Mai 2017 - Seite 33 von 189 - Cloud Computing Köln

By Aja Hammerly, Developer Advocate

A few weeks ago the Google Cloud Ruby team attended RailsConf in Phoenix, Arizona. RailsConf is one of the largest conferences for Ruby programmers in the world and we were happy to spend three days learning and sharing with our community. We enjoyed hearing from folks that are currently using Google Cloud Platform (GCP) and we’re working diligently to integrate their feedback into our future products.

About half of our team had never attended a Ruby conference before. Luckily they were in good company since about half of the attendees at the event were new to Ruby, conferences, tech, or all of the above.

All of us enjoyed the keynotes including Rails core contributor Aaron Patterson’s crap data joke and Rails creator DHH’s discussion of how community values are reflected in programming languages and frameworks. He used Python and Ruby as his examples and showed how while they both share some values like “Readability Counts” they also differ on values like whether there should only be one way to do something.

Daniel Azuma, an engineer on the Google Ruby team, gave a talk titled “What’s my app *really* doing in production?” With so many new Rubyists at the conference this was a fine opportunity to teach people about some of the tools for debugging and profiling that are built in to Ruby and Rails. Among other things, he discussed how you can use ActiveSupport::Notifications to get more information when specific methods are called.

Remi Taylor, another engineer on the Google Ruby team, gave a talk called “Google Cloud <3 Ruby” showing off the new features GCP has for Rubyists. I gave a talk called “Syntax Isn’t Everything: NLP for Rubyists” which showed off Google’s Cloud Natural Language API. Both of our talks generated interest in Google’s Machine Learning APIs and dozens of people tried out the Cloud Vision codelab back at our booth. In the past, Rubyists haven’t been interested in machine learning so it was great to see all the excitement.

At our booth we had great conversations with both new and veteran Rubyists. Many people took advantage of our codelabs to try out Google Cloud with Ruby while there was someone to help available. It was also a chance to have one-on-one conversations with developers from all over the world. Many of the people who stopped by are trying or using Kubernetes for their Rails apps. Others are using App Engine, Cloud Storage or other Google products. This was my third RailsConf since I started at Google, and I’m happy to see that more and more community members are trying Google Cloud products and giving us feedback so we can continue our goal of creating tools that feel good to Rubyists and help them build and run amazing applications.
Quelle: Google Cloud Platform

26. Mai 2017

da Agency

What’s brewing in Visual Studio Team Services: May 2017 Digest

This post series provides the latest updates and news for Visual Studio Team Services and is a great way for Azure users to keep up-to-date with new features being released every three weeks. Visual Studio Team Services offers the best DevOps tooling to create an efficient continuous integration and release pipeline to Azure. This sprint has our Build 2017 conference deliverables in it, so it’s a big one, especially in the CI/CD space. Here’s a recap with all of our conference presentations.

One of our goals is to keep lowering the barrier to entry for automating your application deployment. The ease with which teams can deploy and validate their application is a huge part of how quickly they are able to ship. While our CI/CD system is completely open, by doing deep integrations with Azure we can make setting up deployments extremely simple. It also unlocks many opportunities for richer workflows that span both development and operations. To that end, we are continuing to strive to make VSTS + Azure the best end-to-end DevOps experience.

This month brings a bunch of new capabilities toward realizing that goal. We have significantly expanded the breadth of app type we support:

We now support using the automation agent on the VMs to which you deploy and using it to drive your application deployment. This has easily been our most requested feature for Release Management and we’re excited for it go live.
We continue to give more and more focus to containers. This sprint, we introduce native support for Kubernetes and Service Fabric, the latter being a great option for Windows containers.
We already have great support for deploying to Azure Web Apps, but we’ve expanded the app types we support with our native task to include Node, PHP, and Linux Web Apps with containers. We’ve also expanded the entry point for setting up CI/CD with more options in the Azure portal configuration UI and introduced the ability to set up CI/CD for Azure Web Apps from the AZ CLI.

Let’s dive in!

VM Deployment (Public Preview)

Release Management now supports robust out-of-the-box multi-machine deployment. You can now orchestrate deployments across multiple machines and perform rolling updates while ensuring high availability of the application throughout.

Agent-based deployment capability relies on the same build and deployment agents. However, unlike the current approach where you install the build and deployment agents on a set of proxy servers in an agent pool and drive deployments to remote target servers, you install the agent on each of your target servers directly and drive rolling deployment to those servers. You can use the full task catalog on your target machines.

