mirror of https://github.com/docker/docs.git
WIP: Getting Started, improve deploy to cloud topics/UX of those steps (#4751)
* images to cover AWS deploy Signed-off-by: Victoria Bialas <victoria.bialas@docker.com> * added instructions on opening ports with security groups in AWS Signed-off-by: Victoria Bialas <victoria.bialas@docker.com> * finalized cloud deploy procedure, added info re: unset docker-machine variables Signed-off-by: Victoria Bialas <victoria.bialas@docker.com> * added screen snaps, cleanup, and iteration steps to cloud example Signed-off-by: Victoria Bialas <victoria.bialas@docker.com> * removed edge releases qualification on swarm connect from Desktop apps Signed-off-by: Victoria Bialas <victoria.bialas@docker.com> * added visualizer on cloud screen snap Signed-off-by: Victoria Bialas <victoria.bialas@docker.com> * moved iteration, cleanup step to be without CE steps in part 6 Signed-off-by: Victoria Bialas <victoria.bialas@docker.com>
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@ -429,7 +429,9 @@ same `docker swarm join` command you used on `myvm2`, and capacity will be added
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to your cluster. Just run `docker stack deploy` afterwards, and your app will
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take advantage of the new resources.
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## Cleanup
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## Cleanup and reboot
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### Stacks and swarms
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You can tear down the stack with `docker stack rm`. For example:
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@ -445,6 +447,59 @@ docker stack rm getstartedlab
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> manager, but _you'll need this swarm for part 5, so please keep it
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> around for now_.
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### Unsetting docker-machine shell variable settings
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You can unset the `docker-machine` environment variables in your current shell
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with the following command:
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```
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eval $(docker-machine env -u)
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```
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This disconnects the shell from `docker-machine` created virtual machines,
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and allows you to continue working in the same shell, now using native `docker`
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commands (for example, on Docker for Mac or Docker for Windows). To learn more,
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see the [Machine topic on unsetting environment variables](/machine/get-started/#unset-environment-variables-in-the-current-shell).
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### Restarting Docker machines
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If you shut down your local host, Docker machines will stop running. You can check the status of machines by running `docker-machine ls`.
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```
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$ docker-machine ls
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NAME ACTIVE DRIVER STATE URL SWARM DOCKER ERRORS
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myvm1 - virtualbox Stopped Unknown
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myvm2 - virtualbox Stopped Unknown
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```
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To restart a machine that's stopped, run:
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```
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docker-machine start <machine-name>
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```
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For example:
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```
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$ docker-machine start myvm1
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Starting "myvm1"...
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(myvm1) Check network to re-create if needed...
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(myvm1) Waiting for an IP...
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Machine "myvm1" was started.
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Waiting for SSH to be available...
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Detecting the provisioner...
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Started machines may have new IP addresses. You may need to re-run the `docker-machine env` command.
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$ docker-machine start myvm2
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Starting "myvm2"...
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(myvm2) Check network to re-create if needed...
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(myvm2) Waiting for an IP...
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Machine "myvm2" was started.
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Waiting for SSH to be available...
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Detecting the provisioner...
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Started machines may have new IP addresses. You may need to re-run the `docker-machine env` command.
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```
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[On to Part 5 >>](part5.md){: class="button outline-btn"}
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## Recap and cheat sheet (optional)
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@ -90,25 +90,178 @@ Started Referral', 'Cloud', 'BYOH');"}, this provider does not support swarm
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mode. You can [register your own existing
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swarms](/docker-cloud/cloud-swarm/register-swarms/) with Docker Cloud.
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### Deploy your app
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### Deploy your app on a cloud provider
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[Connect to your swarm via Docker
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Cloud](/docker-cloud/cloud-swarm/connect-to-swarm.md). On Docker for
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Mac or Docker for Windows (Edge releases), you can [connect to your swarms
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directly through the desktop app
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menus](/docker-cloud/cloud-swarm/connect-to-swarm.md#use-docker-for-mac-or-windows-edge-to-connect-to-swarms).
