Copilot in Microsoft Cost Management

QUICK LINKS: 

00:00 — Introduction 

01:03 — Invoice analysis, insights, optimizations 

02:21 — How it works 

03:59- Future AI simulations and what-if modeling 

04:53 — Wrap up 

Link References: 

Stay informed at https://aka.ms/MCM-AIPreview

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Video Transcript:

-What if you could use AI like ChatGPT to gain greater control over your cloud spend in Azure? Well, today I’m going to show you a first look at the GPT-powered AI chat capability for Microsoft Cost Management. Now, whether you are running individual workloads in Azure or managing overall cloud spend for your organization, Microsoft Cost Management, which is available with your subscription from the Azure Portal, reduces the unpredictability of your operational costs, by giving you visibility into your workloads and the related resources driving spend. It helps you to see spending patterns as well as any specific anomalies driving up costs. You can set budgets to limit your cloud spend, share workload costs across different teams and business units, and also identify opportunities for optimizations. 

-There’s a ton of information at your disposal, and by using AI in Microsoft Cost Management, you can ask natural language questions to get the insights you need faster, without being an expert in navigating the Cost Management UI and how to analyze the data. You can just let the AI do this for you. For example, if I want to understand my recent bill, I can ask for help in breaking it down, And I’m provided a break down by categories of spend and their percentage impact on the total invoice. 

-From here I can leverage the generated suggestions to investigate my bill further. For example, I can compare this month’s invoice with the previous month, look at the last three months, charges by subscription or costs specific to networking. I’ll look at how my costs compare to the previous month, and I’m given a number of AI-generated insights on changes causing an increase in charges, again, saving me from doing the analysis myself. Now, importantly it also recommends actions that I can take, for example, I can set a budget to prevent futures overages or add anomaly alerts. To investigate things further, I can next request a break down of costs for a specific subscription. In this case, the AnalyticsTeam-Dev. And in a few seconds, a table of charges by service for the subscription is generated and displayed. I can see my Virtual Machines seem to be a lot higher this month and so I’ll do a natural language query and ask if this is an anomaly for the month. And the AI generated response presents a view of costs over the past six months. 

-And I can see that this is the first time in recent history that costs have spiked I’m also presented with a few suggested prompts to help me resolve the issue, like cost optimizations, cost alerts and data about previous months that I can use to explore further. And this is just for one subscription, but imagine using this type of AI assistance to explore your cloud bill across multiple subscriptions in your organization. You can analyze operational spend data to get to the source of spikes or anomalies in just a fraction of the time it would take to do this yourself, and you are provided with key insights and potential optimizations. 

-How this works behind the scenes is that the AI in Microsoft Cost Management understands user intent, and based on its training interprets the right kind and level of data. It looks at the users’ permissions before making specific API calls to securely orchestrate the retrieval of this data from multiple sources and performs complex analytical tasks at runtime. Retrieved information along with the user prompt is then presented to the large language model. And importantly this retrieved information is not used to train the model, it just provides the necessary knowledge and context to generate a response. Users can engage in multi-turn conversations that build on their initial prompt to get the details they need Importantly, AI generated responses leverage your existing Microsoft Cost Management configurations. Which means it really pays off to tag your resources as we’ve shown on previous shows to set the foundation for granular visibility and to track costs all the way down to the individual resource group level or even the individual resource, depending on the tags you’ve put in place. 

-In fact, you can expect the AI chat capabilities to incrementally help you achieve what you normally would do with Microsoft Cost Management to generate cost insights, and it will also go beyond the capabilities you see today. For example, in the future you’ll also be able to take advantage of AI simulations and what-if modeling to make informed decisions. Let’s say, I want to explore the increase in storage costs should my business growth double, so I’ll paste in my question. And pretty quickly, an answer is generated through near instant modeling of my historical usage data. And again, I’m also presented with suggestions for how to optimize my spend with specific recommended actions, like buying a reservation or adding a savings plan, as well as additional prompts to explore these options further. In this case I want to scope the simulation a bit more by asking: “If I move my storage from the West US region to the East US region, how will that affect my charges?” And based on simulated changes, an assessment of cost saving is presented for this specific scenario, as well as migration-related costs for moving my data. This is just one possible example, but simulations will work for any number of what-if scenarios. 

-So that was a first look at the new GPT powered AI chat capability for Microsoft Cost Management and how this will help you to get even more control over your cloud spend. This is a really important step to making the experience of managing your cloud costs even more seamless so that you can configure smarter budgets or even ask AI to assist with creating optimized budgets for you. To stay informed about availability and to learn more check out aka.ms/MCM-AIPreview. Keep watching and subscribe to Microsoft Mechanics for the latest in tech updates, and we’ll see you next time.