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Amazon Cognito Launches General Availability of a Built-in Customizable User Experience for Sign-in, OAuth 2.0 Support, and Federation with Facebook, Login with Amazon, Google, and SAML providers for User Pools

Today we launched the general availability (GA) of features for Amazon Cognito User Pools that enable application developers to easily add and customize a sign-up and sign-in user experience, use OAuth 2.0, and integrate with Facebook, Google, Login with Amazon, and SAML-based identity providers. Now you can enable your users to sign-up and sign-in using social identity providers, corporate identity providers with SAML, and a username, email address or phone number with Cognito User Pools.
Quelle: aws.amazon.com

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Using Azure Analysis Services over Azure SQL DB and DW

In April we announced the general availability of Azure Analysis Services, which evolved from the proven analytics engine in Microsoft SQL Server Analysis Services. The success of any modern data-driven organization requires that information is available at the fingertips of every business user, not just IT professionals and data scientists, to guide their day-to-day decisions. Self-service BI tools have made huge strides in making data accessible to business users. However, most business users don’t have the expertise or desire to do the heavy lifting that is typically required, including finding the right sources of data, importing the raw data, transforming it into the right shape, and adding business logic and metrics, before they can explore the data to derive insights.

With Azure Analysis Services, a BI professional can create a semantic model over the raw data and share it with business users so that all they need to do is connect to the model from any BI tool and immediately explore the data and gain insights. Azure Analysis Services uses a highly optimized in-memory engine to provide responses to user queries at the speed of thought.

In the video below, I demonstrate to Scott Hanselman how to use Azure Analysis Services over SQL Data Warehouse. In this scenario, Azure Analysis Services servers two major functions:

It provides a semantic model which acts as a lens that your business users look through to get to their data. It presents your underlying database in a way which makes it easy for your users to query without needing to change the structure of that database.
A very fast in memory data caching layer which can answer queries in a fraction of a second. The cache provides users interactive querying over billions of rows of data while reducing the load on the underlying data store.

See the whole video:

You can try the Azure Analysis web designer today to build your own models by linking to it from a server in the Azure portal.

Submit your own ideas for features on our feedback forum. Learn more about Azure Analysis Services and the Azure Analysis Services web designer.
Quelle: Azure

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AWS Encryption SDK now supports data key caching

The AWS Encryption SDK is an encryption library that helps make it easier for you to implement encryption best practices in your application. It enables you to focus on the core functionality of your application, rather than on how to best encrypt and decrypt your data. 
Quelle: aws.amazon.com

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Uber's First Employee Is Out As An Exec But Will Remain On The Board

Tyrone Siu / Reuters

Uber Technologies' first employee and former CEO Ryan Graves is leaving day-to-day operations at the San Francisco-based ride-hailing giant, according to an email sent to employees on Thursday. Graves will still remain on the company's board, which is in the process of finding a replacement for former CEO Travis Kalanick.

“There is another lesson I’ve learned that we should have applied much earlier,” he wrote in an email that was obtained by BuzzFeed News. “We should have taken more time to reflect on our mistakes and make changes together. There always seemed to be another goal, another target, another business or city to launch.”

Graves had worked at Uber for more than seven years, and was originally hired by co-founders Kalanick and Garrett Camp to serve as the company's first CEO in early 2010. After Kalanick took over control of the company, Graves served as the company's president before stepping aside in August 2016, with the hire of former Target chief marketing officer Jeff Jones into the role. (Jones quit in March as Uber faced a series of scandals and allegations of widespread sexism at the company, which eventually led to Kalanick's dismissal.)

In his most recent role, Graves, according to a company blog post, was “a resident entrepreneur and builder” focused on people operations and Uber's delivery services like UberEats. His official title on LinkedIn was Senior Vice President of Operations.

“Well, there is no great time for a move like this one,” he said in his email. “But it’s really important to me that this transition doesn’t take away from the importance of the onboarding process of our new CEO, whoever they might be.”

Quelle: <a href="Uber's First Employee Is Out As An Exec But Will Remain On The Board“>BuzzFeed

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Kompose Helps Developers Move Docker Compose Files to Kubernetes

