Who are you and what have you done with my Containers? 

@tekgrrl #kubernetes #devfest Mandy Waite Developer Advocate +MandyWaite @tekgrrl 

Image by Connie Zhou 

@tekgrrl #kubernetes #devfest job hello_world = { runtime = { cell = 'ic' } // 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 

@tekgrrl #kubernetes #devfest Developer View 

@tekgrrl #kubernetes #devfest web browsers BorgMaster link shard UI shard BorgMaster link shard UI shard BorgMaster link shard UI shard BorgMaster link shard UI shard Scheduler borgcfg web browsers scheduler Borglet Borglet Borglet Borglet Config file BorgMaster link shard UI shard persistent store (Paxos) Binary What just happened? Cell Storage Developer View 

Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Image by Connie Zhou Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! Hello world! 

Google confidential │ Do not distribute Everything at Google runs in containers: • Gmail, Web Search, Maps, ... • MapReduce, batch, ... • GFS, Colossus, ... • Even Google Cloud Platform: VMs run in containers! 

Google confidential │ Do not distribute Everything at Google runs in containers: • Gmail, Web Search, Maps, ... • MapReduce, batch, ... • GFS, Colossus, ... • Even Google’s Cloud Platform: VMs run in containers! We launch over 2 billion containers per week 

Kubernetes 

@tekgrrl #kubernetes #devfest Kubernetes Greek for “Helmsman”; also the root of the words “governor” and “cybernetic” • Runs and manages containers • Inspired and informed by Google’s experiences and internal systems • Supports multiple cloud and bare-metal environments • Supports multiple container runtimes • 100% Open source, written in Go Manage applications, not machines 

@tekgrrl #kubernetes #devfest web browsers y Kubelet Kubelet Kubelet Kubelet Kubernetes Master Replication Controller Scheduler API Server Kube-UI Container Registry kubectl proxy web browsers Kubernetes Architecture 

@tekgrrl #kubernetes #devfest Setting up a cluster • Choose a platform: GCE, AWS, Azure, Rackspace, on-premises, ... • Choose a node OS: CoreOS, Atomic, RHEL, Debian, CentOS, Ubuntu, ... • Provision machines: Boot VMs, install and run kube components, ... • Configure networking: IP ranges for Pods, Services, SDN, ... • Start cluster services: DNS, logging, monitoring, ... • Manage nodes: kernel upgrades, OS updates, hardware failures... Not the easy or fun part, but unavoidable This is where things like Google Container Engine (GKE) really help 

@tekgrrl #kubernetes #devfest The atom of scheduling for containers Represents an application specific logical host Hosts containers and volumes Each has its own routable (no NAT) IP address Ephemeral • Pods are functionally identical and therefore ephemeral and replaceable Pod Web Server Volume Consumers Pods 

@tekgrrl #kubernetes #devfest Can be used to group multiple containers & shared volumes Containers within a pod are tightly coupled Shared namespaces • Containers in a pod share IP, port and IPC namespaces • Containers in a pod talk to each other through localhost Pods Pod Git Synchronizer Node.js App Container Volume Consumers git Repo 

@tekgrrl #kubernetes #devfest Developer View (Pods) spec: containers: - name: mysql image: mysql resources: limits: memory: "512Mi" cpu: "1000m" ports: - containerPort: 3306 name: mysql volumeMounts: - name: mysql-persistent-storage mountPath: /var/lib/mysql volumes: - name: mysql-persistent-storage 

@tekgrrl @googlecloud #oscon Pod Networking (across nodes) Pods have IPs which are routable Pods can reach each other without NAT ● Even across nodes No Brokering of Port Numbers These are fundamental requirements Many solutions ● Flannel, Weave, OpenVSwitch, Cloud Provider 10.1.2.0/24 10.1.1.0/24 10.1.1.211 10.1.1.2 10.1.2.106 10.1.3.0/24 10.1.3.45 10.1.3.17 10.1.3.0/24 

@tekgrrl #kubernetes #devfest Dashboard show: type = FE Pod Pod frontend Pod frontend Pod Pod Dashboard show: version = v2 type = FE version = v2 type = FE version = v2 ● Metadata with semantic meaning ● Membership identifier ● The only Grouping Mechanism Behavior Benefits ➔ Allow for intent of many users (e.g. dashboards) ➔ Build higher level systems … ➔ Queryable by Selectors Labels ← These are important 

@tekgrrl #kubernetes #devfest Developer View (pod with labels) metadata: name: frontend labels: type: frontend version: v2 spec: containers: - name: php-guestbook image: php-guestbook:oscon-eu ... 

@tekgrrl #kubernetes #devfest Replication Controller Pod Pod frontend Pod frontend Pod Pod Replication Controller #pods = 1 version = v2 show: version = v2 version= v1 version = v1 version = v2 Replication Controller #pods = 2 version = v1 show: version = v2 Behavior Benefits ● Keeps Pods running ● Gives direct control of Pod #s ● Grouped by Label Selector ➔ Recreates Pods, maintains desired state ➔ Fine-grained control for scaling ➔ Standard grouping semantics Replication Controllers 

@tekgrrl #kubernetes #devfest Developer View (ReplicationController) replicas: 2 selector: version: v1 template: metadata: name: frontend labels: version: v1 spec: containers: - name: php-guestbook image: php-guestbook:oscon-eu ... 

