandbox

  • Azure Sandbox Azure Sandbox is a collection of interdependent cloud computing configurations for implementing common Azure services on a single subscription. This collection provides a flexible and cost effective sandbox environment for experimenting with Azure services and capabilities.

Azure Marketplace

  • azuremarketplace.microsoft.com: Firefly Firefly’s Cloud Asset Management solution enables Cloud teams to rediscover their entire cloud footprint and manage it more efficiently and consistently as a single inventory across multi-cloud, multi-accounts, and Kubernetes deployments. At the same time, it empowers DevOps to quickly ramp Infrastructure-as-code, and to create and deploy cloud infrastructure safely and consistently within organizational policies.

Microsoft REST API Guidelines

Azure Quick Review

  • github.com/Azure/azqr Azure Quick Review (azqr) is a command-line interface (CLI) tool specifically designed to analyze Azure resources and identify whether they comply with Azure’s best practices and recommendations. Its primary purpose is to provide users with a detailed overview of their Azure resources, enabling them to easily identify any non-compliant configurations or potential areas for improvement.

New Features

Blogs

Azure Training and Certifications

Azure Naming Convention

Mission-critical Architecture on Azure

Understand Azure Load Balancing

Azure Load Testing

Microsoft Linux Distribution CBL Mariner

Azure Patterns

ARM Templates

DevTest

Azure DevOps

Azure DevOps vs GitHub Actions

YAML Schema in DevOps Azure Pipelines

Azure Pipeline Tasks

  • Microsoft/azure-pipelines-tasks This repo contains the tasks that are provided out-of-the-box with Azure Pipelines and Team Foundation Server. This provides open examples on how we write tasks which will help you write other tasks which can be uploaded to your account or server.

Azure DevOps Snippets

  • gist.github.com: This snippet contains the steps to generate a terraform plan and post it as a comment of a pull request in Azure DevOps

    - script: |
        terraform plan -out tf.tfplan
    displayName: Generate Terraform plan
    
    - script: |
        terraform show -no-color tf.tfplan > $(Agent.TempDirectory)/tf.txt
    displayName: Convert Terraform plan to text
    
    - bash: |
        cd $(Agent.TempDirectory)
        ENCODED_URL=$(echo "$(System.CollectionUri)$(System.TeamProject)/_apis/git/repositories/${{ variables.SourceRepositoryName }}/pullRequests/$(System.PullRequest.PullRequestId)/threads?api-version=7.0" | sed 's/ /%20/g')
        jq --rawfile comment tf.txt '.comments[0].content=$comment' <<< '{"comments": [{"parentCommentId": 0,"content": "","commentType": 1}],"status": 1}' |
        curl --request POST "$ENCODED_URL" \
        --header "Content-Type: application/json" \
        --header "Accept: application/json" \
        --header "Authorization: Bearer $SYSTEM_ACCESSTOKEN" \
        --data @- \
        --verbose
    env:
        SYSTEM_ACCESSTOKEN: $(System.AccessToken)
    displayName: 'Post comment with Terraform Plan'
    

Azure AD and RBAC. Azure Tenant and Azure Subscription. Service Principal SPN. Microsoft Entra

Register applications in Azure AD. Authenticate apps and services

Azure AD Pen Testing

Azure Arc. Azureโ€™s Hybrid And Multi-Cloud Platform. GitOps with Azure Arc

Secure DevOps Kit for Azure

Azure App Service

Azure Application Gateway

Azure Functions

Azure Monitor managed service for Prometheus

Mobile Apps

Powershell

Microsoft Graph PowerShell SDK

Powershell repos

Crescendo powershell module

Secrets Management with Powershell

Azure Resource Inventory

Azure CLI. AZ CLI

Azure Run Command

IaC with PowerShell DSC Desired State Configuration

Azure Bicep

Azure Cross region Load Balancer

Azure Traffic Manager

Azure DNS

  • learn.microsoft.com: What is Azure DNS Private Resolver? Azure DNS Private Resolver is a new service that enables you to query Azure DNS private zones from an on-premises environment and vice versa without deploying VM based DNS servers. Customers will no longer need to provision IaaS based solutions on their Virtual Networks to resolve names registered on Azure Private DNS Zones and will be able to do conditional forwarding of domains back to on-prem, multi-cloud and public DNS servers.

Azure OpenVPN

Azure Security

Azure Microsoft Defender for Cloud

Azure Virtual WAN. vWAN

Data Ingestion. Azure Data Factory

  • medium.com/codex: 7 Best Practices for Data Ingestion
    • Data engineering is the practice of designing and building systems for collecting, storing, and analyzing data at scale.
    • Data Ingestion is defined as the process of absorbing data from a vast multitude of sources, and then transferring it to a target site where it can be analyzed and deposited.
    • A Data Engineer spends more than 50% of his time writing different pipelines that move data from one place to another. There are two basic frameworks to achieve the same:
      • ETL: Extract โ€” Transform โ€” Load
      • ELT: Extract โ€” Load โ€” Transform
    • However, in both the frameworks the common element is to be able to extract the data and load it into another destination. This is Data Ingestion.
    • On a broad categorization, there are mainly 3 types of Data Ingestion:
      • Batch-based Data Ingestion: Batch-based ingestion happens at a regularly scheduled time. The data is ingested in batches. This is important when a business needs to monitor daily reports, ex: sales reports for different stores. This is the most commonly used data ingestion use case.
      • Real-time/Streaming Data Ingestion:
        • The process of gathering and transmitting data from source systems in real-time solutions such as Change Data Capture (CDC) is known as Real-Time Data Ingestion.
        • CDC or Streaming Data captures any changes, new transactions, or rollback in real time and moves changed data to the destination, without impacting the database workload.
        • Real-Time Ingestion is critical in areas like power grid monitoring, operational analytics, stock market analytics, dynamic pricing in airlines, and recommendation engines.
      • Lambda-based Data Ingestion Architecture: Lambda architecture in Data ingestion tries to use the best practices of both batch and real-time ingestion.
        • Batch Layer: Computes the data based on the whole picture. This is more accurate however is slower to compute.
        • Speed Layer: Is used for real-time ingestion, the computed data might not be completely accurate, however, gives a real-time picture of the data.
        • Serving layer: The outputs from the batch layer in the form of batch views and those coming from the speed layer in the form of near real-time views get forwarded to the serving. This layer indexes the batch views so that they can be queried in low latency on an ad-hoc basis.
  • mssqltips.com: Choosing Between SQL Server Integration Services and Azure Data Factory
  • techcommunity.microsoft.com: Azure Data Factory: How to split a file into multiple output files with Bicep

WinGet Windows Package Manager CLI

Windows 11

Azure API Management

Azure Container Apps

Azure Container Instances

Azure Container Storage

Windows Server Container Host

Disaster Recovery

Azure Samples (Boilerplates)

Azure Healthcare Data Services

Office 365

Azure Books

Azure OpenAI

Windows Tools

Azure Tools

Images

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Videos

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Tweets

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