Tag Archives: developers

Ionic Pro embodies mobile app dev tools’ DevOps embrace

Driven by a need for speedy app development amid broad digital transformation directives, developers of all skill levels must collaborate to feed an insatiable user base of enterprises and their customers. And software development toolmakers are answering the call with low-code, easy-to-use mobile app dev tools to build enterprise applications.

There are actually two converging forces at work right now, said Joe McKendrick, an analyst at Unisphere Research. Developers increasingly must understand and align with lines of business and take on a more active role in business process management and optimization, user experience and customer experience (UX/CX) design, and DevOps.

Indeed, one in five executives indicate that most applications are developed outside of their IT departments, and 76%said that’s true for at least a portion of their apps, according to a recent survey from Unisphere Research and app dev toolkit maker Kintone. San Francisco based Kintone makes low-code development tools that enable line of business managers to build software that automate workflows, develop shared document repositories, construct reporting dashboards and process data without writing a single line of code.

At the same time, a new generation of business professionals with more tech-savvy employees of all ages, understand how computing can improve their work lives. These nonprofessional developers have begun to pick up low-code tools and have started to help create applications.

“Professional developers and non-developers increasingly see eye to eye on the things that need to be done,” McKendrick said.

Rub a little DevOps on it

As these lines blur, it forces tools and technology providers to address these different ends of the developer spectrum, and still provide tools for teams. Nowhere is this more apparent than in the mobile market.

For instance, Ionic has tuned its open source Ionic Framework to build cross-platform mobile and progressive web applications to woo enterprises with support for teams of developers along with more aspects of the application development lifecycle, including testing.

The Ionic Framework enables developers to target native mobile apps and progressive web apps from the same code base using familiar languages and tools. Earlier this month, Ionic Pro updated its set of cloud-based services and tools introduced in August. It now supports teams to design, build, test and deliver mobile and progressive web apps across the development lifecycle — from design and testing, to tracking errors and shipping hot code updates. The pro version includes collaborative tools to facilitate team development.

In essence, Ionic Pro overlays a DevOps veneer onto the Ionic Framework, although users who are typically front-end developers likely won’t think of it in that way, said Max Lynch, CEO of Ionic. The tool lets developers collaborate on projects via a shared database, remain aware of all build activity and coding changes, build apps using a drag-and-drop design, test different versions of apps with users, deliver different releases to different user segments, track and analyze coding errors, and ship hotfixes and live updates in real time without going through app stores.

Brian Aguilar, director of product at MarketWatch, which uses the older version of Ionic’s tool set, said his team has tested the recent product version, particularly features such as Ionic View, for remote testing and to allow external users to look at the app without installing it.

“That’s beneficial to us because we have a small QA team,” he said.

MarketWatch has considered the Ionic Pro Live Deploy feature for live updating apps. “I’m also intrigued by the Ionic Creator rapid prototyping tool,” Aguilar said.

Ionic Pro fosters developer collaboration
Ionic Pro screenshot displaying some of its collaborative development capabilities.

Low-code to the rescue

Ionic competes with Microsoft’s Xamarin unit and Progress Software’s Telerik, among others. At the recent Microsoft Connect, Xamarin introduced Visual Studio App Center, the next generation of Xamarin Test Center, which enables developers to build, distribute, monitor and integrate push notifications. Xamarin also introduced .NET Embedding, tooling with which developers can integrate .NET libraries and user interfaces written in C# into existing iOS, Android and macOS apps written in Objective-C, Swift and Java.

Also last month, Progress Software introduced tooling for its NativeScript open source framework to build native cross-platform mobile apps. NativeScript Sidekick provides starter templates, plug-ins, cloud builds, augmented reality support and more for building mobile apps.

“Low-code development platforms such as these, increase the range of people from all professions who now engage in some form of application development,” according to Unisphere’s McKendrick.

[Application development] is now a part of many job descriptions or daily routines, formally and informally. … Many people [are building] apps on company time, and that’s OK.
Joe McKendrickanalyst, Unisphere Research

“[Application development] is now a part of many job descriptions or daily routines, formally and informally,” he said. “Our survey found many people build apps on company time, and that’s OK.”

Mobile apps are the perfect target for low-code platforms, McKendrick said, because they are well-governed templates, and have set the standard and represent a huge breakthrough in low-code development. In addition, they have firm guardrails to ensure versioning, compatibility and security. Moreover, low-code tools have become much easier to use than the old power user tools including PowerBuilder and the older Visual Basic versions like VB6.

“Along with graphics, today’s tools have a lot of intelligence embedded within them that address all the protocols and dependencies behind the scenes,” he said.

This all comes full circle back to Ionic and its Creator tool. “I wouldn’t call it a ‘low-code’ tool, because most low-code tools are there to broaden the reach of creators, to give tolling to nonprofessional developers to create something,” said Michael Facemire, an analyst at Forrester Research. However, Ionic Creator helps to fast forward all the stages of the software development lifecycle to get a professional developer a head start, he said.

