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Azure Stream Analytics now supports MATCH_RECOGNIZE

MATCH_RECOGNIZE in Azure Stream Analytics significantly reduces the complexity and cost associated with building, modifying, and maintaining queries that match sequence of events for alerts or further data computation.

What is Azure Stream Analytics?

Azure Stream Analytics is a fully managed serverless PaaS offering on Azure that enables customers to analyze and process fast moving streams of data and deliver real-time insights for mission critical scenarios. Developers can use a simple SQL language, extensible to include custom code, in order to author and deploy powerful analytics processing logic that can scale-up and scale-out to deliver insights with milli-second latencies.

Traditional way to incorporate pattern matching in stream processing

Many customers use Azure Stream Analytics to continuously monitor massive amounts of data, detecting sequence of events and deriving alerts or aggregating data from those events. This in essence is pattern matching.

For pattern matching, customers traditionally relied on multiple joins, each one detecting a single event in particular. These joins are combined to find a sequence of events, compute results or create alerts. Developing queries for pattern matching is a complex process and very error prone, difficult to maintain and debug. Also, there are limitations when trying to express more complex patterns like Kleene Stars, Kleene Plus, or Wild Cards.

To address these issues and improve customer experience, Azure Stream Analytics provides a MATCH_RECOGNIZE clause to define patterns and compute values from the matched events. MATCH_RECOGNIZE clause increases user productivity as it is easy to read, write and maintain.

Typical scenario for MATCH_RECOGNIZE

Event matching is an important aspect of data stream processing. The ability to express and search for patterns in a data stream enable users to create simple yet powerful algorithms that can trigger alerts or compute values when a specific sequence of events is found.

An example scenario would be a food preparing facility with multiple cookers, each with its own temperature monitor. A shut down operation for a specific cooker need to be generated in case its temperature doubles within five minutes. In this case, the cooker must be shut down as temperature is increasing too rapidly and could either burn the food or cause a fire hazard.

Query
SELECT * INTO ShutDown from Temperature
MATCH_RECOGNIZE (
LIMIT DURATION (minute, 5)
PARTITON BY cookerId
AFTER MATCH SKIP TO NEXT ROW
MEASURES
1 AS shouldShutDown
PATTERN (temperature1 temperature2)
DEFINE
temperature1 AS temperature1.temp > 0,
temperature2 AS temperature2.temp > 2 * MAX(temperature1.temp)
) AS T

In the example above, MATCH_RECOGNIZE defines a limit duration of five minutes, the measures to output when a match is found, the pattern to match and lastly how each pattern variable is defined. Once a match is found, an event containing the MEASURES values will be output into ShutDown. This match is partitioned over all the cookers by cookerId and are evaluated independently from one another.

MATCH_RECOGNIZE brings an easier way to express patterns matching, decreases the time spent on writing and maintaining pattern matching queries and enable richer scenarios that were practically impossible to write or debug before.

Get started with Azure Stream Analytics

Azure Stream Analytics enables the processing of fast-moving streams of data from IoT devices, applications, clickstreams, and other data streams in real-time. To get started, refer to the Azure Stream Analytics documentation.
Quelle: Azure

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Overcoming language difficulties with AI and Azure services

Ever hear the Abbot and Costello routine, “Who’s on first?” It’s a masterpiece of American English humor. But what if it we translated it into another language? With a word-by-word translation, most of what English speakers laugh at, would be lost. Such is the problem of machine translation (translation by computer algorithm.) If a business depends on words to have an impact on the user, then translation services need to be seriously evaluated for accuracy and effect. This is how Lionbridge approaches the entire world of language translation—but now they can harness the capabilities of artificial intelligence (AI). The result is to ensure the translations reach a higher bar.

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.

Efficient partners for communication in life sciences

For those who deal in healthcare or life sciences, language should not be a barrier to finding the right information. The world of research and reporting is not limited to a few human languages. Life science organizations need to be able to find data from anywhere in the world. And for that, a translation service is needed that preserves not just the facts, but the effect of the original data. This is the goal of Lionbridge, a Microsoft partner dedicated to efficient translation.

In addition to localization, Lionbridge also serves as a guard against other dangers related to document handling. For example, there may be insufficient information provided to get a patient’s informed consent. Or a patient’s data can be disclosed by mistake. The penalties for any privacy violations can be steep. Having a third party whose sole business is to govern the documentation provides additional security against data mishandling.

