Capital One CTO George Brady will join us at TC Sessions: Enterprise

When you think of old, giant mainframes that sit in the basement of a giant corporation, still doing the same work they did 30 years ago, chances are you’re thinking about a financial institution. It’s the financial enterprises, though, that are often leading the charge in bringing new technologies and software development practices to their employees and customers. That’s in part because they are in a period of disruption that forces them to become more nimble. Often, this means leaving behind legacy technology and embracing the cloud.

At TC Sessions Enterprise, which is happening on September 5 in San Francisco, Capital One executive VP in charge of its technology operations, George Brady, will talk about the company’s journey from legacy hardware and software to embracing the cloud and open source, all while working in a highly regulated industry. Indeed, Capital One was among the first companies to embrace the Facebook-led Open Compute project and it’s a member of the Cloud Native Computing Foundation. It’s this transformation at Captial One that Brady is leading.

At our event, Brady will join a number of other distinguished panelists to specifically talk about his company’s journey to the cloud. There, Captial One is using serverless compute, for example, to power its Credit Offers API using AWS’s Lambda service, as well as a number of other cloud technologies.

Before joining Capital One in 2014 as its CTO in 2014, Brady ran Fidelity Investment’s global enterprise infrastructure team from 2009 to 2014 and served as Goldman Sachs’ head of global business applications infrastructure before that.

Currently, he leads cloud application and platform productization for Capital One. Part of that portfolio is Critical Stack, a secure container orchestration platform for the enterprise. Capital One’s goal with this work is to help companies across industries become more compliant, secure and cost-effective operating in the public cloud.

Early bird tickets are still on sale for $249, grab yours today before we sell out.

Student tickets are for just $75 – grab them here.


By Frederic Lardinois

AWS is now making Amazon Personalize available to all customers

Amazon Personalize, first announced during AWS re:Invent last November, is now available to all Amazon Web Services customers. The API enables developers to add custom machine learning models to their apps, including ones for personalized product recommendations, search results and direct marketing, even if they don’t have machine learning experience.

The API processes data using algorithms originally created for Amazon’s own retail business,  but the company says all data will be “kept completely private, owned entirely by the customer.” The service is now available to AWS users in three U.S. regions, East (Ohio), East (North Virginia) and West (Oregon), two Asia Pacific regions (Tokyo and Singapore) and Ireland in the European Union, with more regions to launch soon.

AWS customers who have already added Amazon Personalize to their apps include Yamaha Corporation of America, Subway, Zola and Segment. In Amazon’s press release, Yamaha Corporation of America Director of Information Technology Ishwar Bharbhari said Amazon Personalize “saves us up to 60% of the time needed to set up and tune the infrastructure and algorithms for our machine learning models when compared to building and configuring the environment on our own.”

Amazon Personalize’s pricing model charges five cents per GB of data uploaded to Amazon Personalize and 24 cents per training hour used to train a custom model with their data. Real-time recommendation requests are priced based on how many are uploaded, with discounts for larger orders.


By Catherine Shu

AWS remains in firm control of the cloud infrastructure market

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

AWS expands cloud infrastructure offerings with new AMD EPYC-powered T3a instances

Amazon is always looking for ways to increase the options it offers developers in AWS, and to that end, today it announced a bunch of new AMD EPYC-powered T3a instances. These were originally announced at the end of last year at re:Invent, AWS’s annual customer conference.

Today’s announcement is about making these chips generally available. They have been designed for a specific type of burstable workload, where you might not always need a sustained amount of compute power.

“These instances deliver burstable, cost-effective performance and are a great fit for workloads that do not need high sustained compute power but experience temporary spikes in usage. You get a generous and assured baseline amount of processing power and the ability to transparently scale up to full core performance when you need more processing power, for as long as necessary,” AWS’s Jeff Barr wrote in a blog post.

These instances are build on the AWS Nitro System, Amazon’s custom networking interface hardware that the company has been working on for the last several years. The primary components of this system include the Nitro Card I/O Acceleration, Nitro Security Chip and the Nitro Hypervisor.

