Azure App Service plan automatic scale out method

In the premium tier of the Azure App Service plan, there is a new scaling method known as "Automatic". This is currently in Preview.

With this approach, you no longer need to define specific scaling rules, as is the case with rule-based scaling. Instead, you only need to specify the maximum number of instances, and Azure will automatically manage the scaling process.

Once you've configured this method, you can navigate to the App Service plan metrics, such as CPU percentage, and observe how new instances are seamlessly added and subsequently removed from the plan.

On the above graph, the activity on each instance is displayed in distinct colors.

A Deep Dive into Microsoft Teams Adoption - Technical session for Arq Group

I had the privilege of leading two technical sessions for Arq Group, a division of NCS Australia, aimed at facilitating the transition to Microsoft Teams and Azure. Previously reliant on Slack, the organization now seeks to embrace the Microsoft ecosystem, and I was honored to guide them through this migration process.

The sessions saw a remarkable turnout, with over 400 enthusiastic participants actively engaging in the discussions and activities.

Enhance API Security: Safeguard against Cross-Site Scripting (XSS) attacks with Azure Web Application Firewall

In this article, I'll illustrate how Azure Front Door Web Application Firewall (WAF) shields against Cross Side Scripting (XSS) attacks, ensuring robust protection for your applications.

I'm leveraging Azure Front Door Premium, which includes a WAF policy with managed rulesets, providing enhanced security measures for my applications.

We will start the process by assigning the Microsoft Default ruleset to the WAF policy.

That's all we need to do. The WAF will handle the rest.

Let's attempt to simulate a Cross Site Scripting (XSS) attack.

Azure Front Door WAF has effectively countered the attack. Let's examine the WAF logs to review the outcomes. I'm utilizing a simple KQL query as below.

AzureDiagnostics
| where ResourceProvider == "MICROSOFT.CDN" and Category == "FrontDoorWebApplicationFirewallLog" 
and action_s == "AnomalyScoring"
| project requestUri_s, ruleName_s, details_data_s,details_matches_s, action_s

Here are some of the rules that intercepted our malicious request.