The company can’t do this work on its own. It stresses a collaborative partnership approach to achieve the results needed. That begins with having fluency with human languages as well as with the technical domains. From their literature:

“Our team partners with yours to turn sensitive, complex, and frequently-changing content into words that resonate with every end user—from regulatory boards to care providers to patients—around the world. Our clients include pharmaceutical, medical device, medical publishing, and healthcare companies as well as Contract Research Organizations (CROs). Each demands strict attention to detail, expert understanding of nuanced requirements, and the utmost care for the end user.”

It comes as no surprise that Lionbridge depends on a host of skilled, professional translators—10,000 translators across 350 languages.

Specialized solutions

Due to the highly specialized service needs, the company operates as a consultant. After a meeting and evaluation of existing documentation and workflows, they will deliver a new workflow that includes technical services built on Azure. The company also creates a secure document exchange portal for managing translation into 350+ languages. The portal integrates with advanced workflow automation and AI powered translation. This advanced language technology enables far greater speed and volumes to be translated with increasing efficiency, opening up new languages, markets, and constituents for customers.

Lionbridge’s portal and translation management system have the appropriate controls in place in order to support a HIPAA-compliant workflow and are supported by globally distributed “Centers of Excellence.” The staff of the centers ensure adherence to ISO standards and are trained in supporting sensitive content, including personal health information (PHI).

The graphic shows the processes that are involved in creating a translation project. The project must first be defined. The project is then handed off to Lionbridge through their “Freeway Platform.” From there, it undergoes the translation process, with quality checks. The customer can see progress and results at a dashboard until the project is deemed complete.

Azure services used in solution

Azure App Service is used as a compute resource to host applications and is valued for its automated scaling and proactive monitoring.
Azure SQL Database is appreciated for its automated backup, geo-replication, and failover features.
Azure Service Fabric supports the need for a microservices oriented platform.
Azure Storage (mostly blobs) is used in many applications, including for CDN purposes to allow users to access application content in many parts of the words with high speed.
Azure Cognitive Services is used by some applications to provide AI capabilities.

Next steps

To find out more, go to the Lionbridge offering on the Azure Marketplace and click Contact me.

To learn more about other healthcare solutions, go to the Azure for health page.
Quelle: Azure

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Introducing NVv4 Azure Virtual Machines for GPU visualization workloads

Azure offers a wide variety of virtual machine (VM) sizes tailored to meet diverse customer needs. Our NV size family has been optimized for GPU-powered visualization workloads, such as CAD, gaming, and simulation. Today, our customers are using these VMs to power remote visualization services and virtual desktops in the cloud. While our existing NV size VMs work great to run graphics heavy visualization workloads, a common piece of feedback we receive from our customers is that for entry-level desktops in the cloud, only a fraction of the GPU resources is needed. Currently, the smallest sized GPU VM comes with one full GPU and more vCPU/RAM than a knowledge worker desktop requires in the cloud. For some customers, this is not a cost-effective configuration for entry-level scenarios.

Announcing NVv4 Azure Virtual Machines based on AMD EPYC 7002 processors and virtualized Radeon MI25 GPU.

The new NVv4 virtual machine series will be available for preview in the fall. NVv4 offers unprecedented GPU resourcing flexibility, giving customers more choice than ever before. Customers can select from VMs with a whole GPU all the way down to 1/8th of a GPU. This makes entry-level and low-intensity GPU workloads more cost-effective than ever before, while still giving customers the option to scale up to powerful full-GPU processing power.

NVv4 Virtual Machines support up to 32 vCPUs, 112GB of RAM, and 16 GB of GPU memory.

 

Size
vCPU
Memory
GPU memory
Azure network

Standard_NV4as_v4
4
14 GB
2 GB
50 Gbps

Standard_NV8as_v4
8
28 GB
4 GB
50 Gbps

Standard_NV16as_v4
16
56 GB
8 GB
50 Gbps

Standard_NV32as_v4
32
112 GB
16 GB
50 Gbps

With our hardware-based GPU virtualization solution built on top of AMD MxGPU and industry standard SR-IOV technology, customers can securely run workloads on virtual GPUs with dedicated GPU frame buffer. The new NVv4 Virtual Machines will also support Azure Premium SSD disks. NVv4 will have simultaneous multithreading (SMT) enabled for applications that can take advantage of additional vCPUs.

