Category: News
Enhanced Performance in Additional Regions: Azure Synapse Analytics Spark Boosted by up to 77%
We are committed to continually advancing the capabilities of Azure Synapse Analytics Spark, and are pleased to announce substantial improvements that could increase Spark performance by as much as 77%.
Performance Metrics
Our internal testing, utilizing the 1TB TPC-H industry standard benchmark, indicates performance gains of up to 77%. It’s important to note that individual workloads may vary, but the enhancements are designed to benefit all Azure Synapse Analytics Spark users.
Technological Foundations
This performance uptick is attributable to our transition to the latest Azure v5 Virtual Machines. These VMs bring improved CPU performance, increased SSD throughput, and elevated remote storage IOPS.
Regional Availability
We have implemented these performance improvements in the following regions, bold indicates a new region:
Australia East
Australia Southeast
Canada Central
Canada East
Central India
Germany West Central
Japan West
Korea Central
Poland Central
South Africa North
South India
Sweden Central
Switzerland North
Switzerland West
UAE North
UK South
UK West
West Central US
Additionally, all Microsoft Fabric regions, with the exception of Qatar Central, are already operating with these enhanced performance capabilities.
Future Rollout
The global rollout of these improvements is an ongoing process and expected to take several quarters to complete. We will provide updates as additional regions are upgraded. Customers in updated regions will automatically benefit from the performance enhancements at no additional cost.
Next Steps for Users
No action is required on your part to benefit from these improvements. Once your region receives the upgrade, you may notice reduced job completion times. If cost-efficiency is a priority, you may opt to decrease node size or the number of nodes while maintaining improved performance levels.
Learn more about Optimizing Spark performance, Apache Spark pool configurations, Spark compute for Data Engineering and Data Science – Microsoft Fabric
Microsoft Tech Community – Latest Blogs –Read More
Enhanced Performance in Additional Regions: Azure Synapse Analytics Spark Boosted by up to 77%
We are committed to continually advancing the capabilities of Azure Synapse Analytics Spark, and are pleased to announce substantial improvements that could increase Spark performance by as much as 77%.
Performance Metrics
Our internal testing, utilizing the 1TB TPC-H industry standard benchmark, indicates performance gains of up to 77%. It’s important to note that individual workloads may vary, but the enhancements are designed to benefit all Azure Synapse Analytics Spark users.
Technological Foundations
This performance uptick is attributable to our transition to the latest Azure v5 Virtual Machines. These VMs bring improved CPU performance, increased SSD throughput, and elevated remote storage IOPS.
Regional Availability
We have implemented these performance improvements in the following regions, bold indicates a new region:
Australia East
Australia Southeast
Canada Central
Canada East
Central India
Germany West Central
Japan West
Korea Central
Poland Central
South Africa North
South India
Sweden Central
Switzerland North
Switzerland West
UAE North
UK South
UK West
West Central US
Additionally, all Microsoft Fabric regions, with the exception of Qatar Central, are already operating with these enhanced performance capabilities.
Future Rollout
The global rollout of these improvements is an ongoing process and expected to take several quarters to complete. We will provide updates as additional regions are upgraded. Customers in updated regions will automatically benefit from the performance enhancements at no additional cost.
Next Steps for Users
No action is required on your part to benefit from these improvements. Once your region receives the upgrade, you may notice reduced job completion times. If cost-efficiency is a priority, you may opt to decrease node size or the number of nodes while maintaining improved performance levels.
Learn more about Optimizing Spark performance, Apache Spark pool configurations, Spark compute for Data Engineering and Data Science – Microsoft Fabric
Microsoft Tech Community – Latest Blogs –Read More
Enhanced Performance in Additional Regions: Azure Synapse Analytics Spark Boosted by up to 77%
We are committed to continually advancing the capabilities of Azure Synapse Analytics Spark, and are pleased to announce substantial improvements that could increase Spark performance by as much as 77%.
Performance Metrics
Our internal testing, utilizing the 1TB TPC-H industry standard benchmark, indicates performance gains of up to 77%. It’s important to note that individual workloads may vary, but the enhancements are designed to benefit all Azure Synapse Analytics Spark users.
Technological Foundations
This performance uptick is attributable to our transition to the latest Azure v5 Virtual Machines. These VMs bring improved CPU performance, increased SSD throughput, and elevated remote storage IOPS.
Regional Availability
We have implemented these performance improvements in the following regions, bold indicates a new region:
Australia East
Australia Southeast
Canada Central
Canada East
Central India
Germany West Central
Japan West
Korea Central
Poland Central
South Africa North
South India
Sweden Central
Switzerland North
Switzerland West
UAE North
UK South
UK West
West Central US
Additionally, all Microsoft Fabric regions, with the exception of Qatar Central, are already operating with these enhanced performance capabilities.
Future Rollout
The global rollout of these improvements is an ongoing process and expected to take several quarters to complete. We will provide updates as additional regions are upgraded. Customers in updated regions will automatically benefit from the performance enhancements at no additional cost.
Next Steps for Users
No action is required on your part to benefit from these improvements. Once your region receives the upgrade, you may notice reduced job completion times. If cost-efficiency is a priority, you may opt to decrease node size or the number of nodes while maintaining improved performance levels.
Learn more about Optimizing Spark performance, Apache Spark pool configurations, Spark compute for Data Engineering and Data Science – Microsoft Fabric
Microsoft Tech Community – Latest Blogs –Read More
Enhanced Performance in Additional Regions: Azure Synapse Analytics Spark Boosted by up to 77%
We are committed to continually advancing the capabilities of Azure Synapse Analytics Spark, and are pleased to announce substantial improvements that could increase Spark performance by as much as 77%.
