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Kubernetes Technical Deep Dive
2015-10 Huawei R&D Vision Forum
Vishnu Kannan <vishnuk@google.com>
Software Engineer
@vishh (Github, IRC)
Google has been developing
and using containers to
manage our applications for
over 10 years.
Images by Connie Zhou
Everything at Google runs in
containers:
• Gmail, Web Search, Maps, ...
• MapReduce, batch, ...
• GFS, Colossus, ...
• Even Google’s Cloud Platform:
VMs run in containers!
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
But it’s all so different!
• Deployment
• Management, monitoring
• Isolation (very complicated!)
• Updates
• Discovery
• Scaling, replication, sets
A fundamentally different way of
managing applications requires
different tooling and abstractions
Images by Connie Zhou
Kubernetes
Greek for “Helmsman”; also the root of the
word “Governor” and “cybernetic”
• Container orchestrator
• Runs and manages containers
• Supports multiple cloud and bare-metal
environments
• Inspired and informed by Google’s
experiences and internal systems
• 100% Open source, written in Go
Manage applications, not machines
kubelet
UI
kubeletCLI
API
users master nodes
The 10000 foot view
apiserver
kubelet
scheduler
controllers
UI
All you really care about
API
Container
Cluster
Container clusters: A story in two parts
Container clusters: A story in two parts
1. Setting up the cluster
• Choose a cloud: 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
2. Using the cluster
• Run Pods & Containers
• Replication controllers
• Services
• Volumes
This is the fun part!
A distinct set of problems from cluster setup and management
Don’t make developers deal with cluster administration!
Accelerate development by focusing on the applications, not the cluster
Container clusters: A story in two parts
Basic Architecture
Networking
10.1.1.0/24
172.16.1.1
172.16.1.2
Docker networking
10.1.2.0/24
172.16.1.1
10.1.3.0/24
172.16.1.1
10.1.1.0/24
172.16.1.1
172.16.1.2
Docker networking
10.1.2.0/24
172.16.1.1
10.1.3.0/24
172.16.1.1
NAT
NAT
NAT
NAT
NAT
Kubernetes networking
IPs are routable
• vs docker default private IP
Pods can reach each other without NAT
• 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)
10.1.1.0/24
172.16.1.1
172.16.1.2
Kubernetes networking
10.1.2.0/24
172.16.1.1
10.1.3.0/24
172.16.1.1
Pods
Pods
Small group of containers & volumes
Tightly coupled
The atom of scheduling & placement in
Kubernetes
Shared namespace
• share IP address & localhost
• share IPC
Mortal
• can die, cannot be reborn
Example: data puller & web server
Consumers
Content
Manager
File
Puller
Web
Server
Volume
Pod
Volumes
Very similar to Docker’s concept
Pod scoped storage
Share the pod’s lifetime & fate
Support many types of volume plugins
• Empty dir (and tmpfs)
• Host path
• Git repository
• GCE Persistent Disk
• AWS Elastic Block Store
• iSCSI
• NFS
• GlusterFS
• Ceph File and RBD
• Cinder
• Secret
• ...
Labels & Selectors
Arbitrary metadata
Attached to any API object
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
App: MyApp
Phase: prod
Role: FE
App: MyApp
Phase: test
Role: FE
App: MyApp
Phase: prod
Role: BE
App: MyApp
Phase: test
Role: BE
Selectors
App: MyApp
Phase: prod
Role: FE
App: MyApp
Phase: test
Role: FE
App: MyApp
Phase: prod
Role: BE
App: MyApp
Phase: test
Role: BE
App = MyApp
Selectors
App: MyApp
Phase: prod
Role: FE
App: MyApp
Phase: test
Role: FE
App: MyApp
Phase: prod
Role: BE
App: MyApp
Phase: test
Role: BE
App = MyApp, Role = FE
Selectors
App: MyApp
Phase: prod
Role: FE
App: MyApp
Phase: test
Role: FE
App: MyApp
Phase: prod
Role: BE
App: MyApp
Phase: test
Role: BE
App = MyApp, Role = BE
Selectors
Selectors
App: MyApp
Phase: prod
Role: FE
App: MyApp
Phase: test
Role: FE
App: MyApp
Phase: prod
Role: BE
App: MyApp
Phase: test
Role: BE
App = MyApp, Phase = prod
App: MyApp
Phase: prod
Role: FE
App: MyApp
Phase: test
Role: FE
App: MyApp
Phase: prod
Role: BE
App: MyApp
Phase: test
Role: BE
App = MyApp, Phase = test
Selectors
ReplicationControllers
ReplicationControllers
An example of control loops
Runs out-of-process wrt API server
Have 1 job: ensure N copies of a pod
• if too few, start new ones
• if too many, kill some
• grouped by a selector
Cleanly layered on top of the core
• all access is by public APIs
Replicated pods are fungible
• No implied order or identity
ReplicationController
- name = “my-rc”
- selector = {“App”: “MyApp”}
- podTemplate = { ... }
- replicas = 4
API Server
How
many?