For customers looking to utilize GPU-powered VMs as part of the desktop as a service (DaaS) offering, Windows Virtual Desktop provides a comprehensive desktop and application virtualization service running in Azure. The new NVv4-series Virtual Machines will be supported by Windows Virtual Desktop as well as Azure Batch  for cloud-native batch processing.

Remote display application and protocols are key to a good end user experience with VDI/DaaS in the cloud. The new virtual machine series will work with Windows Remote Desktop (RDP) 10, Teradici PCoIP, and HDX 3D Pro. The AMD Radeon GPUs support DirectX 9 through 12, OpenGL 4.6, and Vulkan 1.1.

Customers can sign up for NVv4 access today by filling out this form. NVv4 Virtual Machines will initially be available later this year in the South Central US and West Europe Azure regions and will be available in additional regions soon thereafter.
Quelle: Azure

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Introducing the new HBv2 Azure Virtual Machines for high-performance computing

Announcing the second-generation HB-series Azure Virtual Machines for high-performance computing (HPC). HBv2 Virtual Machines are designed to deliver leadership-class performance, message passing interface (MPI) scalability, and cost efficiency for a variety of real-world HPC workloads.

HBv2 Virtual Machines feature 120 AMD EPYC™ 7002-series CPU cores, 480 GB of RAM, 480 MB of L3 cache, and no simultaneous multithreading (SMT). HBv2 Virtual Machines provide up to 350 GB/sec of memory bandwidth, which is 45-50 percent more than comparable x86 alternatives and three times faster than what most HPC customers have in their datacenters today.

Size
CPU cores
Memory: GB
Memory per CPU Core: GB
Local SSD: GiB
RDMA network
Azure network

Standard_HB120rs
120
480 GB
4 GB
1.6 TB
200 Gbps
40 Gbps

‘r’ denotes support for RDMA. ‘s’ denotes support for Premium SSD disks.

Each HBv2 virtual machine (VM) also features up to 4 teraFLOPS of double-precision performance, and up to 8 teraFLOPS of single-precision performance. This is a four times increase over our first generation of HB-series Virtual Machines, and substantially improves performance for applications demanding the fastest memory and leadership-class compute density.

Below are preliminary benchmarks on HBv2 across several common HPC applications and domains:

To drive optimal at-scale message passing interface (MPI) performance, HBv2 Virtual Machines feature 200 Gb/s HDR InfiniBand from our technology partners at Mellanox. The InfiniBand fabric backing HBv2 Virtual Machines is a non-blocking fat-tree with a low-diameter design for consistent, ultra-low latencies. Customers can use standard Mellanox/OFED drivers just as they would on a bare metal environment. HBv2 Virtual Machines officially support RDMA verbs and hence support all InfiniBand based MPIs, such as OpenMPI, MVAPICH2, Platform MPI, and Intel MPI. Customers can also leverage hardware offload of MPI collectives to realize additional performance, as well as efficiency gains for commercially licensed applications.

Across a single virtual machine scale set, customers can run a single MPI job on HBv2 Virtual Machines at up to 36,000 cores. For our largest customers, HBv2 Virtual Machines support up to 80,000 cores for single jobs.

Customers can also maximize the Ethernet interface of HBv2 Virtual Machines by using the SRIOV-based accelerated networking in Azure, which will yield up to 40 Gb/s of bandwidth, consistent, and low latencies.

Finally, the new H-series Virtual Machines feature local NVMe SSDs to deliver ultra-fast temporary storage for the full range of file sizes and I/O patterns. Using modern burst-buffer technologies like BeeGFS BeeOND, the new H-series Virtual Machines can deliver more than 900 GB/sec of peak injection I/O performance across a single virtual machine scale set. The new H-series Virtual Machines will also support Azure Premium SSD disks.

Customers can accelerate their HBv2 deployments with a variety resources optimized and pre-configured by the Azure HPC team. Our pre-built HPC image for CentOS is tuned for optimal performance and bundles key HPC tools like various MPI libraries, compilers, and more. The AzureHPC Project helps customers deploy an end-to-end Azure HPC environment reliably and quickly, and includes deployment scripts for setting up building blocks for networking, compute, schedulers, and storage. Also included is a growing list of tutorials for running HPC applications themselves.

