ConSol is an IT consulting company. Enthusiasm for coding and hacking is what unites us. ConSol Labs is a technical playing field where we can share our Open Source involvement. We use this site to blog about our area of personal interest, from the daily business at work and from our spare time projects.
Database communication is an essential part of many applications, when persistent data storage is required. May it be orders, customer data, product recommendations or product information, if persistent storage is in place, the data contains a certain business value. Therefore it’s important that your software handles your persistent storage the right way.
In this blog post you’ll learn how to test your database communication using Citrus.
At this year’s FOSDEM conference I did a 30 minutes presentation on Monitoring Legacy Java Applications with Prometheus. The talk gives an overview of some of the options you have for monitoring Java applications with Prometheus when you cannot modify the application’s source code:
The video is available below.
In diesem Blogartikel wird gezeigt, wie das Monitoring-Plugin check_nwc_health auf eigene Bedürfnisse angepasst bzw. erweitert werden kann.
Ursprünglich sollte nur die Logik des Modes
ha-role modifiziert werden, um den Status von Cluster-Nodes nur zu reporten, anstatt zu alarmieren. Heraus kam eine Statusanzeige im Thruk-Frontend auf Basis von Host-Macros…
There are a lot of articles that show how to monitor an OpenShift cluster (including the monitoring of Nodes and the underlying hardware) with Prometheus running in the same OpenShift cluster. This article however is based on a different scenario: You are responsible for an application on an OpenShift cluster and want to monitor just this application, but you don’t have any administrative permission on it. The reason for this can be that you are working in a big company where the operation of the OpenShift environment is outsourced or the process to introduce a new monitoring solution takes way too long or the current monitoring solution doesn’t match your requirements and so on.
In this article I’m going to show you how to setup the monitoring of a demo application in 6 easy steps. The example is built in that manner that it will be easy for you to do the same for your application. A side note: If the OpenShift cluster that you are using will be monitored in the future with a different Prometheus setup, you don’t need to start from scratch. You might need to tweak the configuration of your scraping a bit and you need to move your dashboard to a different Grafana but that should be it.
Imagine your’re working on a bigger feature in a complex piece of software. Your implementation is complete, all tests in scope turned green and you push your changes for integration testing. Then, some integration tests from a completely different module fail and you have no clue which change may have caused this. Now you start analyzing the issue. Probing your commits by hand would end up in a very tedious process for sure. Thankfully git can do all the work for you, while you enjoy a cup of coffee.
The high-level command
git bisect allows you to automatically run a specified test procedure, while it’s crawling through your commit history to find the bad revision.
Just in time before X-Mas holidays starts, we crate a huge release of our open source end-to-end testing framework Sakuli. The v1.1.0 release brings a bunch of new features and a brand new documentation with. The list of the current changes you will find bellow. Also we created a Short Overview Presentation so that you be able to get quick intro about what purpose of Sakuli is.
Also we wan’t to say a big THANK YOU for the great support of our contributors, our valued supporting companies and at least ConSol for making this possible as open source software. Double Thumbs up!!!
The Tutorial “Docker based E2E application monitoring with Xfce UI and OMD Labs” describes how to:
Sources: see github.com/ConSol/sakuli-examples
The Prometheus monitoring tool follows a white-box monitoring approach: Applications actively provide metrics about their internal state to the Prometheus server. In order to instrument an application with Prometheus metrics, you have to add a metrics library and call that library in the application’s source code. However, DevOps teams do not always have the option to modify the source code of the applications they are running.
When developing software that exchanges data with other components or services you may be confronted with the proper simulation of those foreign services during integration testing. This is because you need to connect with a foreign service
that is simply not available on your local machine or in a test environment.
For unit testing purpose you can use mocks that help out to simulate proper responses. There will be times where your software is deployed to a test environment
in order to perform some acceptance tests with your stakeholders before going to a final release. Usually this is also done with the customer exploring the software through manual testing. In these situations traditional service mocking is not
a good option and you need a real simulator instance that receives requests and responds with proper test data.
This is exactly what the Citrus simulator project provides for you. Standalone simulation and complex request/response processing with solid validation capabilities. The Citrus simulator provides a very easy and reliable definition of inbound and outbound messages for different scenarios.
Good news is that this is not only for Http REST interfaces but also for SOAP WebService, JMS, RMI, mail messaging and many more. So you can use the simulator whenever you need to integrate with another service that is simply not available on your local machine or in your test environment.
Docker Headless VNC Container 1.2.0 has been released today. The different Docker images contains a complete VNC based, headless UI environment for testautomation like Sakuli does or simply for web browsing and temporary work in a throw-away UI container. The functionality is pretty near to a VM based image, but can be started in seconds instead of minutes. Each Docker image has therefore installed the following components: