Tag Archives: microsoft-azure

Microsoft Azure expands its NoSQL portfolio with Managed Instances for Apache Cassandra

Posted on by

At its Ignite conference today, Microsoft announced the launch of Azure Managed Instance for Apache Cassandra, its latest NoSQL database offering and a competitor to Cassandra-centric companies like Datastax. Microsoft describes the new service as a ‘semi-managed offering that will help companies bring more of their Cassandra-based workloads into its cloud.

“Customers can easily take on-prem Cassandra workloads and add limitless cloud scale while maintaining full compatibility with the latest version of Apache Cassandra,” Microsoft explains in its press materials. “Their deployments gain improved performance and availability, while benefiting from Azure’s security and compliance capabilities.”

Like its counterpart, Azure SQL Manages Instance, the idea here is to give users access to a scalable, cloud-based database service. To use Cassandra in Azure before, businesses had to either move to Cosmos DB, its highly scalable database service which supports the Cassandra, MongoDB, SQL and Gremlin APIs, or manage their own fleet of virtual machines or on-premises infrastructure.

Cassandra was originally developed at Facebook and then open-sourced in 2008. A year later, it joined the Apache Foundation and today it’s used widely across the industry, with companies like Apple and Netflix betting on it for some of their core services, for example. AWS launched a managed Cassandra-compatible service at its re:Invent conference in 2019 (it’s called Amazon Keyspaces today), Microsoft only launched the Cassandra API for Cosmos DB last November. With today’s announcement, though, the company can now offer a full range of Cassandra-based servicer for enterprises that want to move these workloads to its cloud.


By Frederic Lardinois

Microsoft challenges Twilio with the launch of Azure Communication Services

Posted on by

Microsoft today announced the launch of Azure Communication Services, a new set of features in its cloud that enable developers to add voice and video calling, chat and text messages to their apps, as well as old-school telephony.

The company describes the new set of services as the “first fully managed communication platform offering from a major cloud provider,” and that seems right, given that Google and AWS offer some of these features, including the AWS notification service, for example, but not as part of a cohesive communication service. Indeed, it seems Azure Communication Service is more of a competitor to the core features of Twilio or up-and-coming MessageBird.

Over the course of the last few years, Microsoft has built up a lot of experience in this area, in large parts thanks to the success of its Teams service. Unsurprisingly, that’s something Microsoft is also playing up in its announcement.

“Azure Communication Services is built natively on top a global, reliable cloud — Azure. Businesses can confidently build and deploy on the same low latency global communication network used by Microsoft Teams to support 5B+ meeting minutes daily,” writes Scott Van Vliet, corporate vice president for Intelligent Communication at the company.

Microsoft also stresses that it offers a set of additional smart services that developers can tap into to build out their communication services, including its translation tools, for example. The company also notes that its services are encrypted to meet HIPPA and GDPR standards.

Like similar services, developers access the various capabilities through a set of new APIs and SDKs.

As for the core services, the capabilities here are pretty much what you’d expect. There’s voice and video calling (and the ability to shift between them). There’s support for chat and, starting in October, users will also be able to send text messages. Microsoft says developers will be able to send these to users anywhere, with Microsoft positioning it as a global service.

Provisioning phone numbers, too, is part of the services and developers will be able to provision those for in-bound and out-bound calls, port existing numbers, request new ones and — most importantly for contact-center users — integrate them with existing on-premises equipment and carrier networks.

“Our goal is to meet businesses where they are and provide solutions to help them be resilient and move their business forward in today’s market,” writes Van Vliet. “We see rich communication experiences – enabled by voice, video, chat, and SMS – continuing to be an integral part in how businesses connect with their customers across devices and platforms.”


By Frederic Lardinois

Microsoft brings data services to its Arc multi-cloud management service

Posted on by

Microsoft today launched a major update to its Arc multi-cloud service that allows Azure customers to run and manage workloads across clouds — including those of Microsoft’s competitors — and their on on-premises data centers. First announced at Microsoft Ignite in 2019, Arc was always meant to not just help users manage their servers but to also allow them to run data services like Azure SQL and Azure Database for PostgreSQL close to where their data sits.

Today, the company is making good on this promise with the preview launch of Azure Arc enabled data services with support for, as expected, Azure SQL and Azure Database for PostgreSQL.

