Container Orchestration and Management Systems

Comparison from Technical View Harry Zhang, Member of #CNCF

The Scope of This Talk• Kubernetes

• by Cloud Native Computing Foundation

• Docker 1.12+ • by Docker Inc.

• Compose + Swarm is kind of legacy, so they will not be included in this talk

• Mesos • by Apache Software Foundation

• only with Marathon, DC/OS is not included (the scope of later is larger)

Chapter 1: Core Idea and Architecture

Kubernetes• Build right things with containers by following concepts and conventions

• like a “Spring Framework” in container eco-system • Design

• master • api-server, scheduler, controller-manager

• node • kubelet, kube-proxy

• independent binaries • Pros: modular, transparent, manageable • Cons: a little bit complex to setup (1.4 is much better now)

• network & volume plugins • driven by control loops

kubeletSyncLoop

kubeletSyncLoop

proxy

proxy

1 Pod created

etcd

scheduler

api-server

Kubernetes

kubeletSyncLoop

kubeletSyncLoop

proxy

proxy

2 Pod object added

etcd

scheduler

api-server

Kubernetes

kubeletSyncLoop

kubeletSyncLoop

proxy

proxy

3.1 New pod object detected3.2 Bind pod with node

etcd

scheduler

api-server

Kubernetes

kubeletSyncLoop

kubeletSyncLoop

proxy

proxy

4.1 Detected pod bind with me4.2 Start containers in pod

etcd

scheduler

api-server

Kubernetes

kubeletSyncLoop

controller-managerControlLoop

kubeletSyncLoop

proxy

proxy

Objects:podreplicanamespaceserviceendpointjobdeployment volume petset …

etcd

scheduler

api-server

Reconcile:desired world VS real world

handler

Kubernetes

Tips: Control Theory*

*Andrei, Neculai (2005). "Modern Control Theory – A historical Perspective"

• It’s the basic model for: • Kubernetes controller and all other event loops • SwarmKit orchestrator • …

ControlLoop

Docker 1.12+• Build-in cluster support for Docker containers

• powered by swarmkit • SwarmtKit Design

• build-in data store • manager

• several components build into one binary • control loop driven

• worker • use pull model to connect with manager

WARNING: SwarmKit is currently a primitive project, expect change of this part

Allocator

DispatcherScheduler

Orchestrator• API: accept commands from client

• Create object in raft based memory store

• github.com/coreos/etcd/raft for consensus

• github.com/hashicorp/go-memdb for in-memory object storage

• state, cluster, node, service, task, network …

$ docker service createAPI

Store

SwarmKit Manager

Allocator

DispatcherScheduler

• Create Tasks from Service object

• Task: “start a container” etc

• Reconcile loop for Service objects

• Control Theory again

Orchestrator

API

Store

Orchestrator

Service (replica=2)

Task

Task

check if replica=2 or not

SwarmKit Manager

• Allocates IP addresses to Services and Tasks

• (and allocate volumes in the future)

• VIP and ports for Service

• IP for all endpoints (veth pairs) in the network the task is attached to

Orchestrator

DispatcherScheduler

API

Store

Allocator

SwarmKit Manager

Network Create

• Assign Task to Node

• unassignedTasks

• nodeHeap

• search in heap to find the best node which meets the constraints && has lightest workloads

• ReadyFilter, ResourceFilter, ConstraintFilter

Orchestrator

Dispatcher

API

Store

Scheduler

Allocator

SwarmKit Manager

Manager

• Nodes (agents) management

• Dispatch assigned Task to corresponding Node

Orchestrator

API

Store

Allocator

SwarmKit Manager

Scheduler Dispatcher

Dispatcher

Agent

Agent

Agentgrpc stream

grpc stream

grpc stream

Task

• Worker:

• connect to Dispatcher to check assigned tasks

• executor: execute tasks (containers) on this Node

Worker

Executor

Agent Agent

AdapterDocker Daemon

docker.sockWorker

Executor

Worker

Executor

Agent

Mesos 1.0• A distributed systems kernel

• originally designed to run big data job • core idea: fine-grained resource sharing

• Mesos Design • Master + Slave + Zookeeper • two level scheduling

• scheduler + executor = framework • need to use frameworks like Marathon for orchestration and management

• containerizer • multiple container runtime & image support (>=1.0)

MPI job

MPI scheduler

Hadoop job

Hadoop scheduler

Allocation module

Mesosmaster

Mesos slaveMPI

executor

Mesos slaveMPI

executor

tasktask

Resource offer

Pick framework to offer resources to

*Animate: Operating Systems and Systems Programming Lecture 24 Anthony D. Joseph https://cs162.eecs.berkeley.edu/