Today’s release comes on top of the announcement last year that the company would be releasing EC2 instances powered by Arm-based AWS Graviton Processors, another option for developers, who are looking for a solution for scale-out workloads.

It also comes on the heels of last month’s announcement that it was releasing EC2 M5 and R5 instances, which use lower-cost AMD chips. These are also built on top of the Nitro System.

The EPCY processors are available starting today in seven sizes in your choice of spot instances, reserved instances or on-demand, as needed. They are available in US East in northern Virginia, US West in Oregon, Europe in ireland, US East in Ohio and Asia-Pacific in Singapore.


By Ron Miller

Docker developers can now build Arm containers on their desktops

Docker and Arm today announced a major new partnership that will see the two companies collaborate in bringing improved support for the Arm platform to Docker’s tools.

The main idea here is to make it easy for Docker developers to build their applications for the Arm platform right from their x86 desktops and then deploy them to the cloud (including the Arm-based AWS EC2 A1 instances), edge and IoT devices. Developers will be able to build their containers for Arm just like they do today, without the need for any cross-compliation.

This new capability, which will work for applications written in Javascript/Node.js, Python, Java, C++, Ruby, .NET core, Go, Rust and PHP, will become available as a tech preview next week, when Docker hosts its annual North American developer conference in San Francisco.

Typically, developers would have to build the containers they want to run on the Arm platform on an Arm-based server. With this system, which is the first result of this new partnership, Docker essentially emulates an Arm chip on the PC for building these images.

“Overnight, the 2 million Docker developers that are out there can use the Docker commands they already know and become Arm developers,” Docker EVP of Business Development David Messina told me. “Docker, just like we’ve done many times over, has simplified and streamlined processes and made them simpler and accessible to developers. And in this case, we’re making x86 developers on their laptops Arm developers overnight.”

Given that cloud-based Arm servers like Amazon’s A1 instances are often signficantly cheaper than x86 machines, users can achieve some immediate cost benefits by using this new system and running their containers on Arm.

For Docker, this partnership opens up new opportunities, especially in areas where Arm chips are already strong, including edge and IoT scenarios. Arm, similarly, is interested in strengthening its developer ecosystem by making it easier to develop for its platform. The easier it is to build apps for the platform, the more likely developers are to then run them on servers that feature chips from Arm’s partners.

“Arm’s perspective on the infrastructure really spans all the way from the endpoint, all the way through the edge to the cloud data center, because we are one of the few companies that have a presence all the way through that entire path,” Mohamed Awad, Arm’s VP of Marketing, Infrastructure Line of Business, said. “It’s that perspective that drove us to make sure that we engage Docker in a meaningful way and have a meaningful relationship with them. We are seeing compute and the infrastructure sort of transforming itself right now from the old model of centralized compute, general purpose architecture, to a more distributed and more heterogeneous compute system.”

Developers, however, Awad rightly noted, don’t want to have to deal with this complexity, yet they also increasingly need to ensure that their applications run on a wide variety of platform and that they can move them around as needed. “For us, this is about enabling developers and freeing them from lock-in on any particular area and allowing them to choose the right compute for the right job that is the most efficient for them,” Awad said.

Mesina noted that the promise of Docker has long been to remove the dependence of applications from the infrastructure they run on. Adding Arm support simply extends this promise to an additional platform. He also stressed that the work on this was driven by the company’s enterprise customers. These are the users who have already set up their systems for cloud-native development with Docker’s tools — at least for their x86 development. Those customers are now looking at developing for their edge devices, too, and that often means developing for Arm-based devices.

Awad and Messina both stressed that developers really don’t have to learn anything new to make this work. All of the usual Docker commands will just work.

 


By Frederic Lardinois

The right way to do AI in security

Artificial intelligence applied to information security can engender images of a benevolent Skynet, sagely analyzing more data than imaginable and making decisions at lightspeed, saving organizations from devastating attacks. In such a world, humans are barely needed to run security programs, their jobs largely automated out of existence, relegating them to a role as the button-pusher on particularly critical changes proposed by the otherwise omnipotent AI.

