Tag Archives: Azure

How to Secure Your Azure SQL Database

  1. Authentication and Authorization:
    • Use Azure Active Directory (Azure AD) authentication for better security.
    • Implement firewall rules to control access to your database.
    • Assign minimal permissions to users based on their roles (principle of least privilege).
  2. Encryption:
    • Enable Transparent Data Encryption (TDE) to protect data at rest.
    • Use Always Encrypted to secure sensitive data in transit.
    • Consider client-side encryption for additional protection.
  3. Auditing and Monitoring:
    • Enable Azure SQL Auditing to track database activity.
    • Set up Azure Monitor to receive alerts and insights.
    • Regularly review logs and audit trails.
  4. Network Security:
    • Isolate your database using Virtual Network Service Endpoints.
    • Restrict public access and use private endpoints.
  5. Patch Management:
    • Keep your database engine up to date with the latest security patches.
    • Regularly review vulnerability assessments.
  6. Backup and Recovery:
    • Implement automated backups and test recovery procedures (remember a backup is only theoretically there unless it has been tested and proven to work).
    • Store backups conforming to the 3-2-1 Backup Rule explained below (do not assume your backups are safe just because they are in the cloud).

The 3-2-1 Backup Rule: Ensuring Data Resilience

The 3-2-1 Rule is a robust strategy that emphasizes redundancy, resilience, and data availability. Here’s what it entails:

  1. Three Copies of Your Data:
    • Maintain the original data and create at least two additional copies.
  2. Two Different Types of Media for Storage:
    • Store your data on distinct forms of media (e.g., hard drives, tapes) to enhance redundancy.
  3. At Least One Copy Off-Site:
    • Safeguard one backup copy in an off-site location, separate from your primary data and on-site backups.

By adhering to this rule, you mitigate single points of failure, protect against corruption, and ensure data safety even in unexpected events or disasters

How to fix an Azure Data Factory Pull Request Merge Conflict

Typically most pipeline development use cases can be handled directly within Data Factory through the Azure Web Portal. However where the line can get blurred sometimes between working in the cloud and working locally is with DevOps GIT.

If a GIT based deployment gets tangled there is an expectation you will be able to work through the desktop interface for GIT or worse fall back to using command line.

This is necessary because before a GIT pull request can complete, any conflicts with the target branch must be resolved and this usually involves issuing a few commands to put the matter right. The options for resolving conflicts through the web portal by default are limited to nonexistent which is at odds with the very high level, low code approach of developing pipelines in Data Factory.

Luckily if a merge conflict occurs there is an extension you can try.

https://marketplace.visualstudio.com/items?itemName=ms-devlabs.conflicts-tab

A conflict might occur because the master branch is no longer in sync with the development branch for example i.e. the master branch was changed after a development branch was created from it. When a pull request is created this may throw a merge conflict error blocking the merge from proceeding. Without resorting to code the extension above will allow you to choose between the source and target branch and specify which has the correct file version.