Microsoft Copilot for Azure

A practical hands-on experience.

What’s the buzz all about ? Many in the industry see it as a game changer. I will share my experience with Copilot for Azure today (not to be confused with other Copilots, such as GitHub Copilot, Windows Copilot, Dynamics 365 Copilot, Microsoft 365 Copilot etc.).

At the time of writing this article, Microsoft Copilot for Azure is in public preview phase. This morning, I received a much awaited email stating : Welcome to the limited public preview of Microsoft Copilot for Azure! Congratulations! It seemed, I was the chosen one. No pun intended, I was. After all, it holds a promise to bring a paradigm shift in simplifying cloud operations. A promise which is close to my heart: pretty much the new way of working.

It also validates my own prediction on Horizon5 (H5) in my article Next Quarter Century of GenAI. H5 is about Executable AI evolution from Generative AI.

I will divide this article into two sections, Theory and Practical hands-on.

Section 1: Theory

On November 15th 2023, Microsoft announced Microsoft Copilot for Azure, an AI companion, that helps you design, operate, optimize, and troubleshoot your cloud infrastructure and services. Combining the power of cutting-edge large language models (LLMs) with the Azure Resource Model, Copilot for Azure enables rich understanding and management of everything that’s happening in Azure, from the cloud to the edge.

Azure users can gain new insights into their workloads, unlock untapped Azure functionality and orchestrate tasks across both cloud and edge. It leverages Large Language Models (LLMs), the Azure control plane and insights about a user’s Azure and Arc-enabled assets. All of this is carried out within the framework of Azure’s steadfast commitment to safeguarding the customer’s data security and privacy.

Let me provide a summary.

Fig. 1

• Leverages large language model (LLM) and Azure control plane
• Answers questions about your Azure managed environment
• Generates queries for your Azure managed environment
• Performs tasks and safely acts on your behalf for your managed environment
• Makes high-quality recommendations and takes actions within your organization’s policy and privacy

So, with this, you can understand your Azure environment, work smarter with your Azure services, write and optimize code for your applications on Azure.

Section 2: Practical hands-on

I logged into Azure console. Copilot icon appeared at the top bar for me to happily click on it (and I did just that). It is provided as a sidebar on the portal itself, so as you navigate the portal services, Copilot stays with you and understands the context from your browsing as well.

Fig. 2

To start with, I asked how many resources are running (for me). It replied accurately right there — 184 resources.

Further, I asked Copilot to list all VMs that are not running now as shown in Fig. 3. It understood the context within my resources in the subscription (tenant id).

Fig. 3

Next, I asked which resources were created in the last 24 hours and it showed up those as shown in Fig. 4.

Fig. 4

Next steps are quite more interesting. It was a real augmented experience. Copilot (digital worker) and I (human worker) worked together. I asked to help me create a low cost VM and it executed required steps one by one for the given context and gave me options to enable or skip those features. From Fig 5, to Fig 11 it executed all required steps, allowed me to check the right options and so on.

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Fig. 9

Fig. 10

And here, we came to the step of final creation of VM as shown in Fig. 11.

Fig. 11

In the next step, I wanted Copilot to open the ARO cluster service section. It opened it up in my second attempt as show in Fig. 12.

Fig. 12

Further, I asked Copilot to create a cluster. Here it gave me the required commands and steps with Run option. When I clicked on Run, it opened the command shell expecting me to run the commands as shown in Fig. 13.

Fig. 13

Then, I wanted to validate if there any security weakness related to a storage account (in test environment, of course).

It asked me if I would like Copilot to run security checks. I clicked on Yes, and it ran the security checks for the particular storage account and listed those weaknesses straight away as shown in Fig. 14.

Fig. 14

Here, I wanted to find out the Service Health of all resources that belong to my tenant. As you see below in Fig. 15, I input specific prompts realted to outage, impact, health events etc. It reported the correct status on those.