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1. [Connect to your swarm via Docker
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Cloud](/docker-cloud/cloud-swarm/connect-to-swarm.md). There are a couple of different ways to connect:
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Either way, this opens a terminal whose context is your local machine, but whose
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Docker commands are routed up to the swarm running on your cloud service
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provider. This is the same shell configuration method you've already learned
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with `docker-machine env`. You directly access both your local file system and
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your remote swarm, enabling pure `docker` commands:
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* From the Docker Cloud web interface in Swarm mode, select Swarms at
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the top of the page, click the swarm you want to connect to, and copy-paste the given command into a command line terminal.
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```shell
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docker stack deploy -c docker-compose.yml getstartedlab
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```
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That's it! Your app is running in production and is managed by Docker Cloud.
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Or ...
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* On Docker for Mac or Docker for Windows, you can [connect to your swarms directly through the desktop app menus](/docker-cloud/cloud-swarm/connect-to-swarm.md#use-docker-for-mac-or-windows-edge-to-connect-to-swarms).
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Either way, this opens a terminal whose context is your local machine,
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but whose Docker commands are routed up to the swarm running on your
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cloud service provider. You directly access both your local file system
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and your remote swarm, enabling pure `docker` commands.
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2. Run `docker stack deploy -c docker-compose.yml getstartedlab` to deploy
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the app on the cloud hosted swarm.
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```shell
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docker stack deploy -c docker-compose.yml getstartedlab
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Creating network getstartedlab_webnet
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Creating service getstartedlab_web
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Creating service getstartedlab_visualizer
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Creating service getstartedlab_redis
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```
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Your app is now running on your cloud provider.
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#### Run some swarm commands to verify the deployment
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You can use the swarm command line, as you've done already, to browse and manage
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the swarm. Here are some examples that should look familiar by now:
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* Use `docker node ls` to list the nodes.
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```shell
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[getstartedlab] ~ $ docker node ls
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ID HOSTNAME STATUS AVAILABILITY MANAGER STATUS
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9442yi1zie2l34lj01frj3lsn ip-172-31-5-208.us-west-1.compute.internal Ready Active
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jr02vg153pfx6jr0j66624e8a ip-172-31-6-237.us-west-1.compute.internal Ready Active
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thpgwmoz3qefdvfzp7d9wzfvi ip-172-31-18-121.us-west-1.compute.internal Ready Active
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n2bsny0r2b8fey6013kwnom3m * ip-172-31-20-217.us-west-1.compute.internal Ready Active Leader
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```
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* Use `docker service ls` to list services.
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```shell
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[getstartedlab] ~/sandbox/getstart $ docker service ls
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ID NAME MODE REPLICAS IMAGE PORTS
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x3jyx6uukog9 dockercloud-server-proxy global 1/1 dockercloud/server-proxy *:2376->2376/tcp
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ioipby1vcxzm getstartedlab_redis replicated 0/1 redis:latest *:6379->6379/tcp
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u5cxv7ppv5o0 getstartedlab_visualizer replicated 0/1 dockersamples/visualizer:stable *:8080->8080/tcp
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vy7n2piyqrtr getstartedlab_web replicated 5/5 sam/getstarted:part6 *:80->80/tcp
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```
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* Use `docker service ps <service>` to view tasks for a service.
