MicrosoftThis looks super complicated and doesn't convey the information I need to make our Azure OpenAI implementation a success. I'm having an issue because you split up nearly every piece of the solution across separate subscriptions. The management overhead is much more significant than it would be with a single subscription. And it doesn't make sense since we can expect a single team to implement a ChatGPT-like solution. Why would they make the separate subscriptions? If they didn't own the identity solution, it could be an individual subscription managed by a different team, but that's not what you're telling us here.
Another thing that bothers me is the inclusion of many Azure services. You don't need all that to run a ChatGPT solution. You can start with a lot less if you're willing to use public networking. If you want private networking, you still don't need much of what's in your reference architecture. For example, why not use an Azure Web App behind Azure Frontdoor integrated with a Virtual Network that connects the OpenAI service through a private endpoint? It's just as secure but much less expensive.
I would love to see this split up in a few diagrams and add a better explanation of why it makes sense to include the components that you're proposing:
- A networking diagram explaining how to set up networking so that I can keep the connection between my web app and OpenAI private.
- A logical diagram that explains the relationship between the web app, OpenAI, and possibly Azure Cognitive Search.
- A diagram that explains the authorization and authentication configuration.
I would skip everything around managing subscriptions, policies, etc. It's generic to Azure, and there are a lot of articles to explain how to set that up.
- A separate article to explain how to set up authentication from the web app to Azure AD with OpenID Connect
- A separate article to explain how to manage subscriptions in Azure.
- A separate article to explain how to set up cost management.
Sorry for the harsh feedback, but this sort of content from Microsoft bothers me a lot. I hope to see something a bit more refined soon.
Azure Landing Zones provide a solid foundation for your cloud environment. When deploying complex AI services such as Azure OpenAI, using a Landing Zone approach helps you manage your resources in a structured, consistent manner, ensuring governance, compliance, and security are properly maintained.
\n\n
In this article, we delve into the synergy of Azure Landing Zones and Azure OpenAI Service, building a secure and scalable AI environment. unpacking the Azure OpenAI Landing Zone architecture, which integrates numerous Azure services for optimal AI workloads. Furthermore we will also explore security measures and the significance of monitoring for operational success.
\n\n
Introduction to Azure OpenAI Service
\n\n
Azure OpenAI Service is a managed AI service that enables you to deploy and manage AI models based on OpenAI technologies such as GPT-4. This service is integrated with Azure Machine Learning, allowing you to build, train, and deploy AI models with the scalability, security, and efficiency of Azure. In addition, Azure OpenAI provides flexible pricing options, making it cost-effective for various use cases.
\nAzure OpenAI Service integrates seamlessly with other Azure services giving you the flexibility to build and deploy complex AI applications with ease.
\n\n
Reference Architecture
\n\n
\n
\n
The Azure OpenAI Landing Zone is a reference architecture that integrates a variety of services to create a seamless infrastructure for running OpenAI workloads.
\n\n
The Azure OpenAI Landing Zone integrates all these services to provide a secure and efficient environment for deploying and running OpenAI workloads. This architecture is designed to be scalable, resilient, and customizable to suit the unique needs of your applications.
\n\n
Network and Security
\n\n
Azure provides a robust set of networking and security features that can be used to secure your OpenAI workloads.
\n\n
\n
Monitoring Azure OpenAI Service
\n\n
When you have critical applications and business processes relying on Azure resources, you want to monitor those resources for their availability, performance, and operation.
\n\n
Azure OpenAI Service collects the same kinds of monitoring data as other Azure resources. Platform metrics and the Activity log are collected and stored automatically, but can be routed to other locations by using a diagnostic setting.
\n\n
Azure Monitor alerts proactively notify you when important conditions are found in your monitoring data. They allow you to identify and address issues in your system before your customers notice them. In the context of Azure Open AI you can proactively analyze and monitor metrics such as Blocked Calls, client errors and others.
\n\n
Conclusion
\n\n
In conclusion, this article offers a brief exploration of how Azure Landing Zones and Azure OpenAI Service work together, providing a strong foundation for creating secure and scalable AI applications. It digs deep into the details of the Azure OpenAI Landing Zone reference architecture, highlighting how it blends various Azure services to enhance and streamline OpenAI tasks.
\n\n
The discussion extends to key features of Azure's strong network and security offerings, including Azure Virtual Network, Private Link, and Network Security Groups. These elements play an essential role in protecting your OpenAI projects.
\n\n
Finally, the combination of Azure Landing Zones and Azure OpenAI Service offers a powerful toolkit, making it easier to build, deploy, and manage AI applications. With Azure Landing Zones, you can rest assured that your Azure OpenAI deployments are set up for success, fulfilling your needs for governance, compliance, and security.
