Customers have been using Azure Stack in a number of different ways. We continue to see Azure Stack used in connected and disconnected scenarios as a platform for building applications to deploy both on-premises as well as in Azure.
Quelle: Azure
At Microsoft Build 2019, we announced the general availability of Azure Shared Image Gallery, making it easier to manage, share, and globally distribute custom virtual machine (VM) images in Azure.
Shared Image Gallery provides a simple way to share your applications with others in your organization, within or across Azure Active Directory (AD) tenants and regions. This enables you to expedite regional expansion or DevOps processes and simplify your cross-region HA/DR setup.
Shared Image Gallery also supports larger deployments. You can now deploy up to a 1,000 virtual machine instances in a scale set, up from 600 with managed images.
Here is what one of our customers had to say about the feature:
“Shared Image Gallery enables us to build all our VM images from a single Azure DevOps pipeline and to deploy IaaS VMs from these images in any subscription in any tenant in any region, without the added complexity of managing and distributing copies of managed images or VHDs across multiple subscriptions or regions.”
– Stanley Merkx, an Infrastructure Engineer at VIVAT, a Netherlands based insurance company
Regional availability
Shared Image Gallery now supports all Azure public cloud regions as target regions and all generally available Azure public cloud regions, with the exception of South Africa regions as a source region. Check the list of source and target regions.
In the coming months, this feature will also be available in sovereign clouds.
Quota
The default quota that is supported on Shared Image Gallery resources include:
100 shared image galleries per subscription per region
1,000 image definitions per subscription per region
10,000 image versions per subscription per region
Users can request for a higher quota based on their requirements. Learn how you can track usage in your subscription.
Pricing
There is no extra charge for using the Shared Image Gallery service. You will only pay for the following:
Storage charges for image versions and replicas in each region, source and target
Network egress charges for replication across regions
Getting started
CLI
PowerShell
Azure portal
API
Quickstart templates
.NET
Java
Let’s take a quick look at what you can do with Shared Image Gallery.
Manage your images better
We introduced three new Azure Resource Manager resources as part of the feature—gallery, image definition, and image version—which helps you organize images in logical groups. You can also publish multiple versions of your images as and when you update or patch the applications.
Share images across subscriptions and Azure Active Directory tenants
One of the key capabilities that Shared Image Gallery provides is a way to share your images across subscriptions. Since all three newly introduced constructs are Azure Resource Manager resources, you can use Azure role-based access control (RBAC) to share your galleries or image definitions with other users who can then deploy VMs in their subscriptions, even across Azure Active Directory tenants.
A few common scenarios where sharing images across tenants becomes useful are:
A company acquires another and suddenly the Azure infrastructure is spread across Azure AD tenants.
A company with multiple subsidiaries that use Azure is likely to have multiple Azure AD tenants.
Learn more about how to share your images across tenants.
Distribute your images globally
We understand that business happens at a global scale and you don’t want your organization to be limited by the platform. Shared Image Gallery provides a way to globally distribute your images based on your organizational needs. You only need to specify the target regions and Shared Image Gallery will replicate your image versions to the regions specified.
Scale your deployments
With Shared Image Gallery, you can now deploy up to a 1,000 VM instances in a VM scale set, an increase from 600 with managed images. We also introduced a concept of image replicas for better deployment performance, reliability, and consistency. You can set a different replica count in each target region based on your regional scale needs. Since each replica is a deep copy of your image, you can scale your deployments linearly with each extra replica versus a managed image.
Learn more about how to use replicas.
Make your images highly available
With the general availability of Shared Image Gallery, you can choose to store your images in zone-redundant storage (ZRS) accounts in regions with Availability Zones. You can also choose to specify storage account type for each of the target regions. Check the regional availability of zone-redundant storage.
Quelle: Azure
Data scientists have a dynamic role. They need environments that are fast and flexible while upholding their organization’s security and compliance policies. Notebook Virtual Machine (VM), announced in May 2019, resolves these conflicting requirements while simplifying the overall experience for data scientists.