For his part, Mike Sigle, senior vice president of product development at New York City-based Napa Group, said the new Ionic View feature allows them to instantly share their latest codebase both internally and externally with just a few mouse clicks.

“We’ve established several channels, including Lab, where we try out fresh ideas that need instant feedback from our clients; Development, a stable branch of our latest code; Staging, where we smoke-test an app against a production API endpoint; and Production, the version users currently have,” he said.

Moreover, “Ionic Pro provides us huge technology benefits, as well as business benefits,” said Peter Chatzky, president and CEO of Napa Group. “We can streamline staff by having a single, smaller team develop for both iOS and Android platforms, thereby developing complex apps faster and at reduced cost. As we bring new ideas to market, Ionic allowed us to create modern apps without favoring a specific mobile platform or limiting our initial user base.”

AWS SageMaker brings machine learning to developers

LAS VEGAS — Amazon Web Services released a tool this week to empower developers to build smarter, artificial intelligence-driven applications like the AI experts.

Among the deluge of technologies introduced here at AWS re:Invent 2017, the company’s annual customer and partner event, is a tool called SageMaker. Its function is to help developers add machine learning services to applications.

Machine learning is an artificial intelligence technology that enables applications to learn without being explicitly programmed, and become smarter based on the frequency and volume of new data they ingest and analyze. Few developers are experts in machine learning, however.

SageMaker is geared to that audience. It’s a fully managed service for developers and data scientists who wish to build, train and manage their own machine learning models. Developers can choose among ten of the most common deep learning algorithms, specify their data source, and the tool installs and configures the underlying drivers and frameworks. It natively integrates with machine language frameworks such as TensorFlow and Apache MXNet and will support other frameworks as well.

Alternatively, developers can specify their own algorithm and framework.

The National Football League said it will use SageMaker to extend its next-generation stats initiative to add visualizations, stats and experiences for fans, as well as provide up-to-date information about players on the field, said Michelle McKenna-Doyle, the NFL’s senior vice president and CIO, here this week.

To supplement SageMaker, AWS created DeepLens, a wireless, deep-learning-enabled, programmable video camera for developers to hone their skills with machine learning. One example of DeepLens cited by AWS included recognizing the numbers on a license plate to trigger a home automation system and open a garage door.

AWS’ goal is to democratize access to machine learning technology for developers anywhere, so that individual developers could have access to the same technology as large enterprises, said Swami Sivasubramanian, vice president of machine learning at AWS.

SageMaker is one example of this, said Mark Nunnikhoven, vice president of cloud research at Dallas-based Trend Micro.

“I’ve worked with those technology stacks quite a lot over the last decade and there’s so much complexity …, but now any user doesn’t have to care about it,” he said. “They can do really advanced machine learning very, very easily.”

AWS ups the ante for AI

The general pattern in the market for AI application development has been twofold, said Rob Koplowitz, an analyst at Forrester Research in Cambridge, Mass. There are AI frameworks for data scientists that are extremely flexible but require special skills, and higher-level APIs that are accessible to programmers — and in some cases even non-programmers.

“Amazon wants to provide a middle ground with more flexibility,” Koplowitz said. “It’s an interesting approach and we’re looking forward to getting real work feedback from developers.”

AWS has to play catch-up here with other cloud platform companies that wish to bring machine learning to mainstream programmers. IBM provides developers access to its Watson AI services, and Microsoft has its Cognitive Services and Azure Machine Learning Workbench tools. Reducing the complexity of building machine learning models is among the more difficult areas for businesses, so this is a step in the right direction for AWS, said Judith Hurwitz, founder and CEO at Hurwitz & Associates in Needham, Mass.

Computational intelligence in general, and AI and deep learning in particular, is a hot market with a small community of experts among the biggest tech companies from Facebook to IBM.

“They all have a lot of the same core competencies, but they’re distributing them in different ways,” said Trend Micro’s Nunnikhoven.

Google tends to be more technical, while AWS now wants to make AI more accessible. Microsoft targets specific business analytics uses for AI, IBM wants to show more real-world use cases in areas such as healthcare and financial services, and Apple is looking at AI for privacy and devices. But they’re all contributing back to the same projects, such as Apache Mahout and Spark MLlib, Google’s TensorFlow, Microsoft’s Cognitive Toolkit, and others.

SageMaker should help alleviate developers’ fears that data scientists will make them into second-class citizens, but AWS may have aimed too low with SageMaker, said Holger Mueller, principal analyst at Constellation Research in San Francisco. He said he believes it’s more of a kit to empower business users to create machine learning applications.

Other AWS AI-based services

Other AI-enabled AWS services unveiled this week include Amazon Comprehend, a managed natural language processing service for documents or other textual data that integrates with other AWS services to provide analytics, and Amazon Rekognition Video, which can track people and recognize faces and objects in videos stored in Amazon S3.

