In November 2015, I blogged about the announcement to bring .NET to RHEL from the .NET Core upstream project to enterprise customers and developers, both as an RPM and as a Linux container. That was quite a moment for the industry and, quite frankly, for me as well, having participated in the discussions that led to the significant announcement with Microsoft. Since then, we have been in tight collaboration to make sure this day would actually arrive. Despite the usual challenges with a relatively new open source project, the project was
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If you’re heading to DockerCon 16 next week in Seattle, connect with us to see why Fortune 500 organizations trust Red Hat for enterprise deployments. Red Hat subject matter experts will be onsite to walk you through real-world use cases for securely developing, deploying and managing container-based applications.
Attend the State of Container Security Session
Join two of Red Hat’s Docker contributors discussing the state of container security today. Senior Software Engineer Mrunal Patel and Thomas Cameron, Global Evangelist of Emerging Technology are presenting on how you can secure your containerized microservices without slowing down development.
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It’s been just over three years since Solomon Hykes presented the world with the (so far) most creative way to use the tar command: the Docker project. Not only does the project combine existing container-technologies and make them easier to use, but its well-timed introduction drove an unprecedented rate of adoption for new technology.
Did people run containers before the Docker project? Yes, but it was harder to do so. The broader community was favoring LXC, and Red Hat was working on a libvirt-based model for Red Hat Enterprise Linux. With OpenShift 2, Red Hat had already been running containers in production for several years – both in an online PaaS as well as on-premise for enterprise customers. The model pre-Docker however was fundamentally different from what we are seeing today: rather than enabling completely independent runtimes inside the containers, the approach in
Continue reading “In Defense of the Pet Container, Part 1: Prelude – The Only Constant is Complexity”
The recent release of Red Hat Cloud Suite marked a new milestone for Red Hat and our customers. First, it is the first in what will become a family of suites. Second, it enables enterprise IT to transform their application development and operations toward an agile, innovation center based on hybrid cloud and devops technologies. Curating a broad set of open source technologies, Red Hat Cloud Suite offers a turnkey Cloud solution with a container-based app-development platform, private-cloud infrastructure, and a common management framework. Specifically, Red Hat Cloud Suite includes
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In Architecting Containers Part 4: Workload Characteristics and Candidates for Containerization we investigated the level of effort necessary to containerize different types of workloads. In this article I am going to address several challenges facing organizations that are deploying containers – how to patch containers and how to determine which teams are responsible for the container images. Should they be controlled by development or operations?
In addition, we are going to take a look at
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Many development and operations teams are looking for guidelines to help them determine what applications can be containerized and how difficult it may be. In Architecting Containers Part 3: How the User Space Affects Your Applications we took an in depth look at how the user space affects applications for both developers and operations. In this article we are going to take a look at workload characteristics and the level of effort required to containerize different types of applications.
The goal of this article is to provide guidance based on current capabilities and best practices within
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In our previous posts, we’ve explored the Red Hat container ecosystem, the Red Hat Container Development Kit (CDK), OpenShift as a local deployment and OpenShift in production. In this final post of the series, we’re going to take a look at how a team can take advantage of the advanced features of OpenShift in order to automatically move new versions of applications from development to production — a process known as Continuous Delivery (or Continuous Deployment, depending on the level of automation).
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In a previous blog post we took a look at the Red Hat Container Development Kit (CDK) and how it can be used to build and deploy applications within a development environment that closely mimics a production OpenShift cluster. In this post, we’ll take an in-depth look at what a production OpenShift cluster looks like — the individual components, their functions, and how they relate to each other. We’ll also check out how OpenShift supports scaling up and scaling out applications in a production environment.
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IT decision makers seem to be up in arms regarding discussions on “next generation” technologies. In the past three months it has been nearly impossible to hold a conversation where the terms cloud, OpenStack, or (Linux) containers don’t surface. Hot topics and buzzwords aside, it has become clear (to me) that the right mix of market conditions are causing organizations to express a renewed interest in enterprise virtualization.
Many organizations are now ready to adopt the next generation of server hardware. The popular Ivy Bridge and Sandy Bridge chipsets from Intel are four to five years old and those who purchased such hardware tend to refresh their equipment every four to five years. In addition, we see Intel Haswell technology approaching its third anniversary. Organizations that lease hardware on a three year cycle will also be looking at what the next generation of hardware has to offer.
What does a potential wave of hardware refresh have to do with a renewed interest in enterprise virtualization? To no one’s surprise
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There is a lot of confusion around which pieces of your application you should break into multiple containers and why. I recently responded to this thread on the Docker user mailing list which led me to writing today’s post. In this post I plan to examine an imaginary Java application that historically ran on a single Tomcat server and to explain why I would break it apart into separate containers. In an attempt to make things interesting – I will also aim to
Continue reading “Container Tidbits: When Should I Break My Application into Multiple Containers?”