Barbara Forbes
Azure Architect @ Zure | Azure MVP | GitHub Star
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Barbara Forbes is an Azure Architect & consultant at Zure in the Netherlands, a Microsoft Azure MVP, Microsoft Certified Trainer (MCT), and a GitHub Star. She works at the intersection of technology, strategy, education, and development. Her focus is on the Microsoft Cloud Adoption Framework, Generative AI, Infrastructure as Code, PowerShell, and GitHub.
Barbara loves explaining things in an accessible manner; in person, as a teacher for LinkedIn Learning and as a frequent speaker at conferences and user groups. She is actively involved in the tech community, including being part of the organization of European events
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Secure access to your Azure environment: Let's count the ways
Azure's web-based access is incredibly convenient, allowing you to enter the portal from any device, anywhere. But this convenience isn't exclusive to you; it's also a potential gateway for those with malicious intent, trying to exploit your resources, data and budget. The consequences from a security breach can be huge.
In an era where digital protection is needed more than ever, navigating the security tools can be overwhelming. Some tools might slow down your processes. Is the added security worth the potential decrease in speed? Is it necessary?
This session is your guide through the security options available to cloud engineers. We'll explore MFA, PIM, JIT, VPN, PAW, and other three-letter abbreviations that stand between you and your Azure environment intruders. Discover modern tools that not only secure your Azure space but could also be used for on-premises access through Azure.
By the end of our journey, you'll have a blueprint for creating the most secure environment. You'll leave equipped to make informed decisions about which security measures are right for your setup. Let's secure your Azure landscape together.
The Microsoft Cloud Adoption Framework: What the Docs don’t tell you
The Microsoft Cloud Adoption Framework for Azure promises a flexible environment where developers have the freedom to innovate while keeping data and resources secure. Sounds great right? It is, but real life implementations can often come with some challenges. Including the first world problem of too much documentation.
In this session, we'll look at the Cloud Adoption Framework and how you can use it effectively. I will take your through each step of the Framework and the challenges that came with them in the real world implementations. Spoiler alert: It’s often not the technology that’s the problem! By the end of this talk you will have actionable knowledge to shape your own Azure journey to its fullest potential
Deploying to Azure: Azure DevOps Pipelines vs GitHub Actions
When using Infrastructure as Code, it’s crucial to maintain the highest possible quality and security of your code. Automated tests and deployments help us achieve a consistent and stable Azure environment.
But which tool should you use? Both Azure DevOps and GitHub Actions are professional tools to achieve this goal, but how do they compare? In this session, we will explore the similarities and differences between these two tools. How much time does it take to learn them, how much management do they require, and how do they integrate with Azure? Together, we’ll discover which of the two best fits your situation.
No cartoons in Azure: Creating a solid naming- and tagging strategy
Working with Azure brings a very familiar challenge: the naming convention. Who remembers inheriting servers named after cartoons, vegetables, scientists or random jokes? It's always funny until it starts scaling. With Azure, you reach this point very fast and it pays to get it right directly.
In this talk, we will look at the choices to make, the technical and strategical challenges and some tips & tricks from the field. Last but not least, let's see how we can integrate that naming- and tagging convention in our Infrastructure as Code to help get the most consistent environment. You will thank yourself later!
Implementing Azure Policies: Before the Portal
As your Azure environment grows, you'll need to find ways to keep everything organized. Especially with structures like the Microsoft Cloud Adoption Framework, it's important to set boundaries to manage the endless possibilities that Azure has to offer. So you create policies to help maintain control, security, and compliance in your environment.
But where do you begin? The options seem endless. Should you use all of them?
In this talk, we'll look at the starting point. Guess what; it isn't the Azure portal. We'll see how to determine the policies you need and how to simplify your Azure experience rather than complicate it.
We'll also address common challenges and mistakes in Azure policy as seen from the field. At the end, you will have a clearer understanding that will help you make the best choices and make Azure policy work for you.
Coding smarter with GitHub Copilot
AI is changing the way we work. But how do we actually create more value with it?
You've seen what GitHub Copilot can do. But in this session, we will focus on what matters: how to get consistently better results, instead of feeling like you’re explaining your code to a toddler.
Through live demos, we’ll explore how GitHub tools can be customized and managed to become your (slightly annoying) coworker. One that actually saves time, comes up with options you might miss, and occasionally surprises you in a good way.
You’ll walk away with a clear overview and practical tips on which tools and models to use.
Let's find out how we can make AI work for us to bring our ideas to life.
This title was written by AI — and that’s only the beginning
What happens when you let AI write your code, your posts, and your plans? In this talk I share what happened when I put AI to work across everything: shipping apps to production, managing my LinkedIn presence, automating my planning, learning new frameworks.
Each experiment showed the same pattern: AI gives back exactly as much as you put into managing it. I will tell you what worked, what failed, and how you can improve your own results based on my lessons learned.
You'll leave with real examples, an honest cost/benefit breakdown, and a clear sense of how to get more value out of your artificial friend, without losing the human logic behind it.