There are two services now in preview — Amazon Transcribe, which lets developers turn audio files into punctuated text, and Amazon Translate, which uses neural machine translation techniques to translate text from one language to another. Translate currently supports English and six other languages — Arabic, French, German, Portuguese, Simplified Chinese and Spanish — with more languages to come in 2018.

Visual Studio Live Share aims to spur developer collaboration

NEW YORK — Developers at Microsoft’s event here last week got a sneak peek at a tool that aims to boost programmer productivity and improve application quality.

Microsoft’s Visual Studio Live Share, displayed at its Connect(); 2017 conference, lets developers work on the same code in real time. It also continues to bolster the company’s credibility in their eyes, delivering tools and services that make their jobs easier.

The software brings the Agile practice of pair programming to a broader set of programmers, except the programmers do not need to be physically together. Developers can remotely access and debug the same code in their respective editor or integrated development environment and share their full project context, rather than just their screens. Visual Studio Live Share works across multiple machines. Interested developers can sign up to join the Visual Studio Live Share preview, set for early 2018. It will be a limited, U.S.-only preview.

“It works not just between Visual Studio Code sessions between two Macs or between two Visual Studio sessions on Windows, but you can, in fact, have teams composed of multiple different parts of the Visual Studio family on multiple different operating systems all developing simultaneously,” said Scott Guthrie, executive vice president in Microsoft’s cloud and enterprise group.

The ability for developers to collaboratively debug and enhance the quality of applications in real time is extremely useful for developers looking for help with coding issues. While the capability has been around in various forms for 20 years, by integrating it into the Visual Studio tool set, Microsoft aims to standardize live sharing of code.

Scott Guthrie, Microsoft executive vice president of cloud and enterprise, presenting the keynote at Connect(); 2017.
Scott Guthrie, Microsoft executive vice president of cloud and enterprise, presenting the keynote at Connect(); 2017.

“I will be happy to see full collaboration make it to a shipping product,” said Theresa Lanowitz, an analyst at Voke, a research firm in Minden, Nev. “I had that capability shipping in 1994 at Taligent.”

Thomas Murphy, an analyst at Gartner, said he likes what he has heard about Visual Studio Live Share thus far, but wants to see it firsthand and compare it with pair programming tools such as AtomPair.

“[Microsoft is] doing a great job of being open and participating in open software in a nice incremental fashion,” he said. “But does it bring them new developers? That is a harder question. I think there are still plenty of people that think of Microsoft as the old world, and they are now in the new world.”

General availability of Visual Studio App Center

There are still plenty of [developers] that think of Microsoft as the old world, and they are now in the new world.
Thomas Murphyanalyst, Gartner

Also this week, Microsoft made its Visual Studio App Center generally available. Formerly known as Visual Studio Mobile Center and based on Xamarin Test Cloud, Visual Studio App Center is essentially a mobile backend as a service that provides a DevOps environment to help developers manage the lifecycle of their mobile apps. Objective-C, Swift, Android Java, Xamarin and React Native developers can all use Visual Studio App Center, according to the company.

Once a developer connects a code repository to Visual Studio App Center, the tool automatically creates a release pipeline of automated builds, tests the app in the cloud, manages distribution of the app to beta testers and app stores, and monitors usage of the app with crash analytics data using HockeyApp analytics tool Microsoft acquired in 2014.

“HockeyApp is very useful for telemetry data; that was a good acquisition,” Lanowitz said. Xamarin’s mobile development tools, acquired by Microsoft in 2016, also are strong, she said.

Darryl K. Taft covers DevOps, software development tools and developer-related issues as news writer for TechTarget’s SearchSoftwareQuality, SearchCloudApplications, SearchMicroservices and TheServerSide. Contact him at dtaft@techtarget.com or @darrylktaft on Twitter.

Azure DevOps Projects helps ease release automation

NEW YORK — Microsoft’s new Azure DevOps Projects tool lets developers configure a DevOps pipeline and connect it to the cloud with no prior knowledge of how to do so.

Azure DevOps Projects, released to public preview at the Microsoft Connect(); conference here this week, is a scaffolding system for developers to configure a full DevOps pipeline and connect to Microsoft’s Azure cloud services in less than five minutes.

With digital transformation efforts in full swing across enterprises in nearly every industry, developers are driven harder than ever to speed up application releases. In the process, they also want to ensure quality and security and to manage these apps more efficiently. This is where DevOps becomes critical and where a simplified way to get started with DevOps could be useful.

Abel Wang, a senior cloud developer advocate for DevOps at Microsoft, demonstrated how, with a series of clicks to provide information about the type of application and programming language used, Azure DevOps Projects sets up a Git repository and wires up automated build and release pipelines. Everything is automatic, although developers can customize the configuration.

“We make it ridiculously easy to go to a full DevOps environment,” Wang said.

Azure DevOps Projects comes out of the intersection of Microsoft’s Visual Studio family of tools and services — particularly Video Studio Team Services (VSTS) — and the Azure cloud platform.

It’s hard to set up your DevOps pipeline, because developers often manually integrate a lot of different tools, said Scott Guthrie, executive vice president of Microsoft’s cloud and enterprise group. However, VSTS is fully integrated with Azure.

