class: title, self-paced Docker <br/> Orchestration <br/> Workshop --- class: title, in-person .small[ Deploy and scale containers with Docker native, open source orchestration .small[.small[ **Be kind to the WiFi!** *Use the 5G network* <br/> *Don't use your hotspot* <br/> *Don't stream videos from YouTube, Netflix, etc. <br/>(if you're bored, watch local content instead)* Thank you! ] ] ] --- class: in-person ## Intros - Hello! We are AJ ([@s0ulshake](https://twitter.com/s0ulshake)) & Jérôme ([@jpetazzo](https://twitter.com/jpetazzo)) -- class: in-person - This is our collective Docker knowledge:  <!-- Reminder, when updating the agenda: when people are told to show up at 9am, they usually trickle in until 9:30am (except for paid training sessions). If you're not sure that people will be there on time, it's a good idea to have a breakfast with the attendees at e.g. 9am, and start at 9:30. --> --- class: in-person ## Agenda <!-- - Agenda: --> <!-- .small[ - 09:00-10:30 part 1 - 10:30-11:00 coffee break - 11:00-12:30 part 2 - 12:00-13:00 lunch break - 13:00-14:30 part 3 - 14:30-14:45 coffee break - 14:45-16:00 part 4 - 16:00-16:01 Q&A ] --> - The tutorial will run from 9:00am to 12:20pm - This will be fast-paced, but DON'T PANIC! - All the content is publicly available (slides, code samples, scripts) - There will be a coffee break at 10:30am <br/> (please remind me if I forget about it!) - Feel free to interrupt for questions at any time - Live feedback, questions, help on [Gitter](chat) ??? class: in-person ## Disclaimer - This will be slightly different from the posted abstract - Lots of things happened between the CFP and today - Docker 1.13 - Docker 17.03 - There is enough content here for a whole day - We will cover about a half of the whole program - And I'll give you ways to continue learning on your own, should you choose to! --- ## A brief introduction - This was initially written to support in-person, instructor-led workshops and tutorials - You can also follow along on your own, at your own pace - We included as much information as possible in these slides - We recommend having a mentor to help you ... - ... Or be comfortable spending some time reading the Docker [documentation](https://docs.docker.com/) ... - ... And looking for answers in the [Docker forums](forums.docker.com), [StackOverflow](http://stackoverflow.com/questions/tagged/docker), and other outlets --- class: self-paced ## Hands on, you shall practice - Nobody ever became a Jedi by spending their lives reading Wookiepedia - Likewise, it will take more than merely *reading* these slides to make you an expert - These slides include *tons* of exercises - They assume that you have access to a cluster of Docker nodes - If you are attending a workshop or tutorial: <br/>you will be given specific instructions to access your cluster - If you are doing this on your own: <br/>you can use [Play-With-Docker](http://www.play-with-docker.com/) and read [these instructions](https://github.com/jpetazzo/orchestration-workshop#using-play-with-docker) for extra details ??? <!-- grep '^# ' index.html | grep -v '<br' | tr '#' '-' --> --- class: in-person ## Chapter 1: getting started - Pre-requirements - VM environment - Our sample application - Running the application - Introducing SwarmKit --- class: in-person ## Chapter 2: scaling out our app on Swarm - Creating our first Swarm - Docker Machine - Running our first Swarm service - Deploying a local registry - Overlay networks - Global scheduling - Scripting image building and pushing - Integration with Compose --- class: in-person ## Chapter 3: operating the Swarm - Breaking into an overlay network - Securing overlay networks - Rolling updates - (Secrets management and encryption at rest) - [Centralized logging](#logging) - Metrics collection --- class: in-person ## Chapter 4: bonus material - Dealing with stateful services - Controlling Docker from a container - Node management - What's next? --- # Pre-requirements - Computer with internet connection and a web browser - For instructor-led workshops: an SSH client to connect to remote machines - on Linux, OS X, FreeBSD... you are probably all set - on Windows, get [putty](http://www.putty.org/), Microsoft [Win32 OpenSSH](https://github.com/PowerShell/Win32-OpenSSH/wiki/Install-Win32-OpenSSH), [Git BASH](https://git-for-windows.github.io/), or [MobaXterm](http://mobaxterm.mobatek.net/) - For self-paced learning: SSH is not necessary if you use [Play-With-Docker](http://www.play-with-docker.com/) - Some Docker knowledge (but that's OK if you're not a Docker expert!) --- class: in-person, extra-details ## Nice-to-haves - [Mosh](https://mosh.org/) instead of SSH, if your internet connection tends to lose packets <br/>(available with `(apt|yum|brew) install mosh`; then connect with `mosh user@host`) - [GitHub](https://github.com/join) account <br/>(if you want to fork the repo; also used to join Gitter) - [Gitter](https://gitter.im/) account <br/>(to join the conversation during the workshop) - [Slack](https://community.docker.com/registrations/groups/4316) account <br/>(to join the conversation after the workshop) - [Docker Hub](https://hub.docker.com) account <br/>(it's one way to distribute images on your Swarm cluster) --- class: extra-details ## Extra details - This slide should have a little magnifying glass in the top right corner (If it doesn't, it's because CSS is hard — Jérôme is only a backend person, alas) - Slides with that magnifying glass indicate slides providing extra details - Feel free to skip them if you're in a hurry! --- ## Hands-on sections - The whole workshop is hands-on - We will see Docker in action - You are invited to reproduce all the demos - All hands-on sections are clearly identified, like the gray rectangle below .exercise[ - This is the stuff you're supposed to do! - Go to [container.training](http://container.training/) to view these slides - Join the [chat room](chat) ] --- class: in-person # VM environment - To follow along, you need a cluster of five Docker Engines - If you are doing this with an instructor, see next slide - If you are doing (or re-doing) this on your own, you can: - create your own cluster (local or cloud VMs) with Docker Machine ([instructions](https://github.com/jpetazzo/orchestration-workshop/tree/master/prepare-machine)) - use [Play-With-Docker](http://play-with-docker.com) ([instructions](https://github.com/jpetazzo/orchestration-workshop#using-play-with-docker)) - create a bunch of clusters for you and your friends ([instructions](https://github.com/jpetazzo/orchestration-workshop/tree/master/prepare-vms)) --- class: pic, in-person  --- class: in-person ## You get five VMs - Each person gets 5 private VMs (not shared with anybody else) - They'll remain up until the day after the tutorial - You should have a little card with login+password+IP addresses - You can automatically SSH from one VM to another .exercise[ <!-- ```bash for N in $(seq 1 5); do ssh -o StrictHostKeyChecking=no node$N true done for N in $(seq 1 5); do (. docker-machine rm -f node$N ssh node$N "docker ps -aq | xargs -r docker rm -f" ssh node$N sudo rm -f /etc/systemd/system/docker.service ssh node$N sudo systemctl daemon-reload echo Restarting node$N. ssh node$N sudo systemctl restart docker echo Restarted node$N. ) & done wait ``` --> - Log into the first VM (`node1`) with SSH or MOSH - Check that you can SSH (without password) to `node2`: ```bash ssh node2 ``` - Type `exit` or `^D` to come back to node1 <!-- ```meta ^D ``` --> ] --- class: in-person ## If doing or re-doing the workshop on your own ... --- class: self-paced ## How to get your own Docker nodes? - Use [Play-With-Docker](http://www.play-with-docker.com/)! -- - Main differences: - you don't need to SSH to the machines <br/>(just click on the node that you want to control in the left tab bar) - Play-With-Docker automagically detects exposed ports <br/>(and displays them as little badges with port numbers, above the terminal) - You can access HTTP services by clicking on the port numbers - exposing TCP services requires something like [ngrok](https://ngrok.com/) or [supergrok](https://github.com/jpetazzo/orchestration-workshop#using-play-with-docker) <!-- - If you use VMs deployed with Docker Machine: - you won't have pre-authorized SSH keys to bounce across machines - you won't have host aliases --> --- class: self-paced ## Using Play-With-Docker - Open a new browser tab to [www.play-with-docker.com](http://www.play-with-docker.com/) - Confirm that you're not a robot - Click on "ADD NEW INSTANCE": congratulations, you have your first Docker node! - When you will need more nodes, just click on "ADD NEW INSTANCE" again - Note the countdown in the corner; when it expires, your instances are destroyed - If you give your URL to somebody else, they can access your nodes too <br/> (You can use that for pair programming, or to get help from a mentor) - Loving it? Not loving it? Tell it to the wonderful authors, [@marcosnils](https://twitter.com/marcosnils) & [@xetorthio](https://twitter.com/xetorthio)! --- ## We will (mostly) interact with node1 only - Unless instructed, **all commands must be run from the first VM, `node1`** - We will only checkout/copy the code on `node1` - When we will use the other nodes, we will do it mostly through the Docker API - We will log into other nodes only for initial setup and a few "out of band" operations <br/>(checking internal logs, debugging...) --- ## Terminals Once in a while, the instructions will say: <br/>"Open a new terminal." There are multiple ways to do this: - create a new window or tab on your machine, and SSH into the VM; - use screen or tmux on the VM and open a new window from there. You are welcome to use the method that you feel the most comfortable with. --- ## Tmux cheatsheet - Ctrl-b c → creates a new window - Ctrl-b n → go to next window - Ctrl-b p → go to previous window - Ctrl-b " → split window top/bottom - Ctrl-b % → split window left/right - Ctrl-b Alt-1 → rearrange windows in columns - Ctrl-b Alt-2 → rearrange windows in rows - Ctrl-b arrows → navigate to other windows - Ctrl-b d → detach session - tmux attach → reattach to session --- ## Brand new versions! - Engine 17.09 - Compose 1.16 - Machine 0.12 .exercise[ - Check all installed versions: ```bash docker version docker-compose -v docker-machine -v ``` ] --- ## Wait, what, 17.09 ?!? -- - Docker 1.13 = Docker 17.03 (year.month, like Ubuntu) - Every month, there is a new "edge" release (with new features) - Every quarter, there is a new "stable" release - Docker CE releases are maintained 4+ months - Docker EE releases are maintained 12+ months - For more details, check the [Docker EE announcement blog post](https://blog.docker.com/2017/03/docker-enterprise-edition/) --- class: extra-details ## Docker CE vs Docker EE - Docker EE: - $$$ - certification for select distros, clouds, and plugins - advanced management features (fine-grained access control, security scanning...) - Docker CE: - free - available through Docker Mac, Docker Windows, and major Linux distros - perfect for individuals and small organizations --- class: extra-details ## Why? - More readable for enterprise users (i.e. the very nice folks who are kind enough to pay us big $$$ for our stuff) - No impact for the community (beyond CE/EE suffix and version numbering change) - Both trains leverage the same open source components (containerd, libcontainer, SwarmKit...) - More predictible release schedule (see next slide) --- class: pic  --- ## What was added when? |||| | ---- | ----- | --- | | 2015 | 1.9 | Overlay (multi-host) networking, network/IPAM plugins | 2016 | 1.10 | Embedded dynamic DNS | 2016 | 1.11 | DNS round robin load balancing | 2016 | 1.12 | Swarm mode, routing mesh, encrypted networking, healthchecks | 2017 | 1.13 | Stacks, attachable overlays, image squash and compress | 2017 | 1.13 | Windows Server 2016 Swarm mode | 2017 | 17.03 | Secrets | 2017 | 17.04 | Update rollback, placement preferences (soft constraints) | 2017 | 17.05 | Multi-stage image builds, service logs | 2017 | 17.06 | Swarm configs, node/service events | 2017 | 17.06 | Windows Server 2016 Swarm overlay networks, secrets --- class: title All right! <br/> We're all set. <br/> Let's do this. --- name: part-1 class: title, self-paced Part 1 --- # Our sample application - Visit the GitHub repository with all the materials of this workshop: <br/>https://github.com/jpetazzo/orchestration-workshop - The application is in the [dockercoins]( https://github.com/jpetazzo/orchestration-workshop/tree/master/dockercoins) subdirectory - Let's look at the general layout of the source code: there is a Compose file [docker-compose.yml]( https://github.com/jpetazzo/orchestration-workshop/blob/master/dockercoins/docker-compose.yml) ... ... and 4 other services, each in its own directory: - `rng` = web service generating random bytes - `hasher` = web service computing hash of POSTed data - `worker` = background process using `rng` and `hasher` - `webui` = web interface to watch progress --- class: extra-details ## Compose file format version *Particularly relevant if you have used Compose before...* - Compose 1.6 introduced support for a new Compose file format (aka "v2") - Services are no longer at the top level, but under a `services` section - There has to be a `version` key at the top level, with value `"2"` (as a string, not an integer) - Containers are placed on a dedicated network, making links unnecessary - There are other minor differences, but upgrade is easy and straightforward --- ## Links, naming, and service discovery - Containers can have network aliases (resolvable through DNS) - Compose file version 2+ makes each container reachable through its service name - Compose file version 1 did require "links" sections - Our code can connect to services using their short name (instead of e.g. IP address or FQDN) - Network aliases are automatically namespaced (i.e. you can have multiple apps declaring and using a service named `database`) --- ## Example in `worker/worker.py`  --- ## What's this application? --- class: pic  (DockerCoins 2016 logo courtesy of [@XtlCnslt](https://twitter.com/xtlcnslt) and [@ndeloof](https://twitter.com/ndeloof). Thanks!) --- ## What's this application? - It is a DockerCoin miner! 💰🐳📦🚢 -- - No, you can't buy coffee with DockerCoins -- - How DockerCoins works: - `worker` asks to `rng` to generate a few random bytes - `worker` feeds these bytes into `hasher` - and repeat forever! - every second, `worker` updates `redis` to indicate how many loops were done - `webui` queries `redis`, and computes and exposes "hashing speed" in your browser --- ## Getting the application source code - We will clone the GitHub repository - The repository also contains scripts and tools that we will use through the workshop .exercise[ <!-- ```bash [ -d orchestration-workshop ] && mv orchestration-workshop orchestration-workshop.$$ ``` --> - Clone the repository on `node1`: ```bash git clone git://github.com/jpetazzo/orchestration-workshop ``` ] (You can also fork the repository on GitHub and clone your fork if you prefer that.) --- # Running the application Without further ado, let's start our application. .exercise[ - Go to the `dockercoins` directory, in the cloned repo: ```bash cd ~/orchestration-workshop/dockercoins ``` - Use Compose to build and run all containers: ```bash docker-compose up ``` ] Compose tells Docker to build all container images (pulling the corresponding base images), then starts all containers, and displays aggregated logs. --- ## Lots of logs - The application continuously generates logs - We can see the `worker` service making requests to `rng` and `hasher` - Let's put that in the background .exercise[ - Stop the application by hitting `^C` <!-- ```meta ^C ``` --> ] - `^C` stops all containers by sending them the `TERM` signal - Some containers exit immediately, others take longer <br/>(because they don't handle `SIGTERM` and end up being killed after a 10s timeout) --- ## Restarting in the background - Many flags and commands of Compose are modeled after those of `docker` .exercise[ - Start the app in the background with the `-d` option: ```bash docker-compose up -d ``` - Check that our app is running with the `ps` command: ```bash docker-compose ps ``` ] `docker-compose ps` also shows the ports exposed by the application. --- class: extra-details ## Viewing logs - The `docker-compose logs` command works like `docker logs` .exercise[ - View all logs since container creation and exit when done: ```bash docker-compose logs ``` - Stream container logs, starting at the last 10 lines for each container: ```bash docker-compose logs --tail 10 --follow ``` <!-- ```meta ^C ``` --> ] Tip: use `^S` and `^Q` to pause/resume log output. --- class: extra-details ## Upgrading from Compose 1.6 .warning[The `logs` command has changed between Compose 1.6 and 1.7!] - Up to 1.6 - `docker-compose logs` is the equivalent of `logs --follow` - `docker-compose logs` must be restarted if containers are added - Since 1.7 - `--follow` must be specified explicitly - new containers are automatically picked up by `docker-compose logs` --- ## Connecting to the web UI - The `webui` container exposes a web dashboard; let's view it .exercise[ - With a web browser, connect to `node1` on port 8000 - Remember: the `nodeX` aliases are valid only on the nodes themselves - In your browser, you need to enter the IP address of your node ] You should see a speed of approximately 4 hashes/second. More precisely: 4 hashes/second, with regular dips down to zero. <br/>This is because Jérôme is incapable of writing good frontend code. <br/>Don't ask. Seriously, don't ask. This is embarrassing. --- class: extra-details ## Why does the speed seem irregular? - The app actually has a constant, steady speed: 3.33 hashes/second <br/> (which corresponds to 1 hash every 0.3 seconds, for *reasons*) - The worker doesn't update the counter after every loop, but up to once per second - The speed is computed by the browser, checking the counter about once per second - Between two consecutive updates, the counter will increase either by 4, or by 0 - The perceived speed will therefore be 4 - 4 - 4 - 0 - 4 - 4 - etc. *We told you to not ask!!!* --- ## Scaling up the application - Our goal is to make that performance graph go up (without changing a line of code!) --- ## Scaling workers on a single node - Docker Compose supports scaling - Let's scale `worker` and see what happens! .exercise[ - Start one more `worker` container: ```bash docker-compose scale worker=2 ``` - Look at the performance graph (it should show a x2 improvement) - Look at the aggregated logs of our containers (`worker_2` should show up) - Look at the impact on CPU load with e.g. top (it should be negligible) ] --- ## Adding more workers - Great, let's add more workers and call it a day, then! .exercise[ - Start eight more `worker` containers: ```bash docker-compose scale worker=10 ``` - Look at the performance graph: does it show a x10 improvement? - Look at the aggregated logs of our containers - Look at the impact on CPU load and memory usage <!-- ```bash sleep 5 killall docker-compose ``` --> ] --- ## Clean up - Before moving on, let's remove those containers .exercise[ - Tell Compose to remove everything: ```bash docker-compose down ``` ] --- class: title Scaling out --- # SwarmKit - [SwarmKit](https://github.com/docker/swarmkit) is an open source toolkit to build multi-node systems - It is a reusable library, like libcontainer, libnetwork, vpnkit ... - It is a plumbing part of the Docker ecosystem --- ## SwarmKit features - Highly-available, distributed store based on [Raft]( https://en.wikipedia.org/wiki/Raft_%28computer_science%29) <br/>(avoids depending on an external store: easier to deploy; higher performance) - Dynamic reconfiguration of Raft without interrupting cluster operations - *Services* managed with a *declarative API* <br/>(implementing *desired state* and *reconciliation loop*) - Integration with overlay networks and load balancing - Strong emphasis on security: - automatic TLS keying and signing; automatic cert rotation - full encryption of the data plane; automatic key rotation - least privilege architecture (single-node compromise ≠ cluster compromise) - on-disk encryption with optional passphrase --- class: extra-details ## Where is the key/value store? - Many orchestration systems use a key/value store backed by a consensus algorithm <br/> (k8s→etcd→Raft, mesos→zookeeper→ZAB, etc.) - SwarmKit implements the Raft algorithm directly <br/> (Nomad is similar; thanks [@cbednarski](https://twitter.com/@cbednarski), [@diptanu](https://twitter.com/diptanu) and others for point it out!) - Analogy courtesy of [@aluzzardi](https://twitter.com/aluzzardi): *It's like B-Trees and RDBMS. They are different layers, often associated. But you don't need to bring up a full SQL server when all you need is to index some data.* - As a result, the orchestrator has direct access to the data <br/> (the main copy of the data is stored in the orchestrator's memory) - Simpler, easier to deploy and operate; also faster --- ## SwarmKit concepts (1/2) - A *cluster* will be at least one *node* (preferably more) - A *node* can be a *manager* or a *worker* - A *manager* actively takes part in the Raft consensus, and keeps the Raft log - You can talk to a *manager* using the SwarmKit API - One *manager* is elected as the *leader*; other managers merely forward requests to it - The *workers* get their instructions from the *managers* - Both *workers* and *managers* can run containers --- ## Illustration  --- ## SwarmKit concepts (2/2) - The *managers* expose the SwarmKit API - Using the API, you can indicate that you want to run a *service* - A *service* is specified by its *desired state*: which image, how many instances... - The *leader* uses different subsystems to break down services into *tasks*: <br/>orchestrator, scheduler, allocator, dispatcher - A *task* corresponds to a specific container, assigned to a specific *node* - *Nodes* know which *tasks* should be running, and will start or stop containers accordingly (through the Docker Engine API) You can refer to the [NOMENCLATURE](https://github.com/docker/swarmkit/blob/master/design/nomenclature.md) in the SwarmKit repo for more details. --- ## Swarm Mode - Since version 1.12, Docker Engine embeds SwarmKit - All the SwarmKit features are "asleep" until you enable "Swarm Mode" - Examples of Swarm Mode commands: - `docker swarm` (enable Swarm mode; join a Swarm; adjust cluster parameters) - `docker node` (view nodes; promote/demote managers; manage nodes) - `docker service` (create and manage services) ??? - The Docker API exposes the same concepts - The SwarmKit API is also exposed (on a separate socket) --- ## You need to enable Swarm mode to use the new stuff - By default, all this new code is inactive - Swarm Mode can be enabled, "unlocking" SwarmKit functions <br/>(services, out-of-the-box overlay networks, etc.) .exercise[ - Try a Swarm-specific command: ```bash docker node ls ``` ] -- You will get an error message: ``` Error response from daemon: This node is not a swarm manager. [...] ``` --- # Creating our first Swarm - The cluster is initialized with `docker swarm init` - This should be executed on a first, seed node - .warning[DO NOT execute `docker swarm init` on multiple nodes!] You would have multiple disjoint clusters. .exercise[ - Create our cluster from node1: ```bash docker swarm init ``` ] -- class: advertise-addr If Docker tells you that it `could not choose an IP address to advertise`, see next slide! --- class: advertise-addr ## IP address to advertise - When running in Swarm mode, each node *advertises* its address to the others <br/> (i.e. it tells them *"you can contact me on 10.1.2.3:2377"*) - If the node has only one IP address (other than 127.0.0.1), it is used automatically - If the node has multiple IP addresses, you **must** specify which one to use <br/> (Docker refuses to pick one randomly) - You can specify an IP address or an interface name <br/>(in the latter case, Docker will read the IP address of the interface and use it) - You can also specify a port number <br/>(otherwise, the default port 2377 will be used) --- class: advertise-addr ## Which IP address should be advertised? - If your nodes have only one IP address, it's safe to let autodetection do the job .small[(Except if your instances have different private and public addresses, e.g. on EC2, and you are building a Swarm involving nodes inside and outside the private network: then you should advertise the public address.)] - If your nodes have multiple IP addresses, pick an address which is reachable *by every other node* of the Swarm - If you are using [play-with-docker](http://play-with-docker.com/), use the IP address shown next to the node name .small[(This is the address of your node on your private internal overlay network. The other address that you might see is the address of your node on the `docker_gwbridge` network, which is used for outbound traffic.)] Examples: ```bash docker swarm init --advertise-addr 10.0.9.2 docker swarm init --advertise-addr eth0:7777 ``` --- ## Token generation - In the output of `docker swarm init`, we have a message confirming that our node is now the (single) manager: ``` Swarm initialized: current node (8jud...) is now a manager. ``` - Docker generated two security tokens (like passphrases or passwords) for our cluster - The CLI shows us the command to use on other nodes to add them to the cluster using the "worker" security token: ``` To add a worker to this swarm, run the following command: docker swarm join \ --token SWMTKN-1-59fl4ak4nqjmao1ofttrc4eprhrola2l87... \ 172.31.4.182:2377 ``` --- class: extra-details ## Checking that Swarm mode is enabled .exercise[ - Run the traditional `docker info` command: ```bash docker info ``` ] The output should include: ``` Swarm: active NodeID: 8jud7o8dax3zxbags3f8yox4b Is Manager: true ClusterID: 2vcw2oa9rjps3a24m91xhvv0c ... ``` --- ## Running our first Swarm mode command - Let's retry the exact same command as earlier .exercise[ - List the nodes (well, the only node) of our cluster: ```bash docker node ls ``` ] The output should look like the following: ``` ID HOSTNAME STATUS AVAILABILITY MANAGER STATUS 8jud...ox4b * node1 Ready Active Leader ``` --- ## Adding nodes to the Swarm - A cluster with one node is not a lot of fun - Let's add `node2`! - We need the token that was shown earlier -- - You wrote it down, right? -- - Don't panic, we can easily see it again 😏 --- ## Adding nodes to the Swarm .exercise[ - Show the token again: ```bash docker swarm join-token worker ``` - Switch to `node2` - Copy-paste the `docker swarm join ...` command <br/>(that was displayed just before) ] --- class: extra-details ## Check that the node was added correctly - Stay on `node2` for now! .exercise[ - We can still use `docker info` to verify that the node is part of the Swarm: ```bash docker info | grep ^Swarm ``` ] - However, Swarm commands will not work; try, for instance: ``` docker node ls ``` - This is because the node that we added is currently a *worker* - Only *managers* can accept Swarm-specific commands --- ## View our two-node cluster - Let's go back to `node1` and see what our cluster looks like .exercise[ - Switch back to `node1` - View the cluster from `node1`, which is a manager: ```bash docker node ls ``` ] The output should be similar to the following: ``` ID HOSTNAME STATUS AVAILABILITY MANAGER STATUS 8jud...ox4b * node1 Ready Active Leader ehb0...4fvx node2 Ready Active ``` --- ## Adding more manager nodes - Right now, we have only one manager (node1) - If we lose it, we lose quorum - and that's *very bad!* - Containers running on other nodes will be fine ... - But we won't be able to get or set anything related to the cluster - If the manager is permanently gone, we will have to do a manual repair! - Nobody wants to do that ... so let's make our cluster highly available --- class: self-paced ## Adding more managers With Play-With-Docker: ```bash TOKEN=$(docker swarm join-token -q manager) for N in $(seq 4 5); do export DOCKER_HOST=tcp://node$N:2375 docker swarm join --token $TOKEN node1:2377 done unset DOCKER_HOST ``` --- class: in-person ## Building our full cluster - We could SSH to nodes 3, 4, 5; and copy-paste the command -- class: in-person - Or we could use the AWESOME POWER OF THE SHELL! -- class: in-person  -- class: in-person - No, not *that* shell --- class: in-person ## Let's form like Swarm-tron - Let's get the token, and loop over the remaining nodes with SSH .exercise[ - Obtain the manager token: ```bash TOKEN=$(docker swarm join-token -q manager) ``` - Loop over the 3 remaining nodes: ```bash for NODE in node3 node4 node5; do ssh $NODE docker swarm join --token $TOKEN node1:2377 done ``` ] [That was easy.](https://www.youtube.com/watch?v=3YmMNpbFjp0) --- ## You can control the Swarm from any manager node .exercise[ - Try the following command on a few different nodes: ```bash docker node ls ``` ] On manager nodes: <br/>you will see the list of nodes, with a `*` denoting the node you're talking to. On non-manager nodes: <br/>you will get an error message telling you that the node is not a manager. As we saw earlier, you can only control the Swarm through a manager node. --- class: self-paced ## Play-With-Docker node status icon - If you're using Play-With-Docker, you get node status icons - Node status icons are displayed left of the node name - No icon = no Swarm mode detected - Solid blue icon = Swarm manager detected - Blue outline icon = Swarm worker detected  --- ## Dynamically changing the role of a node - We can change the role of a node on the fly: `docker node promote XXX` → make XXX a manager <br/> `docker node demote XXX` → make XXX a worker .exercise[ - See the current list of nodes: ``` docker node ls ``` - Promote any worker node to be a manager: ``` docker node promote <node_name_or_id> ``` ] --- ## How many managers do we need? - 2N+1 nodes can (and will) tolerate N failures <br/>(you can have an even number of managers, but there is no point) -- - 1 manager = no failure - 3 managers = 1 failure - 5 managers = 2 failures (or 1 failure during 1 maintenance) - 7 managers and more = now you might be overdoing it a little bit --- ## Why not have *all* nodes be managers? - Intuitively, it's harder to reach consensus in larger groups - With Raft, writes have to go to (and be acknowledged by) all nodes - More nodes = more network traffic - Bigger network = more latency --- ## What would McGyver do? - If some of your machines are more than 10ms away from each other, <br/> try to break them down in multiple clusters (keeping internal latency low) - Groups of up to 9 nodes: all of them are managers - Groups of 10 nodes and up: pick 5 "stable" nodes to be managers <br/> (Cloud pro-tip: use separate auto-scaling groups for managers and workers) - Groups of more than 100 nodes: watch your managers' CPU and RAM - Groups of more than 1000 nodes: - if you can afford to have fast, stable managers, add more of them - otherwise, break down your nodes in multiple clusters --- ## What's the upper limit? - We don't know! - Internal testing at Docker Inc.: 1000-10000 nodes is fine - deployed to a single cloud region - one of the main take-aways was *"you're gonna need a bigger manager"* - Testing by the community: [4700 heterogenous nodes all over the 'net](https://sematext.com/blog/2016/11/14/docker-swarm-lessons-from-swarm3k/) - it just works - more nodes require more CPU; more containers require more RAM - scheduling of large jobs (70000 containers) is slow, though (working on it!) --- ## Real-life deployment methods -- Running commands manually over SSH -- (lol jk) -- - Using your favorite configuration management tool - [Docker for AWS](https://docs.docker.com/docker-for-aws/#quickstart) - [Docker for Azure](https://docs.docker.com/docker-for-azure/) --- # Running our first Swarm service - How do we run services? Simplified version: `docker run` → `docker service create` .exercise[ - Create a service featuring an Alpine container pinging Google resolvers: ```bash docker service create alpine ping 8.8.8.8 ``` - Check the result: ```bash docker service ps <serviceID> ``` ] --- ## `--detach` for service creation (New in Docker Engine 17.05) If you are running Docker 17.05 or later, you will see the following message: ``` Since --detach=false was not specified, tasks will be created in the background. In a future release, --detach=false will become the default. ``` Let's ignore it for now; but we'll come back to it in just a few minutes! --- ## Checking service logs (New in Docker Engine 17.05) - Just like `docker logs` shows the output of a specific local container ... - ... `docker service logs` shows the output of all the containers of a specific service .exercise[ - Check the output of our ping command: ```bash docker service logs <serviceID> ``` ] Flags `--follow` and `--tail` are available, as well as a few others. Note: by default, when a container is destroyed (e.g. when scaling down), its logs are lost. --- class: extra-details ## Before Docker Engine 17.05 - Docker 1.13/17.03/17.04 have `docker service logs` as an experimental feature <br/>(available only when enabling the experimental feature flag) - We have to use `docker logs`, which only works on local containers - We will have to connect to the node running our container <br/>(unless it was scheduled locally, of course) --- class: extra-details ## Looking up where our container is running - The `docker service ps` command told us where our container was scheduled .exercise[ - Look up the `NODE` on which the container is running: ```bash docker service ps <serviceID> ``` - If you use Play-With-Docker, switch to that node's tab, or set `DOCKER_HOST` - Otherwise, `ssh` into tht node or use `$(eval docker-machine env node...)` ] --- class: extra-details ## Viewing the logs of the container .exercise[ - See that the container is running and check its ID: ```bash docker ps ``` - View its logs: ```bash docker logs <containerID> ``` - Go back to `node1` afterwards ] --- ## Scale our service - Services can be scaled in a pinch with the `docker service update` command .exercise[ - Scale the service to ensure 2 copies per node: ```bash docker service update <serviceID> --replicas 10 ``` - Check that we have two containers on the current node: ```bash docker ps ``` ] --- ## View deployment progress (New in Docker Engine 17.05) - Commands that create/update/delete services can run with `--detach=false` - The CLI will show the status of the command, and exit once it's done working .exercise[ - Scale the service to ensure 3 copies per node: ```bash docker service update <serviceID> --replicas 15 --detach=false ``` ] Note: `--detach=false` will eventually become the default. With older versions, you can use e.g.: `watch docker service ps <serviceID>` --- ## Expose a service - Services can be exposed, with two special properties: - the public port is available on *every node of the Swarm*, - requests coming on the public port are load balanced across all instances. - This is achieved with option `-p/--publish`; as an approximation: `docker run -p → docker service create -p` - If you indicate a single port number, it will be mapped on a port starting at 30000 <br/>(vs. 32768 for single container mapping) - You can indicate two port numbers to set the public port number <br/>(just like with `docker run -p`) --- ## Expose ElasticSearch on its default port .exercise[ - Create an ElasticSearch service (and give it a name while we're at it): ```bash docker service create --name search --publish 9200:9200 --replicas 7 \ --detach=false elasticsearch`:2` ``` ] Note: don't forget the **:2**! The latest version of the ElasticSearch image won't start without mandatory configuration. --- ## Tasks lifecycle - During the deployment, you will be able to see multiple states: - assigned (the task has been assigned to a specific node) - preparing (this mostly means "pulling the image") - starting - running - When a task is terminated (stopped, killed...) it cannot be restarted (A replacement task will be created) --- class: extra-details  --- ## Test our service - We mapped port 9200 on the nodes, to port 9200 in the containers - Let's try to reach that port! .exercise[ - Try the following command: ```bash curl localhost:9200 ``` ] (If you get `Connection refused`: congratulations, you are very fast indeed! Just try again.) ElasticSearch serves a little JSON document with some basic information about this instance; including a randomly-generated super-hero name. --- ## Test the load balancing - If we repeat our `curl` command multiple times, we will see different names .exercise[ - Send 10 requests, and see which instances serve them: ```bash for N in $(seq 1 10); do curl -s localhost:9200 | jq .name done ``` ] Note: if you don't have `jq` on your Play-With-Docker instance, just install it: ```bash apk add --no-cache jq ``` --- ## Load balancing results Traffic is handled by our clusters [TCP routing mesh]( https://docs.docker.com/engine/swarm/ingress/). Each request is served by one of the 7 instances, in rotation. Note: if you try to access the service from your browser, you will probably see the same instance name over and over, because your browser (unlike curl) will try to re-use the same connection. --- ## Under the hood of the TCP routing mesh - Load balancing is done by IPVS - IPVS is a high-performance, in-kernel load balancer - It's been around for a long time (merged in the kernel since 2.4) - Each node runs a local load balancer (Allowing connections to be routed directly to the destination, without extra hops) --- ## Managing inbound traffic There are many ways to deal with inbound traffic on a Swarm cluster. - Put all (or a subset) of your nodes in a DNS `A` record - Assign your nodes (or a subset) to an ELB - Use a virtual IP and make sure that it is assigned to an "alive" node - etc. --- class: btw-labels ## Managing HTTP traffic - The TCP routing mesh doesn't parse HTTP headers - If you want to place multiple HTTP services on port 80, you need something more - You can setup NGINX or HAProxy on port 80 to do the virtual host switching - Docker Universal Control Plane provides its own [HTTP routing mesh]( https://docs.docker.com/datacenter/ucp/2.1/guides/admin/configure/use-domain-names-to-access-services/) - add a specific label starting with `com.docker.ucp.mesh.http` to your services - labels are detected automatically and dynamically update the configuration --- class: btw-labels ## You should use labels - Labels are a great way to attach arbitrary information to services - Examples: - HTTP vhost of a web app or web service - backup schedule for a stateful service - owner of a service (for billing, paging...) - etc. --- ## Pro-tip for ingress traffic management - It is possible to use *local* networks with Swarm services - This means that you can do something like this: ```bash docker service create --network host --mode global traefik ... ``` (This runs the `traefik` load balancer on each node of your cluster, in the `host` network) - This gives you native performance (no iptables, no proxy, no nothing!) - The load balancer will "see" the clients' IP addresses - But: a container cannot simultaneously be in the `host` network and another network (You will have to route traffic to containers using exposed ports or UNIX sockets) --- ## Visualize container placement - Let's leverage the Docker API! .exercise[ - Get the source code of this simple-yet-beautiful visualization app: ```bash cd ~ git clone git://github.com/dockersamples/docker-swarm-visualizer ``` - Build and run the Swarm visualizer: ```bash cd docker-swarm-visualizer docker-compose up -d ``` ] --- ## Connect to the visualization webapp - It runs a web server on port 8080 .exercise[ - Point your browser to port 8080 of your node1's public ip (If you use Play-With-Docker, click on the (8080) badge) ] - The webapp updates the display automatically (you don't need to reload the page) - It only shows Swarm services (not standalone containers) - It shows when nodes go down - It has some glitches (it's not Carrier-Grade Enterprise-Compliant ISO-9001 software) --- ## Why This Is More Important Than You Think - The visualizer accesses the Docker API *from within a container* - This is a common pattern: run container management tools *in containers* - Instead of viewing your cluster, this could take care of logging, metrics, autoscaling ... - We can run it within a service, too! We won't do it, but the command would look like: ```bash docker service create \ --mount source=/var/run/docker.sock,type=bind,target=/var/run/docker.sock \ --name viz --constraint node.role==manager ... ``` Credits: the visualization code was written by [Francisco Miranda](https://github.com/maroshii). <br/> [Mano Marks](https://twitter.com/manomarks) adapted it to Swarm and maintains it. --- ## Terminate our services - Before moving on, we will remove those services - `docker service rm` can accept multiple services names or IDs - `docker service ls` can accept the `-q` flag - A Shell snippet a day keeps the cruft away .exercise[ - Remove all services with this one liner: ```bash docker service ls -q | xargs docker service rm ``` ] --- class: title Our app on Swarm --- ## What's on the menu? In this part, we will: - **build** images for our app, - **ship** these images with a registry, - **run** services using these images. --- ## Why do we need to ship our images? - When we do `docker-compose up`, images are built for our services - These images are present only on the local node - We need these images to be distributed on the whole Swarm - The easiest way to achieve that is to use a Docker registry - Once our images are on a registry, we can reference them when creating our services --- class: extra-details ## Build, ship, and run, for a single service If we had only one service (built from a `Dockerfile` in the current directory), our workflow could look like this: ``` docker build -t jpetazzo/doublerainbow:v0.1 . docker push jpetazzo/doublerainbow:v0.1 docker service create jpetazzo/doublerainbow:v0.1 ``` We just have to adapt this to our application, which has 4 services! --- ## The plan - Build on our local node (`node1`) - Tag images so that they are named `localhost:5000/servicename` - Upload them to a registry - Create services using the images --- ## Which registry do we want to use? .small[ - **Docker Hub** - hosted by Docker Inc. - requires an account (free, no credit card needed) - images will be public (unless you pay) - located in AWS EC2 us-east-1 - **Docker Trusted Registry** - self-hosted commercial product - requires a subscription (free 30-day trial available) - images can be public or private - located wherever you want - **Docker open source registry** - self-hosted barebones repository hosting - doesn't require anything - doesn't come with anything either - located wherever you want ] --- class: extra-details ## Using Docker Hub *If we wanted to use the Docker Hub...* <!-- ```meta ^{ ``` --> - We would log into the Docker Hub: ```bash docker login ``` - And in the following slides, we would use our Docker Hub login (e.g. `jpetazzo`) instead of the registry address (i.e. `127.0.0.1:5000`) <!-- ```meta ^} ``` --> --- ## Using the open source registry - We need to run a `registry:2` container <br/>(make sure you specify tag `:2` to run the new version!) - It will store images and layers to the local filesystem <br/>(but you can add a config file to use S3, Swift, etc.) - Docker *requires* TLS when communicating with the registry - unless for registries on `127.0.0.0/8` (i.e. `localhost`) - or with the Engine flag `--insecure-registry` <!-- --> - Our strategy: publish the registry container on port 5000, <br/>so that it's available through `127.0.0.1:5000` on each node --- class: manual-btp # Deploying a local registry - We will create a single-instance service, publishing its port on the whole cluster .exercise[ - Create the registry service: ```bash docker service create --name registry --publish 5000:5000 registry:2 ``` - Try the following command, until it returns `{"repositories":[]}`: ```bash curl 127.0.0.1:5000/v2/_catalog ``` ] (Retry a few times, it might take 10-20 seconds for the container to be started. Patience.) --- class: manual-btp ## Testing our local registry - We can retag a small image, and push it to the registry .exercise[ - Make sure we have the busybox image, and retag it: ```bash docker pull busybox docker tag busybox 127.0.0.1:5000/busybox ``` - Push it: ```bash docker push 127.0.0.1:5000/busybox ``` ] --- class: manual-btp ## Checking what's on our local registry - The registry API has endpoints to query what's there .exercise[ - Ensure that our busybox image is now in the local registry: ```bash curl http://127.0.0.1:5000/v2/_catalog ``` ] The curl command should now output: ```json {"repositories":["busybox"]} ``` --- class: manual-btp ## Build, tag, and push our application container images - Compose has named our images `dockercoins_XXX` for each service - We need to retag them (to `127.0.0.1:5000/XXX:v1`) and push them .exercise[ - Set `REGISTRY` and `TAG` environment variables to use our local registry - And run this little for loop: ```bash cd ~/orchestration-workshop/dockercoins REGISTRY=127.0.0.1:5000 TAG=v1 for SERVICE in hasher rng webui worker; do docker tag dockercoins_$SERVICE $REGISTRY/$SERVICE:$TAG docker push $REGISTRY/$SERVICE done ``` ] --- class: manual-btp # Overlay networks - SwarmKit integrates with overlay networks - Networks are created with `docker network create` - Make sure to specify that you want an *overlay* network <br/>(otherwise you will get a local *bridge* network by default) .exercise[ - Create an overlay network for our application: ```bash docker network create --driver overlay dockercoins ``` ] --- class: manual-btp ## Viewing existing networks - Let's confirm that our network was created .exercise[ - List existing networks: ```bash docker network ls ``` ] --- class: manual-btp ## Can you spot the differences? The networks `dockercoins` and `ingress` are different from the other ones. Can you see how? -- class: manual-btp - They are using a different kind of ID, reflecting the fact that they are SwarmKit objects instead of "classic" Docker Engine objects. - Their *scope* is `swarm` instead of `local`. - They are using the overlay driver. --- class: manual-btp, extra-details ## Caveats .warning[In Docker 1.12, you cannot join an overlay network with `docker run --net ...