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Saved by uncleflo on May 12th, 2019.
Every organization which has adopted DevOps practices wants to quickly adopt "Continuous" everything, be it Integration, Deployment, Testing or, Monitoring. For a successful DevOps operation, CI/CD is very important for any small or big size organization to shorter development cycles and innovate faster, reduce deployment failures, safe Rollbacks and reduce MTTR (mean time to recover). In this article, we will uncover a new way of bringing continuous integration and continuous delivery of applications to your Kuberenetes cluster. We are using Jenkins as the CI tool which will poll the Git repositories to build Docker images on commits and push it to Docker registry. We will use Spinnaker as the CD tool which continuously polls the Docker registry and triggers the deployment pipelines to update applications in your Kubernetes cluster.
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Saved by uncleflo on December 27th, 2017.
At the first Docker Helsinki Meetup for 2017 on January 17th, we heard about three interesting use cases of the ins and outs of how Docker is used in production at Solita, Zalando and Pipedrive. We also heard about the good, the bad and the ugly of running Docker in production. Solita's Use Case: Firstly, Heikki Simperi from Solita explained how his company uses Docker to handle the various apps and systems associated with their management of the Finnish National Railway Service (VR), as well as the problems they've run into when using Docker. Solita runs a variety of their own apps on Docker, including a navigator for train drivers, a construction notification system and a traffic controller app. Heikki reiterated that it's important for the downtime to be minimal when the apps involved are ones responsible for railway management and that "anything over a 3-5 min downtime causes delays for trains, but nobody dies". Most of the issues they experienced using Docker were related to building an image, having a private repository, removing or starting up a container, or a bug inside an app. Overall, the running usage of the Docker platform has been stable, with "zero downtime". The problems have lessened after upgrading to each new Docker version and they are experiencing less and less problems as time goes on. They are looking forward to the release of Docker 1.12 on a stable channel from Red Hat.
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Saved by uncleflo on December 7th, 2014.
The Blinn–Phong reflection model (also called the modified Phong reflection model) is a modification to the Phong reflection model developed by Jim Blinn. Blinn–Phong is the default shading model used in OpenGL and Direct3D's fixed-function pipeline (before Direct3D 10 and OpenGL 3.1), and is carried out on each vertex as it passes down the graphics pipeline; pixel values between vertices are interpolated by Gouraud shading by default, rather than the more computationally-expensive Phong shading.
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