In addition, Microsoft is making the core feature of Arc, Arc enabled servers, generally available. These are the tools at the core of the service that allow enterprises can use the standard Azure Portal to manage and monitor their Windows and Linux servers across their multi-cloud and edge environments.

Image Credits: Microsoft

“We’ve always known that enterprises are looking to unlock the agility of the cloud — they love the app model, they love the business model — while balancing a need to maintain certain applications and workloads on premises,” Rohan Kumar, Microsoft’s corporate VP for Azure Data said. “A lot of customers actually have a multi-cloud strategy. In some cases, they need to keep the data specifically for regulatory compliance. And in many cases, they want to maximize their existing investments. They’ve spent a lot of CapEx.”

As Kumar stressed, Microsoft wants to meet customers where they are, without forcing them to adopt a container architecture, for example, or replace their specialized engineered appliances to use Arc.

“Hybrid is really [about] providing that flexible choice to our customers, meeting them where they are, and not prescribing a solution,” he said.

He admitted that this approach makes engineering the solution more difficult, but the team decided that the baseline should be a container endpoint and nothing more. And for the most part, Microsoft packaged up the tools its own engineers were already using to run Azure services on the company’s own infrastructure to manage these services in a multi-cloud environment.

“In hindsight, it was a little challenging at the beginning, because, you can imagine, when we initially built them, we didn’t imagine that we’ll be packaging them like this. But it’s a very modern design point,” Kumar said. But the result is that supporting customers is now relatively easy because it’s so similar to what the team does in Azure, too.

Kumar noted that one of the selling points for the Azure Data Services is also that the version of Azure SQL is essentially evergreen, allowing them to stop worrying about SQL Server licensing and end-of-life support questions.

You can now use Azure to manage resources anywhere, including on AWS and Google Cloud


By Frederic Lardinois

Google Cloud’s new BigQuery Omni will let developers query data in GCP, AWS and Azure

Posted on by

At its virtual Cloud Next ’20 event, Google today announced a number of updates to its cloud portfolio, but the public alpha launch of BigQuery Omni is probably the highlight of this year’s event. Powered by Google Cloud’s Anthos hybrid-cloud platform, BigQuery Omni allows developers to use the BigQuery engine to analyze data that sits in multiple clouds, including those of Google Cloud competitors like AWS and Microsoft Azure — though for now, the service only supports AWS, with Azure support coming later.

Using a unified interface, developers can analyze this data locally without having to move data sets between platforms.

“Our customers store petabytes of information in BigQuery, with the knowledge that it is safe and that it’s protected,” said Debanjan Saha, the GM and VP of Engineering for Data Analytics at Google Cloud, in a press conference ahead of today’s announcement. “A lot of our customers do many different types of analytics in BigQuery. For example, they use the built-in machine learning capabilities to run real-time analytics and predictive analytics. […] A lot of our customers who are very excited about using BigQuery in GCP are also asking, ‘how can they extend the use of BigQuery to other clouds?’ ”

Image Credits: Google

Google has long said that it believes that multi-cloud is the future — something that most of its competitors would probably agree with, though they all would obviously like you to use their tools, even if the data sits in other clouds or is generated off-platform. It’s the tools and services that help businesses to make use of all of this data, after all, where the different vendors can differentiate themselves from each other. Maybe it’s no surprise then, given Google Cloud’s expertise in data analytics, that BigQuery is now joining the multi-cloud fray.

“With BigQuery Omni customers get what they wanted,” Saha said. “They wanted to analyze their data no matter where the data sits and they get it today with BigQuery Omni.”

Image Credits: Google

He noted that Google Cloud believes that this will help enterprises break down their data silos and gain new insights into their data, all while allowing developers and analysts to use a standard SQL interface.

Today’s announcement is also a good example of how Google’s bet on Anthos is paying off by making it easier for the company to not just allow its customers to manage their multi-cloud deployments but also to extend the reach of its own products across clouds. This also explains why BigQuery Omni isn’t available for Azure yet, given that Anthos for Azure is still in preview, while AWS support became generally available in April.


