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Ryan welcomes Jaime DeLanghe, chief product officer at Slack, to chat about how they’re preparing to integrate everybody’s agents in their chat application.
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Sr. Content Developer at Microsoft, working remotely in PA, TechBash conference organizer, former Microsoft MVP, Husband, Dad and Geek.
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This post is a quick update to walk through the new flow. If you read the previous one, think of this as the easier path I wish I had the first time round. If you have not seen the original, you can find it here: Integrating Microsoft Foundry with OpenClaw: Step by Step Model Configuration | Microsoft Community Hub
Pre-requisite:
You will need the Azure CLI (azure-cli) installed on your machine. The official install guide for Linux is here: https://learn.microsoft.com/en-us/cli/azure/install-azure-cli-linux?view=azure-cli-latest
I am on Linux so I went the Homebrew route, which keeps things simple. The formula is here: https://formulae.brew.sh/formula/azure-cli
Microsoft also has official docs covering the Homebrew/Linuxbrew install: https://learn.microsoft.com/en-us/cli/azure/install-azure-cli-macos?view=azure-cli-latest#install-with-homebrew
Once Homebrew is ready, run this in your terminal:
brew install azure-cli
Why this matters:
Before this update, every Foundry model you wanted to use in OpenClaw needed its own API key and endpoint pasted into the config. It worked, but it was tedious, and keys are easy to leak if you are copying them around. The Azure AD path solves both problems. You authenticate as yourself (or a service principal), OpenClaw asks Azure for the list of Foundry resources you have access to, and it brings the models in automatically.
Signing in to Microsoft Foundry from OpenClaw via Azure AD
A device-code OAuth handshake replaces the old static-API-key flow. OpenClaw delegates auth to the local Azure CLI; the CLI handles the browser-side sign-in, holds the resulting tokens, and refreshes them silently. OpenClaw then walks the Azure resource graph, subscriptions → Foundry resources → model deployments and registers each model into its own config. No API keys move through OpenClaw at any point.
Walking through the new flow:
Start with the command to onboard openclaw as if you were setting up OpenClaw for the first time:
openclaw onboard
Kick things off with the OpenClaw onboard command, the same one you would use when setting up OpenClaw for the first time. When it prompts you, choose update values.
Next, you will be asked to configure your models. Scroll down a little and you will see Microsoft Foundry listed as a supported provider. Pick it.
From here, you have two options. You can sign in with an API key, which is what I covered in the previous blog post, or you can sign in through Azure AD. The Azure AD path is easier and more secure, so that is the one we will use.
OpenClaw will give you a URL and a device code. Copy the URL into your browser and use the code to complete the sign in. (This is where the az CLI from the pre-requisite section earns its keep.)
If everything worked, you should see a success prompt similar to this:
Once you are signed in, OpenClaw will ask you to pick the Azure subscription that your Microsoft Foundry resource lives in. Pick the subscription, then pick the Foundry resource where your models are deployed.
And that is pretty much it. All the models you have deployed to that Foundry resource get pulled into OpenClaw automatically. Compared to the old way of pasting API keys and endpoints one by one, this is a huge time saver, and you do not have to babysit any keys.
From here you can start using your Foundry-deployed models inside OpenClaw straight away:
Wrapping up
The Azure AD sign-in option in OpenClaw is one of those small updates that quietly removes a real pain point. If you have ever juggled multiple Foundry endpoints and rotated keys across them, you already know why. With this flow, you sign in once, your models show up, and you can get back to actually building.
If you have not tried OpenClaw with Microsoft Foundry yet, this is a good time to give it a go. And if you were holding off because of the key management overhead, that excuse is gone now.
References
Previous post on integrating Microsoft Foundry with OpenClaw using API keys: Integrating Microsoft Foundry with OpenClaw: Step by Step Model Configuration | Microsoft Community Hub
Install the Azure CLI on Linux: https://learn.microsoft.com/en-us/cli/azure/install-azure-cli-linux?view=azure-cli-latest
Install the Azure CLI on macOS: https://learn.microsoft.com/en-us/cli/azure/install-azure-cli-macos?view=azure-cli-latest#install-with-homebrew
Homebrew formula for azure-cli: https://formulae.brew.sh/formula/azure-cli
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This article assumes you already have an Azure Foundry project and resource deployed in Microsoft Foundry. The options referenced here are documented in detail in the linked articles; this post serves as a consolidated step by step guide bringing them all together and explaining where each option is most useful.