Such a vision is still in the realm of science fiction. AI in information security is more like an eager, callow puppy attempting to learn new tricks – minus the disappointment written on their faces when they consistently fail. No one’s job is in danger of being replaced by security AI; if anything, a larger staff is required to ensure security AI stays firmly leashed.

Arguably, AI’s highest use case currently is to add futuristic sheen to traditional security tools, rebranding timeworn approaches as trailblazing sorcery that will revolutionize enterprise cybersecurity as we know it. The current hype cycle for AI appears to be the roaring, ferocious crest at the end of a decade that began with bubbly excitement around the promise of “big data” in information security.

But what lies beneath the marketing gloss and quixotic lust for an AI revolution in security? How did AL ascend to supplant the lustrous zest around machine learning (“ML”) that dominated headlines in recent years? Where is there true potential to enrich information security strategy for the better – and where is it simply an entrancing distraction from more useful goals? And, naturally, how will attackers plot to circumvent security AI to continue their nefarious schemes?

How did AI grow out of this stony rubbish?

The year AI debuted as the “It Girl” in information security was 2017. The year prior, MIT completed their study showing “human-in-the-loop” AI out-performed AI and humans individually in attack detection. Likewise, DARPA conducted the Cyber Grand Challenge, a battle testing AI systems’ offensive and defensive capabilities. Until this point, security AI was imprisoned in the contrived halls of academia and government. Yet, the history of two vendors exhibits how enthusiasm surrounding security AI was driven more by growth marketing than user needs.


By Arman Tabatabai

On balance, the cloud has been a huge boon to startups

Today’s startups have a distinct advantage when it comes to launching a company because of the public cloud. You don’t have to build infrastructure or worry about what happens when you scale too quickly. The cloud vendors take care of all that for you.

But last month when Pinterest announced its IPO, the company’s cloud spend raised eyebrows. You see, the company is spending $750 million a year on cloud services, more specifically to AWS. When your business is primarily focused on photos and video, and needs to scale at a regular basis, that bill is going to be high.

That price tag prompted Erica Joy, a Microsoft engineer to publish this Tweet and start a little internal debate here at TechCrunch. Startups, after all, have a dog in this fight, and it’s worth exploring if the cloud is helping feed the startup ecosystem, or sending your bills soaring as they have with Pinterest.

For starters, it’s worth pointing out that Ms. Joy works for Microsoft, which just happens to be a primary competitor of Amazon’s in the cloud business. Regardless of her personal feelings on the matter, I’m sure Microsoft would be more than happy to take over that $750 million bill from Amazon. It’s a nice chunk of business, but all that aside, do startups benefit from having access to cloud vendors?


By Ron Miller

Pixeom raises $15M for its software-defined edge computing platform

Pixeom, a startup that offers a software-defined edge computing platform to enterprises, today announced that it has raised a $15M funding round from Intel Capital, National Grid Partners and previous investor Samsung Catalyst Fund. The company plans to use the new funding to expands its go-to-market capacity and invest in product development.

If the Pixeom name sounds familiar, that may be because you remember it as a Raspberry Pie-based personal cloud platform. Indeed, that’s the service the company first launched back in 2014. It quickly pivoted to an enterprise model, though. As Pixeom CEO Sam Nagar told me, that pivot came about after a conversation the company had with Samsung about adopting its product for that company’s needs. In addition, it was also hard to find venture funding. The original Pixeom device allowed users to set up their own personal cloud storage and other applications at home. While there is surely a market for these devices, especially among privacy conscious tech enthusiasts, it’s not massive, especially as users became more comfortable with storing their data in the cloud. “One of the major drivers [for the pivot] was that it was actually very difficult to get VC funding in an industry where the market trends were all skewing towards the cloud,” Nagar told me.

At the time of its launch, Pixeom also based its technology on OpenStack, the massive open source project that helps enterprises manage their own data centers, which isn’t exactly known as a service that can easily be run on a single machine, let alone a low-powered one. Today, Pixeom uses containers to ship and manage its software on the edge.

What sets Pixeom apart from other edge computing platforms is that it can run on commodity hardware. There’s no need to buy a specific hardware configuration to run the software, unlike Microsoft’s Azure Stack or similar services. That makes it significantly more affordable to get started and allows potential customers to reuse some of their existing hardware investments.