By Frederic Lardinois

Microsoft launches Azure Synapse Link to help enterprises get faster insights from their data

Posted on by

At its Build developer conference, Microsoft today announced Azure Synapse Link, a new enterprise service that allows businesses to analyze their data faster and more efficiently, using an approach that’s generally called ‘hybrid transaction/analytical processing’ (HTAP). That’s a mouthful, it essentially enables enterprises to use the same database system for analytical and transactional workloads on a single system. Traditionally, enterprises had to make some tradeoffs between either building a single system for both that was often highly over-provisioned or to maintain separate systems for transactional and analytics workloads.

Last year, at its Ignite conference, Microsoft announced Azure Synapse Analytics, an analytics service that combines analytics and data warehousing to create what the company calls “the next evolution of Azure SQL Data Warehouse.” Synapse Analytics brings together data from Microsoft’s services and those from its partners and makes it easier to analyze.

“One of the key things, as we work with our customers on their digital transformation journey, there is an aspect of being data-driven, of being insights-driven as a culture, and a key part of that really is that once you decide there is some amount of information or insights that you need, how quickly are you able to get to that? For us, time to insight and a secondary element, which is the cost it takes, the effort it takes to build these pipelines and maintain them with an end-to-end analytics solution, was a key metric we have been observing for multiple years from our largest enterprise customers,” said Rohan Kumar, Microsoft’s corporate VP for Azure Data.

Synapse Link takes the work Microsoft did on Synaps Analytics a step further by removing the barriers between Azure’s operational databases and Synapse Analytics, so enterprises can immediately get value from the data in those databases without going through a data warehouse first.

“What we are announcing with Synapse Link is the next major step in the same vision that we had around reducing the time to insight,” explained Kumar. “And in this particular case, a long-standing barrier that exists today between operational databases and analytics systems is these complex ETL (extract, transform, load) pipelines that need to be set up just so you can do basic operational reporting or where, in a very transactionally consistent way, you need to move data from your operational system to the analytics system, because you don’t want impact the performance of the operational system in any way because that’s typically dealing with, depending on the system, millions of transactions per second.”

ETL pipelines, Kumar argued, are typically expensive and hard to build and maintain, yet enterprises are now building new apps — and maybe even line of business mobile apps — where any action that consumers take and that is registered in the operational database is immediately available for predictive analytics, for example.

From the user perspective, enabling this only takes a single click to link the two, while it removes the need for managing additional data pipelines or database resources. That, Kumar said, was always the main goal for Synapse Link. “With a single click, you should be able to enable real-time analytics on you operational data in ways that don’t have any impact on your operational systems, so you’re not using the compute part of your operational system to do the query, you actually have to transform the data into a columnar format, which is more adaptable for analytics, and that’s really what we achieved with Synapse Link.”

Because traditional HTAP systems on-premises typically share their compute resources with the operational database, those systems never quite took off, Kumar argued. In the cloud, with Synapse Link, though, that impact doesn’t exist because you’re dealing with two separate systems. Now, once a transaction gets committed to the operational database, the Synapse Link system transforms the data into a columnar format that is more optimized for the analytics system — and it does so in real time.

For now, Synapse Link is only available in conjunction with Microsoft’s Cosmos DB database. As Kumar told me, that’s because that’s where the company saw the highest demand for this kind of service, but you can expect the company to add support for available in Azure SQL, Azure Database for PostgreSQL and Azure Database for MySQL in the future.

Microsoft’s Azure Synapse Analytics bridges the gap between data lakes and warehouses


By Frederic Lardinois

Google Cloud’s fully-managed Anthos is now generally available for AWS

Posted on by

A year ago, back in the days of in-person conferences, Google officially announced the launch of its Anthos multi-cloud application modernization platform at its Cloud Next conference. The promise of Anthos was always that it would allow enterprises to write their applications once, package them into containers and then manage their multi-cloud deployments across GCP, AWS, Azure and their on-prem data centers.

Until now, support for AWS and Azure was only available in preview, but today, the company is making support for AWS and on-premises generally available. Microsoft Azure support remains in preview, though.

“As an AWS customer now, or a GCP customer, or a multi-cloud customer, […] you can now run Anthos on those environments in a consistent way, so you don’t have to learn any proprietary APIs and be locked in,” Eyal Manor, the VP of engineering in charge of Anthos, told me. “And for the first time, we enable the portability between different infrastructure environments as opposed to what has happened in the past where you were locked into a set of API’s.”