A deployment group is a logical group of targets (machines) with agents installed on each of them. Deployment groups represent your physical environments, such as single-box Dev, multi-machine QA, and a farm of machines for UAT/Prod. They also specify the security context for your physical environments.

You can use this against any VM that you register our agent with. We’ve also made it very easy to register with Azure with support for a Azure VM extension that auto-installs the agent when the VM spins up. We will automatically inherit the tags on the Azure VM when it’s registered in VSTS.

Once you have a deployment group, you simply configure what you want us to execute on that deployment group. You can control what gets run on which machines using tags and control how fast or slow the rollout happens.

When the deployment is run, the logs show the progression across the entire group of machines you are targeting.

This feature is now an integrated part of Release Management. There are no additional licenses required to use it.

While we’re on the topic of deploying to different environments, check out our post on configuring your release pipelines for safe deployments.

Azure virtual machine scale set deployment

Another common pattern being use for deployment is to create a full machine image for each version of the application and then deploy that. To make that easier we have a new Build immutable machine image task that uses Packer to generate a machine image after deploying applications and all the required prerequisites. The tasks takes either deployment script or packer configuration template to create the machine image and stores it in an Azure Storage account. This image can than be used for Azure Virtual Machine Scale Set deployments that work well for this type of immutable image deployment. You can learn more in our post on deploying applications to VM scale sets.

Built-in tasks for building and deploying container based applications

With this release we have pulled most of the tasks in our Docker extension into the product by default, improved them, and introduced a set of new tasks and templates for making a set of container scenarios easier.

Docker: Build, push, or run Docker images, or run a Docker command. This task can be used with Docker or Azure Container registry. You can now use our built-in service principal authentication with ACR to make it even easier to use.
Docker-Compose: Build, push, or run multi-container Docker applications. This task can be used with Docker or Azure Container registry.
Kubernetes: Deploy, configure, or update your Kubernetes cluster in Azure Container Service by running kubectl commands.
Service Fabric: Deploy containers to a Service Fabric Cluster. Service Fabric is the best choice today for running Windows Containers in the cloud. In fact, this is where more and more of VSTS itself is running each sprint.

Azure Web App deployment updates

We have made many enhancements for Azure Web Applications:

Azure App Service deployment task supports Node.js, Python applications to be deployed.
Azure App Service deployment task supports deploying to Azure Web App for Linux using containers.
Azure portal Continuous Delivery is expanded to now support Node applications.

We have also introduced CI/CD support into the latest version of the Azure CLI for configuring CI/CD. Here is an example:

az appservice web source-control config –name mywebapp –resource-group mywebapp_rg –repo-url https://myaccount.visualstudio.com/myproject/_git/myrepo –cd-provider vsts –cd-app-type AspNetCore

Deploy to Azure Government Cloud

Customers with Azure subscriptions in Government clouds can now configure Azure Resource Manager service endpoint to target national clouds.

With this, you can now use Release Management to deploy any application to Azure resources hosted in government clouds, using the same deployment tasks. Read more about this in our on setting up continuous delivery to Microsoft Azure Government.

Automatic linking from work items to builds

With this new setting in the build definition, users can track the builds that have incorporated their work without having to search through a large set of builds manually. Each successful build associated with the work item automatically appears in the development section of the work item form.

To enable this feature, toggle the setting under Options in your build definition.

Note: The feature is only available for definitions building Team Services Git or TFVC repos, and only through the new build definition editor.

Using Jenkins for Continuous Integration with Team Services

Jenkins is a popular continuous integration build server, and there are multiple ways to use Jenkins as a CI server with Team Services. Jenkins’ built-in Git Plugin or Team Foundation Server Plugin can poll a Team Services repository every few minutes and queue a job when changes are detected. For those who need tighter integration, Team Services provides two additional ways to achieve it: 1) the Jenkins Service Hook, and 2) Jenkins build and release tasks.

Team Services adds capabilities over the Jenkins Service Hook by including connectors that allow its build and release systems to integrate with Jenkins. These connectors can be chosen from the list of tasks to execute as steps in a Team Services build or release definition.

A Team Services build or release will queue a Jenkins job and download resulting artifacts. Since these tasks execute in a light-weight, long-polling agent that can be installed in your data center, there is no need to modify inbound firewall rules for Team Services to access your Jenkins server from the cloud.

You can learn more in our blog post on integrating with Jenkins.