Pixeom brands this capability as ‘software-defined edge computing’ and there is clearly a market for this kind of service. While the company hasn’t made a lot of waves in the press, more than a dozen Fortune 500 companies now use its services. With that, the company now has revenues in the double-digit millions and its software manages more than a million devices worldwide.

As is so often the case in the enterprise software world, these clients don’t want to be named, but Nagar tells me that they include one of the world’s largest fast food chains, for example, which uses the Pixeom platform in its stores.

On the software side, Pixeom is relatively cloud agnostic. One nifty feature of the platform is that it is API-compatible with Google Cloud Platform, AWS and Azure and offers an extensive subset of those platforms’ core storage and compute services, including a set of machine learning tools. Pixeom’s implementation may be different, but for an app, the edge endpoint on a Pixeom machine reacts the same way as its equivalent endpoint on AWS, for example.

Until now, Pixeom mostly financed its expansion — and the salary of its over 90 employees — from its revenue. It only took a small funding round when it first launched the original device (together with a Kickstarter campaign). Technically, this new funding round is part of this, so depending on how you want to look at this, we’re either talking about a very large seed round or a Series A round.


By Frederic Lardinois

Vizion.ai launches its managed Elasticsearch service

Setting up Elasticsearch, the open-source system that many companies large and small use to power their distributed search and analytics engines, isn’t the hardest thing. What is very hard, though, is to provision the right amount of resources to run the service, especially when your users’ demand comes in spikes, without overpaying for unused capacity. Vizion.ai’s new Elasticsearch Service does away with all of this by essentially offering Elasticsearch as a service and only charging its customers for the infrastructure they use.

Vizion’s service automatically scales up and down as needed. It’s a managed service and delivered as a SaaS platform that can support deployments on both private and public clouds, with full API compatibility with the standard Elastic stack that typically includes tools like Kibana for visualizing data, Beats for sending data to the service and Logstash for transforming the incoming data and setting up data pipelines. Users can easily create several stacks for testing and development, too, for example.

Vizion.ai GM and VP Geoff Tudor

“When you go into the AWS Elasticsearch service, you’re going to be looking at dozens or hundreds of permutations for trying to build your own cluster,” Vision.ai’s VP and GM Geoff Tudor told me. “Which instance size? How many instances? Do I want geographical redundancy? What’s my networking? What’s my security? And if you choose wrong, then that’s going to impact the overall performance. […] We do balancing dynamically behind that infrastructure layer.” To do this, the service looks at the utilization patterns of a given user and then allocates resources to optimize for the specific use case.

What Vizion has done here is take some of the work from its parent company Panzura, a multi-cloud storage service for enterprises that has plenty of patents around data caching, and applied it to this new Elasticsearch service.

There are obviously other companies that offer commercial Elasticsearch platforms already. Tudor acknowledges this, but argues that his company’s platform is different. With other products, he argues, you have to decide on the size of your block storage for your metadata upfront, for example, and you typically want SSDs for better performance, which can quickly get expensive. Thanks to Panzura’s IP, Vizion.ai is able to bring down the cost by caching recent data on SSDs and keeping the rest in cheaper object storage pools.

He also noted that the company is positioning the overall Vizion.ai service, with the Elasticsearch service as one of the earliest components, as a platform for running AI and ML workloads. Support for TensorFlow, PredictionIO (which plays nicely with Elasticsearch) and other tools is also in the works. “We want to make this an easy serverless ML/AI consumption in a multi-cloud fashion, where not only can you leverage the compute, but you can also have your storage of record at a very cost-effective price point.”


By Frederic Lardinois

New conflict evidence surfaces in JEDI cloud contract procurement process

For months, the drama has been steady in the Pentagon’s decade long, $10 billion JEDI cloud contract procurement process. This week the plot thickened when the DOD reported that it has found new evidence of a possible conflict of interest, and has reopened its internal investigation into the matter.