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","introduction":"","coverImage":null,"coverImageProperties":{"__typename":"CoverImageProperties","style":"STANDARD","titlePosition":"BOTTOM","altText":""},"currentRevision":{"__ref":"Revision:revision:3882102_10"},"latestVersion":{"__typename":"FriendlyVersion","major":"3","minor":"0"},"metrics":{"__typename":"MessageMetrics","views":196303},"visibilityScope":"PUBLIC","canonicalUrl":null,"seoTitle":"Azure OpenAI Landing Zone reference architecture","seoDescription":"Explore how Azure Landing Zones and Azure OpenAI Service synergize to create robust, secure, and scalable AI applications. Understand the benefits of continuous monitoring and the evolving journey of deploying complex Azure services. Learn to fulfill your governance, compliance, and security needs with ease","placeholder":false,"originalMessageForPlaceholder":null,"contributors":{"__typename":"UserConnection","edges":[]},"nonCoAuthorContributors":{"__typename":"UserConnection","edges":[]},"coAuthors":{"__typename":"UserConnection","edges":[]},"blogMessagePolicies":{"__typename":"BlogMessagePolicies","canDoAuthoringActionsOnBlog":{"__typename":"PolicyResult","failureReason":{"__typename":"FailureReason","message":"error.lithium.policies.blog.action_can_do_authoring_action.accessDenied","key":"error.lithium.policies.blog.action_can_do_authoring_action.accessDenied","args":[]}}},"archivalData":null,"customFields":[],"body":"Azure Landing Zones provide a solid foundation for your cloud environment. When deploying complex AI services such as Azure OpenAI, using a Landing Zone approach helps you manage your resources in a structured, consistent manner, ensuring governance, compliance, and security are properly maintained.
\n\n
In this article, we delve into the synergy of Azure Landing Zones and Azure OpenAI Service, building a secure and scalable AI environment. unpacking the Azure OpenAI Landing Zone architecture, which integrates numerous Azure services for optimal AI workloads. Furthermore we will also explore security measures and the significance of monitoring for operational success.
\n\n
Introduction to Azure OpenAI Service
\n\n
Azure OpenAI Service is a managed AI service that enables you to deploy and manage AI models based on OpenAI technologies such as GPT-4. This service is integrated with Azure Machine Learning, allowing you to build, train, and deploy AI models with the scalability, security, and efficiency of Azure. In addition, Azure OpenAI provides flexible pricing options, making it cost-effective for various use cases.
\nAzure OpenAI Service integrates seamlessly with other Azure services giving you the flexibility to build and deploy complex AI applications with ease.
\n\n
Reference Architecture
\n\n
\n
\n
\n
The Azure OpenAI Landing Zone is a reference architecture that integrates a variety of services to create a seamless infrastructure for running OpenAI workloads.
\n\n
The Azure OpenAI Landing Zone integrates all these services to provide a secure and efficient environment for deploying and running OpenAI workloads. This architecture is designed to be scalable, resilient, and customizable to suit the unique needs of your applications.
\n\n
Network and Security
\n\n
Azure provides a robust set of networking and security features that can be used to secure your OpenAI workloads.
\n\n
\n
Monitoring Azure OpenAI Service
\n\n
When you have critical applications and business processes relying on Azure resources, you want to monitor those resources for their availability, performance, and operation.
\n\n
Azure OpenAI Service collects the same kinds of monitoring data as other Azure resources. Platform metrics and the Activity log are collected and stored automatically, but can be routed to other locations by using a diagnostic setting.
\n\n
Azure Monitor alerts proactively notify you when important conditions are found in your monitoring data. They allow you to identify and address issues in your system before your customers notice them. In the context of Azure Open AI you can proactively analyze and monitor metrics such as Blocked Calls, client errors and others.
\n\n
Conclusion
\n\n
In conclusion, this article offers a brief exploration of how Azure Landing Zones and Azure OpenAI Service work together, providing a strong foundation for creating secure and scalable AI applications. It digs deep into the details of the Azure OpenAI Landing Zone reference architecture, highlighting how it blends various Azure services to enhance and streamline OpenAI tasks.
\n\n
The discussion extends to key features of Azure's strong network and security offerings, including Azure Virtual Network, Private Link, and Network Security Groups. These elements play an essential role in protecting your OpenAI projects.
\n\n
Finally, the combination of Azure Landing Zones and Azure OpenAI Service offers a powerful toolkit, making it easier to build, deploy, and manage AI applications. With Azure Landing Zones, you can rest assured that your Azure OpenAI deployments are set up for success, fulfilling your needs for governance, compliance, and security.
