$ docker -context production container ls Exporting and importing Docker contexts If your kubeconfig has more than one context, the current context ( kubectl config current-context) will be used. For this to work, you will need a valid kubeconfig file in /home/ubuntu/.kube/config. The following can be used to create a config with Kubernetes as the default orchestrator using the existing kubeconfig stored in /home/ubuntu/.kube/config. You can view the new context with docker context ls and docker context inspect.
Different contexts update#
For example, if you switch your current Kubernetes config using kubectl config use-context, the default Docker context will dynamically update itself to the new Kubernetes endpoint. It does not have a meta.json configuration file, and it dynamically updates based on the current configuration. Note: The default context behaves differently than manually created contexts. Each new context you create gets its own meta.json stored in a dedicated sub-directory of ~/.docker/contexts/. The new context is stored in a meta.json file below ~/.docker/contexts/. Successfully created context "docker-test" $ docker context create docker-test \ -default-stack-orchestrator =swarm \ -docker host =unix:///var/run/docker.sock The easiest way to see what a context looks like is to view the default context. Run docker context to verify that your Docker client supports contexts.Ī context is a combination of several properties. A Docker client that supports the top-level context command.To follow the examples in this guide, you’ll need: Once these contexts are configured, you can use the top-level docker context use to easily switch between them.įor information on using Docker Context to deploy your apps to the cloud, see Deploying Docker containers on Azure and Deploying Docker containers on ECS.
prod-swarm contains everything required to manage a Swarm cluster in a production environment. dev-k8s contains the endpoint data and security credentials to configure and manage a Kubernetes cluster in a development environment. The docker context command makes it easy to configure these contexts and switch between them.Īs an example, a single Docker client on your company laptop might be configured with two contexts dev-k8s and prod-swarm.
Each context contains all of the endpoint and security information required to manage a different cluster or node. This guide shows how contexts make it easy for a single Docker CLI to manage multiple Swarm clusters, multiple Kubernetes clusters, and multiple individual Docker nodes.Ī single Docker CLI can have multiple contexts. This paper contributes to the growing academic and policy literature on algorithmic management, proposing a conceptual framework for empirical investigations and a basic compass for policy making in this area.Estimated reading time: 9 minutes Introduction In algorithmic management, these technological developments are combined and used for re-organising control and re-shaping power balances in the workplace. This is because it increases considerably the organisational ability of controlling complex economic and work processes, as it benefits from the massive capacity to collect, store and process information of digital technologies. The paper argues that while algorithmic management should be understood as the digital evolution of certain pre-existing trends that have long characterised the organisation of economic activity, it is potentially disruptive. The paper defines algorithmic management as the use of computer-programmed procedures for the coordination of labour input in an organisation and puts it into context to discuss its usage in both digital labour platforms and ‘regular’ workplaces and companies, exploring its implications and providing a few policy suggestions.
This paper provides a conceptual framework for the emerging phenomenon of algorithmic management and outlines some of the implications for work, from work organisation to working conditions (job quality).
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