Manor stressed that Anthos was designed to be multi-cloud from day one. As for why AWS support is launching ahead of Azure, Manor said that there was simply more demand for it. “We surveyed the customers and they said, hey, we want, in addition to GCP, we want AWS,” he said. But support for Azure will come later this year and the company already has a number of preview customers for it. In addition, Anthos will also come to bare metal servers in the future.

Looking even further ahead, Manor also noted that better support for machine learning workloads in on the way. Many businesses, after all, want to be able to update and run their models right where their data resides, no matter what cloud that may be. There, too, the promise of Anthos is that developers can write the application once and then run it anywhere.

“I think a lot of the initial response and excitement was from the developer audiences,” Jennifer Lin, Google Cloud’s VP of product management, told me. “Eric Brewer had led a white paper that we did to say that a lot of the Anthos architecture sort of decouples the developer and the operator stakeholder concerns. There hadn’t been a multi-cloud shared software architecture where we could do that and still drive emerging and existing applications with a common shared software stack.”

She also noted that a lot of Google Cloud’s ecosystem partners endorsed the overall Anthos architecture early on because they, too, wanted to be able to write once and run anywhere — and so do their customers.

Plaid is one of the launch partners for these new capabilities. “Our customers rely on us to be always available and as a result we have very high reliability requirements,” said Naohiko Takemura, Plaid’s head of engineering. “We pursued a multi-cloud strategy to ensure redundancy for our critical KARTE service. Google Cloud’s Anthos works seamlessly across GCP and our other cloud providers preventing any business disruption. Thanks to Anthos, we prevent vendor lock-in, avoid managing cloud-specific infrastructure, and our developers are not constrained by cloud providers.”

With this release, Google Cloud is also bringing deeper support for virtual machines to Anthos, as well as improved policy and configuration management.

Over the next few months, the Anthos Service Mesh will also add support for applications that run in traditional virtual machines. As Lin told me, “a lot of this is is about driving better agility and talking the complexity out of it so that we have abstractions that work across any environment, whether it’s legacy or new or on-prem or AWS or GCP.”

Google’s hybrid cloud platform is coming to AWS and Azure


By Frederic Lardinois

Tech giants should let startups defer cloud payments

Posted on by

Google, Amazon, and Microsoft are the landlords. Amidst the Coronavirus economic crisis, startups need a break from paying rent. They’re in a cash crunch. Revenue has stopped flowing in, capital markets like venture debt are hesitant, and startups and small-to-medium sized businessesf are at risk of either having to lay off huge numbers of employees and/or shut down.

Meanwhile, the tech giants are cash rich. Their success this decade means they’re able to weather the storm for a few months. Their customers cannot.

Cloud infrastructure costs area amongst many startups’ top expenses besides payroll. The option to pay these cloud bills later could save some from going out of business or axing huge parts of their staff. Both would hurt the tech industry, the economy, and the individuals laid off. But most worryingly for the giants, it could destroy their customer base.

The mass layoffs have already begun. Soon we’re sure to start hearing about sizable companies shutting down, upended by COVID-19. But there’s still an opportunity to stop a larger bloodbath from ensuing.

That’s why I have a proposal: cloud relief.

The platform giants should let startups and small businesses defer their cloud infrastructure payments for three to six months until they can pay them back in installments. Amazon AWS, Google Cloud, Microsoft Azure, these companies’ additional infrastructure products, and other platform providers should let customers pause payment until the worst of the first wave of the COVID-19 economic disruption passes. Profitable SAAS providers like Salesforce could give customers an extension too.

There are plenty of altruistic reasons to do this. They have the resources to help businesses in need. We all need to support each other in these tough times. This could protect tons of families. Some of these startups are providing important services to the public and even discounting them, thereby ramping up their bills while decreasing revenue.

Then there are the PR reasons. After years of techlash and anti-trust scrutiny, here’s the chance for the giants to prove their size can be beneficial to the world. Recruiters could use it as a talking point. “We’re the company that helped save Silicon Valley.” There’s an explanation for them squirreling away so much cash: the rainy day has finally arrived.