Performance Metrics
Our internal testing, utilizing the 1TB TPC-H industry standard benchmark, indicates performance gains of up to 77%. It’s important to note that individual workloads may vary, but the enhancements are designed to benefit all Azure Synapse Analytics Spark users.
Technological Foundations
This performance uptick is attributable to our transition to the latest Azure v5 Virtual Machines. These VMs bring improved CPU performance, increased SSD throughput, and elevated remote storage IOPS.
Regional Availability
We have implemented these performance improvements in the following regions, bold indicates a new region:
Australia East
Australia Southeast
Canada Central
Canada East
Central India
Germany West Central
Japan West
Korea Central
Poland Central
South Africa North
South India
Sweden Central
Switzerland North
Switzerland West
UAE North
UK South
UK West
West Central US
Additionally, all Microsoft Fabric regions, with the exception of Qatar Central, are already operating with these enhanced performance capabilities.
Future Rollout
The global rollout of these improvements is an ongoing process and expected to take several quarters to complete. We will provide updates as additional regions are upgraded. Customers in updated regions will automatically benefit from the performance enhancements at no additional cost.
Next Steps for Users
No action is required on your part to benefit from these improvements. Once your region receives the upgrade, you may notice reduced job completion times. If cost-efficiency is a priority, you may opt to decrease node size or the number of nodes while maintaining improved performance levels.
Learn more about Optimizing Spark performance, Apache Spark pool configurations, Spark compute for Data Engineering and Data Science – Microsoft Fabric
Microsoft Tech Community – Latest Blogs –Read More
Enhanced Performance in Additional Regions: Azure Synapse Analytics Spark Boosted by up to 77%
We are committed to continually advancing the capabilities of Azure Synapse Analytics Spark, and are pleased to announce substantial improvements that could increase Spark performance by as much as 77%.
Performance Metrics
Our internal testing, utilizing the 1TB TPC-H industry standard benchmark, indicates performance gains of up to 77%. It’s important to note that individual workloads may vary, but the enhancements are designed to benefit all Azure Synapse Analytics Spark users.
Technological Foundations
This performance uptick is attributable to our transition to the latest Azure v5 Virtual Machines. These VMs bring improved CPU performance, increased SSD throughput, and elevated remote storage IOPS.
Regional Availability
We have implemented these performance improvements in the following regions, bold indicates a new region:
Australia East
Australia Southeast
Canada Central
Canada East
Central India
Germany West Central
Japan West
Korea Central
Poland Central
South Africa North
South India
Sweden Central
Switzerland North
Switzerland West
UAE North
UK South
UK West
West Central US
Additionally, all Microsoft Fabric regions, with the exception of Qatar Central, are already operating with these enhanced performance capabilities.
Future Rollout
The global rollout of these improvements is an ongoing process and expected to take several quarters to complete. We will provide updates as additional regions are upgraded. Customers in updated regions will automatically benefit from the performance enhancements at no additional cost.
Next Steps for Users
No action is required on your part to benefit from these improvements. Once your region receives the upgrade, you may notice reduced job completion times. If cost-efficiency is a priority, you may opt to decrease node size or the number of nodes while maintaining improved performance levels.
Learn more about Optimizing Spark performance, Apache Spark pool configurations, Spark compute for Data Engineering and Data Science – Microsoft Fabric
Microsoft Tech Community – Latest Blogs –Read More
Enhanced Performance in Additional Regions: Azure Synapse Analytics Spark Boosted by up to 77%
We are committed to continually advancing the capabilities of Azure Synapse Analytics Spark, and are pleased to announce substantial improvements that could increase Spark performance by as much as 77%.
Performance Metrics
Our internal testing, utilizing the 1TB TPC-H industry standard benchmark, indicates performance gains of up to 77%. It’s important to note that individual workloads may vary, but the enhancements are designed to benefit all Azure Synapse Analytics Spark users.
Technological Foundations
This performance uptick is attributable to our transition to the latest Azure v5 Virtual Machines. These VMs bring improved CPU performance, increased SSD throughput, and elevated remote storage IOPS.
Regional Availability
We have implemented these performance improvements in the following regions, bold indicates a new region:
Australia East
Australia Southeast
Canada Central
Canada East
Central India
Germany West Central
Japan West
Korea Central
Poland Central
South Africa North
South India
Sweden Central
Switzerland North
Switzerland West
UAE North
UK South
UK West
West Central US
Additionally, all Microsoft Fabric regions, with the exception of Qatar Central, are already operating with these enhanced performance capabilities.
Future Rollout
The global rollout of these improvements is an ongoing process and expected to take several quarters to complete. We will provide updates as additional regions are upgraded. Customers in updated regions will automatically benefit from the performance enhancements at no additional cost.
Next Steps for Users
No action is required on your part to benefit from these improvements. Once your region receives the upgrade, you may notice reduced job completion times. If cost-efficiency is a priority, you may opt to decrease node size or the number of nodes while maintaining improved performance levels.
Learn more about Optimizing Spark performance, Apache Spark pool configurations, Spark compute for Data Engineering and Data Science – Microsoft Fabric
Microsoft Tech Community – Latest Blogs –Read More
Enhanced Performance in Additional Regions: Azure Synapse Analytics Spark Boosted by up to 77%
We are committed to continually advancing the capabilities of Azure Synapse Analytics Spark, and are pleased to announce substantial improvements that could increase Spark performance by as much as 77%.