MPI job

MPI scheduler

Hadoop job

Hadoop scheduler

Allocation module

Mesos master

Mesos slaveMPI

executor

Mesos slaveMPI

executor

tasktask

Pick framework to offer resources toResource

offer

Resource offer = list of (node, availableResources)

E.g. { (node1, <2 CPUs, 4 GB>), (node2, <3 CPUs, 2 GB>) }

*Animate: Operating Systems and Systems Programming Lecture 24 Anthony D. Joseph https://cs162.eecs.berkeley.edu/

MPI job

MPI scheduler

Hadoop job

Hadoop scheduler

Allocation module

Mesos master

Mesos slaveMPI

executorHadoop executor

Mesos slaveMPI

executor

tasktask

Pick framework to offer resources to

taskFramework-specific

scheduling

Resource offer

Launches and isolates executors

*Animate: Operating Systems and Systems Programming Lecture 24 Anthony D. Joseph https://cs162.eecs.berkeley.edu/

How Docker plug into Mesos?• Before 1.0

• Docker Containerizer • Docker image -> task -> mesos-docker-executor -> Docker Daemon

• Mesos 1.0 • Supporting multiple runtime & images • MesosContainerizer

• “Mesos native container stack” • Isolators • Launcher

Mesos slave

Hadoop executor

task

mesos-docker-executor

Checkpoint

Kubernetes Docker SwarmKit Mesos+Marathon

Design control loops drivencontrol loops driven (but in single binary)

two level scheduling

Coordination etcd build-in raft Zookeeper

Container Runtime multiple single, but has potential for more OCI runtimes multiple

Container Image Docker Image, ACI, more in future Docker Image Docker Image, ACI, more

in future Docker Daemon no need need no need

About Build-In Data Store

Pros Cons

easy to setup hard to understand & debug

fewer round trips hard to do backup/restore, migration, monitoring/audit

easy to do performance tuning lack of mgmt API like:etcd admin guide

Chapter 2: Control Panel

Control Panel: Orchestration + Management• “Defines when and what to do next through out the automated workflow”

• workload management • secret management • configuration management • scale and autoscaling • stateful workload • … and more

Workload Managemente.g. “a web server with 2 replicas”

Kubernetes Docker SwarmKit Mesos+Marathon

Description Deployment Service Application

Version Control yes (revision) not yet yes (deployments)

• Kubernetes “Deployment”• $ kubectl create -f <deployment-yaml> • $ kubectl edit <deployment>

• this will open and edit object stored in etcd • update will trigger rolling update

• $ kubectl set image <deployment> • $ kubectl scale —replicas=5 <deployment> … • $ kubectl rollout history <deployment> • $ kubectl rollout undo <deployment> —to-revision=<version>

$ kubectl edit <deployment> …

• Docker SwarmKit “Service”• $ docker service create SERVICE —replicas=5 … • $ docker service scale SERVICE=REPLICAS • $ docker service update [OPTIONS] SERVICE

• rolling update • 30+ update options are supported

• —container-label-add value • —container-label-rm value • --env-add value • --env-rm value • —image string • …

• Mesos + Marathon “Application”• $ dcos marathon app start [--force] <app-id> [<instances>] • $ dcos marathon app update [--force] <app-id> [<properties>…]

• rolling update • app dependencies are respected

• $ dcos marathon app version list [--max-count=<max-count>] <app-id> … • $ dcos marathon deployment list [--json <app-id>] • $ dcos marathon deployment rollback <deployment-id>

Secret Management• Kubernetes

• Secret volume • encrypted and stored in etcd • consumed by ENV or volume

• Docker SwarmKit • under discussion: https://github.com/docker/swarmkit/issues/1329

• Mesos + Marathon • only in DC/OS

• stored in ZooKeeper, exposed as ENV in Marathon

• Another similar feature is Configuration Management

Configuration Management• Kubernetes

• ConfigMap • stored in etcd, consumed by ENV or volume

• $ kubectl create configmap example-redis-config —from-file=docs/redis-config

• Docker SwarmKit • under discussion: https://github.com/docker/swarmkit/issues/1329

• Mesos + Marathon • not yet

Autoscaling• Kubernetes

• HorizontalPodAutoScaler • default: CPU • Custom Metrics:

• user defined endpoint, e.g. http://localhost:9100/metrics • share same metric data structure with CNCF projects like Prometheus

• Docker SwarmKit • not yet: https://github.com/docker/swarmkit/issues/486#issuecomment-219133613