But the capitalistic truth and the story they could sell to Wall Street is that it’s not good for our business if our customers go out of business. Look at what happened to infrastructure providers in the dotcom crash. When tons of startups vaporized, so did the profits for those selling them hosting and tools. Any government stimulus for businesses would be better spent by them paying employees than paying the cloud companies that aren’t in danger. Saving one future Netflix from shutting down could cover any short-term loss from helping 100 other businesses.

This isn’t a handout. These startups will still owe the money. They’d just be able to pay it a little later, spread out over their monthly bills for a year or so. Once mass shelter-in-place orders subside, businesses can operate at least a little closer to normal, and investors get less cautious, customers will have the cash they need to pay their dues. Plus interest if necessary.

Meanwhile, they’ll be locked in and loyal customers for the foreseeable future. Cloud vendors could gate the deferment to only customers that have been with them for X amount of months or that have already spent Y amount on the platform. The vendors could also offer the deferment on the condition that customers add a year or more to their existing contracts. Founders will remember who gave them the benefit of the doubt.

cloud ice cream cone imagine

Consider it a marketing expense. Platforms often offer discounts or free trials to new customers. Now it’s existing customers that need a reprieve. Instead of airport ads, the giants could spend the money ensuring they’ll still have plenty of developers building atop them by the end of 2020.

Beyond deferred payment, platforms could just push the due date on all outstanding bills to three or six months from now. Alternatively, they could offer a deep discount such as 50% off for three months if they didn’t want to deal with accruing debt and then servicing it. Customers with multi-year contracts could offered the opportunity to downgrade or renegotiate their contracts without penalties. Any of these might require giving sales quota forgiveness to their account executives.

It would likely be far too complicated and risky to accept equity in lieu of cash, a cut of revenue going forward, or to provide loans or credit lines to customers. The clearest and simplest solution is to let startups skip a few payments, then pay more every month later until they clear their debt. When asked for comment or about whether they’re considering payment deferment options, Microsoft declined, and Amazon and Google did not respond.

To be clear, administering payment deferment won’t be simple or free. There are sure to be holes that cloud economists can poke in this proposal, but my goal is to get the conversation startup. It could require the giants to change their earnings guidance. Rewriting deals with significantly sized customers will take work on both ends, and there’s a chance of breach of contract disputes. Giants would face the threat of customers recklessly using cloud resources before shutting down or skipping town.

Most taxing would be determining and enforcing the criteria of who’s eligible. The vendors would need to lay out which customers are too big so they don’t accidentally give a cloud-intensive but healthy media company a deferment they don’t need. Businesses that get questionably excluded could make a stink in public. Executing on the plan will require staff when giants are stretched thin trying to handle logistics disruptions, misinformation, and accelerating work-from-home usage.

Still, this is the moment when the fortunate need to lend a hand to the vulnerable. Not a hand out, but a hand up. Companies with billions in cash in their coffers could save those struggling to pay salaries. All the fundraisers and info centers and hackathons are great, but this is how the tech giants can live up to their lofty mission statements.

We all live in the cloud now. Don’t evict us. #CloudRelief

—

Thanks to Falon Fatemi, Corey Quinn, Ilya Fushman, Jason Kim, Ilya Sukhar, and Michael Campbell for their ideas and feedback on this proposal


By Josh Constine

Microsoft Azure gets into ag tech with the preview of FarmBeats

Posted on by

At its annual Ignite event in Orlando, Fla., Microsoft today announced that  Azure FarmBeats, a project that until now was mostly a research effort, will be available as a public preview and in the Azure Marketplace, starting today. FarmBeats is Microsoft’s project that combines IoT sensors, data analysis and machine learning.

“The goal of FarmBeats is to augment farmers’ knowledge and intuition about their own farm with data and data-driven insights,” Microsoft explained in today’s announcement. The idea behind FarmBeats is to take in data from a wide variety of sources, including sensors, satellites, drones and weather stations, and then turn that into actionable intelligence for farmers, using AI and machine learning. 

In addition, FarmBeats also wants to be somewhat of a platform for developers who can then build their own applications on top of this data that the platform aggregates and evaluates.