A Summary:
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Need |
Best Option |
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Quick day-over-day visual, minimal setup |
Grafana Dashboard (Option 3) |
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Custom growth % calculations |
App Insights + KQL in Log Analytics (Option 4) |
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Shareable, interactive report |
Azure Workbooks (Option 5) |
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Per-user/per-agent granularity |
APIM + App Insights (Option 6) |
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Quick one-off chart, export to Excel |
Microsoft Foundry Monitor tab or App Insights Metrics Explorer (Option 1 and 2) |
Option 1. Within the Microsoft Foundry Portal (Quickest, No Setup)
If you have models deployed in Microsoft Foundry and would like to monitor its usage, go to the New Foundry Portal → Build → Models → Monitor tab.
View metrics such as:
- Estimated cost
- Total token usage
- Input vs. output tokens
- Number of requests
This is the simplest way to monitor both model and agent usage.
For PAYG plans:
You can also view your total allocated quota (and figure out which Tier you are on) using the Quota Management Screen (New Foundry Portal → Operate → Quota tab).
This screen shows how much your total allocated quota is, per model in a given subscription + region + Deployment Type (Global, Data Zones or Regional). For eg., in the image below, for gpt-4o, I am allocated 7M total TPM in my subscription. I am only using 150K TPM of the allocated 7M TPM amount.
Which means, my requests will get throttled if I exceed the 150K TPM limit. To avoid throttling, I would need to increase my shared allocation limit.
NOTE: you are charged for usage, so if you allow more capacity, you use more, so you pay more.
Option 2: Azure Monitor Metrics Explorer
This is already built into the Azure Portal and gives you time-series charts out of the box.
- Go to Azure Portal → your Azure OpenAI / Foundry resource → Monitoring → Metrics
- Select a metric like AzureOpenAIRequests or TokenTransaction
- Set Aggregation to Sum (total) or Max and Time granularity to 1 day
- Split by ModelDeploymentName to see per-model trends
- Adjust the time range (e.g., last 30 days) — you'll see day-over-day bars/lines
Tip: You can pin these charts to an Azure Dashboard for a persistent view, or click Share → Download to Excel to get the raw data for your own analysis.
Option 3: Azure Managed Grafana (Best Pre-Built Dashboard)
This is the best option for a polished, real-time, day-over-day dashboard with no custom code. There's a pre-built AI Foundry dashboard ready to import. [grafana.com], [Create a M...ed Grafana]
How to set it up:
- Create an Azure Managed Grafana workspace (if you don't have one)
- In Grafana, go to Dashboards → New → Import → enter dashboard ID 24039 (for Foundry)
- Select your Azure Monitor data source and point it to your Foundry resource
- Tip: You can also import this directly from the Azure Portal: Monitor → Dashboards with Grafana → AI Foundry.
- That's it — the dashboard gives you (per model deployment):
Token trends over time (inference, prompt, completion — day over day)
Request trends over time (AzureOpenAIRequests as a time series)
Latency trends (bonus)
NOTE: Default time range is 7 days — adjust to 30/60/90 days for growth trends
Option 4: Application Insights + KQL Queries (Most Flexible, Custom Reports)
If you want fully custom day-over-day growth calculations (e.g., % change day-to-day), this is the way. [azurefeeds.com]
Setup:
- Ensure your Foundry project is connected to an Application Insights resource (Foundry → Settings → Connected Resources).
- Open up App Insights resource → Logs → New Query or choose a sample query. In the images below, we simply ran 'requests' and set the time range to 24 hours.
- There is also a Kusto Query Language (KQL) mode or Simple mode on the right-hand side:
- Simple mode will let you run out of the box samples.
- KQL mode will open up a query window for you to enter custom queries.
- Below are the results in grid view.
Same view but showing a chart:
Export options:
Another way to get the above graphs are via Log Analytics. Simply enable Diagnostic Settings on your Azure OpenAI resource → send to a Log Analytics workspace. Open Log Analytics → Logs and try our your sample queries.