Performance Metrics
Our internal testing, utilizing the 1TB TPC-H industry standard benchmark, indicates performance gains of up to 77%. It’s important to note that individual workloads may vary, but the enhancements are designed to benefit all Azure Synapse Analytics Spark users.
Technological Foundations
This performance uptick is attributable to our transition to the latest Azure v5 Virtual Machines. These VMs bring improved CPU performance, increased SSD throughput, and elevated remote storage IOPS.
Regional Availability
We have implemented these performance improvements in the following regions, bold indicates a new region:
Australia East
Australia Southeast
Canada Central
Canada East
Central India
Germany West Central
Japan West
Korea Central
Poland Central
South Africa North
South India
Sweden Central
Switzerland North
Switzerland West
UAE North
UK South
UK West
West Central US
Additionally, all Microsoft Fabric regions, with the exception of Qatar Central, are already operating with these enhanced performance capabilities.
Future Rollout
The global rollout of these improvements is an ongoing process and expected to take several quarters to complete. We will provide updates as additional regions are upgraded. Customers in updated regions will automatically benefit from the performance enhancements at no additional cost.
Next Steps for Users
No action is required on your part to benefit from these improvements. Once your region receives the upgrade, you may notice reduced job completion times. If cost-efficiency is a priority, you may opt to decrease node size or the number of nodes while maintaining improved performance levels.
Learn more about Optimizing Spark performance, Apache Spark pool configurations, Spark compute for Data Engineering and Data Science – Microsoft Fabric
Microsoft Tech Community – Latest Blogs –Read More
Enhanced Performance in Additional Regions: Azure Synapse Analytics Spark Boosted by up to 77%
We are committed to continually advancing the capabilities of Azure Synapse Analytics Spark, and are pleased to announce substantial improvements that could increase Spark performance by as much as 77%.
Performance Metrics
Our internal testing, utilizing the 1TB TPC-H industry standard benchmark, indicates performance gains of up to 77%. It’s important to note that individual workloads may vary, but the enhancements are designed to benefit all Azure Synapse Analytics Spark users.
Technological Foundations
This performance uptick is attributable to our transition to the latest Azure v5 Virtual Machines. These VMs bring improved CPU performance, increased SSD throughput, and elevated remote storage IOPS.
Regional Availability
We have implemented these performance improvements in the following regions, bold indicates a new region:
Australia East
Australia Southeast
Canada Central
Canada East
Central India
Germany West Central
Japan West
Korea Central
Poland Central
South Africa North
South India
Sweden Central
Switzerland North
Switzerland West
UAE North
UK South
UK West
West Central US
Additionally, all Microsoft Fabric regions, with the exception of Qatar Central, are already operating with these enhanced performance capabilities.
Future Rollout
The global rollout of these improvements is an ongoing process and expected to take several quarters to complete. We will provide updates as additional regions are upgraded. Customers in updated regions will automatically benefit from the performance enhancements at no additional cost.
Next Steps for Users
No action is required on your part to benefit from these improvements. Once your region receives the upgrade, you may notice reduced job completion times. If cost-efficiency is a priority, you may opt to decrease node size or the number of nodes while maintaining improved performance levels.
Learn more about Optimizing Spark performance, Apache Spark pool configurations, Spark compute for Data Engineering and Data Science – Microsoft Fabric
Microsoft Tech Community – Latest Blogs –Read More
Enhanced Performance in Additional Regions: Azure Synapse Analytics Spark Boosted by up to 77%
We are committed to continually advancing the capabilities of Azure Synapse Analytics Spark, and are pleased to announce substantial improvements that could increase Spark performance by as much as 77%.
Performance Metrics
Our internal testing, utilizing the 1TB TPC-H industry standard benchmark, indicates performance gains of up to 77%. It’s important to note that individual workloads may vary, but the enhancements are designed to benefit all Azure Synapse Analytics Spark users.
Technological Foundations
This performance uptick is attributable to our transition to the latest Azure v5 Virtual Machines. These VMs bring improved CPU performance, increased SSD throughput, and elevated remote storage IOPS.
Regional Availability
We have implemented these performance improvements in the following regions, bold indicates a new region:
Australia East
Australia Southeast
Canada Central
Canada East
Central India
Germany West Central
Japan West
Korea Central
Poland Central
South Africa North
South India
Sweden Central
Switzerland North
Switzerland West
UAE North
UK South
UK West
West Central US
Additionally, all Microsoft Fabric regions, with the exception of Qatar Central, are already operating with these enhanced performance capabilities.
Future Rollout
The global rollout of these improvements is an ongoing process and expected to take several quarters to complete. We will provide updates as additional regions are upgraded. Customers in updated regions will automatically benefit from the performance enhancements at no additional cost.
Next Steps for Users
No action is required on your part to benefit from these improvements. Once your region receives the upgrade, you may notice reduced job completion times. If cost-efficiency is a priority, you may opt to decrease node size or the number of nodes while maintaining improved performance levels.
Learn more about Optimizing Spark performance, Apache Spark pool configurations, Spark compute for Data Engineering and Data Science – Microsoft Fabric
Microsoft Tech Community – Latest Blogs –Read More
Enhanced Performance in Additional Regions: Azure Synapse Analytics Spark Boosted by up to 77%
We are committed to continually advancing the capabilities of Azure Synapse Analytics Spark, and are pleased to announce substantial improvements that could increase Spark performance by as much as 77%.
Performance Metrics
Our internal testing, utilizing the 1TB TPC-H industry standard benchmark, indicates performance gains of up to 77%. It’s important to note that individual workloads may vary, but the enhancements are designed to benefit all Azure Synapse Analytics Spark users.
