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 Build High-Performance, Scalable, Distributed Applications with Stacks of Containers. Jerome petazzoni
Build high-performance,
scalable, distributed
applications with
stacks of containers
Добрый
день
Jérôme Petazzoni
(@jpetazzo)
Grumpy French DevOps
- Go away or I will replace you
with a very small shell script
Goal in life:
run everything in containers
- Docker-in-Docker
- VPN-in-Docker
- KVM-in-Docker
- Xorg-in-Docker
- etc
outline
Outline
Why containers?
Containers vs Virtual Machines
High speed communication
Service discovery and load balancing
Conclusions
 Build High-Performance, Scalable, Distributed Applications with Stacks of Containers. Jerome petazzoni
why should
we use
containers?
Packaging format
It's easier to build a container image than a
traditional distro package (.deb, .rpm...)
- Dockerfile
Application dependencies are isolated from the host
- application can use Python X even if the host has Python Y
- application can use distro X even if the host has distro Y
Downside: increased disk usage
- but disks are cheap
Service abstraction*
Service installation “docker pull”→
- no more dependency issues
Service start “docker run”→
- no more fiddling with language-specific wrappers
Service stop “docker stop/kill”→
- no more runaway processes
*If using a standard container format, e.g. Docker
Service abstraction
Service check “docker inspect”→
- no more “is this thing really running or not?”
Service reset “docker run”→
- discard copy-on-write layer to return to original state
- no more “oops, I broke it, how do I fix it?”
- doesn't work in all situations, e.g. data corruption
(but recovery is easier because creating test copies is cheap & fast)
No overhead*
CPU performance
= native performance
Memory performance
= a few % shaved off for (optional) accounting
Network and disk I/O performance
= small overhead; can be reduced to zero
*May require tuning!
Immutable infrastructure
What's an immutable infrastructure?
- re-create images each time you change a line of code
- prevent (or track) modifications of running images
Why is it useful?
- no more deviant servers after manual upgrades
- no more “oops, how do we rollback?” after catastrophic upgrade
- easier security audit (inspect images at rest)
How containers can help?
- container images are easier to create and manage than VM images
Micro-service architecture
What's a micro-service architecture?
- decompose big application into many small services
Why is it useful?
- it's easier to upgrade/refactor/replace a small service
- encourages to have many small teams*, each owning a service
(*small teams are supposedly better, see Jeff Bezos “two-pizza rule”)
How containers can help?
- problem: 10 micro-services instead of 1 big application
= 10x more work to deploy everything
- solution: need extremely easy deployment; hello containers!
 Build High-Performance, Scalable, Distributed Applications with Stacks of Containers. Jerome petazzoni
containers
vs
virtual machines
Virtual Machines
Emulate CPU instructions
(painfully slow)
Emulate hardware (storage, network...)
(painfully slow)
Run as an userland process on top of a kernel
(painfully slow)
Virtual Machines
Use native CPU
(fast!)
Paravirtualized storage, network...
(fast, but higher resource usage)
Run on top of an hypervisor
(faster, but still some overhead)
Containers
Processes isolated from each other
Very little extra code path
(in many cases, it's comparable to UID checking)
Virtual Machines vs Containers
Native CPU
Paravirtualized devices
Hypervisor
Native CPU
Native syscalls
Native kernel
Inter-VM communication
Strong isolation, enforced by hypervisor + hardware
- no fast-path data tranasfer between virtual machines
- yes, there are PCI pass-throughs and things like xenbus,
but that's not easy to use, very specific, not portable
Most convenient method: network protocols (L2/L3)
But: huge advantage from a security POV
Inter-container communication
Tunable isolation
- each namespace can be isolated or shared
Allows normal Unix communication mechanisms
- network protocols on loopback interface
- UNIX sockets
- shared memory
- IPC...
Reuse techniques that we know and love (?)
 Build High-Performance, Scalable, Distributed Applications with Stacks of Containers. Jerome petazzoni
high speed
communication
for containers
Shared localhost
Multiple containers can share the same “localhost”
(by reusing the same network namespace)
Communication over localhost is very very fast
Also: localhost is a well-known address
Shared filesystem
A directory can be shared by multiple containers
(by using a bind-mount)
That directory can contain:
- named pipes (FIFOs)
- UNIX sockets
- memory-mapped files
Bind-mount = zero overhead
Shared IPC
Multiple containers can share IPC resources
(using the special IPC namespace)
Semaphores, Shared Memory, Message Queues...
Is anybody still using this?
Host networking
Containers can share the host's network stack
(by reusing its network namespace)
They can use the host's interfaces without penalty
(high speed, low latency, no overhead!)
Native performance to talk with external containers
Host filesystems
Containers can share a directory with the host
Example: use fast storage (SAN, SSD...) in container
- mount it on the host
- share it with the container
- done!
Native performance to use I/O subsystem
Device nodes
Containers can use the host's devices (if allowed)
Access is granted through “devices” control group
Performance (throughput, latency, CPU usage)...
is the same as using the device on the host
Examples:
- /dev/sd*: raw block device in container
- /dev/video*: GPU in container
- /dev/kvm: VM in container
- and more!
