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427 lines
7.2 KiB
Markdown
427 lines
7.2 KiB
Markdown
# Orchestration, an overview
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In this chapter, we will:
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* Explain what is orchestration and why we would need it.
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* Present (from a high-level perspective) some orchestrators.
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* Show one orchestrator (Kubernetes) in action.
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---
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class: pic
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## What's orchestration?
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---
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## What's orchestration?
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According to Wikipedia:
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*Orchestration describes the __automated__ arrangement,
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coordination, and management of complex computer systems,
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middleware, and services.*
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--
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*[...] orchestration is often discussed in the context of
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__service-oriented architecture__, __virtualization__, provisioning,
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Converged Infrastructure and __dynamic datacenter__ topics.*
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--
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What does that really mean?
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---
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## Example 1: dynamic cloud instances
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--
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- Q: do we always use 100% of our servers?
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--
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- A: obviously not!
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.center[]
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---
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## Example 1: dynamic cloud instances
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- Every night, scale down
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(by shutting down extraneous replicated instances)
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- Every morning, scale up
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(by deploying new copies)
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- "Pay for what you use"
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(i.e. save big $$$ here)
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---
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## Example 1: dynamic cloud instances
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How do we implement this?
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- Crontab
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- Autoscaling (save even bigger $$$)
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That's *relatively* easy.
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Now, how are things for our IAAS provider?
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---
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## Example 2: dynamic datacenter
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- Q: what's the #1 cost in a datacenter?
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--
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- A: electricity!
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--
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- Q: what uses electricity?
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--
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- A: servers, obviously
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- A: ... and associated cooling
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--
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- Q: do we always use 100% of our servers?
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--
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- A: obviously not!
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---
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## Example 2: dynamic datacenter
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- If only we could turn off unused servers during the night...
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- Problem: we can only turn off a server if it's totally empty!
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(i.e. all VMs on it are stopped/moved)
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- Solution: *migrate* VMs and shutdown empty servers
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(e.g. combine two hypervisors with 40% load into 80%+0%,
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<br/>and shutdown the one at 0%)
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---
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## Example 2: dynamic datacenter
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How do we implement this?
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- Shutdown empty hosts (but keep some spare capacity)
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- Start hosts again when capacity gets low
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- Ability to "live migrate" VMs
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(Xen already did this 10+ years ago)
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- Rebalance VMs on a regular basis
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- what if a VM is stopped while we move it?
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- should we allow provisioning on hosts involved in a migration?
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*Scheduling* becomes more complex.
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---
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## What is scheduling?
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According to Wikipedia (again):
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*In computing, scheduling is the method by which threads,
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processes or data flows are given access to system resources.*
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The scheduler is concerned mainly with:
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- throughput (total amount or work done per time unit);
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- turnaround time (between submission and completion);
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- response time (between submission and start);
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- waiting time (between job readiness and execution);
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- fairness (appropriate times according to priorities).
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In practice, these goals often conflict.
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**"Scheduling" = decide which resources to use.**
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---
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## Exercise 1
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- You have:
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- 5 hypervisors (physical machines)
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- Each server has:
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- 16 GB RAM, 8 cores, 1 TB disk
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- Each week, your team asks:
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- one VM with X RAM, Y CPU, Z disk
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Scheduling = deciding which hypervisor to use for each VM.
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Difficulty: easy!
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---
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<!-- Warning, two almost identical slides (for img effect) -->
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## Exercise 2
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- You have:
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- 1000+ hypervisors (and counting!)
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- Each server has different resources:
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- 8-500 GB of RAM, 4-64 cores, 1-100 TB disk
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- Multiple times a day, a different team asks for:
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- up to 50 VMs with different characteristics
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Scheduling = deciding which hypervisor to use for each VM.
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Difficulty: ???
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---
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<!-- Warning, two almost identical slides (for img effect) -->
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## Exercise 2
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- You have:
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- 1000+ hypervisors (and counting!)
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- Each server has different resources:
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- 8-500 GB of RAM, 4-64 cores, 1-100 TB disk
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- Multiple times a day, a different team asks for:
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- up to 50 VMs with different characteristics
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Scheduling = deciding which hypervisor to use for each VM.
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---
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## Exercise 3
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- You have machines (physical and/or virtual)
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- You have containers
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- You are trying to put the containers on the machines
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- Sounds familiar?
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---
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## Scheduling with one resource
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.center[]
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Can we do better?
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---
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## Scheduling with one resource
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.center[]
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Yup!
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---
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## Scheduling with two resources
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.center[]
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---
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## Scheduling with three resources
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.center[]
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---
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## You need to be good at this
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.center[]
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---
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## But also, you must be quick!
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.center[]
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---
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## And be web scale!
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.center[]
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---
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## And think outside (?) of the box!
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.center[]
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---
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## Good luck!
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.center[]
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---
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## TL,DR
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* Scheduling with multiple resources (dimensions) is hard.
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* Don't expect to solve the problem with a Tiny Shell Script.
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* There are literally tons of research papers written on this.
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---
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## But our orchestrator also needs to manage ...
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* Network connectivity (or filtering) between containers.
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* Load balancing (external and internal).
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* Failure recovery (if a node or a whole datacenter fails).
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* Rolling out new versions of our applications.
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(Canary deployments, blue/green deployments...)
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---
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## Some orchestrators
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We are going to present briefly a few orchestrators.
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There is no "absolute best" orchestrator.
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It depends on:
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- your applications,
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- your requirements,
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- your pre-existing skills...
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---
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## Nomad
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- Open Source project by Hashicorp.
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- Arbitrary scheduler (not just for containers).
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- Great if you want to schedule mixed workloads.
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(VMs, containers, processes...)
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- Less integration with the rest of the container ecosystem.
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---
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## Mesos
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- Open Source project in the Apache Foundation.
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- Arbitrary scheduler (not just for containers).
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- Two-level scheduler.
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- Top-level scheduler acts as a resource broker.
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- Second-level schedulers (aka "frameworks") obtain resources from top-level.
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- Frameworks implement various strategies.
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(Marathon = long running processes; Chronos = run at intervals; ...)
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- Commercial offering through DC/OS my Mesosphere.
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---
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## Rancher
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- Rancher 1 offered a simple interface for Docker hosts.
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- Rancher 2 is a complete management platform for Docker and Kubernetes.
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- Technically not an orchestrator, but it's a popular option.
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## Swarm
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- Tightly integrated with the Docker Engine.
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- Extremely simple to deploy and setup, even in multi-manager (HA) mode.
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- Secure by default.
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- Strongly opinionated:
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- smaller set of features,
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- easier to operate.
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---
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## Kubernetes
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- Open Source project initiated by Google.
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- Contributions from many other actors.
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- *De facto* standard for container orchestration.
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- Many deployment options; some of them very complex.
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- Reputation: steep learning curve.
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- Reality:
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- true, if we try to understand *everything*;
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- false, if we focus on what matters.
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---
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## Kubernetes in action
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.center[] |