This is a comprehensive list of hot programming trends, and those that are declining in their popularity.
Hi, I need someone to create a Vagrant box ruby file for me with VM details attached. The Vagrant box should be able to be used for Windows and MAC. The delivery test cases are very simple and are as follows: 1. All settings should be applied and all applications inside the VagrantBox should function well. 2. After ContainerD and ContainerD-CTR tool is installed inside the Vagrant VM, the following CTR basic commands should function successfully (you should be able to start and stop containers) CTR test commands: [login to view URL] Also, you have to provide descriptions in your Vagrant ruby file explaining the tasks each section is performing. Please ensure to create the ruby file as modular as possible for easier modification.
This is something of an "intro" project which could lead to more work in the future. Please make the segmentation model in the following Github repo multiclass: [login to view URL] The change would probably be at around line 206 of the following file, adding some iteration to create a final convolutional block: [login to view URL] Please ensure your final code can be used to train a multi-class model with the "LFW, Labeled Faces in the Wild" dataset referenced in the readme (e.g. a model that can segment out both skin and hair) and deliver a Docker container demonstrating as much along with your final code.
Start a Docker container with the same internal user as the host machine. Most Docker containers start with a root user, or have another user built into the Docker image. In these cases, the docker run --user flag is sufficient to select between the existing users. However, in cases where the image will be pulled, not built, on the host machine, the image may not contain a user that matches the host. Matching the same user id inside the Docker container is useful in cases like handling files mounted from outside the container without affecting file permissions for the host machine's users.
Site Reliability Engineer/Infrastructure & CI Must be within traveling distance of London, Sussex or Surrey. No remote working Help expand our Devops capacity using Terraform for highly available Dockerized Wordpress and Drupal projects on Amazon Web Services (ECS) and Google Cloud (GKE). A good understanding of Infrastructure as Code is essential with experience in building multi-stage continuous integration pipelines using Jenkins. Experience in integrating Prometheus with Docker, ECS, Kubernetes and Bare Metal infrastructure. A hybrid integration is essential to centralise monitoring for our diverse portfolio of cloud and on-premise solutions. Jellyfish also want to consolidate and centralise their logging platform using ELK/EFK as their chosen technology stack. Experience with integrating [login to view URL] technologies into cloud and on-premise environments is key to the success of this role. Skill Requirements Terraform Docker AWS ECS GCP GKE Jenkins Prometheus EFK (ElasticSearch, FluentD/Logstash, Kibana)
We are looking for a Vagrant and ContainerD expert to test Container CheckpointRestore and LiveCold migration between 2 VMs. Brief technical details is: 1. Vagrant box ruby file will be used to initiate the VMs and install all tools needed. 2. ContainerD is the runtime to run containers 3. CRIU is the checkpointrestore and live migration tool between 2 test VMs Deliverables are to provide list of ContainerD-CTR commands & Python code (using gRPC calls) to perform the following: 1. Vagrant ruby file 2. ExportImport containers from DockerHub to ContainerD; 3. Checkpoint and restore a running container 4. LiveCold migrating the container from VM_A to VM_B More detailed instructionstest-cases will be provided.
We are looking for someone with Java/Python /Docker & REST skills to do the following: 1. Add open data sources to Red Sqirl platform (see [login to view URL] for more details) according to instructions which will be provided. See here for an introduction: [login to view URL] [ A list of open data sources will also be provided. A sample data source is: [login to view URL] ] 2. Build simple work flow to show that data source has been successfully added to Red Sqirl. A Docker image on which you can develop and test your work can be found here: [login to view URL] [ If you have a Hadoop cluster you can also run Red Sqirl on that.]