Technological Foundations
This performance uptick is attributable to our transition to the latest Azure v5 Virtual Machines. These VMs bring improved CPU performance, increased SSD throughput, and elevated remote storage IOPS.
Regional Availability
We have implemented these performance improvements in the following regions, bold indicates a new region:
Australia East
Australia Southeast
Canada Central
Canada East
Central India
Germany West Central
Japan West
Korea Central
Poland Central
South Africa North
South India
Sweden Central
Switzerland North
Switzerland West
UAE North
UK South
UK West
West Central US
Additionally, all Microsoft Fabric regions, with the exception of Qatar Central, are already operating with these enhanced performance capabilities.
Future Rollout
The global rollout of these improvements is an ongoing process and expected to take several quarters to complete. We will provide updates as additional regions are upgraded. Customers in updated regions will automatically benefit from the performance enhancements at no additional cost.
Next Steps for Users
No action is required on your part to benefit from these improvements. Once your region receives the upgrade, you may notice reduced job completion times. If cost-efficiency is a priority, you may opt to decrease node size or the number of nodes while maintaining improved performance levels.
Learn more about Optimizing Spark performance, Apache Spark pool configurations, Spark compute for Data Engineering and Data Science – Microsoft Fabric
Microsoft Tech Community – Latest Blogs –Read More
Enhanced Performance in Additional Regions: Azure Synapse Analytics Spark Boosted by up to 77%
We are committed to continually advancing the capabilities of Azure Synapse Analytics Spark, and are pleased to announce substantial improvements that could increase Spark performance by as much as 77%.
Performance Metrics
Our internal testing, utilizing the 1TB TPC-H industry standard benchmark, indicates performance gains of up to 77%. It’s important to note that individual workloads may vary, but the enhancements are designed to benefit all Azure Synapse Analytics Spark users.
Technological Foundations
This performance uptick is attributable to our transition to the latest Azure v5 Virtual Machines. These VMs bring improved CPU performance, increased SSD throughput, and elevated remote storage IOPS.
Regional Availability
We have implemented these performance improvements in the following regions, bold indicates a new region:
Australia East
Australia Southeast
Canada Central
Canada East
Central India
Germany West Central
Japan West
Korea Central
Poland Central
South Africa North
South India
Sweden Central
Switzerland North
Switzerland West
UAE North
UK South
UK West
West Central US
Additionally, all Microsoft Fabric regions, with the exception of Qatar Central, are already operating with these enhanced performance capabilities.
Future Rollout
The global rollout of these improvements is an ongoing process and expected to take several quarters to complete. We will provide updates as additional regions are upgraded. Customers in updated regions will automatically benefit from the performance enhancements at no additional cost.
Next Steps for Users
No action is required on your part to benefit from these improvements. Once your region receives the upgrade, you may notice reduced job completion times. If cost-efficiency is a priority, you may opt to decrease node size or the number of nodes while maintaining improved performance levels.
Learn more about Optimizing Spark performance, Apache Spark pool configurations, Spark compute for Data Engineering and Data Science – Microsoft Fabric
Microsoft Tech Community – Latest Blogs –Read More
Enhanced Performance in Additional Regions: Azure Synapse Analytics Spark Boosted by up to 77%
We are committed to continually advancing the capabilities of Azure Synapse Analytics Spark, and are pleased to announce substantial improvements that could increase Spark performance by as much as 77%.
Performance Metrics
Our internal testing, utilizing the 1TB TPC-H industry standard benchmark, indicates performance gains of up to 77%. It’s important to note that individual workloads may vary, but the enhancements are designed to benefit all Azure Synapse Analytics Spark users.
Technological Foundations
This performance uptick is attributable to our transition to the latest Azure v5 Virtual Machines. These VMs bring improved CPU performance, increased SSD throughput, and elevated remote storage IOPS.
Regional Availability
We have implemented these performance improvements in the following regions, bold indicates a new region:
Australia East
Australia Southeast
Canada Central
Canada East
Central India
Germany West Central
Japan West
Korea Central
Poland Central
South Africa North
South India
Sweden Central
Switzerland North
Switzerland West
UAE North
UK South
UK West
West Central US
Additionally, all Microsoft Fabric regions, with the exception of Qatar Central, are already operating with these enhanced performance capabilities.
Future Rollout
The global rollout of these improvements is an ongoing process and expected to take several quarters to complete. We will provide updates as additional regions are upgraded. Customers in updated regions will automatically benefit from the performance enhancements at no additional cost.
Next Steps for Users
No action is required on your part to benefit from these improvements. Once your region receives the upgrade, you may notice reduced job completion times. If cost-efficiency is a priority, you may opt to decrease node size or the number of nodes while maintaining improved performance levels.
Learn more about Optimizing Spark performance, Apache Spark pool configurations, Spark compute for Data Engineering and Data Science – Microsoft Fabric
Microsoft Tech Community – Latest Blogs –Read More
Enhanced Performance in Additional Regions: Azure Synapse Analytics Spark Boosted by up to 77%
We are committed to continually advancing the capabilities of Azure Synapse Analytics Spark, and are pleased to announce substantial improvements that could increase Spark performance by as much as 77%.
Performance Metrics
Our internal testing, utilizing the 1TB TPC-H industry standard benchmark, indicates performance gains of up to 77%. It’s important to note that individual workloads may vary, but the enhancements are designed to benefit all Azure Synapse Analytics Spark users.
Technological Foundations
This performance uptick is attributable to our transition to the latest Azure v5 Virtual Machines. These VMs bring improved CPU performance, increased SSD throughput, and elevated remote storage IOPS.