“DOD can confirm that new information not previously provided to DOD has emerged related to potential conflicts of interest. As a result of this new information, DOD is continuing to investigate these potential conflicts,” Elissa Smith, Department of Defense spokesperson told TechCrunch.

It’s not clear what this new information is about, but the Wall Street Journal reported this week that senior federal judge Eric Bruggink of the U.S. Court of Federal Claims ordered that the lawsuit filed by Oracle in December would be put on hold to allow the DOD to investigate further.

From the start of the DOD RFP process, there have been complaints that the process itself was designed to favor Amazon, and that were possible conflicts of interest on the part of DOD personnel. The DOD’s position throughout has been that it is an open process and that an investigation found no bearing for the conflict charges. Something forced the department to rethink that position this week.

Oracle in particular has been a vocal critic of the process. Even before the RFP was officially opened, it was claiming that the process unfairly favored Amazon. In the court case, it made the conflict part clearer, claiming that an ex-Amazon employee named Deap Ubhi had influence over the process, a charge that Amazon denied when it joined the case to defend itself. Four weeks ago something changed when a single line in a court filing suggested that Ubhi’s involvement may have been more problematic than the DOD previously believed.

At the time, I wrote:

In the document, filed with the court on Wednesday, the government’s legal representatives sought to outline its legal arguments in the case. The line that attracted so much attention stated, “Now that Amazon has submitted a proposal, the contracting officer is considering whether Amazon’s re-hiring Mr. Ubhi creates an OCI that cannot be avoided, mitigated, or neutralized.” OCI stands for Organizational Conflict of Interest in DoD lingo.

And Pentagon spokesperson Heather Babb told TechCrunch:

“During his employment with DDS, Mr. Deap Ubhi recused himself from work related to the JEDI contract. DOD has investigated this issue, and we have determined that Mr. Ubhi complied with all necessary laws and regulations,” Babb told TechCrunch.

Whether the new evidence that DOD has found is referring to Ubhi’s rehiring by Amazon or not, is not clear at the moment, but it has clearly found new evidence it wants to explore in this case, and that has been enough to put the Oracle lawsuit on hold.

Oracle’s court case is the latest in a series of actions designed to protest the entire JEDI procurement process. The Washington Post reported last spring that co-CEO Safra Catz complained directly to the president. The company later filed a formal complaint with the Government Accountability Office (GAO), which it lost in November when the department’s investigation found no evidence of conflict. It finally made a federal case out of it when it filed suit in federal court in December, accusing the government of an unfair procurement process and a conflict on the part of Ubhi.

The cloud deal itself is what is at the root of this spectacle. It’s a 10-year contract worth up to $10 billion to handle the DOD’s cloud business — and it’s a winner-take-all proposition. There are three out clauses, which means it might never reach that number of years or dollars, but it is lucrative enough, and could possibly provide inroads for other government contracts, that every cloud company wants to win this.

The RFP process closed in October and the final decision on vendor selection is supposed to happen in April. It is unclear whether this latest development will delay that decision.


By Ron Miller

Peltarion raises $20M for its AI platform

Peltarion, a Swedish startup founded by former execs from companies like Spotify, Skype, King, TrueCaller and Google, today announced that it has raised a $20 million Series A funding round led by Euclidean Capital, the family office for hedge fund billionaire James Simons. Previous investors FAM and EQT Ventures also participated, and this round brings the company’s total funding to $35 million.

There is obviously no dearth of AI platforms these days. Peltarion focus on what it calls “operational AI.” The service offers an end-to-end platform that lets you do everything from pre-processing your data to building models and putting them into production. All of this runs in the cloud and developers get access to a graphical user interface for building and testing their models. All of this, the company stresses, ensures that Peltarion’s users don’t have to deal with any of the low-level hardware or software and can instead focus on building their models.

“The speed at which AI systems can be built and deployed on the operational platform is orders of magnitude faster compared to the industry standard tools such as TensorFlow and require far fewer people and decreases the level of technical expertise needed,” Luka Crnkovic-Friis, of Peltarion’s CEO and co-founder, tells me. “All this results in more organizations being able to operationalize AI and focusing on solving problems and creating change.”

