Learn about the benefits of using Docker for ML applications, how to write a Dockerfile, build a Docker image, run a Docker container, push a Docker image to a registry, best practices for Dockerizing ML applications, and deploying a Dockerized ML application on Kubernetes.
Table of contents
Docker FundamentalsDocker ArchitectureDockerfile BasicsLet’s break down the instructions used in this Dockerfile:Best practices for writing Dockerfiles include:Basic Docker CommandsDocker ComposeDocker Compose File StructureDocker Compose CommandsDocker NetworkingDocker Network TypesCreating Custom NetworksDocker Volumes and Data ManagementTypes of Docker VolumesData Persistence Best PracticesDocker SwarmDocker Swarm OverviewDeploying Services to a SwarmDocker SecurityContinuous Integration/Deployment with DockerScanning Docker Images for VulnerabilitiesEssential Docker Commands for Efficient Container ManagementContainer ManagementListing ContainersStarting and Stopping ContainersRemoving ContainersExecuting Commands in ContainersViewing Container Logs and StatsImage ManagementListing ImagesPulling and Pushing ImagesBuilding ImagesRemoving ImagesRunning ContainersBasic Container CreationPort MappingVolume MappingEnvironment VariablesNetworkingCreating NetworksConnecting Containers to NetworksListing NetworksRemoving NetworksVolumesCreating VolumesListing VolumesRemoving VolumesDocker SwarmInitializing a SwarmJoining a SwarmLeaving a SwarmManaging NodesDeploying ServicesManaging StacksNow some of the lesser known Docker Commands in detailedHistoryDf (Nor Pandas Df 😂)PruneExecDocker CPSaving and Loading Docker ImagesStats1 Comment
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