Regional Availability
We have implemented these performance improvements in the following regions, bold indicates a new region:
Australia East
Australia Southeast
Canada Central
Canada East
Central India
Germany West Central
Japan West
Korea Central
Poland Central
South Africa North
South India
Sweden Central
Switzerland North
Switzerland West
UAE North
UK South
UK West
West Central US
Additionally, all Microsoft Fabric regions, with the exception of Qatar Central, are already operating with these enhanced performance capabilities.
Future Rollout
The global rollout of these improvements is an ongoing process and expected to take several quarters to complete. We will provide updates as additional regions are upgraded. Customers in updated regions will automatically benefit from the performance enhancements at no additional cost.
Next Steps for Users
No action is required on your part to benefit from these improvements. Once your region receives the upgrade, you may notice reduced job completion times. If cost-efficiency is a priority, you may opt to decrease node size or the number of nodes while maintaining improved performance levels.
Learn more about Optimizing Spark performance, Apache Spark pool configurations, Spark compute for Data Engineering and Data Science – Microsoft Fabric
Microsoft Tech Community – Latest Blogs –Read More
Enhanced Performance in Additional Regions: Azure Synapse Analytics Spark Boosted by up to 77%
We are committed to continually advancing the capabilities of Azure Synapse Analytics Spark, and are pleased to announce substantial improvements that could increase Spark performance by as much as 77%.
Performance Metrics
Our internal testing, utilizing the 1TB TPC-H industry standard benchmark, indicates performance gains of up to 77%. It’s important to note that individual workloads may vary, but the enhancements are designed to benefit all Azure Synapse Analytics Spark users.
Technological Foundations
This performance uptick is attributable to our transition to the latest Azure v5 Virtual Machines. These VMs bring improved CPU performance, increased SSD throughput, and elevated remote storage IOPS.
Regional Availability
We have implemented these performance improvements in the following regions, bold indicates a new region:
Australia East
Australia Southeast
Canada Central
Canada East
Central India
Germany West Central
Japan West
Korea Central
Poland Central
South Africa North
South India
Sweden Central
Switzerland North
Switzerland West
UAE North
UK South
UK West
West Central US
Additionally, all Microsoft Fabric regions, with the exception of Qatar Central, are already operating with these enhanced performance capabilities.
Future Rollout
The global rollout of these improvements is an ongoing process and expected to take several quarters to complete. We will provide updates as additional regions are upgraded. Customers in updated regions will automatically benefit from the performance enhancements at no additional cost.
Next Steps for Users
No action is required on your part to benefit from these improvements. Once your region receives the upgrade, you may notice reduced job completion times. If cost-efficiency is a priority, you may opt to decrease node size or the number of nodes while maintaining improved performance levels.
Learn more about Optimizing Spark performance, Apache Spark pool configurations, Spark compute for Data Engineering and Data Science – Microsoft Fabric
Microsoft Tech Community – Latest Blogs –Read More
Enhanced Performance in Additional Regions: Azure Synapse Analytics Spark Boosted by up to 77%
We are committed to continually advancing the capabilities of Azure Synapse Analytics Spark, and are pleased to announce substantial improvements that could increase Spark performance by as much as 77%.
Performance Metrics
Our internal testing, utilizing the 1TB TPC-H industry standard benchmark, indicates performance gains of up to 77%. It’s important to note that individual workloads may vary, but the enhancements are designed to benefit all Azure Synapse Analytics Spark users.
Technological Foundations
This performance uptick is attributable to our transition to the latest Azure v5 Virtual Machines. These VMs bring improved CPU performance, increased SSD throughput, and elevated remote storage IOPS.
Regional Availability
We have implemented these performance improvements in the following regions, bold indicates a new region:
Australia East
Australia Southeast
Canada Central
Canada East
Central India
Germany West Central
Japan West
Korea Central
Poland Central
South Africa North
South India
Sweden Central
Switzerland North
Switzerland West
UAE North
UK South
UK West
West Central US
Additionally, all Microsoft Fabric regions, with the exception of Qatar Central, are already operating with these enhanced performance capabilities.
Future Rollout
The global rollout of these improvements is an ongoing process and expected to take several quarters to complete. We will provide updates as additional regions are upgraded. Customers in updated regions will automatically benefit from the performance enhancements at no additional cost.
Next Steps for Users
No action is required on your part to benefit from these improvements. Once your region receives the upgrade, you may notice reduced job completion times. If cost-efficiency is a priority, you may opt to decrease node size or the number of nodes while maintaining improved performance levels.
Learn more about Optimizing Spark performance, Apache Spark pool configurations, Spark compute for Data Engineering and Data Science – Microsoft Fabric
Microsoft Tech Community – Latest Blogs –Read More
Enhanced Performance in Additional Regions: Azure Synapse Analytics Spark Boosted by up to 77%
We are committed to continually advancing the capabilities of Azure Synapse Analytics Spark, and are pleased to announce substantial improvements that could increase Spark performance by as much as 77%.
Performance Metrics
Our internal testing, utilizing the 1TB TPC-H industry standard benchmark, indicates performance gains of up to 77%. It’s important to note that individual workloads may vary, but the enhancements are designed to benefit all Azure Synapse Analytics Spark users.
Technological Foundations
This performance uptick is attributable to our transition to the latest Azure v5 Virtual Machines. These VMs bring improved CPU performance, increased SSD throughput, and elevated remote storage IOPS.
