AADSTS65005 error when signing in to Microsoft Cloud services

This post features solutions to fix the AADSTS65005 error when signing in to Microsoft Cloud services. The error usually occurs if the application isn’t registered with Azure AD or it doesn’t have correct permissions applied. The error message reads:

AADSTS65005: The client application has requested access to resource. This request failed because the client did not specify this resource in its requiredResourceAccess list.

OR

Sorry, but we’re having trouble signing vou inAADSTS65005: Invalid resource. The client has requested access to a resource which is not listed in the requested permissions in the client’s application registration.

Fortunately, you can follow some simple suggestions to fix the error.

The AADSTS65005 error in Azure AD usually occurs due to an authentication error during sign-in. However, it may occur due to some other reasons. Some of them are:

To fix the AADSTS65005 error when signing into Microsoft Cloud Services, verify account credentials and manually register for Azure AD. If that doesn’t help, follow these suggestions:

Let’s now see these in detail.

Firstly, double-check your username and password for your Microsoft Account. Also, ensure there aren’t any typing errors and unnecessary capitalizations.

Next, check your network connection. A slow and unstable internet connection can be why the AADSTS65005 error occurs while signing into Microsoft Cloud services. To test, consider restarting your modem/router or connecting to a different network. But if your internet speed comes to be less than the plan you’ve opted for, consider restarting your router and modem. Alternatively, you can also try connectiong to a different network connection.

Registering an application with Azure AD will establish a trust relationship between the app and the Microsoft identity platform. This may help fix the AADSTS65005 error. Follow these steps to create the app registration:

Once the registration process is complete, the Azure portal will display the app registration’s Overview pane.

Next, try registering the application for Dynamics CRM to fix the error AADSTS65005 while signing in to Microsoft Cloud services. Here’s how:

If none of these suggestions helped you, consider contacting your administrator. It may help if you are accessing the Cloud services through an organizational account. They may offer specific guidance based on your organization’s setup and policies.

Read: Fix AADSTS9002313, Invalid Request Microsoft 365 activation error

I hope this helps.

The AADSTS50105 error in Azure indicates an authentication failure when a user attempts to sign into an Azure AD application. This mainly occurs if your Microsoft account is disabled or blocked from accessing the application.

To fix Office 365 Sign in or activation issues, check your internet connection and verify your account credentials. If they don’t, try signing in using a different account.

Putting Fabric in your Data Fabric

In-Depth

Microsoft just held its developer-focused Build conference, this time a hybrid event with both online and warm body attendees.

Satya's keynote was AI, all the time, everywhere, and I have some thoughts on Copilot coming to Windows and basically every other Microsoft app you can think of, which I'll share below.

But first, I'll focus on a much more tangible release, the public preview of Microsoft Fabric. There were 11 sessions focused on this new(ish) data analytics Software-as-a-Service (SaaS) service, and I'll explain where it fits in and why I think it's an important evolution.

Cloud Building Blocks Are Changing Software ForeverOne interesting trend I've been noticing over the last few years is how cloud provider's building blocks can be combined to become more than the sum of their parts.

Take Microsoft Teams for example. Building on top of Microsoft 365 Groups (a building block that never went anywhere by itself), SharePoint and OneDrive for Business storage, plus Exchange mailboxes, this service has seen meteoric growth in just a few years. By themselves, these individual services in Office 365 performed their decades old functions just fine, but when mixed together in just the right way (to compete with Slack) something truly useful emerged.

Or Microsoft Sentinel, one of my favorite services that I use for all my clients for deep security visibility across their digital estates. To store all the security log data from cloud and on-premises sources, they didn't invent a new database and instead used Log Analytics, which was already optimized for huge log data sets and offered fast search capabilities through Kusto Query Language (KQL). To provide the Security Orchestration, Automation and Response (SOAR) piece, they again built on a battle-tested Azure service, Logic Apps, and for advanced hunting scenarios you can use Azure Notebooks (hosted Jupyter Notebooks).

Microsoft Fabric is using the same playbook, combining seven existing Platform-as-a-Service (PaaS) services into a single SaaS service.

Data Everywhere -- for EverythingWith the risk of committing buzzword bingo overload -- an organization's competitive advantage comes down to how well it leverages its data. The confluence of cheap cloud data storage, ubiquitous sensors and cost-effective compute has led to many businesses realizing the value of their data. But it nearly always happens in silos. The marketing department has one place where they gather all their leads and campaign data, whereas manufacturing stores their factory generated production data in another system, followed by distribution in a third system. And there are many systems to choose from, both open source and proprietary, across cloud and on-premises platforms. Of course, if all data was stored in the same place, in the same system, it's value could truly be unlocked for the business as a whole but being a Chief Data Officer is often more like being a Chief Integration Officer.