Quelle: Azure
We continue to expand the Azure Marketplace ecosystem. For this volume, 121 new offers successfully met the onboarding criteria and went live.
Quelle: Azure
With many IoT solutions connecting thousands of hardware endpoints, fixing security issues or upgrading functionality becomes a challenging and expensive task. The ability to update devices is critical for any IoT solution since it ensures that your organization can respond rapidly to security vulnerabilities by deploying fixes. Azure IoT Hub provides many capabilities to enable developers to build device management processes into their solutions, such as device twins for synchronizing device configuration, and automatic device management to deploy configuration changes across large device fleet. We have previously blogged about how these features have been used to implement IoT device firmware updates.
Some customers have told us they need a turn-key IoT device update manager, so we are pleased to share a collaboration with Mender to showcase how IoT devices connected to Azure can be remotely updated and monitored using Mender open source update manager. Mender provides robust over-the-air (OTA) update management via full image updates and dual A/B partitioning with roll-back, managed and monitored through a web-based management UI. Customers can use Mender for updating Linux images that are built with Yocto. By integrating with Azure IoT Hub Device Provisioning Service, IoT device identity credentials can be shared between Mender and IoT Hub which is accomplished using a custom allocation policy and an Azure Function. As a result, operators can monitor IoT device states and analytics through their solution built with Azure IoT Hub, and then assign and deploy updates to those devices in Mender because they share device identities.
Recently, Mender’s CTO Eystein Stenberg came on the IoT Show to show how it works:
Keeping devices updated and secure is important for any IoT solution, and Mender now provides a great new option for Azure customers to implement OTA updates.
Additional resources
• See Mender’s blog post on how to integrate IoT Hub Device Provisioning Service with Mender
• Learn more about automatic device management in IoT Hub
Quelle: Azure
There is a lot more data in the world than can possibly be captured with even the most robust, cutting-edge technology. Edge computing and the Internet of Things (IoT) are just two examples of technologies increasing the volume of useful data. There is so much data being created that the current telecom infrastructure will struggle to transport it and even the cloud may become strained to store it. Despite the advent of 5G in telecom, and the rapid growth of cloud storage, data growth will continue to outpace the capacities of both infrastructures. One solution is to build stateful, data-driven applications with technology from SWIM.AI.
The Azure platform offers a wealth of services for partners to enhance, extend, and build industry solutions. Here we describe how one Microsoft partner uses Azure to solve a unique problem.
Shared awareness and communications
The increase in volume has other consequences, especially when IoT devices must be aware of each other and communicate shared information. Peer-to-peer (P2P) communications between IoT assets can overwhelm a network and impair performance. Smart grids are an example of how sensors or electric meters are networked across a distribution grid to improve the overall reliability and cost of delivering electricity. Using meters to determine the locality of issues can help improve service to a residence, neighborhood, municipality, sector, or region. The notion of shared awareness extends to vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. As networked AI spreads to more cars and devices, so do the benefits of knowing the performance or status of other assets. Other use cases include:
Traffic lights that react to the flow of vehicles across a neighborhood.
Process manufacturing equipment that can determine the impact from previous process steps.
Upstream oil/gas equipment performance that reacts to downstream oil/gas sensor validation.
Problem: Excess data means data loss
When dealing with large volumes of data, enterprises often struggle to determine which data to retain, how much to retain, and for how long they must retain it. By default, they may not retain any of it. Or, they may sub-sample data and retain an incomplete data set. That lost data may potentially contain high value insights. For example, consider traffic information that could be used for efficient vehicle routing, commuter safety, insurance analysis, and government infrastructure reviews. The city of Las Vegas maintains over 1,100 traffic light intersections that can generate more than 45TB of data every day. As stated before, IoT data will challenge our ability to transport and store data at these volumes.
