Review: GitHub vs. Visual Studio Team Services (VSTS) – Should you switch?

January 23, 2016January 23, 2016 de Reviews azure, cloud, coding, git, microsoft, SaaS

Disclaimer: This article is about Visual Studio Team Services (VSTS) and GitHub. The author has a very positive opinion about both services and does not get any offers from Microsoft or GitHub writing this article. The whole article is written IMHO.

Over the last years GitHub has become a success factor for projects related to git repositories for me personally. I also tested several other solutions but mainly I struggeled with the performance or the usability. About 2 years ago I started using Visual Studio Team Services (VSTS) with a work related project. The service looked promising but had a lot of early release issues, so in the last 24 months it was interesting to see how a promising solution became adult. Last week I decided to move away from GitHub for all my closed source projects and rely on Visual Studio Team Service (VSTS). This article gives a deeper look on the main reasons of why I did the move and may help deciders to get detailed information before implementing:

Git-Repository sprawl
Nowadays thanks to bower, npm, bundler or NuGet the amount of Git repositories are growing steadily. When you are focused on component based software development Git is a great helper but the amount of repositories is sprawling because very often every component has its own live in a separated Git repository, which means you have a separate release cycle and a different versioning compared to your main project.

I guess this is the secret source of component managers which are working closely together with git repositories. Of course VSTS and GitHub are supporting multiple git repositories but GitHub lets you pay on a package on git repositories, VSTS lets you pay for users. Especially for small teams paying for users is the better deal, compared to paying for repositories. At the end Microsoft offers a smaller groups of 5 everything for free. This fact stopped my permanent GitHub problem: Having too less private repository space.

GitHub:
O – Allows to have as many GitHub repositories as needed
+ – Generates releases out of tags automatically (good semver integration)
– – Charging base is the count of private git repositories

VSTS:
O – Allows to have as many GitHub repositories as needed
+ – Comes with unlimited git repositories, plans are user based
– – Repository management is not that intuitive as it is in other solutions

Pull Requests and Forks
Forks and pull requests are the most important features GitHub introduced very early to support community driven development. I would say in the open source world Github is the platform when it comes to forks and pull requests. Currently I would never think about moving open source repositories away from GitHub because of this great feature.

When it comes to closed source projects, forking and pull requests are becoming only important in bigger teams with different products or product lines. We are using this feature strongly in our teams at my company. Smaller startups or teams will not use these workflows often but nevertheless it is a road blocker for me to do the 100% switch to VSTS. I guess it took Microsoft around 12 month to deliver it in a more simple way GitHub is doing this.

GitHub
+ – Cross repository forking
+ – Pull requests incl. discussion thread and a lot of community features

VSTS:
O – Supports pull request on repository level

Agile Process support with EPiCs, features and backlogs
When it comes to bigger teams or more structure, people are having the option that to implement a process is the key. This brings me to the biggest enterprise blocker I see in GitHub, the Issue-Tracking system. Companies who migrated to an agile framework like SCRUM or KANBAN need to have the option to work with features, backlogs or bugs. Microsoft delivers with VSTS a highly customizable and adaptable work item management system. The SCRUM and KANBAN template makes perfect sense for agile teams but also the traditional waterfall model can be implemented (even if I don’t understand why someone should do this.)

GitHub
– – It’s just an Issue Tracker
+ – Has good integration into many cloud services

VSTS:
+ – Offers customisable work item management
+ – Comes with templates for agile team structures

Handle your Test-Cases
Even if your projects comes with a great code coverage and good unit tests, the requirements to execute manual tests or just to orchestrate automated integration tests exists. VSTS implements based on the work item management a test case management which has the option to integrate it with automation bots via WinRM and other protocols.

The ability to document test cases and write specific step by step guides how to verify a feature is a big plus esp. in small teams where no dedicated QA resources are hired.

GitHub
O – Ability to integrate with external QA services
– – No integrated test case management

VSTS:
O – Ability to integrate with external QA services
+ – Test Case management is part of the work item management

Centralised Source Code management as migration path
For a couple month Microsoft offers virtual TFS collection, which allows companies that want to go pave the road for git based repositories to stay with the existing centralised source code management besides new git repositories. In the early day VSTS just supported a TFS collection per project space but now maintaining TFS collection is that easy as it is creating new git repositories. This will become very important features for existing TFS customers.

Revised Build-System incl. Linux Support
I guess Microsoft learned very fast that the XAML file based build system was very inflexible and complicated for a SaaS service like VSTS. Because of that a couple month ago a new step based build system was introduced which will orchestrate the build agent out of VSTS

Since Microsoft supports Windows, Linux and Mac build agents there are no road blockers anymore, besides that the hosted build services for VSTS are very rare. There is a build server Microsoft offers out of the box but from my experience you will get more problems customizing that. When you are focused on Azure check also what the Azure App Services can do for you because KuduSync offers out of the box build for your .NET application during deployment.