Microsoft Fabric in a NutshellMicrosoft has one surprisingly popular service / tool for data visualization, Power BI. Incredibly easy to use, even for a non-developer like myself, anyone can download the desktop app and start creating reports and visualizations. That power, coupled with a very easy way to connect to, or import data sources, has made it the go-to tool for many business users.

Meanwhile Microsoft has several popular services in Azure for building data warehouses, such as Data Lake generation 2, and the Synapse family (formerly SQL Data Warehouse). They all require a fair bit of expertise to configure and fine tune, however. Then there's Data Factory, which does Extract, Transform and Load (ETL) on data, thus ingesting it from disparate data stores.

These services are now being reborn in their SaaS form in Fabric. The existing services will continue to function but will not receive (most) new features, as these will be surfaced in Fabric instead.

So, if Fabric brings together existing services, let's look at what's new. First, there's a new data storage location called OneLake (like OneDrive -- get it? There's even a driver so that it can show up on your local drive, just like OneDrive does). It's built on Data Lake but stores all data in the open Delta format (everyone at Build kept calling them Delta- Parquet files, but they're really just Delta files -- tracking changes to the data).

If the data you need isn't in OneLake already, you can either import it, or use shortcuts that can point to other OneLake locations, existing Data Lake gen 2 or Amazon S3 storage accounts (with more sources to come). The One bit is important. You only have one across an entire Azure AD tenant, just like you only have one Fabric instance. This is to alleviate the integration issues mentioned above. Just like in Power BI you can then divide your OneLake into multiple workspaces, with different security and access controls.

Also, you don't have to fine-tune the size of the underlying infrastructure (Spark clusters), as this is SaaS it's all taken care of for you. Note that pricing has not been announced so at this point it's all a bit hand-wavy, but I trust it'll become clearer over time.

In OneLake a database whose tables are managed by Spark is a Lakehouse, whereas a database whose tables are managed by the SQL transaction system is a Warehouse (unstructured vs. structured data). A Warehouse has a SQL connection endpoint, so you can use any other third-party tool that can connect to it for visualization, or other data processing (provided you have the right credentials).

One new component in Fabric is Data Activator, currently in private preview. In demos it's used to take action on data as it's being streamed into Fabric -- take an action when the temperature of a delivery truck exceeds a particular value for example. It's a "no code" environment where you connect triggers ("patterns of data") with actions to achieve the appropriate result.

Here's some other helpful bits of Fabric terminology.

Another interesting aspect is the enablement of Continuous Integration / Continuous Deployment (CI/CD) throughout Fabric. In Power BI this is done by changing the underlying file format. Today a dashboard is stored in the pbix format, but what's coming is storing Power BI in a folder structure compatible with GitHub (and any other source code repository) -- and this is also coming to the other workloads in Fabric.

Data scientists can work together with others in the business, and Fabric will handle their ML models and Notebooks and other artifacts as objects.

Not in the diagram above (the seventh service) is Azure Purview. This data security service works with Fabric to provide sensitive information scanning, lineage (where did this data come from originally and how was it transformed to end up here), endorsement (this data is accurate) and Data Loss Prevention (DLP) to control sharing of sensitive data. In public preview is also the inclusion of ML artifacts into Purview.

Notebooks open in seconds, something that could take minutes in Synapse, and you can now edit them concurrently with other data engineers.

A nice touch is the Admin monitoring reports (inherited from Synapse) which will give you insight into how Power BI and Fabric is used in your tenant, which features are adopted and so on.

Microsoft goes all in on plugins for AI apps

Microsoft aims to extend its ecosystem of AI-powered apps and services, called "copilots," with plug-ins from third-party developers.

Read more about Microsoft Build 2023

Today at its annual Build conference, Microsoft announced that it's adopting the same plug-in standard its close collaborator, OpenAI, introduced for ChatGPT, its AI-powered chatbot -- allowing developers to build plug-ins that work across ChatGPT, Bing Chat (on the web and in the Microsoft Edge sidebar), Dynamics 365 Copilot, Microsoft 365 Copilot and the newly launched Windows Copilot.

"I think over the coming years, this will become an expectation for how all software works," Kevin Scott, Microsoft's CTO, said in a blog post shared with TechCrunch last week.