Data may also become excessive when it’s aggregated. For example, telecom and network equipment typically create snapshots of data and send it every 15 minutes. By normalizing this data into a summary over time, you lose granularity. This means the nature or pattern of data over time along with any unique, intuitive events would be missed. The same applies to any equipment capturing fixed-time, window summary data. The loss of data is detrimental to networks where devices share data, either for awareness or communication. The problem is also compounded, as only snapshots are captured and aggregated for an entire network of thousands or millions of devices. Real-time is the goal.
Real-time is the goal
Near real-time is the current standard for stateless application architectures, but “near” real-time is not fast enough anymore. Real-time processing or processing within milliseconds is the new standard for V2V or V2I communications and requires a much more performant architecture. Swim does this by leveraging stateful API’s. With stateful connections, it’s possible to have a rapid response between peers in a network. Speed has enormous effects on efficiency and reliability and it’s essential for systems where safety is paramount such as preventing crashes. Autonomous systems will rely on real-time performance for safety purposes.
An intelligent edge data strategy
SWIM.AI delivers a solution for building scalable streaming applications. According to their site Meet Swim:
“Instead of configuring a separate message broker, app server and database, Swim provides for its own persistence, messaging, scheduling, clustering, replication, introspection, and security. Because everything is integrated, Swim seamlessly scales across edge, cloud, and client, for a fraction of the infrastructure and development cost of traditional cloud application architectures.”
The figure below shows an abstract view of how Swim can simplify IoT architectures:
Harvest data in mid-stream
SWIM.AI uses the lightweight Swim platform, only generating a 2MB footprint to compute and stream IoT insights, building what they call “data-driven applications.” These applications sit in the data stream and generate unique, intelligent web agents for each data source it sees. These intelligent web agents then process the raw data as it streams, only publishing state changes from the data stream. This streamed data can be used by other web agents or stored in a data lake, such as Azure.
Swim uses the “needle in a haystack” metaphor to explain this unique advantage. Swim allows you to apply a metal detector while harvesting the grain to find the needle, without having to bail, transport, or store the grain before searching for the needle. The advantage is in continuously processing data, where intelligent web agents can learn over time or be influenced by domain experts that set thresholds.
Because of the stateful architecture of Swim, only the minimum data necessary is transmitted over the network. Furthermore, application services need not wait for the cloud to establish application context. This results in extremely low latencies, as the stateful connections don’t incur the latency cost of reading and writing to a database or updating based on poll requests.
On SWIM.AI’s website, a Smart City application shows the real-time status of lights and traffic across a hundred intersections with thousands of sensors. The client using the app could be a connected or an autonomous car approaching the intersection. It could be a handheld device next to the intersection, or a browser a thousand miles away in the contiguous US. The latency to real-time is 75-150ms, less than the blink of an eye across the internet.
Benefits
The immediate benefit is saving costs for transporting and storing data.
Through Swim’s technology, you can retain the granularity. For example, take the case of 10 seconds of TB per day generated from every 1000 traffic light intersections. Winnow that data down to 100 seconds of GB per day. But the harvested dataset fully describes the original raw dataset.
Create efficient networked apps for various data sources. For example, achieve peer-to-peer awareness and communications between assets such as vehicles, devices, sensors, and other data sources across the internet.
Achieve ultra-low latencies in the 75-150 millisecond range. This is the key to creating apps that depend on data for awareness and communications.
Azure services used in the solution
The demonstration of DataFabric from SWIM.AI relies on core Azure services for security, provisioning, management, and storage. DataFabric also uses the Common Data Model to simplify sharing information with other systems, such as Power BI or PowerApps, in Azure. Azure technology enables the customer’s analytics to be integrated with events and native ML and cognitive services.
DataFabric is based on the Microsoft IoT reference architecture and uses the following core components:
IoT Hub: Provides a central point in the cloud to manage devices and their data.
IoT Edge Field gateway: An on-premises solution for delivering cloud intelligence.
Azure Event Hubs: Ingests millions of events per second.