“I think this shows that Microsoft now has a good set of tools and a strengthening set of stuff for ops,” said Thomas Murphy, an analyst with Gartner.

Microsoft has historically been weak in areas such as release automation, but a stronger Azure platform, including Azure DevOps, will help Microsoft better compete with Amazon Web Services (AWS) for enterprise customers. New independent software vendors still target AWS or Cloud Foundry, but in the corporate space — especially retail businesses that view AWS as a competitor — there is a growing business-driven push away from AWS and toward Azure, Murphy said.

Microsoft engineer Donovan Brown previews Azure DevOps Projects at Microsoft Connect(); 2017.
Microsoft engineer Donovan Brown previews Azure DevOps Projects at Microsoft Connect(); 2017.

Microsoft continues to advance cloud for DevOps

Another VSTS capability, release management gates, enables developers to specify conditions necessary to begin or finish a deployment to an environment, automating a process that’s often manual. DevOps pros can configure an environment to deploy and wait a day to ensure there are no blocking work items or monitoring alerts before proceeding with deployment, said Brian Harry, Microsoft’s corporate vice president for Visual Studio Team Services and Team Foundation Server (TFS), in a blog post

VSTS also has free, cloud-hosted continuous integration (CI) and continuous delivery (CD) on macOS, so teams can build and release Apple iOS, macOS, tvOS and watchOS applications without the need for Mac hardware. This also means the VSTS CI/CD system in the cloud covers the gamut of Linux, macOS and Windows in one offering.

Without security and performance, there are no apps of the future, and moving fast only gives you continuous bugs.
Theresa LanowitzCEO, Voke

Microsoft also made generally available Team Foundation Server 2018 and the TFS Database Import Service. Additionally, it released to preview the company’s open source command-line tools for VSTS and YAML support for VSTS build definitions, so developers can represent their build pipeline as code.

Finally, Microsoft launched a new partnership with GitHub to drive adoption of the Microsoft-developed Git Virtual File System (GVFS) as the industry standard to use Git at scale. Microsoft has become one of the most prolific contributors to open source largely through GitHub, and the two have worked together to bring GVFS to the code repository’s 25 million users on Windows, Mac and Linux clients, said Sam Lambert, senior director of infrastructure at GitHub.

Theresa Lanowitz, founder and CEO of Voke, a market research firm in Minden, Nev., praised Microsoft for its strong release management updates with software such as Azure DevOps Projects, but she expected to hear and see more about security and performance. “Without security and performance, there are no apps of the future, and moving fast only gives you continuous bugs,” she said.

“Our research shows low automation and low adoption of any commercial release management tool for full lifecycle traceability — of all assets,” she said in an interview from Microsoft Connect();, noting that enterprise integration issues may be partly to blame for low adoption of these tools.

AWS and Microsoft announce Gluon, making deep learning accessible to all developers – News Center

New open source deep learning interface allows developers to more easily and quickly build machine learning models without compromising training performance. Jointly developed reference specification makes it possible for Gluon to work with any deep learning engine; support for Apache MXNet available today and support for Microsoft Cognitive Toolkit coming soon.

SEATTLE and REDMOND, Wash. — Oct. 12, 2017 — On Thursday, Amazon Web Services Inc. (AWS), an Amazon.com company (NASDAQ: AMZN), and Microsoft Corp. (NASDAQ: MSFT) announced a new deep learning library, called Gluon, that allows developers of all skill levels to prototype, build, train and deploy sophisticated machine learning models for the cloud, devices at the edge and mobile apps. The Gluon interface currently works with Apache MXNet and will support Microsoft Cognitive Toolkit (CNTK) in an upcoming release. With the Gluon interface, developers can build machine learning models using a simple Python API and a range of prebuilt, optimized neural network components. This makes it easier for developers of all skill levels to build neural networks using simple, concise code, without sacrificing performance. AWS and Microsoft published Gluon’s reference specification so other deep learning engines can be integrated with the interface. To get started with the Gluon interface, visit https://github.com/gluon-api/gluon-api/.

Developers build neural networks using three components: training data, a model and an algorithm. The algorithm trains the model to understand patterns in the data. Because the volume of data is large and the models and algorithms are complex, training a model often takes days or even weeks. Deep learning engines like Apache MXNet, Microsoft Cognitive Toolkit and TensorFlow have emerged to help optimize and speed the training process. However, these engines require developers to define the models and algorithms up front using lengthy, complex code that is difficult to change. Other deep learning tools make model-building easier, but this simplicity can come at the cost of slower training performance.

The Gluon interface gives developers the best of both worlds — a concise, easy-to-understand programming interface that enables developers to quickly prototype and experiment with neural network models, and a training method that has minimal impact on the speed of the underlying engine. Developers can use the Gluon interface to create neural networks on the fly, and to change their size and shape dynamically. In addition, because the Gluon interface brings together the training algorithm and the neural network model, developers can perform model training one step at a time. This means it is much easier to debug, update and reuse neural networks.