As Microsoft noted during the development process, having satellite imagery is one thing, but that can’t capture all of the data on a farm. For that, you need in-field sensors and other data — yet all of this heterogeneous data then has to be merged and analyzed somehow. Farms also often don’t have great internet connectivity. Because of this, the FarmBeats team was among the first to leverage Microsoft’s efforts in using TV white space for connectivity and, of course, Azure IoT Edge for collecting all of the data.


By Frederic Lardinois

Microsoft’s Azure Synapse Analytics bridges the gap between data lakes and warehouses

Posted on by

At its annual Ignite conference in Orlando, Fla., Microsoft today announced a major new Azure service for enterprises: Azure Synapse Analytics, which Microsoft describes as “the next evolution of Azure SQL Data Warehouse.” Like SQL Data Warehouse, it aims to bridge the gap between data warehouses and data lakes, which are often completely separate. Synapse also taps into a wide variety of other Microsoft services, including Power BI and Azure Machine Learning, as well as a partner ecosystem that includes Databricks, Informatica, Accenture, Talend, Attunity, Pragmatic Works and Adatis. It’s also integrated with Apache Spark.

The idea here is that Synapse allows anybody working with data in those disparate places to manage and analyze it from within a single service. It can be used to analyze relational and unstructured data, using standard SQL.

Screen Shot 2019 10 31 at 10.11.48 AM

Microsoft also highlights Synapse’s integration with Power BI, its easy to use business intelligence and reporting tool, as well as Azure Machine Learning for building models.

With the Azure Synapse studio, the service provides data professionals with a single workspace for prepping and managing their data, as well as for their big data and AI tasks. There’s also a code-free environment for managing data pipelines.

As Microsoft stresses, businesses that want to adopt Synapse can continue to use their existing workloads in production with Synapse and automatically get all of the benefits of the service. “Businesses can put their data to work much more quickly, productively, and securely, pulling together insights from all data sources, data warehouses, and big data analytics systems,” writes Microsoft CVP of Azure Data, Rohan Kumar.

In a demo at Ignite, Kumar also benchmarked Synapse against Google’s BigQuery. Synapse ran the same query over a petabyte of data in 75% less time. He also noted that Synapse can handle thousands of concurrent users — unlike some of Microsoft’s competitors.


By Frederic Lardinois

Kadena brings free private blockchain service to Azure Marketplace

Posted on by

The hype around blockchain seems to have cooled a bit, but companies like Kadena have been working on enterprise-grade solutions for some time, and continue to push the technology forward. Today, the startup announced that Kadena Scalable Permissioned Blockchain on Azure is available for free in the Azure Marketplace.

Kadena co-founder and CEO Will Martino says today’s announcement builds on the success of last year’s similar endeavor involving AWS. “Our private chain is designed for enterprise use. It’s designed for being high performance is designed for integrating with traditional back ends. And by bringing that chain to AWS marketplace, and now to Microsoft Azure, we are servicing almost all of the enterprise blockchain market that takes place in the cloud,” Martino told TechCrunch.

The free product enables companies to get comfortable with the technology and build a Proof of Concept (PoC) without making a significant investment in the tooling. The free tool provides 2000 transactions a second across 4 nodes. Once companies figure this out and want to scale, that’s when the company begins making money, but Martino recognizes that the technology is still immature and companies need to get comfortable with it, and that’s what the free versions on the cloud platforms like Azure are encouraging.

Martino says Kadena favors a hybrid approach to enterprise blockchain that combines public and private chains, and in his view, gives customers the best of both worlds. “You can run a smart contract on our public chain Web protocol that will be launching on October 30th, and that smart contract can be linked to a cluster of private permission chain nodes that are running the other half of the application. This allows you to have all of the market access and openness and transparency and ownerlessness of a public network, while also having the control and the security that you find in a private network,” he said.

Martino and co-founder Stuart Popejoy both worked at JPMorgan on early blockchain projects, but left to start Kadena in 2016. The company has raised $14.9 million to date.

The blockchain begins finding its way in the enterprise


By Ron Miller

Microsoft Azure CTO Mark Russinovich will join us for TC Sessions: Enterprise on September 5

Posted on by

Being the CTO for one of the three major hypercloud providers may seem like enough of a job for most people, but Mark Russinovich, the CTO of Microsoft Azure, has a few other talents in his back pocket. Russinovich, who will join us for a fireside chat at our TechCrunch Sessions: Enterprise event in San Francisco on September 5 (p.s. early-bird sale ends Friday), is also an accomplished novelist who has published four novels, all of which center around tech and cybersecurity.