`.] Starting with version 1.13, you can, if the network was created with the `--attachable` flag. *Why is that?* Placing a container on a network requires allocating an IP address for this container. The allocation must be done by a manager node (worker nodes cannot update Raft data). As a result, `docker run --net ...` requires collaboration with manager nodes. It alters the code path for `docker run`, so it is allowed only under strict circumstances. --- class: manual-btp ## Run the application - First, create the `redis` service; that one is using a Docker Hub image .exercise[ - Create the `redis` service: ```bash docker service create --network dockercoins --name redis redis ``` ] --- class: manual-btp ## Run the other services - Then, start the other services one by one - We will use the images pushed previously .exercise[ - Start the other services: ```bash REGISTRY=127.0.0.1:5000 TAG=v1 for SERVICE in hasher rng webui worker; do docker service create --network dockercoins --detach=true \ --name $SERVICE $REGISTRY/$SERVICE:$TAG done ``` ] ??? ## Wait for our application to be up - We will see later a way to watch progress for all the tasks of the cluster - But for now, a scrappy Shell loop will do the trick .exercise[ - Repeatedly display the status of all our services: ```bash watch "docker service ls -q | xargs -n1 docker service ps" ``` - Stop it once everything is running ] --- class: manual-btp ## Expose our application web UI - We need to connect to the `webui` service, but it is not publishing any port - Let's reconfigure it to publish a port .exercise[ - Update `webui` so that we can connect to it from outside: ```bash docker service update webui --publish-add 8000:80 --detach=false ``` ] Note: to "de-publish" a port, you would have to specify the container port. </br>(i.e. in that case, `--publish-rm 80`) --- class: manual-btp ## What happens when we modify a service? - Let's find out what happened to our `webui` service .exercise[ - Look at the tasks and containers associated to `webui`: ```bash docker service ps webui ``` ] -- class: manual-btp The first version of the service (the one that was not exposed) has been shutdown. It has been replaced by the new version, with port 80 accessible from outside. (This will be discussed with more details in the section about stateful services.) --- class: manual-btp ## Connect to the web UI - The web UI is now available on port 8000, *on all the nodes of the cluster* .exercise[ - If you're using Play-With-Docker, just click on the `(8000)` badge - Otherwise, point your browser to any node, on port 8000 ] --- ## Scaling the application - We can change scaling parameters with `docker update` as well - We will do the equivalent of `docker-compose scale` .exercise[ - Bring up more workers: ```bash docker service update worker --replicas 10 --detach=false ``` - Check the result in the web UI ] You should see the performance peaking at 10 hashes/s (like before). --- class: manual-btp # Global scheduling - We want to utilize as best as we can the entropy generators on our nodes - We want to run exactly one `rng` instance per node - SwarmKit has a special scheduling mode for that, let's use it - We cannot enable/disable global scheduling on an existing service - We have to destroy and re-create the `rng` service --- class: manual-btp ## Scaling the `rng` service .exercise[ - Remove the existing `rng` service: ```bash docker service rm rng ``` - Re-create the `rng` service with *global scheduling*: ```bash docker service create --name rng --network dockercoins --mode global \ --detach=false $REGISTRY/rng:$TAG ``` - Look at the result in the web UI ] --- class: extra-details, manual-btp ## Why do we have to re-create the service to enable global scheduling? - Enabling it dynamically would make rolling updates semantics very complex - This might change in the future (after all, it was possible in 1.12 RC!) - As of Docker Engine 17.05, other parameters requiring to `rm`/`create` the service are: - service name - hostname - network --- class: swarm-ready ## How did we make our app "Swarm-ready"? This app was written in June 2015. (One year before Swarm mode was released.) What did we change to make it compatible with Swarm mode? -- .exercise[ - Go to the app directory: ```bash cd ~/orchestration-workshop/dockercoins ``` - See modifications in the code: ```bash git log -p --since "4-JUL-2015" -- . ':!*.yml*' ':!*.html' ``` ] --- class: swarm-ready ## What did we change in our app since its inception? - Compose files - HTML file (it contains an embedded contextual tweet) - Dockerfiles (to switch to smaller images) - That's it! -- class: swarm-ready *We didn't change a single line of code in this app since it was written.* -- class: swarm-ready *The images that were [built in June 2015]( https://hub.docker.com/r/jpetazzo/dockercoins_worker/tags/) (when the app was written) can still run today ... <br/>... in Swarm mode (distributed across a cluster, with load balancing) ... <br/>... without any modification.* --- class: swarm-ready ## How did we design our app in the first place? - [Twelve-Factor App](https://12factor.net/) principles - Service discovery using DNS names - Initially implemented as "links" - Then "ambassadors" - And now "services" - Existing apps might require more changes! --- class: manual-btp # Integration with Compose - The previous section showed us how to streamline image build and push - We will now see how to streamline service creation (i.e. get rid of the `for SERVICE in ...; do docker service create ...` part) --- ## Compose file version 3 (New in Docker Engine 1.13) - Almost identical to version 2 - Can be directly used by a Swarm cluster through `docker stack ...` commands - Introduces a `deploy` section to pass Swarm-specific parameters - Resource limits are moved to this `deploy` section - See [here](https://github.com/aanand/docker.github.io/blob/8524552f99e5b58452fcb1403e1c273385988b71/compose/compose-file.md#upgrading) for the complete list of changes - Supersedes *Distributed Application Bundles* (JSON payload describing an application; could be generated from a Compose file) --- class: manual-btp ## Removing everything - Before deploying using "stacks," let's get a clean slate .exercise[ - Remove *all* the services: ```bash docker service ls -q | xargs docker service rm ``` ] --- ## Our first stack We need a registry to move images around. Without a stack file, it would be deployed with the following command: ```bash docker service create --publish 5000:5000 registry:2 ``` Now, we are going to deploy it with the following stack file: ```yaml version: "3" services: registry: image: registry:2 ports: - "5000:5000" ``` --- ## Checking our stack files - All the stack files that we will use are in the `stacks` directory .exercise[ - Go to the `stacks` directory: ```bash cd ~/orchestration-workshop/stacks ``` - Check `registry.yml`: ```bash cat registry.yml ``` ] --- ## Deploying our first stack - All stack manipulation commands start with `docker stack` - Under the hood, they map to `docker service` commands - Stacks have a *name* (which also serves as a namespace) - Stacks are specified with the aforementioned Compose file format version 3 .exercise[ - Deploy our local registry: ```bash docker stack deploy registry --compose-file registry.yml ``` ] --- ## Inspecting stacks - `docker stack ps` shows the detailed state of all services of a stack .exercise[ - Check that our registry is running correctly: ```bash docker stack ps registry ``` - Confirm that we get the same output with the following command: ```bash docker service ps registry_registry ``` ] --- class: manual-btp ## Specifics of stack deployment Our registry is not *exactly* identical to the one deployed with `docker service create`! - Each stack gets its own overlay network - Services of the task are connected to this network <br/>(unless specified differently in the Compose file) - Services get network aliases matching their name in the Compose file <br/>(just like when Compose brings up an app specified in a v2 file) - Services are explicitly named `<stack_name>_<service_name>` - Services and tasks also get an internal label indicating which stack they belong to --- ## Testing our local registry - Connecting to port 5000 *on any node of the cluster* routes us to the registry - Therefore, we can use `localhost:5000` or `127.0.0.1:5000` as our registry .exercise[ - Issue the following API request to the registry: ```bash curl 127.0.0.1:5000/v2/_catalog ``` ] It should return: ```json {"repositories":[]} ``` If that doesn't work, retry a few times; perhaps the container is still starting. --- ## Pushing an image to our local registry - We can retag a small image, and push it to the registry .exercise[ - Make sure we have the busybox image, and retag it: ```bash docker pull busybox docker tag busybox 127.0.0.1:5000/busybox ``` - Push it: ```bash docker push 127.0.0.1:5000/busybox ``` ] --- ## Checking what's on our local registry - The registry API has endpoints to query what's there .exercise[ - Ensure that our busybox image is now in the local registry: ```bash curl http://127.0.0.1:5000/v2/_catalog ``` ] The curl command should now output: ```json "repositories":["busybox"]} ``` --- ## Building and pushing stack services - When using Compose file version 2 and above, you can specify *both* `build` and `image` - When both keys are present: - Compose does "business as usual" (uses `build`) - but the resulting image is named as indicated by the `image` key <br/> (instead of `<projectname>_<servicename>:latest`) - it can be pushed to a registry with `docker-compose push` - Example: ```yaml webfront: build: www image: myregistry.company.net:5000/webfront ``` --- ## Using Compose to build and push images .exercise[ - Try it: ```bash docker-compose -f dockercoins.yml build docker-compose -f dockercoins.yml push ``` ] Let's have a look at the `dockercoins.yml` file while this is building and pushing. --- ```yaml version: "3" services: rng: build: dockercoins/rng image: ${REGISTRY-127.0.0.1:5000}/rng:${TAG-latest} deploy: mode: global ... redis: image: redis ... worker: build: dockercoins/worker image: ${REGISTRY-127.0.0.1:5000}/worker:${TAG-latest} ... deploy: replicas: 10 ``` --- ## Deploying the application - Now that the images are on the registry, we can deploy our application stack .exercise[ - Create the application stack: ```bash docker stack deploy dockercoins --compose-file dockercoins.yml ``` ] We can now connect to any of our nodes on port 8000, and we will see the familiar hashing speed graph. --- ## Maintaining multiple environments There are many ways to handle variations between environments. - Compose loads `docker-compose.yml` and (if it exists) `docker-compose.override.yml` - Compose can load alternate file(s) by setting the `-f` flag or the `COMPOSE_FILE` environment variable - Compose files can *extend* other Compose files, selectively including services: ```yaml web: extends: file: common-services.yml service: webapp ``` See [this documentation page](https://docs.docker.com/compose/extends/) for more details about these techniques. --- class: extra-details ## Good to know ... - Compose file version 3 adds the `deploy` section - Compose file version 3.1 adds support for secrets - You can re-run `docker stack deploy` to update a stack - ... But unsupported features will be wiped each time you redeploy (!) (This will likely be fixed/improved soon) - `extends` doesn't work with `docker stack deploy` (But you can use `docker-compose config` to "flatten" your configuration) --- ## Summary - We've seen how to set up a Swarm - We've used it to host our own registry - We've built our app container images - We've used the registry to host those images - We've deployed and scaled our application - We've seen how to use Compose to streamline deployments - Awesome job, team! --- class: title, in-person Operating the Swarm --- name: part-2 class: title, self-paced Part 2 --- class: self-paced ## Before we start ... The following exercises assume that you have a 5-nodes Swarm cluster. If you come here from a previous tutorial and still have your cluster: great! Otherwise: check [part 1](#part-1) to learn how to setup your own cluster. We pick up exactly where we left you, so we assume that you have: - a five nodes Swarm cluster, - a self-hosted registry, - DockerCoins up and running. The next slide has a cheat sheet if you need to set that up in a pinch. --- class: self-paced ## Catching up Assuming you have 5 nodes provided by [Play-With-Docker](http://www.play-with-docker/), do this from `node1`: ```bash docker swarm init --advertise-addr eth0 TOKEN=$(docker swarm join-token -q manager) for N in $(seq 2 5); do DOCKER_HOST=tcp://node$N:2375 docker swarm join --token $TOKEN node1:2377 done git clone git://github.com/jpetazzo/orchestration-workshop cd orchestration-workshop/stacks docker stack deploy --compose-file registry.yml registry docker-compose -f dockercoins.yml build docker-compose -f dockercoins.yml push docker stack deploy --compose-file dockercoins.yml dockercoins ``` You should now be able to connect to port 8000 and see the DockerCoins web UI. --- # Updating services - We want to make changes to the web UI - The process is as follows: - edit code - build new image - ship new image - run new image --- class: extra-details ## But first... - Restart the workers .exercise[ - Just scale back to 10 replicas: ```bash docker service update dockercoins_worker --replicas 10 ``` - Check that they're running: ```bash docker service ps dockercoins_worker ``` ] --- ## Updating a single service the hard way - To update a single service, we could do the following: ```bash REGISTRY=localhost:5000 TAG=v0.2 IMAGE=$REGISTRY/dockercoins_webui:$TAG docker build -t $IMAGE webui/ docker push $IMAGE docker service update dockercoins_webui --image $IMAGE ``` - Make sure to tag properly your images: update the `TAG` at each iteration (When you check which images are running, you want these tags to be uniquely identifiable) --- ## Updating services the easy way - With the Compose inbtegration, all we have to do is: ```bash export TAG=v0.2 docker-compose -f composefile.yml build docker-compose -f composefile.yml push docker stack deploy -c composefile.yml nameofstack ``` -- - That's exactly what we used earlier to deploy the app - We don't need to learn new commands! --- ## Updating the web UI - Let's make the numbers on the Y axis bigger! .exercise[ - Edit the file `webui/files/index.html` - Locate the `font-size` CSS attribute and increase it (at least double it) - Save and exit - Build, ship, and run: ```bash export TAG=v0.2 docker-compose -f dockercoins.yml build docker-compose -f dockercoins.yml push docker stack deploy -c dockercoins.yml dockercoins ``` ] --- ## Viewing our changes - Wait at least 10 seconds (for the new version to be deployed) - Then reload the web UI - Or just mash "reload" frantically - ... Eventually the legend on the left will be bigger! --- ## Making changes .exercise[ - Edit `~/orchestration-workshop/dockercoins/worker/worker.py` - Locate the line that has a `sleep` instruction - Increase the `sleep` from `0.1` to `1.0` - Save your changes and exit ] --- ## Rolling updates - Let's change a scaled service: `worker` .exercise[ - Edit `worker/worker.py` - Locate the `sleep` instruction and change the delay - Build, ship, and run our changes: ```bash export TAG=v0.3 docker-compose -f dockercoins.yml build docker-compose -f dockercoins.yml push docker stack deploy -c dockercoins.yml dockercoins ``` ] --- ## Viewing our update as it rolls out .exercise[ - Check the status of the `dockercoins_worker` service: ```bash watch docker service ps dockercoins_worker ``` - Hide the tasks that are shutdown: ```bash watch -n1 "docker service ps dockercoins_worker | grep -v Shutdown.*Shutdown" ``` ] If you had stopped the workers earlier, this will automatically restart them. By default, SwarmKit does a rolling upgrade, one instance at a time. We should therefore see the workers being updated one my one. --- ## Changing the upgrade policy - We can set upgrade parallelism (how many instances to update at the same time) - And upgrade delay (how long to wait between two batches of instances) .exercise[ - Change the parallelism to 2 and the delay to 5 seconds: ```bash docker service update dockercoins_worker \ --update-parallelism 2 --update-delay 5s ``` ] The current upgrade will continue at a faster pace. --- ## Changing the policy in the Compose file - The policy can also be updated in the Compose file - This is done by adding an `update_config` key under the `deploy` key: ```yaml deploy: replicas: 10 update_config: parallelism: 2 delay: 10s ``` --- ## Rolling back - At any time (e.g. before the upgrade is complete), we can rollback: - by editing the Compose file and redeploying; - or with the special `--rollback` flag .exercise[ - Try to rollback the service: ```bash docker service update dockercoins_worker --rollback ``` ] What happens with the web UI graph? --- ## The fine print with rollback - Rollback reverts to the previous service definition - If we visualize successive updates as a stack: - it doesn't "pop" the latest update - it "pushes" a copy of the previous update on top - ergo, rolling back twice does nothing - "Service definition" includes rollout cadence - Each `docker service update` command = a new service definition --- class: extra-details ## Timeline of an upgrade - SwarmKit will upgrade N instances at a time <br/>(following the `update-parallelism` parameter) - New tasks are created, and their desired state is set to `Ready` <br/>.small[(this pulls the image if necessary, ensures resource availability, creates the container ... without starting it)] - If the new tasks fail to get to `Ready` state, go back to the previous step <br/>.small[(SwarmKit will try again and again, until the situation is addressed or desired state is updated)] - When the new tasks are `Ready`, it sets the old tasks desired state to `Shutdown` - When the old tasks are `Shutdown`, it starts the new tasks - Then it waits for the `update-delay`, and continues with the next batch of instances --- name: healthchecks class: healthchecks # Health checks (New in Docker Engine 1.12) - Commands that are executed on regular intervals in a container - Must return 0 or 1 to indicate "all is good" or "something's wrong" - Must execute quickly (timeouts = failures) - Example: ```bash curl -f http://localhost/_ping || false ``` - the `-f` flag ensures that `curl` returns non-zero for 404 and similar errors - `|| false` ensures that any non-zero exit status gets mapped to 1 - `curl` must be installed in the container that is being checked --- class: healthchecks ## Defining health checks - In a Dockerfile, with the [HEALTHCHECK](https://docs.docker.com/engine/reference/builder/#healthcheck) instruction ``` HEALTHCHECK --interval=1s --timeout=3s CMD curl -f http://localhost/ || false ``` - From the command line, when running containers or services ``` docker run --health-cmd "curl -f http://localhost/ || false" ... docker service create --health-cmd "curl -f http://localhost/ || false" ... ``` - In Compose files, with a per-service [healthcheck](https://docs.docker.com/compose/compose-file/#healthcheck) section ```yaml www: image: hellowebapp healthcheck: test: "curl -f https://localhost/ || false" timeout: 3s ``` --- class: healthcheck ## Using health checks - With `docker run`, health checks are purely informative - `docker ps` shows health status - `docker inspect` has extra details (including health check command output) - With `docker service`: - unhealthy tasks are terminated (i.e. the service is restarted) - failed deployments can be rolled back automatically <br/>(by setting *at least* the flag `--update-failure action rollback`) --- class: healthcheck ## Automated rollbacks Here is a comprehensive example using the CLI: ```bash docker service update \ --update-delay 5s \ --update-failure-action rollback \ --update-max-failure-ratio .25 \ --update-monitor 5s \ --update-parallelism 1 \ --rollback-delay 5s \ --rollback-failure-action pause \ --rollback-max-failure-ratio .5 \ --rollback-monitor 5s \ --rollback-parallelism 0 \ --health-cmd "curl -f http://localhost/ || exit 1" \ --health-interval 2s \ --health-retries 1 \ --image yourimage:newversion \ yourservice ``` --- class: healthcheck ## Implementing auto-rollback in practice We will use the following Compose file (`stacks/dockercoins+healthchecks.yml`): ```yaml ... hasher: build: dockercoins/hasher image: ${REGISTRY-127.0.0.1:5000}/hasher:${TAG-latest} deploy: replicas: 7 update_config: delay: 5s failure_action: rollback max_failure_ratio: .5 monitor: 5s parallelism: 1 ... ``` --- class: healthcheck ## Enabling auto-rollback .exercise[ - Go to the `stacks` directory: ```bash cd ~/orchestration-workshop/ ``` - Deploy the updated stack: ```bash docker deploy dockercoins --compose-file dockercoins+healthchecks.yml ``` ] This will also scale the `hasher` service to 7 instances. --- class: healthcheck ## Visualizing a rolling update First, let's make an "innocent" change and deploy it. .exercise[ - Update the `sleep` delay in the code: ```bash sed -i "s/sleep 0.1/sleep 0.2/" dockercoins/hasher/hasher.rb ``` - Build, ship, and run the new image: ```bash docker-compose -f dockercoins+healthchecks.yml build docker-compose -f dockercoins+healthchecks.yml push docker service update dockercoins_hasher \ --detach=false --image=127.0.0.1:5000/hasher:latest ``` ] --- class: healthcheck ## Visualizing an automated rollback And now, a breaking change that will cause the health check to fail: .exercise[ - Change the HTTP listening port: ```bash sed -i "s/80/81/" dockercoins/hasher/hasher.rb ``` - Build, ship, and run the new image: ```bash docker-compose -f dockercoins+healthchecks.yml build docker-compose -f dockercoins+healthchecks.yml push docker service update dockercoins_hasher \ --detach=false --image=127.0.0.1:5000/hasher:latest ``` ] --- class: healthcheck ## Command-line options available for health checks, rollbacks, etc. Batteries included, but swappable .small[ ``` --health-cmd string Command to run to check health --health-interval duration Time between running the check (ms|s|m|h) --health-retries int Consecutive failures needed to report unhealthy --health-start-period duration Start period for the container to initialize before counting retries towards unstable (ms|s|m|h) --health-timeout duration Maximum time to allow one check to run (ms|s|m|h) --no-healthcheck Disable any container-specified HEALTHCHECK --restart-condition string Restart when condition is met ("none"|"on-failure"|"any") --restart-delay