Maven for Package Management (Public Preview)

Java developers share components by packaging up their code in Maven artifacts, the Java equivalent of a NuGet package. Team Services customers needing a place to host Maven artifacts used to have to use third-party services, like Nexus or Artifactory, to meet their needs. We’re proud to announce that Team Services Package Management now supports hosting Maven artifacts! Check out our getting started guide.

You’ll also want to check out our recent blog post on the extensive support for Java development with Team Services.

New Git branch policies configuration experience

Branch policies are a great way to ensure quality in your branches by requiring code reviews, automatically running a build and tests for each PR, and more. We’ve redesigned the branch policies configuration experience and added some great new capabilities. One of the most powerful features is the ability to configure policies for branch folders. You can do this from the Branches view by selecting a branch folder and choosing Branch policies from the context menu.

This will open the new policies configuration UX, where you can configure policies that apply to all of the branches in the branch folder.

If you’re using the build policy, you can now configure multiple builds for a single branch. There are also new options to specify the type of trigger, automatic or manual. Manual triggers are useful for things like automated test runs that might take a long time to run, and you only really need to run once before completing the pull request. The build policy also has a display name that is useful if you’re configuring multiple builds.

Share Git pull requests with teams

The Share Pull Request action is a handy way to notify reviewers. In this release, we’ve added support for teams and groups, so you can notify everyone involved the pull request in a single step.

Visualize your Git repository

Team Services now supports showing a graph while showing commit history for repositories or files. Now you can easily create a mental model of all your branches and commits for your git repositories using git graph. The graph shows all your commits in topological order.

The key elements of the git graph include:

The git graph is right-aligned, so commits associated with the default branch or the selected branch appear on the right while the rest of the graph grows on the left.
Merge commits are represented by grey dots connected to their first parent and second parent.
Normal commits are represented by blue dots.
If the parent commit of a commit is not visible in the view port on the next 50 commits, then we excise the commit connection. Once you click the arrow, the commit is connected to its parent commit.

You can read more in our post on the Git graph and advanced filters.

Delivery Plans general availability

We are excited to announce that Delivery Plans is out of preview and is now included in the basic access level of VSTS. Delivery Plans is an organizational tool that helps users drive cross-team visibility and alignment by tracking work status on an iteration-based calendar. Users can tailor their plan to include any team or backlog level from across projects in the account. Furthermore, Field Criteria on Plans enables users to further customize their view, while Markers highlight important dates.

Delivery Plans is currently only available for VSTS; however, it will be included in the upcoming TFS 2017 Update 2 release.

Check out the marketplace page for Delivery Plans to learn more and install the extension.

Delivery timeline markers

Have you been looking for a way to highlight key dates on your Delivery Plan? Now you can with plan markers. Plan markers let you visualize key dates for teams directly on your deliver plan. Markers have an associated color and label. The label shows up when you click the marker dot.

Work item search general availability

Thank you all for installing and using the Work Item Search preview from the marketplace. It has been one of our most highly rated extensions. With this release, we are making it easier for you to use work item search by making it a built-in feature of VSTS.

You can get started with work item search using the search box:

Updated process customization experience

We have modernized our pages when customizing your process. The page now includes a breadcrumb in the top to clearly show the context you are in when editing the process or the work item types inside the process.

Also, it’s much easier to start customizing your work item form. When you select Customize from the context menu in a work item, we automatically create an inherited process for you, if you are not already using one, and bring you into the layout editor.

Insight into your projects with Analytics

Our new Analytics service brings you and your team new insights into the health and status of your work. Analytics is currently in preview, and at this early stage includes three new dashboard widgets, Lead Time, Cycle Time, and Cumulative Flow Diagram (CFD). You can install Analytics from the VS Team Services Marketplace.

We released a long list of new features the last couple of sprints. Be sure to read the release notes for May 11th and April 19th for a full list.

Happy coding!
Quelle: Azure

26. Mai 2017

da Agency

Is Shazam's Game Show The Future Of Unscripted TV?

Jamie Foxx with contestants on the new show Beat Shazam.

Michael Becker / FOX

On a recent afternoon at CBS’s Studio 36 in LA, at the center of a glowing teal and purple set lit up like the inside of a Poké Ball, the actor, comedian, and musician Jamie Foxx was whipping an eager game show audience into a froth. Rebounding after a commercial break, he leaned into a shopworn catchphrase, and the crowd, on cue, shouted back with glee.

“The money’s going!”

“Up!”

“The money’s going!”

“Up!”

