Monitoring systems are usually composed of three layers: a database layer that hosts metrics data, a layer to display the stored metric data graphically in dashboards, and an alerting layer to send out notifications via methods such as email, on-call notification systems, and chat platforms. This article presents an overview of the components used in Red Hat OpenShift‘s Application Monitoring Operator, how to install them using the Operator, and an example of the Operator in action.
Continue reading “Understanding Red Hat OpenShift’s Application Monitoring Operator”
In this article, I demonstrate a systematic method to configure LDAP user and group synchronization in Red Hat OpenShift, as well as OpenShift role-based access control (RBAC) for these LDAP users and groups. Following these steps makes the management of your LDAP users and groups within OpenShift much easier. I achieve this goal by demonstrating:
- How to validate your
ldap parameters with
ldaptool prior to installing OpenShift.
- How to enable LDAP authentication in OpenShift for specific LDAP groups and organization units.
- The scripts and commands that let you synchronize members of your LDAP groups to OpenShift, which in turn lets you apply custom OpenShift RBAC rules on specific users or groups.
Continue reading “How to configure LDAP user authentication and RBAC in Red Hat OpenShift 3.11”
This article explains how to configure a Python application running within an OpenShift pod to communicate with the Red Hat OpenShift cluster via
openshift-restclient-python, the OpenShift Python client.
Continue reading “Controlling Red Hat OpenShift from an OpenShift pod”
JBoss Tools 4.12.0 and Red Hat CodeReady Studio 12.12 for Eclipse 2019-06 are here and are waiting for you. In this article, I’ll cover the highlights of the new releases and show how to get started.
Continue reading “Get started with Red Hat CodeReady Studio 12.12.0.GA and JBoss Tools 4.12.0.Final for Eclipse 2019-06”
We are thrilled to announce an updated release of the data streaming component of our messaging suite, Red Hat AMQ streams 1.2, which is part of Red Hat integration.
Red Hat AMQ streams, based on the Apache Kafka project, offers a distributed backbone that allows microservices and other applications to share data with extremely high throughput and extremely low latency. AMQ streams makes running and managing Apache Kafka a Kubernetes-native experience, by additionally delivering Red Hat OpenShift Operators, a simplified and automated way to deploy, manage, upgrade and configure a Kafka ecosystem installation on Kubernetes.
Continue reading “Announcing Red Hat AMQ streams 1.2 with Apache Kafka 2.2 support”
Automation is what we (developers) do. We automate ticket sales and automobiles and streaming music services and everything you can possibly tie into an analog-to-digital converter. But, have we taken the time to automate our processes?
In this article, I’ll show how to build an automated integration and continuous delivery pipeline using Jenkins CI/CD and Red Hat OpenShift 4. I will not dive into a lot of details—and there are a lot of details—but we’ll get a good overview. The details will be explained later in this series of blog posts.
Continue reading “Get started with Jenkins CI/CD in Red Hat OpenShift 4”
Since Red Hat OpenShift Container Platform was first released, Red Hat Middleware products were provided to deploy on it and help developers to build more complex solutions. Messaging Brokers are a very important piece in most new application architectures, such as microservices, event sourcing, and CQRS. Red Hat JBoss AMQ was provided from the beginning to deploy Messaging Brokers on Red Hat OpenShift easily.
Continue reading Automated migration from JBoss AMQ 6 to Red Hat AMQ 7 on Red Hat OpenShift
Working with Red Hat Fuse 7 on Spring Boot is straightforward. In my field experience, I have seen many development (a.k.a. integrator) teams moving to Fuse 7 on Spring Boot for their new integration platforms on Red Hat OpenShift Container Platform (well aligned with agile integration).
Lately, however, I have also seen some teams worried about the size of the final images and the deployment pipeline. In most cases, they had developed a set of common libraries or frameworks to extend or to homogenize the final integration projects. All the cases have the same result:
- Several dependencies copied in each integration project
- Always replacing the container images with the latest fat JAR (including the same dependencies) in each build pipeline
Spring Boot is usually packaged as “fat JARS” that contain all runtime dependencies. Although this is quite convenient, because you only need a JRE and a single JAR to run the application, in a container environment such as Red Hat OpenShift, you have to build a full container image to deploy your application.
Continue reading “Optimizing Red Hat Fuse 7 Spring Boot container images”
As part of the Red Hat UKI Professional Services team, I have worked with several customers who are implementing AMQ Broker on Red Hat OpenShift Container Platform (OCP). One question customers typically ask is, “How do we validate that the AMQ configuration is correct for our scenario?” Previously, I would have suggested one of the following:
These tools can give you indicators around:
- Is the broker up and running? That is, can it receive/publish messages for this configuration?
- Can the broker handle a certain performance characteristic? That is, what is my minimum publish rate per second for this configuration?
- And much more.
The problem with these tools is that you cannot choose the client technology. This could lead to real-world differences and limited technology choices, which in turn might lead you down the wrong technology path. In other words:
- Do you get the same performance from JMeter versus the AMQ clients you would use in production? Are you comparing like for like? Apples with apples?
So, what do I think is the answer? Quiver . In this article, I’ll provide an overview and demo of using Quiver with Red Hat AMQ on Red Hat OpenShift. If you’re looking for more information on Red Hat AMQ and how it can help, check out this webinar.
Continue reading “Using Quiver with AMQ on Red Hat OpenShift Container Platform”
Red Hat OpenShift Container Platform is a platform-as-a-service (PaaS). It orchestrates and manages containerized applications through Kubernetes. Although OpenShift Container Platform supports cloud-native applications, it also supports custom-built applications. OpenShift Container Platform can run on a hybrid cloud configuration providing the flexibility to expand and grow.
Red Hat OpenStack Platform is an infrastructure-as-a-service (IaaS). This means it is a cloud-based platform that provides virtual servers and other resources. Users either manage it through a web-based dashboard, through command-line tools, or through RESTful web services.
If you are considering Red Hat OpenShift Container Platform on OpenStack Platform, there are several advantages, including easily increasing the number of compute nodes and using dynamic storage.
In this article, I will outline the main points required to successfully install Red Hat OpenShift Container Platform on OpenStack Platform. Because my OpenStack knowledge is limited, I reached out to my colleagues for help and will not address too many OpenStack technical details here.
Continue reading “How to install Red Hat OpenShift 3.11 on OpenStack 13”