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Building the Layers of the Scalable
Cluster for Containers
by Barak Michener
About Me
distributed systems
engineer
@barakmich
github.com/barakmich
EpicHack.com
https://twitter.com/gabrtv/status/539805332432637952
Good artists copy…. (or fork?)
the OSI Model
reduced API contracts
OS
kernel
systemd
lvm
ssh
python
java
nginx
mysql
openssl
app
distrodistrodistrodistrodistrodistrodistr
python
java
nginx
mysql
openssl
app
distrodistrodistrodistrodistrodistrodistr
kernel
systemd
lvm
ssh
python
openssl-A
app1
distrodistrodistrodistrodistrodistrodistr java
openssl-B
app2
java
openssl-B
app3
kernel
systemd
lvm
ssh
super-powers
OS
Opportunity for automatic updates.
Consistent set of software across hosts.
Base OS independent from app.
design for host failure
clustering
etcd
/etc
distributed
(or daemon?)
open source software
sequentially consistent
exposed via HTTP
runtime reconfigurable
Available
Available
Available
Unavailable
Available
Leader
Follower
Leader
Follower
Available
Leader
Follower
Temporarily Unavailable
Leader
Follower
Available
1 2 3 4
{Log
1 2 3 4
Entries
1 2 3 4
Indexes
Sequential Consistency
Operations* are atomically executed in the
same sequential order on all machines.
1
1
1
2
Pet=dog
Pet=cat
Pet=cat
1
2
PUT Pet = cat
PUT Pet = dog
1
1
1
2
2
1
2
PUT Pet = cat
PUT Pet = dog
Pet=dog
Pet=dog
Pet=cat
1
1
1
2
2
2
1
2
PUT Pet = cat
PUT Pet = dog
Pet=dog
Pet=dog
Pet=dog
Sequential Consistency
Real-time
1
1
1
2
GET Pet @ 10:00.0 -> 1[cat]!?
GET Pet @ 10:00.0 -> 2[dog]
2
1
1
1
2
2
2
GET Pet @ 10:00.1 -> 1[dog]
Sequential Consistency
Index Time
1
1
1
2
GET Pet @ 2 -> blocking
GET Pet @ 2 -> 2[dog]
2
1
1
1
2
GET Pet @ 2 -> 2[dog]
2
2
etcd guarantees that a get at
index X will always return the
same result.
Avoid thinking in terms of real time because with network
latency the result is always out-of-date.
Quorum GETs
GET via Raft
1
1
1
2
2
1
1
1
2
QGET A
2
1
1
1
2
QGET A -> 2[dog]
2
2
1
1
1
2
QGET A -> 2[dog]
2
2
3
3
https://aphyr.com/posts/313-strong-
consistency-models
super-powers
etcd
Share configuration data across hosts.
Resilient to host failures.
Designed for consistency across hosts.
what can we build
together?
cluster
resources
We have some important primitives
now
What cluster-wide services can we
provide?
Network, Disk, Compute (kublets)
Personal opinion: ls /dev
super-powers
flannel
Partition a IP range -- hand out an IP to
each container (consistently)
Speed! (Avoiding userspace is good)
getting work to servers
orchestration
You
Orchestrator API
Scheduler, Network, NS
Machine(s)
while true {
todo = diff(desState, curState)
schedule(todo)
}
while true {
todo = diff(desState, curState)
schedule(todo)
}
while true {
todo = diff(desState, curState)
schedule(todo)
}
while true {
todo = diff(desState, curState)
schedule(todo)
}
fleet
mesos
kubernetes
swarm
job scheduling
super-powers
orchestration
Think about app capacity first.
Take advantage of
compute/memory/disk/network
resources.
Build on etcd resilience to host failure.
run and isolate apps
containers
what is it exactly?
containers
Containers
Userspace Tarballs
libc
python
django
app.py
example.com/myapp
"Lifts" myapp from the OS into Layer 6
$ container fetch example.com/myapp
$ container run example.com/myapp
Pull from layer 6
Invoke in layer 2
pid ns
isolated pid 1
user ns
isolated uid 0
network ns
isolated netdev
mount ns
isolated /
cgroups
manage resources
cgroups
count resources
cgroups
limit resources
how are they created?
containers
Application (you, MySQL, ElasticSearch)Layer 3
Linux Distro (Ubuntu, Red Hat, CentOS)Layer 2
Physical (Bare Metal, OpenStack, AWS, DO)Layer 1
revisiting today’s Model
App MySQL
ElasticSearch
App MySQL
ElasticSearch
a Cluster
a Cluster
a Cluster
a Cluster
@coreoslinux

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