Bold pronouncements aside, the new plug-in framework lets Microsoft's family of "copilots" -- apps that use AI to assist users with various tasks, such as writing an email or generating images -- interact with a range of different software and services. Using IDEs like Visual Studio, Codespaces and Visual Studio Code, developers can build plug-ins that retrieve real-time information, incorporate company or other business data and take action on a user’s behalf.

A plug-in could let the Microsoft 365 Copilot, for example, make arrangements for a trip in line with a company's travel policy, query a site like WolframAlpha to solve an equation or answer questions about how certain legal issues at a firm were handled in the past.

Customers in the Microsoft 365 Copilot Early Access Program will gain access to new plug-ins from partners in the coming weeks, including Atlassian, Adobe, ServiceNow, Thomson Reuters, Moveworks and Mural. Bing Chat, meanwhile, will see new plug-ins added to its existing collection from Instacart, Kayak, Klarna, Redfin and Zillow, and those same Bing Chat plug-ins will come to Windows within Windows Copilot.

The OpenTable plug-in allows Bing Chat to search across restaurants for available bookings, for example, while the Instacart plug-in lets the chatbot take a dinner menu, turn it into a shopping list and place an order to get the ingredients delivered. Meanwhile, the new Bing plug-in brings web and search data from Bing into ChatGPT, complete with citations.

Story continues

Scott describes plug-ins as a bridge between an AI system, like ChatGPT, and data a third party wants to keep private or proprietary. A plug-in gives an AI system access to those private files, enabling it to, for example, answer a question about business-specific data.

There's certainly growing demand for such a bridge as privacy becomes a major issue with generative AI, which has a tendency to leak sensitive data, like phone numbers and email addresses, from the datasets on which it was trained. Looking to minimize risk, companies including Apple and Samsung have banned employees from using ChatGPT and similar AI tools over concerns employees might mishandle and leak confidential data to the system.

"What a plugin does is it says ‘Hey, we want to make that pattern reusable and set some boundaries about how it gets used," John Montgomery, CVP of AI platform at Microsoft, said in a canned statement.

There are three types of plug-ins within Microsoft's new framework: ChatGPT plug-ins, Microsoft Teams message extensions and Power Platform connectors.

Microsoft Copilot plugins

Image Credits: Microsoft

Teams message extensions, which allow users to interact with a web service through buttons and forms in Teams, aren't new. Nor are Power Platform connectors, which act as a wrapper around an API that allows the underlying service to "talk' to apps in Microsoft's Power Platform portfolio (e.g. Power Automate). But Microsoft's expanding their reach, letting developers tap new and existing message extensions and connectors to extend Microsoft 365 Copilot, the company's assistant feature for Microsoft 365 apps and services like Word, Excel and PowerPoint.

For instance, Power Platform connectors can be used to import structured data into the "Dataverse," Microsoft's service that stores and manages data used by internal business apps, that Microsoft 365 Copilot can then access. In a demo during Build, Microsoft showed how Dentsu, a public relations firm, tapped Microsoft 365 Copilot together with a plug-in for Jira and data from Atlassian’s Confluence without having to write new code.

Microsoft says that developers will be able to create and debug their own plug-ins in a number of ways, including through its Azure AI family of apps, which is adding capabilities to run and test plug-ins on private enterprise data. Azure OpenAI Service, Microsoft's managed, enterprise-focused product designed to give businesses access to OpenAI’s technologies with added governance features, will also support plug-ins. And Teams Toolkit for Visual Studio will gain features for piloting plug-ins.

As for how they'll be distributed, Microsoft says that developers will be able to configure, publish and manage plug-ins through the Developer Portal for Teams, among other places. They'll also be able to monetize them, although the company wasn't clear on how, exactly, pricing will work.

In any case, with plug-ins, Microsoft's playing for keeps in the highly competitive generative AI race. Plug-ins transform the company's "copilots" into aggregators, essentially -- putting them on a path to becoming one-stop shops for both enterprise and consumer customers.

Microsoft no doubt perceives the lock-in opportunity as increasingly key as the company faces competitive pressure from startups and tech giants alike building generative AI, including Google and Anthropic. One could imagine plug-ins becoming a lucrative new source of revenue down the line as apps and services rely more and more on generative AI. And it could allay the fears of businesses who claim generative AI trained on their data violates their rights; Getty Images and Reddit, among others, have taken steps to prevent companies from training generative AI on their data without some form of compensation.

I'd expect rivals to answer Microsoft's and OpenAI's plug-ins framework with plug-ins frameworks of their own. But Microsoft has a first-mover advantage, as OpenAI had with ChatGPT. And that can't be underestimated.