Regional Availability
We have implemented these performance improvements in the following regions, bold indicates a new region:
Australia East
Australia Southeast
Canada Central
Canada East
Central India
Germany West Central
Japan West
Korea Central
Poland Central
South Africa North
South India
Sweden Central
Switzerland North
Switzerland West
UAE North
UK South
UK West
West Central US
Additionally, all Microsoft Fabric regions, with the exception of Qatar Central, are already operating with these enhanced performance capabilities.
Future Rollout
The global rollout of these improvements is an ongoing process and expected to take several quarters to complete. We will provide updates as additional regions are upgraded. Customers in updated regions will automatically benefit from the performance enhancements at no additional cost.
Next Steps for Users
No action is required on your part to benefit from these improvements. Once your region receives the upgrade, you may notice reduced job completion times. If cost-efficiency is a priority, you may opt to decrease node size or the number of nodes while maintaining improved performance levels.
Learn more about Optimizing Spark performance, Apache Spark pool configurations, Spark compute for Data Engineering and Data Science – Microsoft Fabric
Microsoft Tech Community – Latest Blogs –Read More
Stop Worrying and Love the Outage, Vol II: DCs, custom ports, and Firewalls/ACLs
Hello, it’s Chris Cartwright from the Directory Services support team again. This is the second entry in a series where I try to provide the IT community with some tools and verbiage that will hopefully save you and your business many hours, dollars and frustrations. Here we’re going to focus on some major direct and/or indirect changes to Active Directory that tend be pushed onto AD administrators. I want to arm you with the knowledge required for those conversations, and hopefully some successful deflection. After all, isn’t it better to learn the hard lessons from others, if you can?
Periodically, we get cases for replication failures, many times, involving lingering objects. Almost without fail, the cause is one of the following reasons:
DNS
SACL/DACL size
Network communication issues
Network communications issues almost always come down to a “blinky box” in the middle that is doing something it shouldn’t be, whether due to defective hardware/software, misconfiguration or the ever-present misguided configuration. Today, we’re going to focus on the third, a misguided configuration. That is to say, the things that your compliancy section has said must be done, that have little to no security benefit, but can easily result in a multi-hour, multi-day, or even (yes) multi-long outage. To be fair, the portents of an outage should be readily apparent with any monitoring in place. However, sometimes reporting agents are not installed, fail to function properly, or misconfigured or events themselves are missed (alert fatigue). So, one of things to do when compliancy starts talking about locking down DC communications is to ask them…
What is the problem you are trying to solve?
Have you been asked to isolate DCs? Create a lag site? Make sure that X DCs can only replicate with Y DCs?
The primary effect of doing any of this is alert fatigue for replication errors, which is a path to outage later. Additionally, if you have “Bridge all site links” enabled, you are giving the KCC the wrong information to create site links.
Don’t permanently isolate DCs
Don’t create lag sites
Do make sure you have backups in place
Do make sure KCC has the correct information, and then let it be unless your network topology changes.
Do make sure all DCs in the forest can reach all DCs in the forest (If your networks are fully routable)
Have you been asked to configure DCs to restrict the RPC ports they can use?
Every AD administrator should be familiar with the firewall ports and how RPC works. By default, DCs will register on these port ranges and listen for traffic. The RPC Endpoint Mapper keeps track of these ports and tells incoming requests where to go. One thing that RPC Endpoint Mapper will not do is keep track of firewall or ACL changes that were made.
Again, what is the security benefit here? It is one thing to control DC communications outbound from the perimeter. It is another thing to suggest that X port is more secure than Y port, especially when we’re talking about ports upon which DCs are listening. If your compliancy team is worried about rogue applications listening on DCs, you have bigger problems..like rogue applications existing on your DCs, presumably put there by rogue agents who now have control over your entire Active Directory.
The primary effect of “locking down” a DC in this way is not to improve security, but to mandate the creation or modification of some document with fine print, “Don’t forget to add these registry keys to avoid an outage”, that will inevitably be lost during turnover. Furthermore, going too far can lead to port exhaustion, another type of outage.
Don’t restrict AD/Netlogon to static ports without exhaustively discussing the risks involved, and heavily documenting it.
Don’t restrict the RPC dynamic range without exhaustively discussing the risks involved, and heavily documenting it.
Do restrict inbound/outbound perimeter traffic to your DCs.
“Hey, you said multi-day or multi-week outages. It’s not that hard to fix replication!”
It is true that once you’ve found the network issue preventing replication that it is usually an easy fix. However, if the “easy” fix is to rehost all your global catalog partitions with tens of thousands of objects on 90+ DCs, requiring manual administrative intervention, and a specific sequence of commands because your environment is filled with lingering objects, you’re going to be busy for a while.
Wrapping it up
As the venerable Aaron Margosis said, “…if you stick with the Windows defaults wherever possible or industry-standard configurations such as the Microsoft Windows security guidance or the USGCB, and use proven enterprise management technologies instead of creating and maintaining your own, you will increase flexibility, reduce costs, and be better able to focus on your organization’s real mission.”
Security is critical in this day and age, but so is understanding the implications and reasons beyond some check box on an audit document. Monitoring is also critical, but of little use if polluted with noise. Remember who will be mainlining caffeine all night to get operations back online when the lingering objects start rolling in, because it will not be the people that click the “scan” button once a month…
References
Creating a Site Link Bridge Design | Microsoft Learn
You Are Not Smarter Than The KCC | Microsoft Learn
Configure firewall for AD domain and trusts – Windows Server | Microsoft Learn
RPC over IT/Pro – Microsoft Community Hub
Remote Procedure Call (RPC) dynamic port work with firewalls – Windows Server | Microsoft Learn
Restrict Active Directory RPC traffic to a specific port – Windows Server | Microsoft Learn
10 Immutable Laws of Security | Microsoft Learn
Sticking with Well-Known and Proven Solutions | Microsoft Learn
Chris “Was it really worth it” Cartwright
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Azure DevOps blog closing -> moving to DevBlogs
Hello! We will be closing this Azure DevOps blog soon on Tech Community as part of consolidation efforts. We appreciate your continued readership and interest in this topic.