 Build High-Performance, Scalable, Distributed Applications with Stacks of Containers. Jerome petazzoni
service
discovery,
load balancing
Service discovery is not a new problem
Usually not important for …
- small architectures
- low server count
- static deployments
But with containers...
- container count can be very high
- deployments are very dynamic
you need
service
discovery
Name resolution
Provide custom /etc/hosts in container
(or give a custom DNS resolver to the container)
Easy to integrate in code (just connect to e.g. “db”)
But:
- no way to push changes to the application
- some libraries won't re-resolve
- might need to restart containers when service address changes
- service must run on well-known port
Environment variables (or SRV records)
Solves the “well-known port” requirement
Harder to integrate in code
Doesn't solve the other problems
In-app discovery with config DB
Connect to zookeeper/etcd to find service location
Watch zookeeper/etcd for changes
If change occurs, reconnect
In-app discovery with config DB
Works well, but requires deep code changes
If you support multiple languages, it's a lot of work
Transitioning from a system to another is hard
ambassadors
container host
database container
I'm frontdb!
web container
I want to talk to frontdb!
local
connect
database host web host
database container
I'm frontdb!
web container
I want to talk to frontdb!
wiring container
I actually talk to frontdb!
wiring container
I pretend I'm frontdb!
local
connect
local
connect
?
database host web host
database container
I'm frontdb!
web container
I want to talk to frontdb!
wiring container
I actually talk to frontdb!
wiring container
I pretend I'm frontdb!
local
connect
local
connect
?
 Build High-Performance, Scalable, Distributed Applications with Stacks of Containers. Jerome petazzoni
database host web host
database container
I'm frontdb!
web container
I want to talk to frontdb!
wiring container
I actually talk to frontdb!
wiring container
I pretend I'm frontdb!
local
connect
local
connect
UNICORNS
But! We are adding extra layers!
Yes.
But service/ambassador communication can be:
- over locahost
- over UNIX socket (even better but not always possible)
- over iptables or IPVS (to bypass the ambassador process)
Ambassador implementations
A few examples
- Registrator
https://github.com/progrium/registrator
- Grand Ambassador
https://github.com/cpuguy83/docker-grand-ambassador
- AirBNB SmartStack
https://github.com/airbnb/nerve
https://github.com/airbnb/synapse
Or roll your own
- some HA KV store + HAProxy, stunnel, iptables, IPVS...
- serverless, ad-hoc discovery (avahi, multicast...)
 Build High-Performance, Scalable, Distributed Applications with Stacks of Containers. Jerome petazzoni
conclusions
Thanks to containers, we can...
Build, ship, and run our applications more easily
Decouple application code from “plumbing”
(service discovery, load balancing)
Which allows to implement micro-service archtectures
efficiently (hopefully without the usual drawbacks!)
Which yields higher agility, shorter dev cycles, etc.
Win!
containerize!
thank you!
questions?

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Build High-Performance, Scalable, Distributed Applications with Stacks of Containers. Jerome petazzoni

  • 4. Jérôme Petazzoni (@jpetazzo) Grumpy French DevOps - Go away or I will replace you with a very small shell script Goal in life: run everything in containers - Docker-in-Docker - VPN-in-Docker - KVM-in-Docker - Xorg-in-Docker - etc
  • 6. Outline Why containers? Containers vs Virtual Machines High speed communication Service discovery and load balancing Conclusions
  • 9. Packaging format It's easier to build a container image than a traditional distro package (.deb, .rpm...) - Dockerfile Application dependencies are isolated from the host - application can use Python X even if the host has Python Y - application can use distro X even if the host has distro Y Downside: increased disk usage - but disks are cheap
  • 10. Service abstraction* Service installation “docker pull”→ - no more dependency issues Service start “docker run”→ - no more fiddling with language-specific wrappers Service stop “docker stop/kill”→ - no more runaway processes *If using a standard container format, e.g. Docker
  • 11. Service abstraction Service check “docker inspect”→ - no more “is this thing really running or not?” Service reset “docker run”→ - discard copy-on-write layer to return to original state - no more “oops, I broke it, how do I fix it?” - doesn't work in all situations, e.g. data corruption (but recovery is easier because creating test copies is cheap & fast)
  • 12. No overhead* CPU performance = native performance Memory performance = a few % shaved off for (optional) accounting Network and disk I/O performance = small overhead; can be reduced to zero *May require tuning!
  • 13. Immutable infrastructure What's an immutable infrastructure? - re-create images each time you change a line of code - prevent (or track) modifications of running images Why is it useful? - no more deviant servers after manual upgrades - no more “oops, how do we rollback?” after catastrophic upgrade - easier security audit (inspect images at rest) How containers can help? - container images are easier to create and manage than VM images
  • 14. Micro-service architecture What's a micro-service architecture? - decompose big application into many small services Why is it useful? - it's easier to upgrade/refactor/replace a small service - encourages to have many small teams*, each owning a service (*small teams are supposedly better, see Jeff Bezos “two-pizza rule”) How containers can help? - problem: 10 micro-services instead of 1 big application = 10x more work to deploy everything - solution: need extremely easy deployment; hello containers!