At our event, though, we won’t focus on his literary accomplishments (except for maybe his books about Windows Server) as much as on the trends he’s seeing in enterprise cloud adoption. Microsoft, maybe more so than its competitors, always made enterprise customers and their needs the focus of its cloud initiatives from the outset. Today, as the majority of enterprises is looking to move at least some of their legacy workloads into the cloud, they are often stumped by the sheer complexity of that undertaking.

In our fireside chat, we’ll talk about what Microsoft is doing to reduce this complexity and how enterprises can maximize their current investments into the cloud, both for running new cloud-native applications and for bringing legacy applications into the future. We’ll also talk about new technologies that can make the move to the cloud more attractive to enterprises, including the current buzz around edge computing, IoT, AI and more.

Before joining Microsoft, Russinovich, who has a Ph.D. in computer engineering from Carnegie Mellon, was the co-founder and chief architect of Winternals Software, which Microsoft acquired in 2006. During his time at Winternals, Russinovich discovered the infamous Sony rootkit. Over his 13 years at Microsoft, he moved from Technical Fellow up to the CTO position for Azure, which continues to grow at a rapid clip as it looks to challenge AWS’s leadership in total cloud revenue.

Tomorrow, Friday, August 16 is your last day to save $100 on tickets before prices go up. Book your early-bird tickets now and keep that Benjamin in your pocket.

If you’re an early-stage startup, we only have three demo table packages left! Each demo package comes with four tickets and a great location for your company to get in front of attendees. Book your demo package today before we sell out!


By Frederic Lardinois

Microsoft Azure now lets you have a server all to yourself

Posted on by

Microsoft today announced the preview launch of Azure Dedicated Host, a new cloud service that will allow you to run your virtual machines on single-tenant physical services. That means you’re not sharing any resources on that server with anybody else and you’ll get full control over everything that’s running on that machine.

Previously, Azure already offered isolated Virtual Machine sizes for two very large virtual machine types. Those are still available, but their use cases are comparably limited to these new hosts, which offer far more flexibility.

With this move, Microsoft is following in the footsteps of AWS, which also offers Dedicated Hosts with very similar capabilities. Google Cloud, too, offers what it calls ‘sole-tenant nodes.’

Azure Dedicated Host will support Windows, Linux and SQL Server virtual machines and pricing is per host, independent of the number of virtual machines you end up running on them. You can currently opt for machines with up to 144 physical cores and prices start at $4.039 per hour.

To do this, Microsoft is offering two different processors to power these machines. Type 1 is based on the 2.3 GHz Intel Xeon E5-2673 v4 with up to 3.5 gigahertz of clock speed, while Type 2 features the Intel Xeon® Platinum 8168 with single-core clock speeds of up to 3.7 gigahertz. The available memory ranges from 32GiB to 448GiB. You can find more details here.

As Microsoft notes, these new dedicated hosts can help companies reach their compliance requirements for physical security, data integrity and monitoring. The dedicated hosts still share the same underlying infrastructure as any other host in the Azure data centers, but users have full control over any maintenance window that could impact their servers.

These dedicated hosts can also be grouped into larger host groups in a given Azure region, allowing you to build clusters of your own physical servers inside the Azure data center. Since you’re actually renting a physical machine, any hardware issue on that machine will impact the virtual machines you are running on them, so chances are you’ll want to have multiple dedicated hosts for your failover strategy anyway.

110b3725 54e2 4840 a609 adf18fcbe32f


By Frederic Lardinois

AWS remains in firm control of the cloud infrastructure market

Posted on by

It has to be a bit depressing to be in the cloud infrastructure business if your name isn’t Amazon. Sure, there’s a huge, growing market, and the companies behind Amazon are growing even faster. Yet it seems no matter how fast they grow, Amazon remains a dot on the horizon.