Sample KQL for day-over-day token usage (adjust to your needs):
AzureMetrics | where MetricName in ("TokenTransaction", "ProcessedPromptTokens", "GeneratedTokens") | where TimeGenerated > ago(30d) | summarize DailyTokens = sum(Total) by bin(TimeGenerated, 1d), MetricName | order by TimeGenerated asc | render timechartResult:
Sample KQL for day-over-day growth % (adjust to your needs):
AzureMetrics | where MetricName == "TokenTransaction" | where TimeGenerated > ago(30d) | summarize DailyTokens = sum(Total) by Day = bin(TimeGenerated, 1d) | sort by Day asc | extend PrevDay = prev(DailyTokens) | extend GrowthPct = round((DailyTokens - PrevDay) / PrevDay * 100, 2) | project Day, DailyTokens, GrowthPctOption 5: Azure Monitor Workbooks (Custom Dashboards, Shareable)
Workbooks let you build interactive, parameterized dashboards that combine metrics and KQL logs.
What's more, you can select resources from multiple subscriptions and visualize them all in one place using Workbooks!
- Go to Azure Portal → Monitor → Workbooks → New
- Add a Metrics query panel → select your Log Analytics or App Insights or Foundry resource -> Enter the same query you used in Option 4.
- Do a test run and view the graphs (this can be viewed as charts or a list (grid view)):
4. Save and share with your team.
Option 6: APIM + Application Insights (Granular Per-Caller/Per-Agent Tracking)
1. If your app routes requests through Azure API Management, you can use the azure-openai-emit-token-metric policy to send per-request token metrics to Application Insights with custom dimensions (User ID, Subscription ID, Agent, etc.). [Azure API...osoft Docs]
This is ideal for scenarios like:
- "Which agent consumed the most tokens last week?"
- "What's the token usage per API consumer/team?"
NOTE: Microsoft Foundry resources do not track usage by users. So, fronting your Foundry resource with an APIM could be a way to track users provided you pass the username/id in the request context. How you implement this is upto your app design.
Bonus: Check out all other APIM + AI related policies here:
AI-Gateway/labs/semantic-caching at main · Azure-Samples/AI-Gateway
AI-Gateway/labs/token-rate-limiting at main · Azure-Samples/AI-Gateway
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Composer 2.5 narrows the gap with frontier coding models on key benchmarks while Cursor touts dramatic token‑efficiency at a fraction of the cost. Enterprise strategy is shifting toward harness‑first platforms and agent orchestration, capturing long‑running context, persistent memories, and post‑training improvements to rival model labs. Security research around Mythos Preview shows models synthesizing and refining exploit chains into functional proofs, prompting Cloudflare warnings about a novel class of model‑generated risk as companies operationalize agent tooling.
The AI Daily Brief helps you understand the most important news and discussions in AI.
Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614
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Learn more about the show https://aidailybrief.ai/
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How will Apple follow up on any AI announcements made at WWDC later in June, after Google held its Google I/O keynote? Some leaks of iOS 27's new design could be exciting for a lot of users. And the iPhone 17 is driving Apple's market share within the US, as the overall US smartphone market has declined.
- Apple's new ChatGPT-like Siri App will have auto-deleting chats.
- OpenAI is reportedly preparing legal action against Apple; it wouldn't be the first partner to feel burned.
- Apple explores ways to welcome AI agents in the App Store.
- iOS 27's new design leak sounds a lot like what I've been wanting most.
- iPhone 17 keeps driving Apple marketshare, as US smartphone sales contract.
- iPhone Ultra is coming: Six new features in Apple's high-end model.
- Apple's security has been tough to crack. Mythos helped find a way in.
- Epic Games' 'Fortnite' returns to App Stores worldwide.
- Meta launches Instants, a new iPhone app and Instagram feature for ephemeral sharing.