For Azure DevOps blog posts (including the last 10 posted here), please go here: Azure DevOps Blog (microsoft.com)
Microsoft Tech Community – Latest Blogs –Read More
Azure DevOps blog closing -> moving to DevBlogs
Hello! We will be closing this Azure DevOps blog soon on Tech Community as part of consolidation efforts. We appreciate your continued readership and interest in this topic.
For Azure DevOps blog posts (including the last 10 posted here), please go here: Azure DevOps Blog (microsoft.com)
Microsoft Tech Community – Latest Blogs –Read More
Creating Intelligent Apps on App Service with .NET
You can use Azure App Service to work with popular AI frameworks like LangChain and Semantic Kernel connected to OpenAI for creating intelligent apps. In the following tutorial we will be adding an Azure OpenAI service using Semantic Kernel to a .NET 8 Blazor web application.
Prerequisites
An Azure OpenAI resource or an OpenAI account.
A .NET 8 Blazor Web App. Create the application with a template here.
Setup Blazor web app
For this Blazor web application, we’ll be building off the Blazor template and creating a new razor page that can send and receive requests to an Azure OpenAI OR OpenAI service using Semantic Kernel.
Right click on the Pages folder found under the Components folder and add a new item named OpenAI.razor
Add the following code to the ****OpenAI.razor file and click Save
“/openai”
@rendermode InteractiveServer
<PageTitle>Open AI</PageTitle>
<h3>Open AI Query</h3>
<input placeholder=”Input query” @bind=”newQuery” />
<button class=”btn btn-primary” @onclick=”SemanticKernelClient”>Send Request</button>
<br />
<h4>Server response:</h4> <p>@serverResponse</p>
@code {
public string? newQuery;
public string? serverResponse;
}
Next, we’ll need to add the new page to the navigation so we can navigate to the service.
Go to the NavMenu.razor file under the Layout folder and add the following div in the nav class. Click Save
<div class=”nav-item px-3″>
<NavLink class=”nav-link” href=”openai”>
<span class=”bi bi-list-nested-nav-menu” aria-hidden=”true”></span> Open AI
</NavLink>
</div>
After the Navigation is updated, we can start preparing to build the OpenAI client to handle our requests.
API Keys and Endpoints
In order to make calls to OpenAI with your client, you will need to first grab the Keys and Endpoint values from Azure OpenAI or OpenAI and add them as secrets for use in your application. Retrieve and save the values for later use.
For Azure OpenAI, see this documentation to retrieve the key and endpoint values. For our application, you will need the following values:
deploymentName
endpoint
apiKey
modelId
For OpenAI, see this documentation to retrieve the api keys. For our application, you will need the following values:
apiKey
modelId
Since we’ll be deploying to App Service we can secure these secrets in Azure Key Vault for protection. Follow the Quickstart to setup your Key Vault and add the secrets you saved from earlier.
Next, we can use Key Vault references as app settings in our App Service resource to reference in our application. Follow the instructions in the documentation to grant your app access to your Key Vault and to setup Key Vault references.
Then, go to the portal Environment Variables blade in your resource and add the following app settings:
For Azure OpenAI, use the following:
DEPOYMENT_NAME = @microsoft.KeyVault(SecretUri=https://myvault.vault.azure.net/secrets/mysecret/)
ENDPOINT = @microsoft.KeyVault(SecretUri=https://myvault.vault.azure.net/secrets/mysecret/)
API_KEY = @microsoft.KeyVault(SecretUri=https://myvault.vault.azure.net/secrets/mysecret/)
MODEL_ID = @microsoft.KeyVault(SecretUri=https://myvault.vault.azure.net/secrets/mysecret/)
For OpenAI, use the following:
OPENAI_API_KEY = @microsoft.KeyVault(SecretUri=https://myvault.vault.azure.net/secrets/mysecret/)
OPENAI_MODEL_ID = @microsoft.KeyVault(SecretUri=https://myvault.vault.azure.net/secrets/mysecret/)
Once your app settings are saved, you can bring them into the code by injecting IConfiguration and referencing the app settings. Add the following code to your OpenAI.razor file:
@inject Microsoft.Extensions.Configuration.IConfiguration _config
@code {
private async Task SemanticKernelClient()
{
string deploymentName = _config[“DEPLOYMENT_NAME”];
string endpoint = _config[“ENDPOINT”];
string apiKey = _config[“API_KEY”];
string modelId = _config[“MODEL_ID”];
// OpenAI
string OpenAIModelId = _config[“OPENAI_MODEL_ID”];
string OpenAIApiKey = _config[“OPENAI_API_KEY”];
}
Semantic Kernel
Semantic Kernel is an open-source SDK that enables you to easily develop AI agents to work with your existing code. You can use Semantic Kernel with Azure OpenAI and OpenAI models.
To create the OpenAI client, we’ll first start by installing Semantic Kernel.
To install Semantic Kernel, browse the NuGet package manager in Visual Studio and install the Microsoft.SemanticKernel package. For NuGet Package Manager instructions, see here. For CLI instructions, see here.
Once the Semantic Kernel package is installed, you can now initialize the kernel.
Initialize the Kernel
To initialize the Kernel, add the following code to the OpenAI.razor file.