I’m pleased to announce that Kompose, a conversion tool for developers to transition Docker Compose applications to Kubernetes, has graduated from the Kubernetes Incubator to become an official part of the project. Since our first commit on June 27, 2016, Kompose has achieved 13 releases over 851 commits, gaining 21 contributors since the inception of the project. Our work started at Skippbox (now part of Bitnami) and grew through contributions from Google and Red Hat.The Kubernetes Incubator allowed contributors to get to know each other across companies, as well as collaborate effectively under guidance from Kubernetes contributors and maintainers. Our incubation led to the development and release of a new and useful tool for the Kubernetes ecosystem.We’ve created a reliable, scalable Kubernetes environment from an initial Docker Compose file. We worked hard to convert as many keys as possible to their Kubernetes equivalent. Running a single command gets you up and running on Kubernetes:  kompose up.We couldn’t have done it without feedback and contributions from the community!If you haven’t yet tried Kompose on GitHub check it out!Kubernetes guestbookThe go-to example for Kubernetes is the famous guestbook, which we use as a base for conversion. Here is an example from the official kompose.io site, starting with a simple Docker Compose file.First, we’ll retrieve the file:$ wget https://raw.githubusercontent.com/kubernetes/kompose/master/examples/docker-compose.yamlYou can test it out by first deploying to Docker Compose:$ docker-compose up -dCreating network “examples_default” with the default driverCreating examples_redis-slave_1Creating examples_frontend_1Creating examples_redis-master_1And when you’re ready to deploy to Kubernetes:$ kompose upWe are going to create Kubernetes Deployments, Services and PersistentVolumeClaims for your Dockerized application. If you need different kind of resources, use the kompose convert and kubectl create -f commands instead. INFO Successfully created Service: redis          INFO Successfully created Service: web            INFO Successfully created Deployment: redis       INFO Successfully created Deployment: web         Your application has been deployed to Kubernetes. You can run kubectl get deployment,svc,pods,pvc for detailsCheck out other examples of what Kompose can do.Converting to alternative Kubernetes controllers Kompose can also convert to specific Kubernetes controllers with the use of flags:$ kompose convert –helpUsage:  kompose convert [file] [flags]Kubernetes Flags:      –daemon-set               Generate a Kubernetes daemonset object  -d, –deployment               Generate a Kubernetes deployment object  -c, –chart                    Create a Helm chart for converted objects      –replication-controller   Generate a Kubernetes replication controller object…For example, let’s convert our guestbook example to a DaemonSet:$ kompose convert –daemon-setINFO Kubernetes file “frontend-service.yaml” created INFO Kubernetes file “redis-master-service.yaml” created INFO Kubernetes file “redis-slave-service.yaml” created INFO Kubernetes file “frontend-daemonset.yaml” created INFO Kubernetes file “redis-master-daemonset.yaml” created INFO Kubernetes file “redis-slave-daemonset.yaml” createdKey Kompose 1.0 features With our graduation, comes the release of Kompose 1.0.0, here’s what’s new: Docker Compose Version 3: Kompose now supports Docker Compose Version 3. New keys such as ‘deploy’ now convert to their Kubernetes equivalent.Docker Push and Build Support: When you supply a ‘build’ key within your `docker-compose.yaml` file, Kompose will automatically build and push the image to the respective Docker repository for Kubernetes to consume.New Keys: With the addition of version 3 support, new keys such as pid and deploy are supported. For full details on what Kompose supports, view our conversion document.Bug Fixes: In every release we fix any bugs related to edge-cases when converting. This release fixes issues relating to converting volumes with ‘./’ in the target name. What’s ahead? As we continue development, we will strive to convert as many Docker Compose keys as possible for all future and current Docker Compose releases, converting each one to their Kubernetes equivalent. All future releases will be backwards-compatible.Install KomposeKompose Quick Start Guide Kompose Web Site Kompose Documentation –Charlie Drage, Software Engineer, RedHatThe Kubernetes Incubator helps new projects adopt Kubernetes best practices as well as develop a healthy community. Post questions (or answer questions) on Stack OverflowJoin the community portal for advocates on K8sPortFollow us on Twitter @Kubernetesio for latest updatesConnect with the community on SlackGet involved with the Kubernetes project on GitHub
Quelle: kubernetes

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Data Management Gateway – High Availability and Scalability Preview

We are excited to announce the preview for Data Management Gateway – High Availability and Scalability.

You can now associate multiple on-premise machines to a single logical gateway. The benefits are: 

Higher availability of Data Management Gateway (DMG) – DMG will no longer be the single point of failure in your Big Data solution or cloud data integration with Azure Data Factory, ensuring continuity with up to 4 nodes.

Improved performance and throughput during data movement between on-premises and cloud data stores. Get more information on performance comparisons.
Both Scale out and Scale up support – Not only the DMG can be installed across 4 nodes (scale out), but you can now increase/decrease the concurrent data movement jobs at each node (scale up/down) as per the need.
Note: The Scale up/down feature is now available for all existing Single Node (GA) gateways. This update is not limited to this preview. 
Richer Data Management Gateway Monitoring experience – You can monitor each node status and resource utilization all at one place on the Azure Portal. This helps simplify the DMG management.  

Note: Monitoring is now available for all existing Single Node (GA) gateways. This update is not limited to this preview. 

For more information on the Data Management Gateway ‘High Availability and Scalability’ feature check our documentation.

Getting started

Scenario 1 – Setting up a new ‘Highly Available and Scalable’ Data Management Gateway.

 

 

Scenario 2 – Upgrading existing Data Management Gateway to enable the ‘High Availability and Scalability’ feature.

 

 

Prerequisite – This preview feature is supported on Data Management Gateway version 2.12.xxxx.x and above. Please make sure you are using version 2.12.xxxx.x or above. Download the latest version of Data Management Gateway.

In case you have any queries, please feel free to reach out to us at dmghelp@microsoft.com.
Quelle: Azure