Onstage with Foxx — who was loose and charismatic in a red, white, and black biker jacket, closely cropped haircut, and sculpted beard — were Christina and Steve, romantic partners and contestants on the game show, called Beat Shazam, which premieres tonight on Fox. They’d reached the final round of the game, in which teams compete — first against each other, and then against the titular name-that-song app — to rapidly identify popular songs. Only one song stood between them and the grand prize of $1 million — one song, that is, and Shazam, which is represented in the game by an enormous, circular, smoke-spouting monitor that looms over the stage like an angry deity, or a less-homicidal upgrade of HAL 9000, the sentient computer from 2001: A Space Odyssey.

Christina, from Brooklyn, had tan skin and chest-length, wavy brown hair. Steve, from Nashville, was lanky with round cheeks and a goatee. As on any decent primetime game show, they faced a burdensome choice: take on Shazam and go for the $1 million, or walk away with what they’d earned up to that point in the game — a less transformative but still substantial $197,000. If they challenged Shazam and lost, their money would be halved.

In the audience, the air went thick and quiet with suspense. A sober look fell over Steve's face, as if the weight of the world sat on his shoulders.

“Are you going to beat Shazam, or are you going to walk away?” Foxx asked Christina. She paused, and then declared, cocking her neck from side to side on each syllable, “I'm going to Beat. Sha. Zam!” The room erupted.

“Beat! Sha! Zam! Beat! Sha! Zam! Beat! Sha! Zam!”

Its existence underscores growing interest in franchises with appeal across platforms.

Since it launched in 2002, Shazam’s willingness to march to its own beat has helped the company navigate more than a decade of transformation in both the music and mobile app businesses. Its 300 million users, who use the app over 20 million times per day to identify songs playing in public spaces — bars, coffee shops, on the radio — at the touch of a button, have grown accustomed to seeing its curlicue logo pop up in unlikely places, including in Super Bowl commercials, on cases of Coke, and, as of last year, inside Snapchat’s camera function.

But Beat Shazam — the first primetime TV show based on an app (a play-at-home version will launch concurrently) — is by far the company’s strangest and most high-profile experiment yet. With backing from Foxx, Don’t Forget the Lyrics creator Jeff Apploff, and reality TV kingpin Mark Burnett, its existence underscores both Shazam’s unique cultural footing and a growing interest among tech companies and the entertainment industry in franchises with appeal across platforms. Last fall, The CW premiered a Saturday morning cooking show based on the popular recipe app Dinner Spinner, and a game show based on Candy Crush, hosted by Mario Lopez, will debut on CBS this summer.

“If you’ve got an app that has 300 million users identifying songs, it tells you right off the bat that you’ve got an audience,” Apploff told BuzzFeed News.

Shazam CEO Rich Riley (left) with Chief Revenue Officer Greg Glenday at Shazam's NYC office.

Ricky Rhodes for BuzzFeed News

The first version of Shazam for iPhone — based on a pre-smartphone service where users could dial a number, hold up the mouthpiece of their phone, and receive a text message with information about whatever song was playing — was one of the mobile revolution’s original success stories. After it was released in 2008, the company became a verb, built a business by collecting affiliate fees from the sales it generated for iTunes (over 1 million downloads per day at its peak), and drew investment from blue chip venture capital firms like Kleiner Perkins Caufield & Byers, which helped fund Amazon, Google, and Snapchat.

In 2012, at the height of the initial wave of interest in so-called second-screen experiences that linked mobile devices with television programming, Shazam began offering cast and episode information for TV shows — only to later roll back that functionality due to insufficient demand. Its push into advertising was more fruitful, and last year, Shazam turned its first profit, even as music sales continued to decline amid a broad shift toward streaming. The majority of the company’s income now comes from brand partners, who use Shazam’s in-house creative team and tech — including a new in-app camera that can recognize codes printed on packages and other surfaces — to make their promotional campaigns interactive.

The company continues to evolve. Shazam was an early mover on a trend that has now seized much of Silicon Valley, in which apps on your phone promise to make sense of the world around you. In roughly the past month, both Facebook and Google have announced “augmented reality” products that use your smartphone’s camera to recognize objects in your environment and overlay contextual information, like a restaurant’s Yelp ratings or the name of a flower species.

On a recent episode of the HBO comedy Silicon Valley, a startup providing such a service was described as “Shazam for food.” But the Shazam for food in the real world, or at least the Shazam for food brands, may well just be Shazam — the company unveiled its own AR capabilities at SXSW this year.