- Spotify adopting Apple's new video podcast tech for easier cross-platform publishing
Picks of the Week
- Christina's Pick: Sentinel
- Leo's Pick: RetroWin
- Andy's Pick: Rechargeable Light Bulb
- Jason's Pick: Mister Plimsoll
Hosts: Leo Laporte, Andy Ihnatko, Jason Snell, and Christina Warren
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Summary
In this episode, Andy welcomes back Marcus Buckingham, bestselling author and researcher, to discuss his new book, Design Love In: How to Unleash the Most Powerful Force in Business. For 25 years, Marcus studied the most productive teams, loyal customers, and effective leaders in the world, and the word that kept appearing in his data was one he kept changing: love.
Andy and Marcus explore what love actually means in a business context, including how leaders are really experience makers whether they know it or not. You will hear the remarkable story of Josh D'Amaro, the CEO of Disney, and what his leadership reveals about designing love into a team's daily experience. Marcus unpacks the five feelings that lead people to say they love working for a leader, starting with something counterintuitive: control. The conversation also covers tough love, AI's limits as an experience maker, and how these principles can transform how we lead our families too.
If you're looking for a fresh, evidence-based look at what drives sustained high performance, this episode is for you!
Sound Bites
- "I kept hearing that word (love) and shame on me, but I did keep changing it because I felt like it was a careless exaggeration of the word like or something."
- "Don't keep changing the word (love). The word's the word. The question really should be why and how do we replicate it?"
- "You're paid to change behavior. That's all you're paid to do. You're not paid to run a project. You're paid to change behavior as a leader."
- "When you send an email, it's not an email. It's an experience for the person on the other end. When you call that team meeting, it's not a team meeting. It's an experience."
- "You join a company and then you quit your boss."
- "Undesigned experiences lead to unpredictable outcomes."
- "It's cowardly, not loving. It's cowardly to leave them in that job."
- "I am for you. I am for you. That doesn't always mean that I am going to tell you what you wanna hear. It means I want you to flourish."
- "Loving's an ingredient, right? Loving isn't, 'Be nicer.' Loving's like, 'What are you trying to do for me?'"
- "The beginning of love is rules. The beginning of love is clarity."
Chapters
- 00:00 Introduction
- 01:48 Start of Interview
- 01:57 Why Marcus Spent Decades Avoiding the Word "Love"
- 05:47 Misconceptions About Love in Business
- 11:29 Inside the "Josh Effect"
- 18:02 What Great Leaders Don't Do
- 22:13 Local Leadership and Variation in Team Experience
- 27:54 When Senior Leaders Couldn't Say the Word
- 31:04 Applying the "Is This Loving or Unloving?" Lens
- 37:43 Tough Love and Difficult Performance Conversations
- 46:20 Practical Takeaways: The Five Feelings of Love
- 50:25 AI and the Role of Love in Leadership
- 56:34 Designing Love Into Parenting and Family
- 1:01:26 End of Interview
- 1:01:57 Andy Comments After the Interview
- 1:05:03 Outtakes
Learn More
You can learn more about Marcus and his work at BuckinghamInstitute.com.
For more learning on this topic, check out:
- Episode 252, which is our earlier interview with Marcus Buckingham. That book still impacts how Andy leads years after having Marcus on the first time.
- Episode 332 with Kevin Eikenberry and Wayne Turmel. A discussion about keeping your teams engaged and connected, even if they're not co-located.
- Episode 324 with Jim Harter. Jim is the Chief Scientist at Gallup and they have an insightful discussion about building resilient and thriving teams.
Chat with PMeLa
You can chat directly with PMeLa—the podcast's AI persona—to get episode recommendations and answers to your project management and leadership questions. Visit PeopleAndProjectsPodcast.com/PMeLa to chat with her.
Pass the PMP Exam
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Just go to 5BestResources.PeopleAndProjectsPodcast.com to grab your copy. I'd love to help you get your PMP this year!
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Thank you for joining me for this episode of The People and Projects Podcast!
Talent Triangle: Power Skills
Topics: Leadership, Love in Business, Team Culture, Employee Engagement, Customer Experience, Project Management, AI, Artificial Intelligence, Parenting, Organizational Culture, Experience Design
The following music was used for this episode:
Music: Summer Morning Full Version by MusicLFiles
License (CC BY 4.0): https://filmmusic.io/standard-license
Music: Tuesday by Sascha Ende
License (CC BY 4.0): https://filmmusic.io/standard-license
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