For customers familiar with HPC schedulers and who would like to use these with HBv2 Virtual Machines, Azure CycleCloud is the simplest way to orchestrate autoscaling clusters. Azure CycleCloud supports schedulers such as Slurm, PBSPro, LSF, GridEngine, and HTCondor, and enables hybrid deployments for customers wishing to pair HBv2 Virtual Machines with their existing on-premises clusters. The new H-series Virtual Machines will also be supported by Azure Batch for cloud-native batch processing. HBv2 Virtual Machines will be available to all Azure platform partners.

Customers can sign up for HBv2 access today by filling out this form. HBv2 Virtual Machines will initially be available in the South Central US and West Europe Azure regions, with availability in additional regions soon thereafter.
Quelle: Azure

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Announcing new AMD EPYC™-based Azure Virtual Machines

Microsoft is committed to giving our customers industry-leading performance for all their workloads. After being the first global cloud provider to announce the deployment of AMD EPYC™ based Azure Virtual Machines in 2017, we’ve been working together to continue bringing the latest innovation to enterprises.

Today, we are announcing our second-generation HB-series Azure Virtual Machines, HBv2, which features the latest AMD EPYC 7002 processor. Customers will be able to increase HPC performance and scalability to run materially larger workloads on Azure. We’ll also be bringing the AMD 7002 processors and Radeon Instinct GPUs to our family of cloud-based virtual desktops. Finally, our new Dav3 and Eav3-series Azure Virtual Machines, in preview today, provide more customer choice to meet a broad range of requirements for general purpose workloads using the new AMD EPYC™ 7452 processor.

Our growing Azure HPC offerings

Customers are choosing our Azure HPC offerings (HB-series) incorporating first generation AMD EPYC Naples for their performance and scalability. We’ve seen a 33 percent memory bandwidth advantage with EPYC, and that’s a key factor for many of our customers’ HPC workloads. For example, fluid dynamics is one workload in which this advantage is valuable. Azure has an increasing number of customers for whom this is a core part of their R&D and even production activities. On ANSYS Fluent, a widely used fluid dynamics application, we have measured EPYC-powered HB instances delivering a 54x performance improvement by scaling across nearly 6,000 processor cores. And this is 24 percent faster than a leading bare-metal solution with an identical InfiniBand network. Additionally, earlier this year, Azure became the first cloud to scale a tightly coupled HPC application to 10,000 cores. This is 10x higher than what had been previously possible on any other cloud provider. Azure customers will be among the first to take advantage of this capability to tackle the toughest challenges and innovate with purpose.

New HPC, general purpose, and memory optimized Azure Virtual Machines

Azure is continuing to increase its HPC capabilities, thanks in part to our collaboration with AMD. In preliminary benchmarking, HBv2 VMs featuring 120 CPUs from the second generation EPYC processor are demonstrating performance gains of over 100 percent on HPC workloads like fluid dynamics and automotive crash test analysis. HBv2 scalability limits are also increasing with the cloud’s first deployment of 200 Gigabit InfiniBand, thanks to the second generation EPYC processor’s PCIe 4.0 capability. HBv2 virtual machines (VMs) will support up to 36,000 cores for MPI workloads in a single virtual machine scale set, and up to 80,000 cores for our largest customers.

We’ll also be bringing AMD EPYC 7002 processor to our family of cloud-based remote desktops, pairing with the Radeon MI25 GPU for customers running Windows-based environments. The new series offers unprecedented GPU resourcing flexibility, giving customers more choice than ever before to size virtual machines all the way from 1/8th of a single GPU up to a whole GPU.

Finally, we are also announcing new Azure Virtual Machines as part of the Dv3 and Ev3-series—optimized for general purpose and memory intensive workloads. These new VM sizes feature AMD’s EPYC™ 7452 processor. The new general purpose Da_v3 and Das_v3 Azure Virtual Machines provide up to 64 vCPUs, 256 GiBs of RAM, and 1,600 GiBs of SSD-based temporary storage. Additionally, the new memory optimized Ea_v3 and Eas_v3 Azure Virtual Machines provide up to 64 vCPUs, 432 GiBs of RAM, and 1,600 GiBs of SSD-based temporary storage. Both VM series support Premium SSD disk storage. The new VMs are currently in preview in the East US Azure region and with availability coming soon to other regions.