“The potential of machine learning can only be realized if it is accessible to all developers. Today’s reality is that building and training machine learning models require a great deal of heavy lifting and specialized expertise,” said Swami Sivasubramanian, VP of Amazon AI. “We created the Gluon interface so building neural networks and training models can be as easy as building an app. We look forward to our collaboration with Microsoft on continuing to evolve the Gluon interface for developers interested in making machine learning easier to use.”

“We believe it is important for the industry to work together and pool resources to build technology that benefits the broader community,” said Eric Boyd, corporate vice president of Microsoft AI and Research. “This is why Microsoft has collaborated with AWS to create the Gluon interface and enable an open AI ecosystem where developers have freedom of choice. Machine learning has the ability to transform the way we work, interact and communicate. To make this happen we need to put the right tools in the right hands, and the Gluon interface is a step in this direction.”

“FINRA is using deep learning tools to process the vast amount of data we collect in our data lake,” said Saman Michael Far, senior vice president and CTO, FINRA. “We are excited about the new Gluon interface, which makes it easier to leverage the capabilities of Apache MXNet, an open source framework that aligns with FINRA’s strategy of embracing open source and cloud for machine learning on big data.”

“I rarely see software engineering abstraction principles and numerical machine learning playing well together — and something that may look good in a tutorial could be hundreds of lines of code,” said Andrew Moore, dean of the School of Computer Science at Carnegie Mellon University. “I really appreciate how the Gluon interface is able to keep the code complexity at the same level as the concept; it’s a welcome addition to the machine learning community.”

“The Gluon interface solves the age old problem of having to choose between ease of use and performance, and I know it will resonate with my students,” said Nikolaos Vasiloglou, adjunct professor of Electrical Engineering and Computer Science at Georgia Institute of Technology. “The Gluon interface dramatically accelerates the pace at which students can pick up, apply and innovate on new applications of machine learning. The documentation is great, and I’m looking forward to teaching it as part of my computer science course and in seminars that focus on teaching cutting-edge machine learning concepts across different cities in the U.S.”

“We think the Gluon interface will be an important addition to our machine learning toolkit because it makes it easy to prototype machine learning models,” said Takero Ibuki, senior research engineer at DOCOMO Innovations. “The efficiency and flexibility this interface provides will enable our teams to be more agile and experiment in ways that would have required a prohibitive time investment in the past.”

The Gluon interface is open source and available today in Apache MXNet 0.11, with support for CNTK in an upcoming release. Developers can learn how to get started using Gluon with MXNet by viewing tutorials for both beginners and experts available by visiting https://mxnet.incubator.apache.org/gluon/.

About Amazon Web Services

For 11 years, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud platform. AWS offers over 90 fully featured services for compute, storage, networking, database, analytics, application services, deployment, management, developer, mobile, Internet of Things (IoT), Artificial Intelligence (AI), security, hybrid and enterprise applications, from 44 Availability Zones (AZs) across 16 geographic regions in the U.S., Australia, Brazil, Canada, China, Germany, India, Ireland, Japan, Korea, Singapore, and the UK. AWS services are trusted by millions of active customers around the world — including the fastest-growing startups, largest enterprises, and leading government agencies — to power their infrastructure, make them more agile, and lower costs. To learn more about AWS, visit https://aws.amazon.com.

About Amazon

Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. Customer reviews, 1-Click shopping, personalized recommendations, Prime, Fulfillment by Amazon, AWS, Kindle Direct Publishing, Kindle, Fire tablets, Fire TV, Amazon Echo, and Alexa are some of the products and services pioneered by Amazon. For more information, visit www.amazon.com/about and follow @AmazonNews.

About Microsoft

Microsoft (Nasdaq “MSFT” @microsoft) is the leading platform and productivity company for the mobile-first, cloud-first world, and its mission is to empower every person and every organization on the planet to achieve more.

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Announcing the preview of Java support for Azure Functions

Serverless provides a great model for accelerating app development, but developers want to do it using the programming languages and development tools of their choice. Ever since we first released Azure Functions, support for Java has been a top request. Today, at JavaOne in San Francisco, we’re announcing the public preview of Java support in Azure Functions.

With the recently announced capability to run the open source Azure Functions runtime on cross-platform .NET Core, we’ve architected our runtime to allow a broadened support for different programming languages. Java is the first new language we are introducing in this public preview. The new Java runtime will share all the differentiated features provided by Azure Functions, such as the wide range of triggering options and data bindings, serverless execution model with auto-scale, as well as pay-per-execution pricing.

As a Java developer, you don’t need to use any new tools to develop using Azure Functions. In fact, with our newly released Maven plugin, you can create, build, and deploy Azure Functions from your existing Maven-enabled projects. The new Azure Functions Core Tools will support you to run and debug your Java Functions code locally on any platform.