“We’ve never taken our eye off the ball in terms of the core of what we do, and that’s allowed us to extend our leadership and extend our brand and our capabilities,” said Rich Riley, CEO of Shazam since 2013 and an executive producer of Beat Shazam. “Fortunately for us, interest in music is always increasing, so I think we’ll continue to innovate and look for more big partnerships.”

Michael Becker / FOX

Whether Beat Shazam can match the popularity of its namesake remains to be seen. Apploff said he took the idea from a long-running parlor version of Name That Tune that guests play at his annual New Year’s Eve party. He first approached Riley with the concept over two years ago at the behest of Fox, which, at the time, was working closely with Shazam on the hit music industry drama Empire.

Knowing that viewers could dismiss the show as a corporate cash grab, or simply superfluous, the producers doubled down on entertainment value, luring Foxx — an Grammy and Academy Award winner — and promising A-list special guests and life-changing prize money. They ran through hundreds of iterations of the game before settling on the format, with three teams of two competing against each other until one is left standing to face Shazam. Test versions that featured more teams, or brought in the Shazam character earlier on, felt flat.

“We taped for nine hours one Sunday and threw everything against the wall,” Foxx, who said he last used Shazam to identify a “Bad and Boujee” remix at a nightclub in Budapest, told BuzzFeed News. “The good was really good, but the bad was really bad. I said, ‘Guys, I fucked up. We all fucked up.’ We were thinking, Is this the right thing to do?”

The first hint that they’d found a winning formula came from trial contestants, who’d volunteered to help work through the kinks. “They started saying to us, ‘We’ll stay the whole day! We don’t wanna leave! Let’s play more!’” Apploff said.

Foxx, who figures heavily in ads promoting the show, said he’s already met at least one fan of the concept. On a recent drive in LA, he was startled by a man who pulled his car next to his and started screaming his name. “I thought this dude was trying to harm me or something,” Foxx said. “But the first thing he said was ‘I can beat Shazam!’”

Quelle: <a href="Is Shazam's Game Show The Future Of Unscripted TV?“>BuzzFeed

25. Mai 2017

da Agency

Why your company should be considering a cognitive IVR system

To those of us in the contact center space, one of the most interesting and promising developments has arrived. We can now build cognitive agents that communicate with customers using natural language through voice calls. The industry is finally listening to what customers have been saying for a long time: Traditional interactive voice response (IVR) systems are a terrible way to communicate with people. Come up with something better or we’ll take our business elsewhere.
Many younger customers tend to bypass the voice channel in favor of chatbots and other forms of social communications. But voice calls are still the primary way most companies communicate externally. The problem for companies: even though it’s extremely cost effective for a call to be completely handled inside an IVR system, most calls result in customers opting out to a live agent. It’s more expensive to the company and frustrating to the caller.
It is finally possible to create a cognitive IVR system that can handle deeper interactions with customers. Cognitive self-service chatbots understand natural language. And there have been significant improvements in speech recognition systems that can accurately transcribe narrowband audio into text utterances. Virtual agents created with technologies such as IBM Watson demonstrate the potential cost savings and improvements in customer satisfaction that are achievable when you unleash a cognitive workforce into the field of call automation.
Cognitive IVRs are a win-win for customers and the companies that deploy them. Any form of call automation that significantly drives down the need for live call center agents can result in huge cost savings. But the additional and more subtle benefits tie to customer retention. Cognitive IVRs hold the promise of shorter resolution times, which have a direct correlation to customer satisfaction. If I can get my questions answered quickly by an automated agent and avoid a call queue to speak with a live agent, I will walk away from the experience happier and more likely to return in the future.
As with any new and disruptive technology, there are challenges. How do I create cognitive agents that can handle subtle variations in the way questions are asked? How do I train the system to understand the intricacies of my business? How do I integrate cognitive agents into my existing call center?
IBM recently introduced IBM Voice Gateway. IBM Voice Gateway is a cloud-native orchestration engine that provides a telephony interface into Watson. It addresses the challenges of traditional IVRs by providing a cognitive solution, aimed at improving the overall customer experience. Read the announcement blog for more details.
For the convergence between IVR and cognitive, the future is now. The impact this technology will have on customer communications shouldn’t be underestimated. Not only does it have the potential to greatly drive down the cost of running a large contact center but also it can improve customer satisfaction.
Watch this quick video to learn more about advancing your call center operations with a cognitive solution:

The post Why your company should be considering a cognitive IVR system appeared first on Cloud computing news.
Quelle: Thoughts on Cloud

83% of US teens are familiar with the term “fake news”.

Teens said that if they see something they think is a fake news story on social media, most of them will just ignore it.