It seems inconceivable that AWS can continue to hold sway over such a large market for so long, but as we’ve pointed out before, it has been able to maintain its position through true first-mover advantage. The other players didn’t even show up until several years after Amazon launched its first service in 2006, and they are paying the price for their failure to see the way computing would change the way Amazon did.

They certainly see it now, whether it’s IBM, Microsoft or Google, or Tencent and Alibaba, both of which are growing fast in the China/Asia markets. All of these companies are trying to find the formula to help differentiate themselves from AWS and give them some additional market traction.

Cloud market growth

Interestingly, even though companies have begun to move with increasing urgency to the cloud, the pace of growth slowed a bit in the first quarter to a 42 percent rate, according to data from Synergy Research, but that doesn’t mean the end of this growth cycle is anywhere close.


By Ron Miller

Microsoft brings Azure SQL Database to the edge (and Arm)

Posted on by

Microsoft today announced an interesting update to its database lineup with the preview of Azure SQL Database Edge, a new tool that brings the same database engine that powers Azure SQL Database in the cloud to edge computing devices, including, for the first time, Arm-based machines.

Azure SQL Edge, Azure corporate vice president Julia White writes in today’s announcement, “brings to the edge the same performant, secure and easy to manage SQL engine that our customers love in Azure SQL Database and SQL Server.”

The new service, which will also run on x64-based devices and edge gateways, promises to bring low-latency analytics to edge devices as it allows users to work with streaming data and time-series data, combined with the built-in machine learning capabilities of Azure SQL Database. Like its larger brethren, Azure SQL Database Edge will also support graph data and comes with the same security and encryption features that can, for example, protect the data at rest and in motion, something that’s especially important for an edge device.

As White rightly notes, this also ensures that developers only have to write an application once and then deploy it to platforms that feature Azure SQL Database, good old SQL Server on premises and this new edge version.

SQL Database Edge can run in both connected and fully disconnected fashion, something that’s also important for many use cases where connectivity isn’t always a given, yet where users need the kind of data analytics capabilities to keep their businesses (or drilling platforms, or cruise ships) running.


By Frederic Lardinois

Microsoft launches a drag-and-drop machine learning tool

Posted on by

Microsoft today announced three new services that all aim to simplify the process of machine learning. These range from a new interface for a tool that completely automates the process of creating models, to a new no-code visual interface for building, training and deploying models, all the way to hosted Jupyter-style notebooks for advanced users.

Getting started with machine learning is hard. Even to run the most basic of experiments take a good amount of expertise. All of these new tools great simplify this process by hiding away the code or giving those who want to write their own code a pre-configured platform for doing so.

The new interface for Azure’s automated machine learning tool makes creating a model as easy importing a data set and then telling the service which value to predict. Users don’t need to write a single line of code, while in the backend, this updated version now supports a number of new algorithms and optimizations that should result in more accurate models. While most of this is automated, Microsoft stresses that the service provides “complete transparency into algorithms, so developers and data scientists can manually override and control the process.”

For those who want a bit more control from the get-go, Microsoft also today launched a visual interface for its Azure Machine Learning service into preview that will allow developers to build, train and deploy machine learning models without having to touch any code.

This tool, the Azure Machine Learning visual interface looks suspiciously like the existing Azure ML Studio, Microsoft’s first stab at building a visual machine learning tool. Indeed, the two services look identical. The company never really pushed this service, though, and almost seemed to have forgotten about it despite that fact that it always seemed like a really useful tool for getting started with machine learning.

Microsoft says that this new version combines the best of Azure ML Studio with the Azure Machine Learning service. In practice, this means that while the interface is almost identical, the Azure Machine Learning visual interface extends what was possible with ML Studio by running on top of the Azure Machine Learning service and adding that services’ security, deployment and lifecycle management capabilities.

The service provides an easy interface for cleaning up your data, training models with the help of different algorithms, evaluating them and, finally, putting them into production.

While these first two services clearly target novices, the new hosted notebooks in Azure Machine Learning are clearly geared toward the more experiences machine learning practitioner. The notebooks come pre-packaged with support for the Azure Machine Learning Python SDK and run in what the company describes as a “secure, enterprise-ready environment.” While using these notebooks isn’t trivial either, this new feature allows developers to quickly get started without the hassle of setting up a new development environment with all the necessary cloud resources.


By Frederic Lardinois