Image 1

Figure 1: Azure Functions project in Java created using Maven Archetype

What is even more exciting is that popular IDEs and editors like Eclipse, IntelliJ, and VS Code can be used to develop and debug Azure Functions locally.

Image 2

Figure 2: A serverless function in Java debugged using Visual Studio Code

To get started, look at the Azure Functions Java tutorial to create your first Java function and deploy it to Azure using Maven and Jenkins today. Also, if you’re attending JavaOne, join our sessions and swing by the Azure booth to learn more about building serverless apps in Azure with Java!

Next steps

SAP Data Hub debuts at SAP TechEd 2017

LAS VEGAS SAP developers got a good look at a cloud-centric future at SAP TechEd 2017.

During the opening keynote address, Bjorn Goerke, CTO and president of SAP Cloud Platform, donned the guise of Star Trek‘s Capt. James T. Kirk and compared digital business transformation to the “Kobayashi Maru test” of the Star Trek movies — a no-win conundrum. Because organizations don’t see an obvious answer to the problems posed by digital transformation, they are often paralyzed into inaction.

There are three building blocks to getting around this and solving the Kobyashi Maru test, Goerke said: truth through trusted data, agility in application design and development, and a superior user experience.

To help organizations meet these digital transformation goals, SAP demonstrated a number of new products and services at SAP TechEd 2017. One of these was the new SAP Data Hub, a data management system that was unveiled on Monday at a separate event in New York. SAP also firmly committed itself as a cloud-first company with the following announcements:

  • SAP Cloud Platform will be available on Google Cloud Platform.
  • The SAP ABAP development platform will be available in the cloud.
  • SAP is joining the Cloud Native Computing Foundation.

One hub for organizational data

SAP Data Hub will help organizations manage data from a variety of sources that currently sit in separate silos, Goerke said.

“The challenge that companies face is that there are various data silos, ERP data, data warehouses [and] big data sitting in data lakes,” he said. “The question is, how do you put a consistent layer on top of it so you can make sense out of all those different data sets and correlate them and process them so that you can develop new applications on top of it, do analytics, do data science and drive insights? You need to manage the whole pipeline of data flowing through your different data sets, and this is what SAP Data Hub does.”

The partnership with Google is also very important, according to Goerke.

“Google has provided us with the necessary hardware. So, we have certified SAP HANA and S/4HANA and additional products like the SAP analytics portfolio to run on that infrastructure, and we released SAP Cloud Platform on Google Cloud Platform,” he said. “With that, we have taken the last steps in completing our picture toward a real multicloud platform. It gives our customers a choice to run their digital transformation workloads in the future — whether they want to run them in an SAP cloud, or whether they want to run it through us on an AWS [Amazon Web Services], Azure or Google Cloud Platform; that’s the kind of flexibility our customers have asked us to provide for them.”

ABAP gets cloudy

The biggest cheer from the developer-heavy audience at the opening keynote came when Goerke announced SAP’s venerable ABAP programming environment would be made available in the SAP Cloud Platform — but not until 2018.

“SAP has been around for a while, and ABAP is still one of the key languages and environments that we have to build enterprise applications. S/4HANA itself is built on the ABAP stack, so it’s a rock-solid, extremely powerful enterprise environment,” he said. “We have a few million ABAP developers around the world who have built skills using ABAP to build applications that extend or enhance SAP ERP. But the question is, what do we do with those developers? Do we take them into the cloud? Of course, we have to, so ABAP will be supported in the cloud.”

SAP’s cloud credentials were bolstered by its joining the Cloud Native Computing Foundation, which fosters cloud adoption through systems like Kubernetes.

“The foundation has a lot of big names behind it, like Google and Microsoft, who are putting forces together to drive the technology behind a cloud-native computing model,” Goerke said. “[Technologies] like containerization of IT workloads, with Kubernetes as an orchestration and management environment for containerized workloads. We are joining as a platinum member, [and] that allows us to not only consume the technologies, but influence the direction the technologies take. And there are a number of things that we can contribute from an enterprise perspective.”

Cloud direction is good, but challenge is in details

Gavin Quinn, founder of Mindset Consulting, a Minneapolis-based firm that specializes in Fiori and mobile app development, said SAP’s direction is good, but you have to look into the details.

It’s a great direction, but the meat is still developing.
Gavin Quinnfounder of Mindset Consulting, on SAP’s cloud future

“I saw a lot of promising things for the future; Leonardo is a tremendous idea, and there’s a lot of really tremendous things that you can do, in theory, if all this works,” Quinn said. “But what does it actually cost? How do you roll it out? And what’s the nitty-gritty behind the services? It’s a great direction, but the meat is still developing. Our customers love the concept of it and want in on it, but they don’t know where to start, and that’s where the challenge lies.”

The business transformation SAP talks about may still be beyond the capabilities of most customers, Quinn said.

“For many of [of the developers who attend SAP TechEd], 99% of their time [is on things like] how to get an ABAP report, how to build a BW cube, or maybe how to get to HANA. They’re barely into HANA, and S/4 is well beyond that. So, for some of our base customers, that stuff is hardly on their roadmap,” Quinn said. “There are examples out there, and everyone loves the idea of getting there, but it just takes time. It’s going to be a challenge, but they’re setting the direction.”