GitHub
+ – Many different build services available with GitHub integration (CodeShip, T..)
– – Build definitions are not part of the code project
– – No release management to aggregate several projects

VSTS:
– – Hosted build services for VSTS rare
+ – Build definitions are part of the code project
+ – Release Management allows to aggregate several sub projects

Other services and options:
There are also other options and products on the market and I guess one of the most popular one is Assembla which is pretty comparable to Visual Studio Team Services. Also the products from Atlassian (Jira, BitBucket) are great options supporting your development cycle. This article had the intention to support companies who are dealing with GitHub and / or On Premise TFS and now are thinking about combining the positive of both.

I personally think GitHub could become a great option for enterprises as well, when the Issue-Tracker problem is solved which was mainly the reason why I searched for an alternative!

azure-queue-client: delaying jobs made easy

January 6, 2016 de Misc coding, javascript, node

Microsoft Azure offers a very powerful and cheap queueing system, based on Azure Storage. The node module azure-queue-client is a powerful component for node developers in order to interact with the Azure queues easily.

The updated version of the azure-queue-client now supports delayed jobs. This makes it possible to easily delay a running job in the queue worker for a specific time, .e.g. 5 minutes, 1 hour or any other time less than 7 days in the future.

// config with your settings
var qName = '<<YOURQUEUENAME>>';
var qStorageAccount = '<<YOURACCOUNTNAME>>';
var qStorageSecret = '<<YOURACCOUNTSECRET>>';
var qPolling = 2;

// load the module
var azureQueueClient = new require('../lib/azure-queue-client.js');

// create the listener
var queueListener = new azureQueueClient.AzureQueueListener();

// establish a message handler
queueListener.onMessage(function(message) {

// just logging
 console.log('Message received: ' + JSON.stringify(message));
 console.log('Message Date: ' + new Date());

// generate the delay policy
 var exponentialRetryPolicy = new azureQueueClient.AzureQueueDelayedJobPolicies.ExponentialDelayPolicy(1, 5);

// delay the job
 console.log("Job was delayed " + exponentialRetryPolicy.count(message) + " times");
 console.log("Delaying the job by " + exponentialRetryPolicy.nextTimeout(message) + " seconds");
 return queueListener.delay(message, exponentialRetryPolicy);
});

// start the listening
queueListener.listen(qName, qStorageAccount, qStorageSecret, qPolling, null);

As the code sample shows, the module relies on the concept of delay policies. Implementing custom policies is allowed and supported. Built-in policies are the exponential delay policy and the static delay policy.

The module is actively used and maintained in the azure costs service, so it can be used in production. If you would like to contribute or get more detailed information, please visit the github project page.

Big Data in your browser: Parallel.js

September 7, 2015September 7, 2015 de Misc cloud, coding, javascript, SaaS

Big Data often has something todo with analysing a big amount of data. The nature of this data makes it possible to split it up into smaller parts and let them be processed from many distributed nodes. Inspired from the team of CrowdProcess we like the idea to use the computing power of a growing web browser grid to solve data analytic problems.

The Azure Cost Monitor does not have the requirement to solve big data problems of user A in the browser of user B, we would never do this because of data privacy but we have a lot of statistic jobs which need to be processed. From an architecture perspective the question comes up why not to use a growing amount of browser based compute nodes connected with our system instead? Starting with this idea we identified that WebWorkers in modern browsers are acting like small and primitive compute nodes in big data networks. The team from the SETI@Home project also gave us the hint that this option works very well to solve big data challenges.

A very simple picture was painted very fast on the board to illustrate our requirements. The user should not be disturbed from the pre-calculation of statistic data in his browser and the whole solution should prevent battery drain and unwanted fan activities:

It’s also important to understand that some smaller devices like a RaspberryPI which is used for internet browsing or an older smartphone is not able to process the job in time to generate a great user experience. Because of this, the picture changed a bit and we invented a principal we call “Preemptive Task Offloading”.

“Preemptive Task Offloading” lives from the idea that the server and the browser are using the same programming language and the same threading subsystem to manage tasks. Because of that the service itself can decide whether it moves tasks in the browser on the end user or pre-calculates them on the server to ensure great user experience.

The illustrated solution is able to improve the user experience for your end users dramatically and lowers the hosting costs for SaaS applications in the same time.