","revisions({\"constraints\":{\"isPublished\":{\"eq\":true}},\"first\":1})":{"__typename":"RevisionConnection","totalCount":10}},"Conversation:conversation:3882102":{"__typename":"Conversation","id":"conversation:3882102","solved":false,"topic":{"__ref":"BlogTopicMessage:message:3882102"},"lastPostingActivityTime":"2024-08-08T04:49:03.632-07:00","lastPostTime":"2024-08-08T04:49:03.632-07:00","unreadReplyCount":19,"isSubscribed":false},"ModerationData:moderation_data:3882102":{"__typename":"ModerationData","id":"moderation_data:3882102","status":"APPROVED","rejectReason":null,"isReportedAbuse":false,"rejectUser":null,"rejectTime":null,"rejectActorType":null},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zODgyMTAyLTQ5NTE0Mmk2MTZCMjczN0MxMzI0RjBE?revision=10\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS0zODgyMTAyLTQ5NTE0Mmk2MTZCMjczN0MxMzI0RjBE?revision=10","title":"AIArchitecture.png","associationType":"BODY","width":4458,"height":2661,"altText":null},"Attachment:{\"id\":\"attachment:message3882102AttachmentNumber5\",\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/attachments/gxcuf89792/AzureArchitectureBlog/393/5/AzureLandingZoneOpenAIVisio1.1.zip\"}":{"__typename":"Attachment","id":"attachment:message3882102AttachmentNumber5","filename":"AzureLandingZoneOpenAIVisio1.1.zip","filesize":2785247,"contentType":"application/x-zip-compressed","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/attachments/gxcuf89792/AzureArchitectureBlog/393/5/AzureLandingZoneOpenAIVisio1.1.zip"},"Revision:revision:3882102_10":{"__typename":"Revision","id":"revision:3882102_10","lastEditTime":"2023-08-04T11:17:12.307-07:00"},"BlogReplyMessage:message:3923016":{"__typename":"BlogReplyMessage","id":"message:3923016","conversation":{"__ref":"Conversation:conversation:3882102"},"author":{"__ref":"User:user:2021810"},"revisionNum":1,"uid":3923016,"depth":1,"hasGivenKudo":false,"subscribed":false,"board":{"__ref":"Blog:board:AzureArchitectureBlog"},"subject":"Re: Azure OpenAI Landing Zone reference architecture","readOnly":false,"editFrozen":false,"moderationData":{"__ref":"ModerationData:moderation_data:3923016"},"parent":{"__ref":"BlogTopicMessage:message:3882102"},"body":"This looks super complicated and doesn't convey the information I need to make our Azure OpenAI implementation a success. I'm having an issue because you split up nearly every piece of the solution across separate subscriptions. The management overhead is much more significant than it would be with a single subscription. And it doesn't make sense since we can expect a single team to implement a ChatGPT-like solution. Why would they make the separate subscriptions? If they didn't own the identity solution, it could be an individual subscription managed by a different team, but that's not what you're telling us here.
Another thing that bothers me is the inclusion of many Azure services. You don't need all that to run a ChatGPT solution. You can start with a lot less if you're willing to use public networking. If you want private networking, you still don't need much of what's in your reference architecture. For example, why not use an Azure Web App behind Azure Frontdoor integrated with a Virtual Network that connects the OpenAI service through a private endpoint? It's just as secure but much less expensive.
I would love to see this split up in a few diagrams and add a better explanation of why it makes sense to include the components that you're proposing:
- A networking diagram explaining how to set up networking so that I can keep the connection between my web app and OpenAI private.
- A logical diagram that explains the relationship between the web app, OpenAI, and possibly Azure Cognitive Search.
- A diagram that explains the authorization and authentication configuration.
I would skip everything around managing subscriptions, policies, etc. It's generic to Azure, and there are a lot of articles to explain how to set that up.
- A separate article to explain how to set up authentication from the web app to Azure AD with OpenID Connect
- A separate article to explain how to manage subscriptions in Azure.
- A separate article to explain how to set up cost management.
Sorry for the harsh feedback, but this sort of content from Microsoft bothers me a lot. I hope to see something a bit more refined soon.
","body@stringLength":"2289","rawBody":"This looks super complicated and doesn't convey the information I need to make our Azure OpenAI implementation a success. I'm having an issue because you split up nearly every piece of the solution across separate subscriptions. The management overhead is much more significant than it would be with a single subscription. And it doesn't make sense since we can expect a single team to implement a ChatGPT-like solution. Why would they make the separate subscriptions? If they didn't own the identity solution, it could be an individual subscription managed by a different team, but that's not what you're telling us here.
Another thing that bothers me is the inclusion of many Azure services. You don't need all that to run a ChatGPT solution. You can start with a lot less if you're willing to use public networking. If you want private networking, you still don't need much of what's in your reference architecture. For example, why not use an Azure Web App behind Azure Frontdoor integrated with a Virtual Network that connects the OpenAI service through a private endpoint? It's just as secure but much less expensive.
I would love to see this split up in a few diagrams and add a better explanation of why it makes sense to include the components that you're proposing:
- A networking diagram explaining how to set up networking so that I can keep the connection between my web app and OpenAI private.
- A logical diagram that explains the relationship between the web app, OpenAI, and possibly Azure Cognitive Search.
- A diagram that explains the authorization and authentication configuration.
I would skip everything around managing subscriptions, policies, etc. It's generic to Azure, and there are a lot of articles to explain how to set that up.
- A separate article to explain how to set up authentication from the web app to Azure AD with OpenID Connect
- A separate article to explain how to manage subscriptions in Azure.
- A separate article to explain how to set up cost management.
Sorry for the harsh feedback, but this sort of content from Microsoft bothers me a lot. I hope to see something a bit more refined soon.
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