  • 17. Virtual Machines Emulate CPU instructions (painfully slow) Emulate hardware (storage, network...) (painfully slow) Run as an userland process on top of a kernel (painfully slow)
  • 18. Virtual Machines Use native CPU (fast!) Paravirtualized storage, network... (fast, but higher resource usage) Run on top of an hypervisor (faster, but still some overhead)
  • 19. Containers Processes isolated from each other Very little extra code path (in many cases, it's comparable to UID checking)
  • 20. Virtual Machines vs Containers Native CPU Paravirtualized devices Hypervisor Native CPU Native syscalls Native kernel
  • 21. Inter-VM communication Strong isolation, enforced by hypervisor + hardware - no fast-path data tranasfer between virtual machines - yes, there are PCI pass-throughs and things like xenbus, but that's not easy to use, very specific, not portable Most convenient method: network protocols (L2/L3) But: huge advantage from a security POV
  • 22. Inter-container communication Tunable isolation - each namespace can be isolated or shared Allows normal Unix communication mechanisms - network protocols on loopback interface - UNIX sockets - shared memory - IPC... Reuse techniques that we know and love (?)
  • 25. Shared localhost Multiple containers can share the same “localhost” (by reusing the same network namespace) Communication over localhost is very very fast Also: localhost is a well-known address
  • 26. Shared filesystem A directory can be shared by multiple containers (by using a bind-mount) That directory can contain: - named pipes (FIFOs) - UNIX sockets - memory-mapped files Bind-mount = zero overhead
  • 27. Shared IPC Multiple containers can share IPC resources (using the special IPC namespace) Semaphores, Shared Memory, Message Queues... Is anybody still using this?
  • 28. Host networking Containers can share the host's network stack (by reusing its network namespace) They can use the host's interfaces without penalty (high speed, low latency, no overhead!) Native performance to talk with external containers
  • 29. Host filesystems Containers can share a directory with the host Example: use fast storage (SAN, SSD...) in container - mount it on the host - share it with the container - done! Native performance to use I/O subsystem
  • 30. Device nodes Containers can use the host's devices (if allowed) Access is granted through “devices” control group Performance (throughput, latency, CPU usage)... is the same as using the device on the host Examples: - /dev/sd*: raw block device in container - /dev/video*: GPU in container - /dev/kvm: VM in container - and more!
  • 33. Service discovery is not a new problem Usually not important for … - small architectures - low server count - static deployments But with containers... - container count can be very high - deployments are very dynamic
  • 35. Name resolution Provide custom /etc/hosts in container (or give a custom DNS resolver to the container) Easy to integrate in code (just connect to e.g. “db”) But: - no way to push changes to the application - some libraries won't re-resolve - might need to restart containers when service address changes - service must run on well-known port
  • 36. Environment variables (or SRV records) Solves the “well-known port” requirement Harder to integrate in code Doesn't solve the other problems
  • 37. In-app discovery with config DB Connect to zookeeper/etcd to find service location Watch zookeeper/etcd for changes If change occurs, reconnect
  • 38. In-app discovery with config DB Works well, but requires deep code changes If you support multiple languages, it's a lot of work Transitioning from a system to another is hard
  • 40. container host database container I'm frontdb! web container I want to talk to frontdb! local connect
  • 41. database host web host database container I'm frontdb! web container I want to talk to frontdb! wiring container I actually talk to frontdb! wiring container I pretend I'm frontdb! local connect local connect ?
  • 42. database host web host database container I'm frontdb! web container I want to talk to frontdb! wiring container I actually talk to frontdb! wiring container I pretend I'm frontdb! local connect local connect ?
  • 44. database host web host database container I'm frontdb! web container I want to talk to frontdb! wiring container I actually talk to frontdb! wiring container I pretend I'm frontdb! local connect local connect UNICORNS
  • 45. But! We are adding extra layers! Yes. But service/ambassador communication can be: - over locahost - over UNIX socket (even better but not always possible) - over iptables or IPVS (to bypass the ambassador process)
  • 46. Ambassador implementations A few examples - Registrator https://github.com/progrium/registrator - Grand Ambassador https://github.com/cpuguy83/docker-grand-ambassador - AirBNB SmartStack https://github.com/airbnb/nerve https://github.com/airbnb/synapse Or roll your own - some HA KV store + HAProxy, stunnel, iptables, IPVS... - serverless, ad-hoc discovery (avahi, multicast...)
  • 49. Thanks to containers, we can... Build, ship, and run our applications more easily Decouple application code from “plumbing” (service discovery, load balancing) Which allows to implement micro-service archtectures efficiently (hopefully without the usual drawbacks!) Which yields higher agility, shorter dev cycles, etc. Win!