Azure Blob: Efficient storage that includes options for hot, warm and archived data.
Azure Data Lake storage: A highly scalable and cost-effective data lake solution for big data analytics.
Azure Streaming Analytics: For transforming data into actionable insights and predictions in near real-time.
Next steps
To learn more about other industry solutions, go to the Azure for Manufacturing page.
To find out more about this solution, go to DataFabric for Azure IoT and select Get it now.
Quelle: Azure
News and updates
Microsoft hosts HL7 FHIR DevDays
One of the largest gatherings of healthcare IT developers will come together on the Microsoft campus June 10-12 for HL7 FHIR DevDays, with the goal of advancing the open standard for interoperable health data, called HL7® FHIR® (Fast Healthcare Interoperability Resources, pronounced “fire”). Microsoft is thrilled to host this important conference, and engage with the developer community on everything from identifying immediate use cases to finding ways for all of us to hack together in ways that help advance the FHIR specification.
Announcing self-serve experience for Azure Event Hubs Clusters
For businesses today, data is indispensable. Innovative ideas in manufacturing, health care, transportation, and financial industries are often the result of capturing and correlating data from multiple sources. Now more than ever, the ability to reliably ingest and respond to large volumes of data in real time is the key to gaining competitive advantage for consumer and commercial businesses alike. To meet these big data challenges, Azure Event Hubs offers a fully managed and massively scalable distributed streaming platform designed for a plethora of use cases from telemetry processing to fraud detection.
A look at Azure's automated machine learning capabilities
The automated machine learning capability in Azure Machine Learning service allows data scientists, analysts, and developers to build machine learning models with high scalability, efficiency, and productivity all while sustaining model quality. With the announcement of automated machine learning in Azure Machine Learning service as generally available last December, we have started the journey to simplify artificial intelligence (AI). We are furthering our investment for accelerating productivity with a new release that includes exciting capabilities and features in the areas of model quality, improved model transparency, the latest integrations, ONNX support, a code-free user interface, time series forecasting, and product integrations.
Technical content
Securing the hybrid cloud with Azure Security Center and Azure Sentinel
Infrastructure security is top of mind for organizations managing workloads on-premises, in the cloud, or hybrid. Keeping on top of an ever-changing security landscape presents a major challenge. Fortunately, the power and scale of the public cloud has unlocked powerful new capabilities for helping security operations stay ahead of the changing threat landscape. Microsoft has developed a number of popular cloud based security technologies that continue to evolve as we gather input from customers. This post breaks down a few key Azure security capabilities and explain how they work together to provide layers of protection.
Customize your automatic update settings for Azure Virtual Machine disaster recovery
In today’s cloud-driven world, employees are only allowed access to data that is absolutely necessary for them to effectively perform their job. The ability to hence control access but still be able to perform job duties aligning to the infrastructure administrator profile is becoming more relevant and frequently requested by customers. When we released the automatic update of agents used in disaster recovery (DR) of Azure Virtual Machines (VMs), the most frequent feedback we received was related to access control. The request we heard from you was to allow customers to provide an existing automation account, approved and created by a person who is entrusted with the right access in the subscription. You asked, and we listened!
Azure Stack IaaS – part nine
Before we built Azure Stack, our program manager team called a lot of customers who were struggling to create a private cloud out of their virtualization infrastructure. We were surprised to learn that the few that managed to overcome the technical and political challenges of getting one set up had trouble getting their business units and developers to use it. It turns out they created what we now call a snowflake cloud, a cloud unique to just their organization. This is one of the main problems we were looking to solve with Azure Stack. A local cloud that has not only automated deployment and operations, but also is consistent with Azure so that developers and business units can tap into the ecosystem. In this blog we cover the different ways you can tap into the Azure ecosystem to get the most value out of IaaS.
What is the difference between Azure Application Gateway, Load Balancer, Front Door and Firewall?