Fig. 15

In Fig.16, I learned that it did not provide any cost insights, forecast, trend etc. at the moment whereas It should have, as per the theory. I will retry. I am also sure a lot many features will be added over time. I would like to ask about any sudden cost spike with any resource during the week (will do tomorrow).

Fig. 16

Finally, it seems I ran out of the limit for my conversations with Copilot for the day as shown below.

Fig. 17

In fact, the email I received did state ‘Microsoft Copilot for Azure is experiencing an overwhelming demand from Microsoft customers. As a result, we have implemented conversation and turn limits to ensure that we maintain sufficient capacity to all customers enabled with this feature.’

So, I will talk to my Copilot for My Azure Resources tomorrow evening.

Conclusion:

• Overall, it does demonstrate a promise of AI-augmented cloud operations.
• In public preview phase, it allows to execute a lot in terms of insights, service health, deployments, recommendations, steps, commands etc.
• It performs output completions within the admin’s/user’s subscription or tenant id (rightly so).
• Era has arrived where Human worker and Digital worker can collaborate in real-time to add value to cloud operations.
• It is currently not recommended for production workloads (obviously it is in preview phase). So, we will have to wait (can we?) for its General Availability.

Disclaimer: Personal views, personal hands-on, personal understanding.

Please provide feedback and claps (if you like it). Knowledge shared is knowledge earned, so please share the article with like minded readers.

Thank you as always,

Schedule Azure Automation Runbook with Terraform and Powershell

 

Source: Data Semantics

Azure Automation is a service in Azure that allows you to automate processes from within Azure.

An automation account manages several other resources in order to achieve this. I’d be going over these features in this article and how you can use them to automate a simple task.

Case Study

You are managing a software that collects log files constantly. To save storage costs, you have to be cleaning the storage container regularly, let’s say once every week. How can you automate this in azure?

Everything I’d be showing can be done via the azure portal but we would instead be using Terraform.

Step 1 — Create your Azure Automation Account

As always with azure, first create your resource group where all related resources will reside, followed by the automation account.

I will explain the SystemAssigned Identity bit next:

Step 2 — Set up Access

We used the System Assigned Identity access above. Some older automation accounts use Service Principles, but this brings up issues such as:

• Having to renew certificates every year to maintain access.
• The service principle is given access to the entire subscription, whereas a managed identity can simply be given access to only what it needs.

And more…

Using managed identites to access automation accounts is a newer and very useful feature. We can either use user-assigned managed identities or system-assigned managed identities.

In this case, a system-assigned identity suffices, since we are not using it for any other resources apart from this automation account, so it will be created while deploying the automation account (in the Terraform script above).

Now all we need to do is assign it the required role, using Terraform. Here, I will simply be giving it access to the whole resource group, which is where I’d be placing all the resources involved in the task:

Note: In order for the runbook to access the storage account that contains the logging, it must also be in this resource group logging .

Azure Automation Runbook

We need to first create this resource using Terraform, so Terraform can manage it along with others.

You would create a folder named files in the same directory your Terraform files exist, and then create the script LogCleaning.ps1 inside it.

This is what your PowerShell Workflow script would look like:

This is a very simple script, you could add extras such as a try-catch block or a way to keep a few log files. You can be as creative as you’d like!

Storage Credentials

You would notice the StorageCredentialsName in the runbook. This is used to access the storage account where the logs live. We can get these credentials using the Terraform block below.

Assuming we have already created a storage account to store these files in another Terraform block named log_storage

Automation Schedule and Automation Job Schedule

This is what determines how often the runbook executes. The

You would also notice the Params dictionary in the runbook. There are many ways to pass input parameters to the runbook, but I will be passing it through the schedule in this example since we already require one.

We create a schedule first and then link it to the runbook using a job schedule.

We’re again assumming a storage account was earlier created named log_container

We also need to first get your subscription ID using the snippet below:

Now we will proceed as follows:

And now you just need to run your terraform plan followed by terraform apply and you’d have your logs cleaned up every week without you doing a thing!