• Mesos + Marathon • a stand-by `marathon-autoscale.py` • autoscales application based on the utilization metrics from Mesos

Stateful Workload• Kubernetes

• PetSet: Replicas with stable membership and volumes • stable hostname • ordinal index • stable storage

• Docker SwarmKit • not yet, and don’t suggest stateful service

• Mesos + Marathon • Stateful Applications

• dynamic reservations, reservation labels, and persistent volumes.

cassandra-0

volume 0

cassandra-0.cassandra.default.svc.cluster.local

cassandra-1

volume 1

cassandra-1.cassandra.default.svc.cluster.local

Chapter 3: Service Discovery & Load Balance

NodeNode

Service Discovery & LB• Kubernetes

• Load Balancer • iptables

• External Access • <externalIP route to node(s)>:<port> • NodePort: <ip of any node>:<NodePort> • External LoadBalancer • Ingress (L7)

• Ingress Pod: Nginx, HAproxy • SSL

• Name Service • build-in skyDNS pod

portal iptables rule 10.10.0.116:8001

random mode iptables rules

Pod 2Pod 1

ingress traffic http://foo.bar.com

Node

Ingress Pod

internal traffic

outside traffic

pod rule 2pod rule 1

WorkerWorker

container sandbox

ingress sandbox

Service Discovery & Load Balance

• Docker SwarmKit • Load Balancer

• ipvs NAT mode

• External Access • Routing Mesh

• Name Service • embedded DNS server

• for service and task Container 2Container 1

ipvs

Gossip to update the iptables & ipvs rules

port mapping

iptables iptables

outside traffic (when service created with -p)

internal traffic

ipvs

• Two kinds of sandboxes

• ingress: on every worker

• container: on workers where task lives

• Two networks are needed

• ingress overlay • user-defined overlay

DNS: svc->vip

ingress sandbox

Service Discovery & Load Balance• Mesos + Marathon

• Load Balancer • Marathon-lb: HAproxy based

• virtual addresses (VIPs) in DC/OS

• External Access • http://<public agent ip>:<servicePort> • external load balancer

• Name Service • Mesos-DNS

SlaveSlave

Marathon-lb

Container 2Container 1

Mesos-DNS

Checkpoint

Kubernetes Docker SwarmKit Mesos+Marathon

Filter iptables VIP iptables VIP no need

LB iptables random mode ipvs NAT mode HAproxy

External Access nodeIP:port, Ingress, external IP/LB

Routing Mesh (ingress overlay)

same as expose HAproxy to public

Update watch etcd gossip marathon_lb.py & template

Chapter 4: Scheduling

Kubernetes• Pod as schedule unit

• this is unique, but why? • Multi-Scheduler

• pod1: scheduler1, pod2 : scheduler2 • QoS tiers

• anyone remember the core idea of Borg? • Guaranteed (requests == limit) • Burstable (requests < limit) • Best-Effort (no request & limit)

• More Borg features are on the way • equivalence class, pod level resource boundary …

Burstable Pod

Docker SwarmKit• Task (container) as schedule unit • Multi-Scheduler

• not yet • Strategy

• pipeline of filters • ReadyFilter ResourceFilter ConstraintFilter

• to sort nodeHeap • QoS tiers

• not yet

Mesos + Marathon• Task as schedule unit (Pod support in plan) • Multi-Scheduler

• Mesos is designed to run multiple frameworks (schedulers) • Strategy

• Two level scheduling (the killing weapon of Mesos) • Twitter scale … • fine-grained resource sharing (like Borg)

• QoS tiers • of course

• And much more • task eviction, data locality, max-min fairness, priority, offer reject, Delay Scheduling • and Big Data of course

Chapter 5: Summary

A Use Case: hyper.sh

• hyper.sh is “Docker Done the Right Way” • $ hyper run mysql • $ hyper run --link mysql wordpress • $ hyper fip attach 22.33.44.55 wordpress

• But Hyper.sh is powered by Kubernetes • and also maintain Kubernetes features

Extensibility Really Matters• Hypernetes (h8s = k8s + HyperContainer) is what’s backing Hyper.sh:

• HyperContainer runtime • Multi-tenant network based on Neutron • Custom Cinder plugin with Ceph backend • Custom HAproxy based Service

• Kubernetes is truly extensible and configurable

Just Personal Idea• So, if

• I am a individual developer/org, trying to find something that is friendly and just works

• I use Docker SwarmKit

• I have a “Twitter scale” cluster to manage or I am a Big Data user

• I need Mesos

• But if what I need is a infrastructure layer to build my systems on top of it in right way

• Kubernetes is the choice

THE END @resouer