ABAP in the cloud is a huge deal

SAP’s cloud message was strong, but the move to make ABAP available in the cloud is a huge deal, according to Josh Greenbaum, analyst and founder of Enterprise Applications Consulting. Many CIO’s were concerned that ABAP programmers would be left behind in the cloud-centric digital transformation.

“This extends the knowledge and these assets, both human and technological,” Greenbaum said. “Many CIOs were asking … what happens to my ABAP programmers? Where do they go? What do I do with them? How do I reposition them? Now, by having ABAP available in the cloud, you can develop extensions and new apps in ABAP and run them in the cloud. You can be ready for the next generation of apps. They have to be cloud-ready, so this is good news for developers and IT organizations.”

Why private APIs are the hottest thing around and other news

Nearly three-quarters of software developers spend at least 25% of their time weekly working with APIs, according to a recently released survey from Postman. And those aren’t just any APIs: The majority of developers spend 90% of their time working with internal or private APIs.

At a time when there’s never been more pressure on developers to produce software faster, it’s not surprising that usage of public and private APIs is so high. In the Postman survey, internal or private APIs dominate, but developers still said they spend about 20% of their time using public APIs.

Private APIs are very useful for other internal development practices, like microservices, so it’s not surprising the Postman survey found microservices are considered the “most exciting technology” of 2017. Overall, 27% of the developers surveyed said they were very interested in microservices.

But whether they’re using public or private APIs, the Postman survey takers weren’t completely satisfied with the tools they have, as 80% said they wanted more offerings to help them better utilize APIs. Typically, developers use two tools to manage their workflows at any given time, whether with public or private APIs. And their other complaint was documentation; most felt the supporting information provided with the public or private APIs was insufficient.

How do you stack up?

According to Stack Overflow, the median salary of a developer in the United States just starting out is $75,000. With 15 years of experience, that number rises to just shy of $125,000.

How well do you compare? Well, now there’s a tool that can tell you exactly how you stack up — also from Stack Overflow. The Stack Overflow Salary Calculator looks at location, education, years of experience, what kind of tools you use and what kind of developer you are. Right now, the calculator is limited to the United States, Canada, France, Germany and the United Kingdom.

In the big picture, where you live matters the most when it comes to a paycheck; salaries in the United States are substantially higher than in any of the other countries. The second-most important factor seems to be type of developer, with DevOps developers getting the highest salaries, followed closely by data scientists.

Testing for the iPhone 8

Because timing is everything with software testing, cloud-based testing provider Sauce Labs announced it can now offer same-day testing of iPhone 8 and iPhone 8 Plus applications, as well as support for testing Apple’s new iOS 11 operating system.

These new releases continue to add pressure to software development teams to get applications out quickly and bug-free. In many companies, the answer is to automate testing, but that is far easier said than done in most organizations. And with the growing number of devices that require testing, many teams are turning to third-party test providers. With its latest release, Sauce Labs can now offer customers over 1,000 actual devices to test — either by hand or through an automated process — in a public or private cloud.

Custom Vision Service introduces classifier export, starting with CoreML for iOS 11

To enable developers to build for the intelligent edge, Custom Vision Service from Microsoft Cognitive Services has added mobile model export.

Custom Vision Service is a tool for easily training, deploying, and improving custom image classifiers. With just a handful of images per category, you can train your own image classifier in minutes. Today, in addition to hosting your classifiers at a REST endpoint, you can now export models to run offline, starting with export to the CoreML format for iOS 11. Export will allow you to embed your classifier directly in your application and run it locally on a device. The models you export are optimized for the constraints of a mobile device, so you can classify on device in real time.

Custom Vision Service is designed to build quality classifiers with very small training datasets, helping you build a classifier that is robust to differences in the items you are trying to recognize and that ignores the things you are not interested in. With today’s update, you can easily add real time image classification to your mobile applications. Creating, updating, and exporting a compact model takes only minutes, making it easy to build and iteratively improve your application. More export formats and supported devices are coming in the near future.

A sample app and tutorial for adding real time image classification to an iOS app is now available.

To learn and starting building your own image classifier, visit www.customvision.ai.

Pineapple

Screenshot of a fruit recognition classifier in our sample app.

Delivering Safer Apps with Windows Server 2016 and Docker Enterprise Edition

Windows Server 2016 and Docker Enterprise Edition are revolutionizing the way Windows developers can create, deploy, and manage their applications on-premises and in the cloud. Microsoft and Docker are committed to providing secure containerization technologies and enabling developers to implement security best practices in their applications. This blog post highlights some of the security features in Docker Enterprise Edition and Windows Server 2016 designed to help you deliver safer applications.

For more information on Docker and Windows Server 2016 Container security, check out the full whitepaper on Docker’s site.

