In this post, we will take a look at how we can make services be aware of each other without knowing their exact location. We will make use of Eureka Server which will act as a Discovery Server. Being Spring fans, we will do so by means of Spring Eureka.
In this post, we will take a look at how we can use Google Cloud Vision from a Spring Boot application. With Google Cloud Vision it is possible to derive all kinds of things from images, like labels, face and text recognition, etc. As a bonus, some examples with Python are provided too.
In this post we will explore how we can use Google Cloud Platform’s (GCP) Pub/Sub service in combination with a Spring Boot application using Spring Integration. We will send a message to a sender application which publishes the message to a Topic where a receiver application receives the messages of a Subscription.
In a previous post, we talked about how we can check our Docker images for any known vulnerabilities by means of Anchore Engine. This still required a manual action. Wouldn’t it be great if we could incorporate Anchore Engine into our Jenkins CI build job or pipeline? In this post, we will take a look at how we can accomplish this by means of the Anchore Container Image Scanner Jenkins Plugin.
When using Docker containers in production, we need to ensure that we are following best practices. In this post, we will focus on Ensure images are scanned and rebuilt to include security patches from the CIS Docker Community Benchmark which we discussed previously. The item states that you should scan your images “frequently” for any vulnerabilities and then take the necessary actions to mitigate these vulnerabilities. We will use Anchore Engine in order to accomplish this.
Assume a new developer or test engineer is added to your team. You develop an application with obviously some kind of database and you want them to get up to speed as soon as possible. You could ask them to install the application and database themselves or you could support them with it, but this would cause a lot of effort. What if you handed them over a simple YAML file which would get them up to speed in a few minutes? In this post we will explore some of the capabilities of Docker Compose in order to accomplish this.
In the first part of this post, we explained the Performance Diagnostic Methodology (PDM) and how to use it. But, the proof of the pudding is in the eating and therefore it is now time to apply the methodology. Of course, the best proof would be to apply the methodology to a real world performance issue, but instead of waiting for that, we will try to simulate some performance issues and verify whether the methodology can work.