Last week at a conference in Toronto, an attendee came to the Microsoft booth and asked something that has been asked many times in the past. So, this blog post covers all of it here for everyone’s benefit. What are the differences between Azure Firewall, Azure Application Gateway, Azure Load Balancer, Network Security Groups, Azure Traffic Manager, and Azure Front Door? This blog offers a high-level consolidation of what they each do.
Azure shows
Five tools for building APIs with GraphQL | Five Things
Burke and Chris are back and this week they're bringing you five tools for building API's with GraphQL. True story, they shot this at the end of about a twelve hour day and you can see the pain in Burke's eyes. It's not GraphQL he doesn't like, it's filming for six straight hours. Also, Chris picks whistles over bells (because of course he does) and Burke fights to stay awake for four minutes.
Microservices and more in .NET Core 3.0 | On .NET
Enabling developers to build resilient microservices is an important goal for .NET Core 3.0. In this episode, Shayne Boyer is joined by Glenn Condron and Ryan Nowak from the ASP.NET team who discuss some of the exciting work that's happening in the microservice space for .NET Core 3.0.
Interknowlogy mixes Azure IoT and mixed reality | The Internet of Things Show
When mixed reality meets the Internet of Things through Azure Digital Twins, a new way of accessing data materializes. See how Interknowlogy mixes Azure IoT and Mixed Reality to deliver not only stunning experiences but also accrued efficiency and productivity to workforce.
Bring DevOps to your open-source projects: Top three tips for maintainers | The Open Source Show
Baruch Sadogurksy, Head of Developer Relations at JFrog, and Aaron Schlesinger, Cloud Advocate at Microsoft and Project Athens Maintainer, talk about the art of DevOps for Open Source. Balancing contributor needs with the core DevOps principles of people, process, and tools. You'll learn how to future-proof your projects, avoid the dreaded Bus Factor, and get Aaron and Baruch's advice for evaluating and selecting tools, soliciting contributor input and voting, documenting processes, and so much more.
Episode 282 – Azure Front Door Service | The Azure Podcast
Cynthia talks with Sharad Agrawal on what Azure Front Door Service is, how to choose between Azure Front Door Service, CDN, Azure Traffic Manager and App Gateway, and how to get started.
HTML5 audio not supported
Atley Hunter on the Business of App Development | Azure DevOps Podcast
In this episode, Jeffrey and Atley are discussing the business of app development. Atley describes some of the first apps he’s ever developed, some of the most successful and popular apps he’s ever created, how he’s gone about creating these apps, and gives his tips for other developers in the space.
Industries and partners
Empowering clinicians with mobile health data: Right information, right place, right time
Improving patient outcomes and reducing healthcare costs depends on healthcare providers such as doctors, nurses, and specialized clinician ability to access a wide range of data at the point of patient care in the form of health records, lab results, and protocols. Tactuum, a Microsoft partner, provides the Quris solution that empowers clinicians with access to the right information, the right place, at the right time, enabling them to do their jobs efficiently and with less room for error.
Building a better asset and risk management platform with elastic Azure services
Elasticity means services can expand and contract on demand. This means Azure customers who are on a pay-as-you-go plan will reap the most benefit out of Azure services. Their service is always available, but the cost is kept to a minimum. Together with elasticity, Azure lets modern enterprises migrate and evolve more easily. For financial service providers, the modular approach lets customers benefit from best-of-breed analytics in three key areas. Read the post to learn what they are.
Symantec’s zero-downtime migration to Azure Cosmos DB
How do you migrate live, mission-critical data for a flagship product that must manage billions of requests with low latency and no downtime? The consumer business unit at Symantec faced this exact challenge when deciding to shift from their costly and complex self-managed database infrastructure, to a geographically dispersed and low latency managed database solution on Azure. The Symantec team shared their business requirements and decision to adopt Azure Cosmos DB in a recent case study.
Quelle: Azure
Mobility has become the center of an array of new technologies running the gamut from cloud-based algorithms and ride-sharing services, to edge cognition, assisted driving, and traffic pattern analysis – all in an effort to move people and things from one location to another more efficiently.
Quelle: Azure
This blog post was co-authored by Greg Moore, Corporate Vice President, Microsoft Healthcare and Peter Lee, Corporate Vice President, Microsoft Healthcare.
One of the largest gatherings of healthcare IT developers will come together on the Microsoft campus next week for HL7 FHIR DevDays, with the goal of advancing the open standard for interoperable health data, called HL7® FHIR® (Fast Healthcare Interoperability Resources, pronounced “fire”). Microsoft is thrilled to host this important conference on June 10-12, 2019 on our Redmond campus, and engage with the developer community on everything from identifying immediate use cases to finding ways for all of us to hack together in ways that help advance the FHIR specification.
We believe that FHIR will be an incredibly important piece of the healthcare future. Its modern design enables a new generation of AI-powered applications and services, and it provides an extensible, standardized format that makes it possible for all health IT systems to not only share data so that it can get to the right people where and when they need it, but also turn that data into knowledge. While real work has been underway for many years on HL7 FHIR, today it has become one of the most critical technologies in health data management, leading to major shifts in both the technology and policy of healthcare.
Given the accelerating shift of healthcare to the cloud, FHIR in the cloud presents a potentially historic opportunity to advance health data interoperability. For this reason, last summer in Washington, DC, we stood with leaders from AWS, Google, IBM, Oracle, and Salesforce to make a joint pledge to adopt technologies that promote the interoperability of health data. But we all know that FHIR is not magic. To make the liberation of health data a reality, developers and other stakeholders will need to work together, and so this is why community events like HL7 FHIR DevDays are so important. They allow us to try out new ideas in code and discuss a variety of areas, from the basics of FHIR, to its use with medical devices, imaging, research, security, privacy, and patient empowerment.
The summer of 2019 may indeed be the coming of age for FHIR, with the new version of the standard called “FHIR release 4” (R4) reaching broader adoption, new product updates from Microsoft, and new interop policies from the US government that will encourage the industry to adopt FHIR more broadly.
New FHIR standard progressing quickly
Healthcare developers can start building with greater confidence that FHIR R4 will help connect people, data, and systems. R4 is the first version to be “normative,” which means that it’s an official part of the future specification so that all future versions will be backward compatible.
Microsoft adding more FHIR functionality to Azure
Microsoft is doing its part to realize benefits of health data interop with FHIR, and today we’re announcing that our open source FHIR Server for Azure will support FHIR R4 and is available today.
We have added a new data persistence provider implementation to the open source FHIR Server for Azure. The new SQL persistence provider enables developers to configure their FHIR server instance to use either an Azure Cosmos DB backed persistence layer, or a persistence layer using a SQL database, such as Azure SQL Database. This will make it easier for customers to manage their healthcare applications by adding more capabilities for their preferred SQL provider. It will extend the capability of a FHIR server in Azure to support key business workloads with new features such as chained queries and transactions.
Growing ecosystem of customers and partners
Our Azure API for FHIR already has a broad partner ecosystem in place and customers using the preview service to centralize disparate data.
Northwell Health, the largest employer in New York state with 23 hospitals and 700 practices, is using the Azure API for FHIR to build interoperability into its data flow solution to reduce excess days for patients. This ensures the patient only stays for the period that is required for clinical care and there are no other non-clinical reasons are occurring for delays in discharging the patient.
Our open source implementation of FHIR Server for Azure is already creating a tighter feedback loop with developers and partners for our products who have quickly innovated on top of this open source project.
Darena Solutions used the open source FHIR Server for Azure to develop its Blue Button application with a content management system (CMS) called BlueButtonPRO. This will allow patients to import their data from CMS (through Blue Button). More importantly, it allows patients a simple and secure way to download, view, manage, and share healthcare data from any FHIR portals that they have access to.