In a world where businesses have a plethora of choices, though, why use Peltarion over more established players? “Almost all of our clients are worried about lock-in to any single cloud provider,” Crnkovic-Friis said. “They tend to be fine using storage and compute as they are relatively similar across all the providers and moving to another cloud provider is possible. Equally, they are very wary of the higher-level services that AWS, GCP, Azure, and others provide as it means a complete lock-in.”

Peltarion, of course, argues that its platform doesn’t lock in its users and that other platforms take far more AI expertise to produce commercially viable AI services. The company rightly notes that, outside of the tech giants, most companies still struggle with how to use AI at scale. “They are stuck on the starting blocks, held back by two primary barriers to progress: immature patchwork technology and skills shortage,” said Crnkovic-Friis.

The company will use the new funding to expand its development team and its teams working with its community and partners. It’ll also use the new funding for growth initiatives in the U.S. and other markets.


By Frederic Lardinois

AWS announces new bare metal instances for companies who want more cloud control

When you think about Infrastructure as a Service, you typically pay for a virtual machine that resides in a multi-tenant environment. That means, it’s using a set of shared resources. For many companies that approach is fine, but when a customer wants more control, they may prefer a single tenant system where they control the entire set of hardware resources. This approach is also known as “bare metal” in the industry, and today AWS announced five new bare metal instances.

You end up paying more for this kind of service because you are getting more control over the processor, storage and other resources on your own dedicated underlying server. This is part of the range of products that all cloud vendors offer. You can have a vanilla virtual machine, with very little control over the hardware, or you can go with bare metal and get much finer grain control over the underlying hardware, something that companies require if they are going to move certain workloads to the cloud.

As AWS describes it in the blog post announcing these new instances, these are for highly specific use cases. “Bare metal instances allow EC2 customers to run applications that benefit from deep performance analysis tools, specialized workloads that require direct access to bare metal infrastructure, legacy workloads not supported in virtual environments, and licensing-restricted Tier 1 business critical applications,” the company explained.

The five new products, called m5.metal, m5d.metal, r5.metal, r5d.metal, and z1d.metal (catchy names there, Amazon) offer a variety of resources:

Chart courtesy of Amazon

These new offerings are available starting today as on-demand, reserved or spot instances, depending on your requirements.


By Ron Miller

AWS launches WorkLink to make accessing mobile intranet sites and web apps easier

If your company uses a VPN and/or a mobile device management service to give you access to its intranet and internal web apps, then you know how annoying those are. AWS today launched a new product, Amazon WorkLink,  that promises to make this process significantly easier.

WorkLink is a fully managed service that, for $5 per month and user, allows IT admins to give employees one-click access to internal sites, no matter whether they run on AWS or not.

After installing WorkLink on their phones, employees can then simply use their favorite browser to surf to an internal website (other solutions often force users to use a sub-par proprietary browser). WorkLink the goes to work, securely requests that site and — and that’s the smart part here — a secure WorkLink container converts the site into an interactive vector graphic and sends it back to the phone. Nothing is stored or cached on the phone and AWS says WorkLink knows nothing about personal device activity either. That also means when a device is lost or stolen, there’s no need to try to wipe it remotely because there’s simply no company data on it.

IT can either use a VPN to connect from an AWS Virtual Private Cloud to on-premise servers or use AWS Direct Connect to bypass a VPN solution. The service works with all SAML 2.0 identity providers (which is the majority of identity services used in the enterprise, including the likes of Okta and Ping Identity) and as a fully managed service, it handles scaling and updates in the background.

“When talking with customers, all of them expressed frustration that their workers don’t have an easy and secure way to access internal content, which means that their employees either waste time or don’t bother trying to access content that would make them more productive,” says Peter Hill, Vice President of Productivity Applications at AWS, in today’s announcement. “With Amazon WorkLink, we’re enabling greater workplace productivity for those outside the corporate firewall in a way that IT administrators and security teams are happy with and employees are willing to use.”

WorkLink will work with both Android and iOS, but for the time being, only the iOS app (iOS 12+) is available. For now, it also only works with Safar, with Chrome support coming in the next few weeks. The service is also only available in Europe and North America for now, with additional regions coming later this year.