@code {
@using Microsoft.SemanticKernel;
private async Task SemanticKernelClient()
{
var builder = Kernel.CreateBuilder();
var kernel = builder.Build();
}
}
Here we are adding the using statement and creating the Kernel in a method that we can use when we send the request to the service.
Add your AI service
Once the Kernel is initialized, we can add our chosen AI service to the kernel. Here we will define our model and pass in our key and endpoint information to be consumed by the chosen model.
For Azure OpenAI, use the following code:
var builder = Kernel.CreateBuilder();
builder.Services.AddAzureOpenAIChatCompletion(
deploymentName: deploymentName,
endpoint: endpoint,
apiKey: apiKey,
modelId: modelId
);
var kernel = builder.Build();
For OpenAI, use the following code:
var builder = Kernel.CreateBuilder();
builder.Services.AddOpenAIChatCompletion(
modelId: OpenAIModelId,
apiKey: OpenAIApiKey,
);
var kernel = builder.Build();
Configure prompt and create Semantic function
Now that our chosen OpenAI service client is created with the correct keys we can add a function to handle the prompt. With Semantic Kernel you can handle prompts by the use of a semantic functions, which turn the prompt and the prompt configuration settings into a function the Kernel can execute. Learn more on configuring prompts here.
First, we’ll create a variable that will hold the users prompt. Then add a function with execution settings to handle and configure the prompt. Add the following code to the OpenAI.razor file:
@using Microsoft.SemanticKernel.Connectors.OpenAI
private async Task SemanticKernelClient()
{
var builder = Kernel.CreateBuilder();
builder.Services.AddAzureOpenAIChatCompletion(
deploymentName: deploymentName,
endpoint: endpoint,
apiKey: apiKey,
modelId: modelId
);
var kernel = builder.Build();
var prompt = @”{{$input}} ” + newQuery;
var summarize = kernel.CreateFunctionFromPrompt(prompt, executionSettings: new OpenAIPromptExecutionSettings { MaxTokens = 100, Temperature = 0.2 });
}
Lastly, we’ll need to invoke the function and return the response. Add the following to the OpenAI.razor file:
private async Task SemanticKernelClient()
{
var builder = Kernel.CreateBuilder();
builder.Services.AddAzureOpenAIChatCompletion(
deploymentName: deploymentName,
endpoint: endpoint,
apiKey: apiKey,
modelId: modelId
);
var kernel = builder.Build();
var prompt = @”{{$input}} ” + newQuery;
var summarize = kernel.CreateFunctionFromPrompt(prompt, executionSettings: new OpenAIPromptExecutionSettings { MaxTokens = 100, Temperature = 0.2 })
var result = await kernel.InvokeAsync(summarize);
serverResponse = result.ToString();
}
Here is the example in it’s completed form. In this example, use the Azure OpenAI chat completion service OR the OpenAI chat completion service, not both.
“/openai”
@rendermode InteractiveServer
@inject Microsoft.Extensions.Configuration.IConfiguration _config
<PageTitle>OpenAI</PageTitle>
<h3>OpenAI input query: </h3>
<input class=”col-sm-4″ @bind=”newQuery” />
<button class=”btn btn-primary” @onclick=”SemanticKernelClient”>Send Request</button>
<br />
<br />
<h4>Server response:</h4> <p>@serverResponse</p>
@code {
@using Microsoft.SemanticKernel;
@using Microsoft.SemanticKernel.Connectors.OpenAI
private string? newQuery;
private string? serverResponse;
private async Task SemanticKernelClient()
{
// Azure OpenAI
string deploymentName = _config[“DEPLOYMENT_NAME”];
string endpoint = _config[“ENDPOINT”];
string apiKey = _config[“API_KEY”];
string modelId = _config[“MODEL_ID”];
// OpenAI
// string OpenAIModelId = _config[“OPENAI_DEPLOYMENT_NAME”];
// string OpenAIApiKey = _config[“OPENAI_API_KEY”];
// Semantic Kernel client
var builder = Kernel.CreateBuilder();
// Azure OpenAI
builder.Services.AddAzureOpenAIChatCompletion(
deploymentName: deploymentName,
endpoint: endpoint,
apiKey: apiKey,
modelId: modelId
);
// OpenAI
// builder.Services.AddOpenAIChatCompletion(
// modelId: OpenAIModelId,
// apiKey: OpenAIApiKey
// );
var kernel = builder.Build();
var prompt = @”{{$input}} ” + newQuery;
var summarize = kernel.CreateFunctionFromPrompt(prompt, executionSettings: new OpenAIPromptExecutionSettings { MaxTokens = 100, Temperature = 0.2 });
var result = await kernel.InvokeAsync(summarize);
serverResponse = result.ToString();
}
}
Now save the application and follow the next steps to deploy it to App Service. If you would like to test it locally first at this step, you can swap out the config values at with the literal string values of your OpenAI service. For example: string modelId = “gpt-4-turbo”;
Deploy to App Service
If you have followed the steps above, you are ready to deploy to App Service. If you run into any issues remember that you need to have done the following: grant your app access to your Key Vault, add the app settings with key vault references as your values. App Service will resolve the app settings in your application that match what you’ve added in the portal.
Authentication
Although optional, it is highly recommended that you also add authentication to your web app when using an Azure OpenAI or OpenAI service. This can add a level of security with no additional code. Learn how to enable authentication for your web app here.
Once deployed, browse to the web app and navigate to the Open AI tab. Enter a query to the service and you should see a populated response from the server. The tutorial is now complete and you now know how to use OpenAI services to create intelligent applications.
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