Da_v3 and Das_v3 virtual machines can be used for a broad range of general-purpose applications. Example use cases include most enterprise-grade applications, relational databases, in-memory caching, and analytics. Applications that demand faster CPUs, better local disk performance or higher memories can also benefit from these new VMs. Additionally, the Ea_v3 and Eas_v3 VM series are optimized for other large in-memory business critical workloads.

Taking advantage of these new offerings

Request access to the latest HPC and Remote Desktop virtual machines.
Request access to the new general purpose and memory intensive Azure Virtual Machines. 

Quelle: Azure

da Agency

Better security with enhanced access control experience in Azure Files

We are making it easier for customers to “lift and shift” applications to the cloud while maintaining the same security model used on-premises with the general availability of Azure Active Directory Domain Services (Azure AD DS) authentication for Azure Files. By integrating Azure AD DS, you can mount your Azure file share over SMB using Azure Active Directory (Azure AD) credentials from Azure AD DS domain joined Windows virtual machines (VMs) with NTFS access control lists (ACLs) enforced.

Azure AD DS authentication for Azure Files allows users to specify granular permissions on shares, files, and folders. It unblocks common use cases like single writer and multi-reader scenario for your line of business applications. As the file permission assignment and enforcement experience matches that of NTFS, lifting and shifting your application into Azure is as easy as moving it to a new SMB file server. This also makes Azure Files an ideal shared storage solution for cloud-based services. For example, Windows Virtual Desktop recommends using Azure Files to host different user profiles and leverage Azure AD DS authentication for access control.

Since Azure Files strictly enforces NTFS discretionary access control lists (DACLs), you can use familiar tools like Robocopy to move data into an Azure file share persisting all of your important security control. Azure Files access control lists are also captured in Azure file share snapshots for backup and disaster recovery scenarios. This ensures that file access control lists are preserved on data recovery using services like Azure Backup that leverages file snapshots.

Follow the step-by-step guidance to get started today. To better understand the benefits and capabilities, you can refer to our overview Azure Azure AD DS authentication for Azure Files.

What’s new in general availability?

Based on your feedback, there are several new features to share since the preview:

Seamless integration with Windows File Explorer on permission assignments: When we demoed this feature at Microsoft Ignite 2018, we showed changing and view permissions with a Windows command line tool called icacls. There were clearly some challenges, since icacls is not easily discoverable or consistent with common user behavior. Starting with general availability, you can view or modify the permissions on a file or folder with Windows File Explorer, just like any regular file shares.

New built-in role-based access controls to simplify share level access management: To simplify share-level access management, we have introduced three new built-in role-based access controls—Storage File Data SMB Share Elevated Contributor, Contributor, and Reader. Instead of creating custom roles, you can use the built-in roles for granting share-level permissions for SMB access to Azure Files.

What is next for Azure Files access control experience?

Supporting authentication with Azure Active Directory Domain Services is most useful for application lift and shift scenarios, but Azure Files can help with moving all on-premises file shares, regardless of whether they are providing storage for an application or for end users. Our team is working to extend authentication support to Windows Server Active Directory hosted on-premises or in the cloud.

If you are interested to hear future updates on Azure Files Active Directory Authentication, sign up today. For general feedback on Azure Files, email us at AzureFiles@microsoft.com.
Quelle: Azure

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Disaster recovery of Azure disk encryption (V2) enabled virtual machines

Choosing Azure for your applications and services allows you take advantage of a wide array of security tools and capabilities. These tools and capabilities help make it possible to create secure solutions on Azure. Among these capabilities is Azure disk encryption, designed to help protect and safeguard your data to meet your organizational security and compliance commitments. It uses the industry standard BitLocker Drive Encryption for Windows and DM-Crypt for Linux to provide volume encryption for OS and data disks. The solution is integrated with Azure Key Vault to help you control and manage disk encryption keys and secrets, and ensures that all data on virtual machine (VM) disks are encrypted both in-transit and at rest while in Azure Storage.