3
Start 1
more
OK
How
many?
4
Services
Services
A group of 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
Secrets
Secrets
Problem: how to grant a pod access to a
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 them as “virtual volumes” into Pods
• late-binding
• tmpfs - never touches disk
node
Pod Secret
API
Rolling updates
Rolling Updates
ReplicationController
- replicas: 3
- selector:
- app: MyApp
- version: v1
Service
- app: MyApp
Rolling Updates
ReplicationController
- replicas: 3
- selector:
- app: MyApp
- version: v1
ReplicationController
- replicas: 0
- selector:
- app: MyApp
- version: v2
Service
- app: MyApp
Rolling Updates
ReplicationController
- replicas: 3
- selector:
- app: MyApp
- version: v1
ReplicationController
- replicas: 1
- selector:
- app: MyApp
- version: v2
Service
- app: MyApp
Rolling Updates
ReplicationController
- replicas: 2
- selector:
- app: MyApp
- version: v1
ReplicationController
- replicas: 1
- selector:
- app: MyApp
- version: v2
Service
- app: MyApp
Rolling Updates
ReplicationController
- replicas: 2
- selector:
- app: MyApp
- version: v1
ReplicationController
- replicas: 2
- selector:
- app: MyApp
- version: v2
Service
- app: MyApp
Rolling Updates
ReplicationController
- replicas: 1
- selector:
- app: MyApp
- version: v1
ReplicationController
- replicas: 2
- selector:
- app: MyApp
- version: v2
Service
- app: MyApp
Rolling Updates
ReplicationController
- replicas: 1
- selector:
- app: MyApp
- version: v1
ReplicationController
- replicas: 3
- selector:
- app: MyApp
- version: v2
Service
- app: MyApp
Rolling Updates
ReplicationController
- replicas: 0
- selector:
- app: MyApp
- version: v1
ReplicationController
- replicas: 3
- selector:
- app: MyApp
- version: v2
Service
- app: MyApp
DaemonSets
DaemonSets
Problem: how to run a Pod on every node
• or a subset of nodes
Similar to ReplicationController
• principle: do one thing, don’t overload
“Which nodes?” is a selector
Use familiar tools and patterns
Status: Experimental in Kubernetes v1.1
PersistentVolumes
PersistentVolumes
A higher-level abstraction
• insulation from any one cloud environment
Admin provisions them, users claim them
Independent lifetime and fate
Can be handed-off between pods and lives
until user is done with it
Dynamically “scheduled” and managed, like
nodes and pods
PersistentVolumes
Cluster
Admin
PersistentVolumes
Provision
Cluster
Admin
PersistentVolumes
PersistentVolumes
Cluster
Admin
User
PersistentVolumes
PersistentVolumes
Cluster
Admin
User
PersistentVolumes
PVClaim
Create
PersistentVolumes
Cluster
Admin
User
PersistentVolumes
PVClaim
Binder
PersistentVolumes
Cluster
Admin
User
PersistentVolumes
PVClaim
Pod
Create
PersistentVolumes
Cluster
Admin
User
PersistentVolumes
PVClaim
Pod
*
PersistentVolumes
Cluster
Admin
User
PersistentVolumes
PVClaim
Pod
Delete
*
PersistentVolumes
Cluster
Admin
User
PersistentVolumes
PVClaim
*
PersistentVolumes
Cluster
Admin
User
PersistentVolumes
PVClaim
Pod
Create
*
PersistentVolumes
Cluster
Admin
User
PersistentVolumes
PVClaim
Pod
*
PersistentVolumes
Cluster
Admin
User
PersistentVolumes
PVClaim
Pod
Delete
*
PersistentVolumes
Cluster
Admin
User
PersistentVolumes
PVClaim
Delete
*
PersistentVolumes
Cluster
Admin
User
PersistentVolumes
Recycler
New and coming soon
• Cluster auto-scaling
• Horizontal Pod auto-scaling
• Jobs (run-to-completion)
• Cron
• Privileged containers
• Graceful termination
• Simpler deployments
• Interactive containers
• Network plugins: CNI
• Performance++
• Scalability++ (250 in v1.1)
• High availability masters
• Scheduling
• Cluster federation
• Easier setup
• More volumes
• Private registry
• L7 load-balancing
Kubernetes status & plans
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 in O(week)
• targeting a 3-4 month cadence
The Goal: Shake things up
Containers are a new way of working
Requires new concepts and new tools
Google has a lot of experience...
...but we are listening to the users
Workload portability is important!
Kubernetes is Open
- open community
- open design
- open source
- open to ideas
http://kubernetes.io
https://github.com/kubernetes/kubernetes
slack: kubernetes
twitter: @kubernetesio

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