duration Delay between restart attempts (ns|us|ms|s|m|h) --restart-max-attempts uint Maximum number of restarts before giving up --restart-window duration Window used to evaluate the restart policy (ns|us|ms|s|m|h) --rollback Rollback to previous specification --rollback-delay duration Delay between task rollbacks (ns|us|ms|s|m|h) --rollback-failure-action string Action on rollback failure ("pause"|"continue") --rollback-max-failure-ratio float Failure rate to tolerate during a rollback --rollback-monitor duration Duration after each task rollback to monitor for failure (ns|us|ms|s|m|h) --rollback-order string Rollback order ("start-first"|"stop-first") --rollback-parallelism uint Maximum number of tasks rolled back simultaneously (0 to roll back all at once) --update-delay duration Delay between updates (ns|us|ms|s|m|h) --update-failure-action string Action on update failure ("pause"|"continue"|"rollback") --update-max-failure-ratio float Failure rate to tolerate during an update --update-monitor duration Duration after each task update to monitor for failure (ns|us|ms|s|m|h) --update-order string Update order ("start-first"|"stop-first") --update-parallelism uint Maximum number of tasks updated simultaneously (0 to update all at once) ``` ] Yup ... That's a lot of batteries! --- class: node-info ## Getting task information for a given node - You can see all the tasks assigned to a node with `docker node ps` - It shows the *desired state* and *current state* of each task - `docker node ps` shows info about the current node - `docker node ps <node_name_or_id>` shows info for another node - `docker node ps -a` includes stopped and failed tasks --- # Secrets management and encryption at rest (New in Docker Engine 1.13) - Secrets management = selectively and securely bring secrets to services - Encryption at rest = protect against storage theft or prying - Remember: - control plane is authenticated through mutual TLS, certs rotated every 90 days - control plane is encrypted with AES-GCM, keys rotated every 12 hours - data plane is not encrypted by default (for performance reasons), <br/>but we saw earlier how to enable that with a single flag --- class: secrets ## Secret management - Docker has a "secret safe" (secure key→value store) - You can create as many secrets as you like - You can associate secrets to services - Secrets are exposed as plain text files, but kept in memory only (using `tmpfs`) - Secrets are immutable (at least in Engine 1.13) - Secrets have a max size of 500 KB --- class: secrets ## Creating secrets - Must specify a name for the secret; and the secret itself .exercise[ - Assign [one of the four most commonly used passwords](https://www.youtube.com/watch?v=0Jx8Eay5fWQ) to a secret called `hackme`: ```bash echo love | docker secret create hackme - ``` ] If the secret is in a file, you can simply pass the path to the file. (The special path `-` indicates to read from the standard input.) --- class: secrets ## Creating better secrets - Picking lousy passwords always leads to security breaches .exercise[ - Let's craft a better password, and assign it to another secret: ```bash base64 /dev/urandom | head -c16 | docker secret create arewesecureyet - ``` ] Note: in the latter case, we don't even know the secret at this point. But Swarm does. --- class: secrets ## Using secrets - Secrets must be handed explicitly to services .exercise[ - Create a dummy service with both secrets: ```bash docker service create \ --secret hackme --secret arewesecureyet \ --name dummyservice --mode global \ alpine sleep 1000000000 ``` ] We use a global service to make sure that there will be an instance on the local node. --- class: secrets ## Accessing secrets - Secrets are materialized on `/run/secrets` (which is an in-memory filesystem) .exercise[ - Find the ID of the container for the dummy service: ```bash CID=$(docker ps -q --filter label=com.docker.swarm.service.name=dummyservice) ``` - Enter the container: ```bash docker exec -ti $CID sh ``` - Check the files in `/run/secrets` ] --- class: secrets ## Rotating secrets - You can't change a secret (Sounds annoying at first; but allows clean rollbacks if a secret update goes wrong) - You can add a secret to a service with `docker service update --secret-add` (This will redeploy the service; it won't add the secret on the fly) - You can remove a secret with `docker service update --secret-rm` - Secrets can be mapped to different names by expressing them with a micro-format: ```bash docker service create --secret source=secretname,target=filename ``` --- class: secrets ## Changing our insecure password - We want to replace our `hackme` secret with a better one .exercise[ - Remove the insecure `hackme` secret: ```bash docker service update dummyservice --secret-rm hackme ``` - Add our better secret instead: ```bash docker service update dummyservice \ --secret-add source=arewesecureyet,target=hackme ``` ] Wait for the service to be fully updated with e.g. `watch docker service ps dummyservice`. --- class: secrets ## Checking that our password is now stronger - We will use the power of `docker exec`! .exercise[ - Get the ID of the new container: ```bash CID=$(docker ps -q --filter label=com.docker.swarm.service.name=dummyservice) ``` - Check the contents of the secret files: ```bash docker exec $CID grep -r . /run/secrets ``` ] --- class: secrets ## Secrets in practice - Can be (ab)used to hold whole configuration files if needed - If you intend to rotate secret `foo`, call it `foo.N` instead, and map it to `foo` (N can be a serial, a timestamp...) ```bash docker service create --secret source=foo.N,target=foo ... ``` - You can update (remove+add) a secret in a single command: ```bash docker service update ... --secret-rm foo.M --secret-add source=foo.N,target=foo ``` - For more details and examples, [check the documentation](https://docs.docker.com/engine/swarm/secrets/) --- # Least privilege model - All the important data is stored in the "Raft log" - Managers nodes have read/write access to this data - Workers nodes have no access to this data - Workers only receive the minimum amount of data that they need: - which services to run - network configuration information for these services - credentials for these services - Compromising a worker node does not give access to the full cluster --- ## What can I do if I compromise a worker node? - I can enter the containers running on that node - I can access the configuration and credentials used by these containers - I can inspect the network traffic of these containers - I cannot inspect or disrupt the network traffic of other containers (network information is provided by manager nodes; ARP spoofing is not possible) - I cannot infer the topology of the cluster and its number of nodes - I can only learn the IP addresses of the manager nodes --- ## Guidelines for workload isolation leveraging least privilege model - Define security levels - Define security zones - Put managers in the highest security zone - Enforce workloads of a given security level to run in a given zone - Enforcement can be done with [Authorization Plugins](https://docs.docker.com/engine/extend/plugins_authorization/) --- class: namespaces name: namespaces # Improving isolation with User Namespaces - *Namespaces* are kernel mechanisms to compartimetalize the system - There are different kind of namespaces: `pid`, `net`, `mnt`, `ipc`, `uts`, and `user` - For a primer, see "Anatomy of a Container" ([video](https://www.youtube.com/watch?v=sK5i-N34im8)) ([slides](https://www.slideshare.net/jpetazzo/cgroups-namespaces-and-beyond-what-are-containers-made-from-dockercon-europe-2015)) - The *user namespace* allows to map UIDs between the containers and the host - As a result, `root` in a container can map to a non-privileged user on the host Note: even without user namespaces, `root` in a container cannot go wild on the host. <br/> It is mediated by capabilities, cgroups, namespaces, seccomp, LSMs... --- class: namespaces ## User Namespaces in Docker - Optional feature added in Docker Engine 1.10 - Not enabled by default - Has to be enabled at Engine startup, and affects all containers - When enabled, `UID:GID` in containers are mapped to a different range on the host - Safer than switching to a non-root user (with `-u` or `USER`) in the container <br/> (Since with user namespaces, root escalation maps to a non-privileged user) - Can be selectively disabled per container by starting them with `--userns=host` --- class: namespaces ## User Namespaces Caveats When user namespaces are enabled, containers cannot: - Use the host's network namespace (with `docker run --network=host`) - Use the host's PID namespace (with `docker run --pid=host`) - Run in privileged mode (with `docker run --privileged`) ... Unless user namespaces are disabled for the container, with flag `--userns=host` External volume and graph drivers that don't support user mapping might not work. All containers are currently mapped to the same UID:GID range. Some of these limitations might be lifted in the future! --- class: namespaces ## Filesystem ownership details When enabling user namespaces: - the UID:GID on disk (in the images and containers) has to match the *mapped* UID:GID - existing images and containers cannot work (their UID:GID would have to be changed) For practical reasons, when enabling user namespaces, the Docker Engine places containers and images (and everything else) in a different directory. As a resut, if you enable user namespaces on an existing installation: - all containers and images (and e.g. Swarm data) disappear - *if a node is a member of a Swarm, it is then kicked out of the Swarm* - everything will re-appear if you disable user namespaces again --- class: namespaces ## Picking a node - We will select a node where we will enable user namespaces - This node will have to be re-added to the Swarm - All containers and services running on this node will be rescheduled - Let's make sure that we do not pick the node running the registry! .exercise[ - Check on which node the registry is running: ```bash docker service ps registry ``` ] Pick any other node (noted `nodeX` in the next slides). --- class: namespaces ## Logging into the right Engine .exercise[ - Log into the right node: ```bash ssh node`X` ``` ] --- class: namespaces ## Configuring the Engine .exercise[ - Create a configuration file for the Engine: ```bash echo '{"userns-remap": "default"}' | sudo tee /etc/docker/daemon.json ``` - Restart the Engine: ```bash kill $(pidof dockerd) ``` ] --- class: namespaces ## Checking that User Namespaces are enabled .exercise[ - Notice the new Docker path: ```bash docker info | grep var/lib ``` - Notice the new UID:GID permissions: ```bash sudo ls -l /var/lib/docker ``` ] You should see a line like the following: ``` drwx------ 11 296608 296608 4096 Aug 3 05:11 296608.296608 ``` --- class: namespaces ## Add the node back to the Swarm .exercise[ - Get our manager token from another node: ```bash ssh node`Y` docker swarm join-token manager ``` - Copy-paste the join command to the node ] --- class: namespaces ## Check the new UID:GID .exercise[ - Run a background container on the node: ```bash docker run -d --name lockdown alpine sleep 1000000 ``` - Look at the processes in this container: ```bash docker top lockdown ps faux ``` ] --- class: namespaces ## Comparing on-disk ownership with/without User Namespaces .exercise[ - Compare the output of the two following commands: ```bash docker run alpine ls -l / docker run --userns=host alpine ls -l / ``` ] -- class: namespaces