Beyond securing your applications, it is important to have a disaster recovery plan in place to keep your mission critical applications up and running when planned and unplanned outages occur. Azure Site Recovery helps orchestrate replication, failover, and recovery of applications running on Azure Virtual Machines so that they are available from a secondary region if you have any outages in the primary region.

Azure Site Recovery now supports disaster recovery of Azure disk encryption (V2) enabled virtual machines without Azure Active Directory application. While enabling replication of your VM for disaster recovery, all the required disk encryption keys and secrets are copied from the source region to the target region in the user context. If the user managing disaster recovery does not have the appropriate permissions, the user can hand over the ready-to-use script to the security administrator to copy the keys and secrets and proceed with configuration.

This feature currently supports only Windows VMs using managed disks. The support for Linux VMs using managed disks will be available in the coming weeks. This feature is available in all Azure regions where Azure Site Recovery is available. Configure disaster recovery for Azure disk encryption enabled virtual machines using Azure Site Recovery today and become both secure and protected from outages.
Quelle: Azure

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High Availability Add-On updates for Red Hat Enterprise Linux on Azure

High availability is crucial to mission-critical production environments. The Red Hat Enterprise Linux High Availability Add-On provides reliability and availability to critical production services that use it. Today, we’re sharing performance improvements and image updates around the High Availability Add-On for Red Hat Enterprise Linux (RHEL) on Azure.

Pacemaker

Pacemaker is a robust and powerful open-source resource manager used in highly available compute clusters. It is a key part of the High Availability Add-On for RHEL.

Pacemaker has been updated with performance improvements in the Azure Fencing Agent to significantly decrease Azure failover time, which greatly reduces customer downtime. This update is available to all RHEL 7.4+ users using either the Pay-As-You-Go images or Bring-Your-Own-Subscription images from the Azure Marketplace.

New pay-as-you-go RHEL images with the High Availability Add-On

We now have RHEL Pay-As-You-Go (PAYG) images with the High Availability Add-On available in the Azure Marketplace. These RHEL images have additional access to the High Availability Add-On repositories. Pricing details for these images are available in the pricing calculator.

The following RHEL HA PAYG images are now available in the Marketplace for all Azure regions, including US Government Cloud:

RHEL 7.4 with HA
RHEL 7.5 with HA
RHEL 7.6 with HA

New pay-as-you-go RHEL for SAP images with the High Availability Add-On

We also have RHEL images that include both SAP packages and the High Availability Add-On available in the Marketplace. These images come with access to SAP repositories as well as 4 years of support per standard Red Hat policies. Pricing details for these images are available in the pricing calculator.

The following RHEL for SAP with HA and Update Services images are available in the Marketplace for all Azure regions, including US Government Cloud:

RHEL 7.4 for SAP with HA and Update Services
RHEL 7.5 for SAP with HA and Update Services
RHEL 7.6 for SAP with HA and Update Services

Refer to the Certified and Supported SAP HANA Hardware Directory to see the list of SAP-certified Azure VM sizes.

You can also get a full listing of RHEL images on Azure, including the RHEL with HA and RHEL for SAP with HA images with the following Azure CLI command:

az vm image list –publisher redhat –all

Support

All the RHEL with HA and RHEL for SAP with HA images on Azure are fully supported by the Red Hat and Microsoft integrated support team.

See the support site here and the Red Hat support site here.

Full details on the Red Hat Enterprise Linux support lifecycle are available here.

Next steps

Visit the Red Hat on Azure site to learn more about Red Hat workloads on Azure.
View pricing information at the pricing calculator.
Get started with the RHEL HA PAYG images and the RHEL for SAP with HA PAYG images.
Learn to create a Pacemaker cluster for SAP using RHEL by following our instructions here.
Deploy SAP on RHEL with our Quickstart Guide.

Quelle: Azure

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When to use Azure Service Health versus the status page

If you’re experiencing problems with your applications, a great place to start investigating solutions is through your Azure Service Health dashboard. In this blog post, we’ll explore the differences between the Azure status page and Azure Service Health. We’ll also show you how to get started with Service Health alerts so you can stay better informed about service issues and take action to improve your workloads’ availability.

How and when to use the Azure status page

The Azure status page works best for tracking major outages, especially if you’re unable to log into the Azure portal or access Azure Service Health. Many Azure users visit the status page regularly. It predates Azure Service Health and has a friendly format that shows the status of all Azure services and regions at a glance.