Introduction

Today, many organizations are turning to Docker Enterprise Edition (EE) and Windows Server 2016 to deploy IT applications consistently and efficiently using containers. Container technologies can play a pivotal role in ensuring the applications being deployed in your enterprise are safe — free of malware, up-to-date with security patches, and known to come from a trustworthy source. Docker EE and Windows each play a hand in helping you develop and deploy safer applications according to the following three characteristics:

  1. Usable Security: Secure defaults with tooling that is native to both developers and operators.
  2. Trusted Delivery: Everything needed to run an application is delivered safely and guaranteed not to be tampered with.
  3. Infrastructure Independent: Application and security configurations are portable and can move between developer workstations, testing environments, and production deployments regardless of whether those environments are running in Azure or your own datacenter.

Usable Security

Resource Isolation

Windows Server 2016 ships with support for Windows Server Containers, which are powered by Docker Enterprise Edition. Docker EE for Windows Server is the result of a joint engineering effort between Microsoft and Docker. When you run a Windows Server Container, key system resources are sandboxed for each container and isolated from the host operating system. This means the container does not see the resources available on the host machine, and any changes made within the container will not affect the host or other containers. Some of the resources that are isolated include:

  • File system
  • Registry
  • Certificate stores
  • Namespace (privileged API access, system services, task scheduler, etc.)
  • Local users and groups

Additionally, you can limit a Windows Server Container’s use of the CPU, memory, disk usage, and disk throughput to protect the performance of other applications and containers running on the same host.

Hyper-V Isolation

For even greater isolation, Windows Server Containers can be deployed using Hyper-V isolation. In this configuration, the container runs inside a specially optimized Hyper-V virtual machine with a completely isolated Windows kernel instance. Docker EE handles creating, managing, and deleting the VM for you. Better yet, the same Docker container images can be used for both process isolated and Hyper-V isolated containers, and both types of containers can run side by side on the same host.

Application Secrets

Starting with Docker EE 17.06, support for delivering secrets to Windows Server Containers at runtime is now available. Secrets are simply blobs of data that may contain sensitive information best left out of a container image. Common examples of secrets are SSL/TLS certificates, connection strings, and passwords.

Developers and security operators use and manage secrets in the exact same way — by registering them on manager nodes (in an encrypted store), granting applicable services access to obtain the secrets, and instructing Docker to provide the secret to the container at deployment time. Each environment can use unique secrets without having to change the container image. The container can just read the secrets at runtime from the file system and use them for their intended purposes.

Trusted Delivery

Image Signing and Verification

Knowing that the software running in your environment is authentic and came from a trusted source is critical to protecting your information assets. With Docker Content Trust, which is built into Docker EE, container images are cryptographically signed to record the contents present in the image at the time of signing. Later, when a host pulls the image down, it will validate the signature of the downloaded image and compare it to the expected signature from the metadata. If the two do not match, Docker EE will not deploy the image since it is likely that someone tampered with the image.

Image Scanning and Antimalware

Beyond checking if an image has been modified, it’s important to ensure the image doesn’t contain malware of libraries with known vulnerabilities. When images are stored in Docker Trusted Registry, Docker Security Scanning can analyze images to identify libraries and components in use that have known vulnerabilities in the Common Vulnerabilities and Exposures (CVE) database.

Further, when the image is pulled on a Windows Server 2016 host with Windows Defender enabled, the image will automatically be scanned for malware to prevent malicious software from being distributed through container images.

Windows Updates

Working alongside Docker Security Scanning, Microsoft Windows Update can ensure that your Windows Server operating system is up to date. Microsoft publishes two pre-built Windows Server base images to Docker Hub: microsoft/nanoserver and microsoft/windowsservercore. These images are updated the same day as new Windows security updates are released. When you use the “latest” tag to pull these images, you can rest assured that you’re working with the most up to date version of Windows Server. This makes it easy to integrate updates into your continuous integration and deployment workflow.

Infrastructure Independent

Active Directory Service Accounts

Windows workloads often rely on Active Directory for authentication of users to the application and authentication between the application itself and other resources like Microsoft SQL Server. Windows Server Containers can be configured to use a Group Managed Service Account when communicating over the network to provide a native authentication experience with your existing Active Directory infrastructure. You can select a different service account (even belonging to a different AD domain) for each environment where you deploy the container, without ever having to update the container image.

Docker Role Based Access Control

Docker Enterprise Edition allows administrators to apply fine-grained role based access control to a variety of Docker primitives, including volumes, nodes, networks, and containers. IT operators can grant users predefined permission roles to collections of Docker resources. Docker EE also provides the ability to create custom permission roles, providing IT operators tremendous flexibility in how they define access control policies in their environment.

Conclusion

With Docker Enterprise Edition and Windows Server 2016, you can develop, deploy, and manage your applications more safely using the variety of built-in security features designed with developers and operators in mind. To read more about the security features available when running Windows Server Containers with Docker Enterprise Edition, check out the full whitepaper and learn more about using Docker Enterprise Edition in Azure.