In the first case, it looks like things belong to `root:root`. In the second case, we will see the "real" (on-disk) ownership. -- class: namespaces Remember to get back to `node1` when finished! --- ## A reminder about *scope* - Out of the box, Docker API access is "all or nothing" - When someone has access to the Docker API, they can access *everything* - If your developers are using the Docker API to deploy on the dev cluster ... ... and the dev cluster is the same as the prod cluster ... ... it means that your devs have access to your production data, passwords, etc. - This can easily be avoided --- ## Fine-grained API access control A few solutions, by increasing order of flexibility: - Use separate clusters for different security perimeters (And different credentials for each cluster) -- - Add an extra layer of abstraction (sudo scripts, hooks, or full-blown PAAS) -- - Enable [authorization plugins] - each API request is vetted by your plugin(s) - by default, the *subject name* in the client TLS certificate is used as user name - example: [user and permission management] in [UCP] [authorization plugins]: https://docs.docker.com/engine/extend/plugins_authorization/ [UCP]: https://docs.docker.com/datacenter/ucp/2.1/guides/ [user and permission management]: https://docs.docker.com/datacenter/ucp/2.1/guides/admin/manage-users/ --- class: encryption-at-rest ## Encryption at rest - Swarm data is always encrypted - A Swarm cluster can be "locked" - When a cluster is "locked", the encryption key is protected with a passphrase - Starting or restarting a locked manager requires the passphrase - This protects against: - theft (stealing a physical machine, a disk, a backup tape...) - unauthorized access (to e.g. a remote or virtual volume) - some vulnerabilities (like path traversal) --- class: encryption-at-rest ## Locking a Swarm cluster - This is achieved through the `docker swarm update` command .exercise[ - Lock our cluster: ```bash docker swarm update --autolock=true ``` ] This will display the unlock key. Copy-paste it somewhere safe. --- class: encryption-at-rest ## Locked state - If we restart a manager, it will now be locked .exercise[ - Restart the local Engine: ```bash sudo systemctl restart docker ``` ] Note: if you are doing the workshop on your own, using nodes that you [provisioned yourself](https://github.com/jpetazzo/orchestration-workshop/tree/master/prepare-machine) or with [Play-With-Docker](http://play-with-docker.com/), you might have to use a different method to restart the Engine. --- class: encryption-at-rest ## Checking that our node is locked - Manager commands (requiring access to crypted data) will fail - Other commands are OK .exercise[ - Try a few basic commands: ```bash docker ps docker run alpine echo ♥ docker node ls ``` ] (The last command should fail, and it will tell you how to unlock this node.) --- class: encryption-at-rest ## Checking the state of the node programmatically - The state of the node shows up in the output of `docker info` .exercise[ - Check the output of `docker info`: ```bash docker info ``` - Can't see it? Too verbose? Grep to the rescue! ```bash docker info | grep ^Swarm ``` ] --- class: encryption-at-rest ## Unlocking a node - You will need the secret token that we obtained when enabling auto-lock earlier .exercise[ - Unlock the node: ```bash docker swarm unlock ``` - Copy-paste the secret token that we got earlier - Check that manager commands now work correctly: ```bash docker node ls ``` ] --- class: encryption-at-rest ## Managing the secret key - If the key is compromised, you can change it and re-encrypt with a new key: ```bash docker swarm unlock-key --rotate ``` - If you lost the key, you can get it as long as you have at least one unlocked node: ```bash docker swarm unlock-key -q ``` Note: if you rotate the key while some nodes are locked, without saving the previous key, those nodes won't be able to rejoin. Note: if somebody steals both your disks and your key, .strike[you're doomed! Doooooomed!] <br/>you can block the compromised node with `docker node demote` and `docker node rm`. --- class: encryption-at-rest ## Unlocking the cluster permanently - If you want to remove the secret key, disable auto-lock .exercise[ - Permanently unlock the cluster: ```bash docker swarm update --autolock=false ``` ] Note: if some nodes are in locked state at that moment (or if they are offline/restarting while you disabled autolock), they still need the previous unlock key to get back online. For more information about locking, you can check the [upcoming documentation](https://github.com/docker/docker.github.io/pull/694). --- class: extra-details ## Constraints and global services (New in Docker Engine 1.13) - By default, global services run on *all* nodes ```bash docker service create --mode global ... ``` - You can specify constraints for global services - These services will run only on the node satisfying the constraints - For instance, this service will run on all manager nodes: ```bash docker service create --mode global --constraint node.role==manager ... ``` --- class: extra-details ## Constraints and dynamic scheduling (New in Docker Engine 1.13) - If constraints change, services are started/stopped accordingly (e.g., `--constraint node.role==manager` and nodes are promoted/demoted) - This is particularly useful with labels: ```bash docker node update node1 --label-add defcon=five docker service create --constraint node.labels.defcon==five ... docker node update node2 --label-add defcon=five docker node update node1 --label-rm defcon=five ``` --- class: extra-details ## Shortcomings of dynamic scheduling .warning[If a service becomes "unschedulable" (constraints can't be satisfied):] - It won't be scheduled automatically when constraints are satisfiable again - You will have to update the service; you can do a no-op udate with: ```bash docker service update ... --force ``` .warning[Docker will silently ignore attempts to remove a non-existent label or constraint] - It won't warn you if you typo when removing a label or constraint! --- class: extra-details # Node management - SwarmKit allows to change (almost?) everything on-the-fly - Nothing should require a global restart --- class: extra-details ## Node availability ```bash docker node update <node-name> --availability <active|pause|drain> ``` - Active = schedule tasks on this node (default) - Pause = don't schedule new tasks on this node; existing tasks are not affected You can use it to troubleshoot a node without disrupting existing tasks It can also be used (in conjunction with labels) to reserve resources - Drain = don't schedule new tasks on this node; existing tasks are moved away This is just like crashing the node, but containers get a chance to shutdown cleanly --- class: extra-details ## Managers and workers - Nodes can be promoted to manager with `docker node promote` - Nodes can be demoted to worker with `docker node demote` - This can also be done with `docker node update <node> --role <manager|worker>` - Reminder: this has to be done from a manager node <br/>(workers cannot promote themselves) --- class: extra-details ## Removing nodes - You can leave Swarm mode with `docker swarm leave` - Nodes are drained before being removed (i.e. all tasks are rescheduled somewhere else) - Managers cannot leave (they have to be demoted first) - After leaving, a node still shows up in `docker node ls` (in `Down` state) - When a node is `Down`, you can remove it with `docker node rm` (from a manager node) --- class: extra-details ## Join tokens and automation - If you have used Docker 1.12-RC: join tokens are now mandatory! - You cannot specify your own token (SwarmKit generates it) - If you need to change the token: `docker swarm join-token --rotate ...` - To automate cluster deployment: - have a seed node do `docker swarm init` if it's not already in Swarm mode - propagate the token to the other nodes (secure bucket, facter, ohai...) --- class: extra-details ## Disk space management: `docker system df` - Shows disk usage for images, containers, and volumes - Breaks down between *active* and *reclaimable* categories .exercise[ - Check how much disk space is used at the end of the workshop: ```bash docker system df ``` ] Note: `docker system` is new in Docker Engine 1.13. --- class: extra-details ## Reclaiming unused resources: `docker system prune` - Removes stopped containers - Removes dangling images (that don't have a tag associated anymore) - Removes orphaned volumes - Removes empty networks .exercise[ - Try it: ```bash docker system prune -f ``` ] Note: `docker system prune -a` will also remove *unused* images. --- class: extra-details ## Events - You can get a real-time stream of events with `docker events` - This will report *local events* and *cluster events* - Local events = <br/> all activity related to containers, images, plugins, volumes, networks, *on this node* - Cluster events = <br/>Swarm Mode activity related to services, nodes, secrets, configs, *on the whole cluster* - `docker events` doesn't report *local events happening on other nodes* - Events can be filtered (by type, target, labels...) - Events can be formatted with Go's `text/template` or in JSON --- class: extra-details ## Getting *all the events* - There is no built-in to get a stream of *all the events* on *all the nodes* - This can be achieved with (for instance) the four following services working together: - a Redis container (used as a stateless, fan-in message queue) - a global service bind-mounting the Docker socket, pushing local events to the queue - a similar singleton service to push global events to the queue - a queue consumer fetching events and processing them as you please I'm not saying that you should implement it with Shell scripts, but you totally could. .small[ (It might or might not be one of the initiating rites of the [House of Bash](https://twitter.com/carmatrocity/status/676559402787282944)) ] For more information about event filters and types, check [the documentation](https://docs.docker.com/engine/reference/commandline/events/). --- class: title, extra-details # What's next? ## (What to expect in future versions of this workshop) --- class: extra-details ## Implemented and stable, but out of scope - [Docker Content Trust](https://docs.docker.com/engine/security/trust/content_trust/) and [Notary](https://github.com/docker/notary) (image signature and verification) - Image security scanning (many products available, Docker Inc. and 3rd party) - [Docker Cloud](https://cloud.docker.com/) and [Docker Datacenter](https://www.docker.com/products/docker-datacenter) (commercial offering with node management, secure registry, CI/CD pipelines, all the bells and whistles) - Network and storage plugins --- class: extra-details ## Work in progress - Demo at least one volume plugin <br/>(bonus points if it's a distributed storage system) - ..................................... (your favorite feature here) Reminder: there is a tag for each iteration of the content in the Github repository. It makes it easy to come back later and check what has changed since you did it! --- class: title, self-paced Thank you! --- class: title, in-person That's all folks! <br/> Questions? .small[.small[ Jérôme ([@jpetazzo](https://twitter.com/jpetazzo)) — [@docker](https://twitter.com/docker) AJ ([@s0ulshake](https://twitter.com/s0ulshake)) — *For hire!* <br/> `curl cv.soulshake.net` ]] <!-- <br/> Jérôme ([@jpetazzo](https://twitter.com/jpetazzo)) <br/> Tiffany ([@tiffanyfayj](https://twitter.com/tiffanyfayj)) -->