Fast and Easy integration testing with Docker and Overcast

Challenges with integration testing

Suppose that you are writing a MongoDB driver for java. To verify if all the implemented functionality works correctly, you ideally want to test it against a REAL MongoDB server. This brings a couple of challenges:

  • Mongo is not written in java, so we can not embed it easily in our java application
  • We need to install and configure MongoDB somewhere, and maintain the installation, or write scripts to set it up as part of our test run.
  • Every test we run against the mongo server, will change the state, and tests might influence each other. We want to isolate our tests as much as possible.
  • We want to test our driver against multiple versions of MongoDB.
  • We want to run the tests as fast as possible. If we want to run tests in parallel, we need multiple servers. How do we manage them?

Let’s try to address these challenges.Read more →

Take the Application Release Market Survey

We’re conducting a survey to take the pulse of the Application Release market. We will reveal the top challenges and key initiatives effecting you, your business and the Application Release market in a report to be published in early 2013. The report will offer a comprehensive view of what challenges your peers are facing, the latest trends in application development and key initiatives currently being planned.

This survey will take just five minutes of your time. All personal details will be kept anonymous. Participant will receive a copy of the finding and be entered to win 1 of 3 gift certificates valued at $100, $250 and $500! Take the survey now >

Connecting Continuous Integration to Continuous Delivery

At XebiaLabs, many of the questions we get about our enterprise deployment automation solution Deployit are from users looking for automated deployment as a prerequisite for Continuous Delivery. Often, this the result of initiatives to extend existing Continuous Integration tooling to support application deployments.

Increasing the frequency of whole-application testing, decreasing time-to-production and delivering greater business value faster and more regularly are goals we definitely share, and in this post we’d like to pass on some key experiences and lessons from working together with our users to help them realize Continuous Delivery.
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Scaling the hybrid cloud horizontally

After being derided as “unpure” by cloud enthusiast when the idea was first presented, we can now safely say that the hybrid cloud is here to stay. The mix of dynamic requirements within the enterprise related to government/industry regulations, security and performance require a more flexible environment than the public cloud can offer. So what does a hybrid cloud actually mean? A hybrid cloud is a composition of a private cloud and public cloud. There are two types of scaling patterns when using a hybrid cloud: vertical and horizontal.


A vertical scaling pattern is the better-known scenario. This pattern spreads different components of one application across different clouds. An example of this would be where one part of an application, typically the data, is kept private, while another part is run in the cloud, such as the web front end or calculations being made on the data.


A horizontal hybrid cloud scaling pattern, on the other hand, spreads different instances of applications across different clouds. In this scenario, enterprises develop their own applications and run them in multiple environments, some on-prem, some in the cloud. Developers run it in a test environment, testers test it in a QA environment, and users access the version that has been deployed to the production environment. Each of these environments can be in the cloud or on-prem depending on the security, performance, flexibility and scalability requirements of that environment.
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Cost Effective, Fast and Scalable: Is It Time You Considered Automated App Deployment?

Our approach to software development has changed in the last few years. IT professionals and software developers are working more closely together than ever before. The DevOps trend also extends to an acknowledgement that automation is a key factor in reducing costs and increasing release speeds.

Striving to be cost effective is a constant for any business but the increased focus on speed of deployment is a product of the growth of the Cloud and Agile development methodology. The bottom line is – the faster new features, fixes and improvements reach the customer, the greater their satisfaction. The same principle applies in an enterprise environment – the faster the latest version of an application reaches users, the more productive they can be.

Both environments require scalability. As your product offerings grow and branch out, the delivery method must be capable of handling the changes. In the enterprise environment a large portfolio of software applications is the norm and any deployment solution must be able to scale.

Automated app deployment can reduce costs, increase speed and scale as needed, but before we take a look at the solution let’s discuss the problem.

App Deployment Nightmares

There are a lot of potential problems in deploying applications manually. Not least of which is the time it can consume for developers and IT support. Configuration is the first challenge. Where is the application stored? Which version should be installed? Where should it be installed? Where is the configuration file and how is it applied?

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Deployit Cookbook: Setup Security Roles

Deployit provides fine-grained security settings based on roles and permissions and allows them to be configured through the CLI and in the GUI.

In this example, we’ll be setting up security roles using the GUI. The example environment has two applications, OnlineOrders and SiteSearch that are both deployed to a test server before going to production. There are two different teams developing and deploying the applications. One team can’t see the other’s team application. Moreover, developers can only deploy to the test environment. Deployers can deploy both to the test environment and to production.

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Come on, vagrant up! Saving Vagrant images that don’t get a NAT address

As part of testing and demonstrating our advanced deployment automation1 platform Deployit, we at XebiaLabs use a lot of cloud and Devops tooling to be able to handle all the different types of middleware we support and build, CI and Ops tooling with which we integrate2.

I was recently setting up a Vagrant3 environment to demonstrate Deployit’s Puppet module, which automatically registers new Puppet-provisioned middleware with your deployment automation platform to enable application-tier deployments to it, and ended up wrestling for quite some time with a tricky VirtualBox problem.
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Why Application Release Automation needs a Release and an Operations view

As the interface between Development and Operations, Application Release Management1 handles information that is highly relevant to your Release and Operations teams. Selecting an Application Release Automation solution that provides insight and analytics from both perspectives is thus a key component of an effective DevOps strategy.

Here, we explain how Deployit‘s Infrastructure and new Release Overview features help you achieve this goal.
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Taking Application Release Automation to the Next Level

Whether the driver is Agile, Cloud or DevOps1, or a “plain old” efficiency drive or process improvement initiative, forward-thinking organisations are currently looking for ways to improve their application release processes through automation. In an area where manual activities are still all too common, it’s unsurprising that the initial focus has been on automating the deployment execution – moving all the bits to the right places.

What early adopters have learnt is that, at the enterprise scale, automating release execution quickly introduces a new bottleneck in today’s dynamic IT environments: continuous management of the deployment plan definition. A new generation of application release automation (ARA) tooling avoids this pitfall by leveraging intelligence to automate deployment planning as well as execution.
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