For the time being, AWS’s cloud archrivals Google and Microsoft don’t offer any services that are quite comparable with WorkLink. Google offers its Cloud Identity-Aware Proxy as a VPN alternative and as part of its BeyondCorp program, though that has a very different focus, while Microsoft offers a number of more traditional mobile device management solutions.


By Frederic Lardinois

AWS launches Backup, a fully-managed backup service for AWS

Amazon’s AWS cloud computing service today launched Backup, a new tool that makes it easier for developers on the platform to back up their data from various AWS services and their on-premises apps. Out of the box, the service, which is now available to all developers, lets you set up backup policies for services like Amazon EBS volumes, RDS databases, DynamoDB tables, EFS file systems and AWS Storage Gateway volumes. Support for more services is planned, too. To back up on-premises data, businesses can use the AWS Storage Gateway.

The service allows users to define their various backup policies and retention periods, including the ability to move backups to cold storage (for EFS data) or delete them completely after a certain time. By default, the data is stored in Amazon S3 buckets.

Most of the supported services, except for EFS file systems, already feature the ability to create snapshots. Backup essentially automates that process and creates rules around it, so it’s no surprise that the pricing for Backup is the same as for using those snapshot features (with the exception of the file system backup, which will have a per-GB charge). It’s worth noting that you’ll also pay a per-GB fee for restoring data from EFS file systems and DynamoDB backups.

Currently, Backup’s scope is limited to a given AWS region, but the company says that it plans to offer cross-region functionality later this year.

“As the cloud has become the default choice for customers of all sizes, it has attracted two distinct types of builders,” writes Bill Vass, AWS’s VP of Storage, Automation, and Management Services. “Some are tinkerers who want to tweak and fine-tune the full range of AWS services into a desired architecture, and other builders are drawn to the same breadth and depth of functionality in AWS, but are willing to trade some of the service granularity to start at a higher abstraction layer, so they can build even faster. We designed AWS Backup for this second type of builder who has told us that they want one place to go for backups versus having to do it across multiple, individual services.”

Early adopters of AWS Backup are State Street Corporation, Smile Brands and Rackspace, though this is surely a service that will attract its fair share of users as it makes the life of admins quite a bit easier. AWS does have quite a few backup and storage partners, though, who may not be all that excited to see AWS jump into this market, too, though they often offer a wider range of functionality — including cross-region and offsite backups — than AWS’s service.

 


By Frederic Lardinois

AWS signs on to defend itself in Oracle’s JEDI RFP lawsuit against US government

Just when you didn’t think there could be any more drama over the Pentagon’s decade long, $10 billion JEDI contract RFP, the plot thickened again last week when Amazon Web Services (AWS) joined the US government as a defendant in Oracle’s lawsuit over the Pentagon’s handling of the contract RFP process.

Earlier this month, Oracle filed a complaint in the United States Court of Federal Claims alleging that the JEDI RFP process unfairly favored Amazon, that the single vendor decision (which won’t be made until April), violates federal procurement rules and that two members of the JEDI team had a conflict of interest because of previous affiliations with Amazon Web Services.

AWS filed paperwork to join the case, stating that because of the claims being made by Oracle, it had a direct stake in the outcome. “Oracle’s Complaint specifically alleges conflicts of interest involving AWS. Thus, AWS has direct and substantial economic interests at stake in this case, and its disposition clearly could impair those interests,” the company’s attorneys stated in the motion.

The Motion to Intervene as a Defendant was approved by United States Court of Federal Claims Senior Judge, Eric G. Bruggink the same day.

Oracle filed a complaint alleging essentially the same issues with the Government Accountability Office earlier this year, but the GAO found no wrong-doing in a ruling last month. Oracle decided to take the case to court where it has had some high profile wins in recent years including its case against Google over its use of the Java APIs.

The JEDI contract RFP has attracted attention for the length, the amount of money at stake and the single vendor selection decision. This is a contract that every cloud company badly wants to have. Oracle has made it clear it’s not giving up without a fight, while Amazon Web Services intends to defend itself against Oracle’s claims.


By Ron Miller