One Size Fits None: Make Azure best practices work for your organization
Defaults like the Cloud Adoption Framework, Azure Verified Modules and the Azure Security Benchmark all deliver. Just not straight out of the box. The problem is that Microsoft's guidance is written for the average company, and the average company is hard to find.
We look through what the standards are and why they will or will not work for you. Maybe your company doesn't need the flexibility of AVM, which can be a pain to update. The Cloud Adoption Framework gives developers a freedom plenty of organizations do not actually want. And some Security Benchmark policies will happily block built-in Azure resources.
None of these standards are wrong. They are written for someone else. You leave knowing which parts to adopt, which to adapt, and which to leave alone.
Trust, don't store: how WIF changes your deployment security
Does your deployment pipeline still authenticate with a client secret? In the best case it lives in a vault and rotates on a schedule nobody loves. In the worst case they are stored somewhere unsecured and nobody has touched them since 2021.
Workload Identity Federation replaces that secret with a trust relationship. Nothing to leak, nothing to rotate, nothing stored outside Azure.
In this session we'll explore the systems behind WIF and OpenID Connect and how the two relate. We set up WIF from scratch in both GitHub Actions and Azure DevOps, and go through the limitations that decide whether it works for you. You leave with a migration path and a clear answer if anyone asks you if WIF is the most secure form of authentication
Azure Policy as Code: Lessons from the Field
Azure Policy as Code: Lessons from the Field
I built a fully automated Azure Policy deployment. This is everything I learned, including the parts I would rather not have.
We start with the structure and the building blocks. From there we go into Infrastructure as Code, and how you turn those building blocks into something that's actually yours: definitions, assignments, exemptions, all deployed and managed through code
Then the things I did not see coming. The assumptions that turned out wrong. The parts I had to rebuild. The design choices that looked fine right up until they didn't.
Then, let's talk about all the things I didn't see coming. The assumptions that turned out wrong, the parts I had to rebuild, the design choices that looked fine until they didn't. You get the mistakes so you don't have to make them yourself.
You leave with a blueprint for your own landing zone, and the decisions to make before you write a line of it, because there are some issues you might not have seen coming
AI tools for the Azure Engineer
A deployment failed for reasons the error message is not sharing. Someone needs a policy exemption explained in writing. There is a Bicep pull request waiting. And finance wants to know why the bill went up. How can AI tools simplify your daily tasks?
In this session, we'll explore the best tools to improve your workflow. Discover which ones live up to the hype and can truly make your job easier.
Join me to learn about Copilot for Azure, GitHub Copilot, the browser assistants, Claude Code, and whichever of their relatives still matter by the time I present this. . Through examples and demos we find use cases, risks, costs, benefits and tips on how to make the most of AI in your everyday work.
Your secure score is lying to you
Defender for Cloud gives you a number that I can predict two things about: It will not be 100, and someone will eventually ask why.
Let's talk about other strange findings, like how Defender produces recommendations faster than any team can act on them, charges per plan and per resource type, and runs on the same policy engine you already use for governance. How do you make it work for you? We cover what it gives you beyond a list of findings, which plans earn what they cost, which recommendations to deliberately dismiss, and how to record that decision so it survives an audit.
You leave able to decide what to switch on, what to ignore on purpose, and how to explain both.
Paying by the token: how to regain control over AI spending
AI used to feel free. Pay a monthly fee, run everything in Opus, never think about it again.
That ended. In June 2026 GitHub Copilot stopped charging per request and started charging per token. Claude started working with sessions. These changes left us with a paradox: you pay for the tokens the model spends thinking, and you cannot see or control how many that is.
Lets talk about our options. Let's talk about how to optimize our input and instructions, how caching and context windows work and the difference a model really makes.
Coding agents will never be as cheap as they were, but you will leave able to cut the bill without cutting what you get out of it.
Your app has no MFA: securing managed identities and service principals in Azure
Your pipeline has no MFA. Your app cannot approve anything. For people you constrain who gets in, and you have plenty of tools to do it with. For a workload there is nobody to ask, so all you have left is what the identity is, what it can reach, how long its credential lives, and whether it needs a credential at all.
Let's walk through the options. Managed identity or federated credential. System-assigned or user-assigned. Contributor or Owner, and at what scope should that land? Least privilege sounds great, but it is not always the most practical answer, or even the most secure one, and I will show you where it falls apart.
This is a part of Azure access that is ignored far to often. You will leave with a decision tree and practical tips to improve. The more secure option might actually be easier to maintain
Choose Your Own Adventure: Finding the Right Harness for GitHub Copilot
GitHub Copilot is no longer one tool. It's a chat panel, a scriptable CLI, a background agent, and an editor-native agent mode, four different working styles built on the same model. Step outside GitHub's ecosystem and open source agents like opencode make the choice even harder.
In this session, we will see them all. What are their benefits? Which harness fits which job? Are you missing out if you don't use them all? You will leave with a decision framework to find out what harness might be best for the job, but most importantly: what works best for you.
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