US Health IT Policy proposal to adopt FHIR
The DevDays conference also comes on the heels of the US government’s proposed ruling to improve interoperability of health data embodied in the 21st Century Cures Act, which includes the use of FHIR.
Microsoft supports the focus in these proposed rules on reducing barriers to interoperability because we are confident that the result will be good for patients. Interoperability and the seamless flow of health data will enable a more informed and empowered consumer. We expect the health industry will respond with greater efficiency, better care, and cost savings.
We're at a pivotal moment for health interoperability, where all the bottom-up development in the FHIR community is meeting top-down policy decision at the federal level.
Health data interoperability at Microsoft
Integrating health data into our platforms is a huge commitment for Microsoft, and Azure with FHIR is just the start. Now that FHIR is baked into the core of Azure, the Microsoft cloud will natively speak FHIR as the language for health data as we plan for all our services to inherit that ability.
Healthcare today and into the future will demand a broad perspective and creative, collaborative problem-solving. Looking ahead, Microsoft intends to continue an open, collaborative dialogue with the industry and community, from FHIR DevDays to the hallways of our customers and partners.
FHIR is a part of our healthcare future, and FHIR DevDays is a great place to start designing for that future.
Quelle: Azure
Without the right tools and approach, cloud optimization can be a time-consuming and difficult process. There is an ever growing list of best practices to follow, and it’s constantly in flux as your cloud workloads evolve. Add the challenges and emergencies you face on a day-to-day basis, and it’s easy to understand why it’s hard to be proactive about ensuring your cloud resources are running optimally.
Azure offers many ways to help ensure that you’re running your workloads optimally and getting the most out of your investment.
Three kinds of optimization: organizational, architectural, and tactical
One way to think about these is the altitude of advice and optimization offered: organizational, architectural, or tactical.
At the tactical or resource level, you have Azure Advisor, a free Azure service that helps you optimize your Azure resources for high availability, security, performance, and cost. Advisor scans your resource usage and configuration and provides over 100 personalized recommendations. Each recommendation includes inline actions to make remediating your cloud resource optimizations fast and easy.
At the other end of the spectrum is Azure Architecture Center, a collection of free guides created by Azure experts to help you understand organizational and architectural best practices and optimize your workloads. This guidance is especially useful when you’re designing a new workload for the cloud or migrating an existing workload from on-premises to the cloud.
The guides in the Azure Architecture Center range from the Microsoft Cloud Adoption Framework for Azure, which can help guide your organization’s approach to cloud adoption and strategy, to Azure Reference Architectures, which provides recommended architectures and practices for common scenarios like AI, IoT, microservices, serverless, SAP, web apps, and more.
Start small, gain momentum
There are many ways to get started optimizing your Azure environment. You can align as an organization on your cloud adoption strategy, you can review your workload architecture against the reference architectures we provide, or you can open up Advisor and see which of your resources have best practice recommendations. Those are just a few examples, ultimately it’s a choice only you and your organization can make.
If your organization is like most, it helps to start small and gain momentum. We’ve seen many customers have success kicking off their optimization journey at the tactical or resource level, then the workload level, and ultimately working their way up to the organizational level, where you can consolidate what you’ve learned and implement policy.
Get started with Azure Advisor
When you visit Advisor, you’ll likely find many recommended actions you can take to optimize your environment. Our advice? Don’t get overwhelmed. Just get started. Scan the recommendations for opportunities that are the most meaningful to you and your organization. For some, that might be high availability considerations like VM backup, a common oversight in VM creation, especially when making the transition from dev/test to production. For others, it might be finding cost savings by looking at VMs that are being underutilized.
Once you’ve found a suitable recommendation, go ahead and remediate it as shown in this video. Optimization is an ongoing process and never really finished, but every step you take is a step in the right direction.
Visit Advisor in the Azure portal to get started reviewing and remediating your recommendations. For more in-depth guidance, visit the Azure Advisor documentation. Let us know if you have a suggestion for Advisor by submitting an idea in our feedback tool here.
Quelle: Azure
