} // Cell (cluster) to run in binary = '.../hello_world_webserver' // Program to run args = { port = '%port%' } // Command line parameters requirements = { // Resource requirements ram = 100M disk = 100M cpu = 0.1 } replicas = 5 // Number of tasks } 10000 Developer View
all dependencies. Applications can be depend less on the infrastructure where it runs. • In traditional IT environments, applications needed specific infrastructure. Dependencies needed to be installed beforehand. • Containers incorporate applications and their dependencies so deployment to development, test, and production can be made easier. • Don’t need to be dependent on on-premise, private or public cloud environments. What are Containers?
in just a few milliseconds. Portable Can be run in a many environments. Efficiency Low overhead. Resources use by containers can be limited. Why Containers?
environments, including “bare metal” and “your laptop” The API and the implementation are 100% open The whole system is modular and replaceable Workload portability
apps to know about concepts that are cloud-provider-specific Examples of this: • Network model • Ingress • Service load-balancers • PersistentVolumes * approximately Workload portability
know about concepts that are Kubernetes-specific Examples of this: • Namespaces • Services / DNS • Downward API • Secrets / ConfigMaps Workload portability
into cloud when you are ready Don’t get stuck with a platform that doesn’t work for you Put your app on wheels and move it whenever and wherever you need Workload portability
apiserver kubelet docker kube-proxy iptables 1. User creates Deployment 2. API server saves info to etcd 3. CM finds Deployment and creates ReplicaSet, which creates Pods (unscheduled) 4. Scheduler schedules pods. 5. Kubelet sees pod scheduled to it and tells docker to run the container. 6. Docker pulls and runs the container. 1 2 6 3 5 4 Docker Hub / GCR 1. Deployment 2. ReplicaSet 3. etc.
coupled The atom of scheduling & placement Shared namespace • share IP address & localhost • share IPC, etc. Managed lifecycle • bound to a node, restart in place • can die, cannot be reborn with same ID Example: data puller & web server Consumers Content Manager File Puller Web Server Volume Pod Pods
private IP Pods can reach each other directly • even across nodes No brokering of port numbers • too complex, why bother? This is a fundamental requirement • can be L3 routed • can be underlayed (cloud) • can be overlayed (SDN) Kubernetes networking
overly-brittle container images 12-factor says config comes from the environment • Kubernetes is the environment Manage config via the Kubernetes API Inject config as a virtual volume into your Pods • late-binding, live-updated (atomic) • also available as env vars Status: GA in Kubernetes v1.2 node API Pod Config Map ConfigMaps
secured something • don’t put secrets in the container image! 12-factor says config comes from the environment • Kubernetes is the environment Manage secrets via the Kubernetes API Inject secrets as virtual volumes into your Pods • late-binding, tmpfs - never touches disk • also available as env vars node API Pod Secret Secrets
any one cloud environment Admin provisions them, users claim them • NEW: auto-provisioning (alpha in v1.2) Independent lifetime from consumers • lives until user is done with it • can be handed-off between pods Dynamically “scheduled” and managed, like nodes and pods Claim PersistentVolumes
pods that work together • grouped by a selector Defines access policy • “load balanced” or “headless” Gets a stable virtual IP and port • sometimes called the service portal • also a DNS name VIP is managed by kube-proxy • watches all services • updates iptables when backends change Hides complexity - ideal for non-native apps Virtual IP Client
Generally represent identity Queryable by selectors • think SQL ‘select ... where ...’ The only grouping mechanism • pods under a ReplicationController • pods in a Service • capabilities of a node (constraints) Labels
parallelism vs. required completions • Workflow: restart on failure • Build/test: don’t restart on failure Aggregates success/failure counts Built for batch and big-data work Status: GA in Kubernetes v1.2 ... Jobs
name collisions in the API • poor isolation between users • don’t want to expose things like Secrets Solution: Slice up the cluster • create new Namespaces as needed • per-user, per-app, per-department, etc. • part of the API - NOT private machines • most API objects are namespaced • part of the REST URL path • Namespaces are just another API object • One-step cleanup - delete the Namespace • Obvious hook for policy enforcement (e.g. quota) Namespaces