@tekgrrl #kubernetes #devfest Replication Controller Replication Controller - Name = “backend” - Selector = {“name”: “backend”} - Template = { ... } - NumReplicas = 4 API Server 3 Start 1 more OK 4 How many? How many? Canonical example of control loops Have one job: ensure N copies of a pod ● if too few, start new ones ● if too many, kill some ● group == selector Replicated pods are fungible ● No implied order or identity Replication Controllers 

@tekgrrl #kubernetes #devfest Client Pod Container Pod Container Pod Container Container A logical grouping of pods that perform the same function • grouped by label selector Load balances incoming requests across constituent pods Choice of pod is random but supports session affinity (ClientIP) Gets a stable virtual IP and port • also a DNS nametype = FE • Services Service Label selector: type = FE VIP type = FE type = FE type = FE 

@tekgrrl #kubernetes #devfest Developer View (Service) apiVersion: v1 kind: Service metadata: name: frontend labels: name: frontend-svc spec: type: LoadBalancer ports: - port: 80 targetPort: 80 protocol: TCP selector: type: FE 

@tekgrrl #kubernetes #devfest Node3 Kubelet Proxy Pod Container Container Container Container Pod Container Container Container Container Node3 Kubelet Proxy Pod Container Container Container Container Pod Container Container Container Container Node1 Kubelet Proxy Pod Container Container Pod $ kubectl proxy --www=k8s-visualizer/ Visualizing Kubernetes Master APIs Scheduling REST (pods, services, controllers) AuthN Scheduler Replication Controller Container 

@tekgrrl #kubernetes #devfest Service Label selectors: version = 1.0 type = Frontend Service name = frontend Label selector: type = BE Replication Controller Pod frontend Pod version= v1 version = v1 Replication Controller version = v1 #pods = 1 show: version = v2 type = FE type = FE Scaling Example Pod frontend Pod version = v1 type = FE Replication Controller version = v1 #pods = 2 show: version = v2 Pod Pod Replication Controller version = v1 type = FE #pods = 4 show: version = v2 version = v1 type = FE 

@tekgrrl #kubernetes #devfest Rolling Update Example Service Label selectors: version = 1.0 type = Frontend Service name = backend Label selector: type = BE Replication Controller Pod Pod frontend Pod version= v1 version = v1 Replication Controller version = v1 type = BE #pods = 2 show: version = v2 type = BE type = BE Replication Controller version = v2 type = BE #pods = 2 show: version = v2 Pod version = v2 type = BE version = v2 

@tekgrrl #kubernetes #devfest Service Label selectors: version = 1.0 type = Frontend Service name = backend Label selector: type = BE Replication Controller Pod Pod frontend Pod version= v1 version = v1 Replication Controller version = v1 type = BE #pods = 2 show: version = v2 type = BE type = BE Canary Example Replication Controller Replication Controller version = v2 type = BE #pods = 1 show: version = v2 Pod frontend Pod version = v2 type = BE 

Demo - Visualization 

@tekgrrl #kubernetes #devfest A quick guide to Cluster Nodes Cluster Node Kubelet Proxy disk = ssd Resources Labels Disks 

@tekgrrl #kubernetes #devfest What Resources does it need? What Disk(s) does it need? What node can it run on (NodeName)? What node(s) can it run on (Node Labels)? Finding Potential Nodes Cluster Node Kubelet Proxy disk = ssd 

@tekgrrl #kubernetes #devfest Prefer node with most free resource left after the pod is deployed Prefer nodes with the specified label Minimise number of Pods from the same service on the same node CPU and Memory is balanced after the Pod is deployed [Default] Ranking Potential Nodes Cluster Node Kubelet Proxy disk = ssd 

@tekgrrl #kubernetes #devfest Let’s explore that CPU and memory balancing 

@tekgrrl #kubernetes #devfest Machines (Virtual and Bare Metal) have shapes 

@tekgrrl #kubernetes #devfest Workloads have shapes too 

@tekgrrl #kubernetes #devfest In a container cluster the Machine becomes a Resource Boundary 

@tekgrrl #kubernetes #devfest Machine Shapes Workload Shapes 

@tekgrrl #kubernetes #devfest Computing Tetris 5.5GB RAM Inaccessible CPU Fully Utilized 5.5GB RAM Available 1 CPU Core available Resource Stranding Efficient Bin-Packing Memory Fully Utilized CPU Fully Utilized 

@tekgrrl #kubernetes #devfest Efficient scheduling is key to container management 

@tekgrrl #kubernetes #devfest Open sourced in June, 2014 v1.0 in July, 2015 Google Container Engine (GKE) ● hosted Kubernetes - don’t think about cluster setup ● GA in August, 2015 PaaSes: ● RedHat OpenShift, Deis, Stratos Distros: ● CoreOS Tectonic, Mirantis Murano (OpenStack),RedHat Atomic, Mesos Driving towards a 1.1 release Kubernetes status & plans 

@tekgrrl #kubernetes #devfest Google Container Engine (GA) Managed Kubernetes (Kubernetes v1) Manages Kubernetes master uptime Manages Updates Cluster Resize via Managed Instance Groups Centralised Logging Google Cloud VPN support 

@tekgrrl #kubernetes #devfest Kubernetes is Open Source We want your help! http://kubernetes.io https://github.com/GoogleCloudPlatform/kubernetes irc.freenode.net #google-containers @kubernetesio 

@tekgrrl #kubernetes #devfest Tweet questions to: @tekgrrl Slides: http://bit.ly/1i2PsgE Questions