The Azure status page, however, doesn’t show all information about the health of your Azure services and regions. The status page isn’t personalized, so you need to know exactly which services and regions you’re using and locate them in the grid. The status page also doesn’t include information about non-outage events that could affect your availability. For example, planned maintenance events and health advisories (think service retirements and misconfigurations). Finally, the status page doesn’t have a means of notifying you automatically in the event of an outage or a planned maintenance window that might affect you.

For all of these use cases, we created Azure Service Health.

How and when to use Azure Service Health

At the top of the Azure status page, you’ll find a button directing you to your personalized dashboard. One common misunderstanding is that this button allows you to personalize the status page grid of services and regions. Instead, the button takes you into the Azure portal to Azure Service Health, the best option for viewing Azure events that may impact the availability of your resources.

In Service Health, you’ll find information about everything from minor outages that affect you to planned maintenance events and other health advisories. The dashboard is personalized, so it knows which services and regions you’re using and can even help you troubleshoot by offering a list of potentially impacted resources for any given event.

Service Health’s most useful feature is Service Health alerts. With Service Health alerts, you’ll proactively receive notifications via your preferred channel—email, SMS, push notification, or even webhook into your internal ticketing system like ServiceNow or PagerDuty—if there’s an issue with your services and regions. You don’t have to keep checking Service Health or the status page for updates and can instead focus on other important work.

Set up your Service Health alerts today

Feel free to keep using the status page for quick updates on major outages. However, we highly encourage you make it a habit to visit Service Health to stay informed of all potential impacts to your availability and take advantage of rich features like automated alerting.

Set up your Azure Service Health alerts today in the Azure portal. For more in-depth guidance, visit the Azure Service Health documentation. Let us know if you have a suggestion by submitting an idea here.
Quelle: Azure

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Announcing Azure Databricks unit pre-purchase plan and new regional availability

Azure Databricks is a fast, easy, and collaborative Apache Spark based analytics platform that simplifies the process of building big data and artificial intelligence (AI) solutions. Azure Databricks provides data engineers and data scientists an interactive workplace where they can use the languages and frameworks of their choice. Natively integrated with services like Azure Machine Learning and Azure SQL Data Warehouse, Azure Databricks enables customers to build an end-to-end modern data warehouse, real-time analytics, and machine learning solutions.

Save up to 37 percent on your Azure Databricks workloads

Azure Databricks Unit pre-purchase plan is now generally available—expanding our commitment to make Azure the most cost-effective cloud for running your analytics workloads.

Today, with the Azure Databricks Unit pre-purchase plan, you can start unlocking the benefits of Azure Databricks at significantly reduced costs when you pre-pay for Databricks compute for a one or three-year term. With this new pricing option, you can achieve savings of up to 37 percent compared to pay-as-you-go pricing. You can learn more about the discount tiers on our pricing page. All Azure Databricks SKUs—Premium and Standard SKUs for Data Engineering Light, Data Engineering, and Data Analytics—are eligible for DBU pre-purchase.

Compared with other Azure services with reserved capacity pricing, which have a per hour capacity purchase, this plan allows you to pre-purchase DBUs that can be used at any time. You also have the flexibility to consume units across all workload types and tiers.

Azure Databricks is offered as a first party Azure service. You can pre-purchase Databricks compute either from your Azure prepayment or existing payment instruments.

Azure Databricks is now available in South Africa and South Korea

Azure Databricks is now generally available in additional regions—South Africa and South Korea. These additional locations bring the product worldwide availability count to 26 regions backed by a 99.95 percent SLA.

Driven by the motto of innovation and accessibility, we aim to ensure that we build a cloud infrastructure to serve the needs of customers globally. Stay updated with the region availability for Azure Databricks.

Organizations also benefit from Azure Databricks' native integration with other services like Azure Blob storage, Azure Data Factory, Azure SQL Data Warehouse, Azure Machine Learning, and Azure Cosmos DB. This enables new analytics solutions that support modern data warehousing, advanced analytics, and real-time analytics scenarios.

Get started today

Getting started with DBU pre-purchase is easy, and is done via the Azure portal. For details on how to get started, see our documentation. For more information on discount tiers, please visit the pricing page.
Quelle: Azure