How it works

The first step is to find the lowest common denominator, in our case it’s called JavaScript. Javascript can be executed in all modern browsers and in the server via node.js. Besides this node and web browser has concepts, e.g. WebWorkers to handle multi threading and multi tasking. The second important ingredient is a framework which abstracts the technical handling of threads or tasks because they are working different in the backend or frontend. We identified parallel.js as a great solution for this because it gives us a common interface to the world of parallel tasks in frontend and backend technologies. Last but not least a system needs to identify the capabilities of the browser. For this we are using two main approaches. The first one tries to identify the capability to spin of web workers and identifies the amount of CPUs. For this we are using the CPU Core Estimator to also support older browsers. The second step of capability negotiation is a small fibonacci calculation to identify how fast the browser really is. If we come to a positive result our system starts the task offloading into the web browser, a negative result leads to a small call against our API to get the preprocessed information from our servers.

Conclusion

After testing this idea several weeks, I can say that this approach helps a lot to build high performance applications, with acceptable costs on the server side. Personally I don’t like the approach to give customer sensitive data into the browser of other customers to much, but I think this approach works great in scientific projects. What do you think about big data approaches in the browser? What are your pitfall or challenges in this area? Just leave a comment bellow or push a message on Twitter.

Azure Cost Monitor announces private and shared filters

August 6, 2015 de Misc

The Azure Cost Monitor Team is happy to announce the launch of the new filtering feature, starting today.

Now, users are able to create data filters to get instant access to important or costly services. Filtering enables users to only show results that match a specific criteria. For example a stakeholder may want to only report on a specific tag value or type of cloud service.
It is even possible for team administrators to share created filters with team mates and co-workers, so everyone may stay focused on their cost drivers in the Azure subscriptions.

The system supports a top to bottom “and/or” logic what means that you can create the filters as you would naturally read a sentence. This allows you to combine different attributes in an “and” or “or” clause.

How to get started?
Adding a new filter to the Azure Cost Monitor is this simple:

1) Log In to the Azure Cost Monitor Dashboard and if you don’t have a team account migrate to a team (optional):

2) Select the “Create Filter” drop down at the spending reports page.

3) Add several conditions to the filter and save it:

4) Just switch between different filters by selecting the needed one:

5) If you are the team administrator share a created filter with the team by clicking the “Share with team” button:

Interested in the filtering feature?
Try the new feature today by simply logging into your Azure Cost Monitor. The feature is part of any plan, starting from the free Basic plan up to the Enterprise plan.

Any questions, wishes or ideas? Try our feedback portal or drop a mail to help@azure-costs.com.

Azure Cost Monitor announces Azure Active Directory support

June 21, 2015June 21, 2015 de Azure Cost Monitor aad, acm, azure, billing, cloud, SaaS

The Azure Cost Monitor Team is very pleased to announce the launch of the Azure Active Directory support starting today.

Microsoft Azure Active Directory is an identity and access management cloud solution that provides a robust set of capabilities to manage users and groups. It also helps to secure access to cloud applications including Microsoft online services like Office 365.

With the new feature, the Azure Cost Monitor allows to link teams against an existing Azure Active Directory. By doing so, a centralized identity and access management can be realized easily.
The support of Azure Active Directory Groups, enables you to grant access to dedicated groups of people or departments within your enterprise. This ensures an easy integration into your existing IT service infrastructures .
Last but not least, a seamless sign-in experience for all users (single-sign-on) can be generated by combining the Azure Directory setup with the customer buckets feature.

How to get started?
Linking an existing Azure Active Directory to the Azure Cost Monitor is that simple:

Log in to the Azure Cost Monitor Dashboard and if you don’t have a team account migrate to a team:
Select the “Link to Azure Active Directory” button to start the setup process
Follow the description and login for the first time with a global administrator of your Azure Active Directory to give the required consent that allows users of your Azure Active Directory to sign in to the Azure Cost Monitor.
After the successful consent save the directory settings. All users of the Azure Active Directory can use the Azure Cost Monitor now.
Configure a new bucket so that all users will be redirected to the Active Directory Sign-In process automatically. This step is optional and can be done later as well.

Interested in the Azure Active Directory feature:
The new feature integrates the Azure Cost Monitor more seamless into existing IT service infrastructures and increases the end user experience of your team members and co-workers. Especially the group based permission support allows you to delegate the access management to a centralised IT organisation.

Try the new feature today by simply logging into your Azure Cost Monitor enterprise account. If you don’t have an enterprise subscription, try it for free for a certain time, as we are currently in the technical preview phase.

Any questions, wishes or ideas? Try our feedback portal or drop a mail to help@azure-costs.com.

Thoughts about making software

a blog of Dirk Eisenberg

azure-queue-client: delaying jobs made easy

Azure Cost Monitor announces private and shared filters