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```shell
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[getstartedlab] ~/sandbox/getstart $ docker service ps vy7n2piyqrtr
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ID NAME IMAGE NODE DESIRED STATE CURRENT STATE ERROR PORTS
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qrcd4a9lvjel getstartedlab_web.1 sam/getstarted:part6 ip-172-31-5-208.us-west-1.compute.internal Running Running 20 seconds ago
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sknya8t4m51u getstartedlab_web.2 sam/getstarted:part6 ip-172-31-6-237.us-west-1.compute.internal Running Running 17 seconds ago
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ia730lfnrslg getstartedlab_web.3 sam/getstarted:part6 ip-172-31-20-217.us-west-1.compute.internal Running Running 21 seconds ago
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1edaa97h9u4k getstartedlab_web.4 sam/getstarted:part6 ip-172-31-18-121.us-west-1.compute.internal Running Running 21 seconds ago
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uh64ez6ahuew getstartedlab_web.5 sam/getstarted:part6 ip-172-31-18-121.us-west-1.compute.internal Running Running 22 seconds ago
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```
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#### Open ports to services on cloud provider machines
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At this point, your app is deployed as a swarm on your cloud provider servers,
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as evidenced by the `docker` commands you just ran. But, you still need to
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open ports on your cloud servers in order to:
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* allow communication between the `redis` service and `web` service on
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the worker nodes
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* allow inbound traffic to the `web` service on the worker nodes so that
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Hello World and Visualizer are accessible from a web browser.
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* allow inbound SSH traffic on the server that is running the `manager` (this may be already set on your cloud provider)
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{: id="table-of-ports"}
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These are the ports you need to expose for each service:
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| Service | Type | Protocol | Port |
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| :--- | :--- | :--- | :--- |
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| `web` | HTTP | TCP | 80 |
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| `visualizer` | HTTP | TCP | 8080 |
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| `redis` | TCP | TCP | 6379 |
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Methods for doing this will vary depending on your cloud provider.
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We'll use Amazon Web Services (AWS) as an example.
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> What about the redis service to persist data?
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>
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> To get the `redis` service working, you need to `ssh` into
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the cloud server where the `manager` is running, and make a `data/`
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directory in `/home/docker/` before you run `docker stack deploy`.
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Another option is to change the data path in the `docker-stack.yml` to
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a pre-existing path on the `manager` server. This example does not
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include this step, so the `redis` service is not up in the example output.
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#### Example: AWS
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1. Log in to the [AWS Console](https://aws.amazon.com/){: target="_blank"
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class="_"}, go to the EC2 Dashboard, and click into your **Running Instances**
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to view the nodes.
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2. On the left menu, go to Network & Security > **Security Groups**.
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You'll see security groups related to your swarm
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for `getstartedlab-Manager-<xxx>`, `getstartedlab-Nodes-<xxx>`,
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and `getstartedlab-SwarmWide-<xxx>`.
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3. Select the "Node" security group for the swarm. The group name
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will be something like this: `getstartedlab-NodeVpcSG-9HV9SMHDZT8C`.
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4. Add Inbound rules for the `web`, `visualizer`, and `redis`
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services, setting the Type, Protocol and Port for each as shown in the
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[table above](#table-of-ports), and click **Save** to apply the rules.
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> **Tip**: When you save the new rules, HTTP and TCP
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ports will be auto-created for both IPv4 and IPv6 style addresses.
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5. Go to the list of **Running Instances**, get the public DNS name for
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one of the workers, and paste it into the address bar of your web browser.
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Just as in the previous parts of the tutorial, the Hello World app
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displays on port `80`, and the Visualizer displays on port `8080`.
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### Iteration and cleanup
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From here you can do everything you learned about in previous parts of the
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tutorial.
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* Scale the app by changing the `docker-compose.yml` file and redeploy
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on-the-fly with the `docker stack deploy` command.
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* Change the app behavior by editing code, then rebuild, and push the new image.
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(To do this, follow the same steps you took earlier to [build the
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app](part2.md#build-the-app) and [publish the
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image](part2.md#publish-the-image)).
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* You can tear down the stack with `docker stack rm`. For example:
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```
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docker stack rm getstartedlab
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```
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Unlike the scenario where you were running the swarm on local Docker machine
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VMs, your swarm and any apps deployed on it will continue to run on cloud
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servers regardless of whether you shut down your local host.
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{% endcapture %}
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{% capture enterpriseboilerplate %}
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Customers of Docker Enterprise Edition run a stable, commercially-supported
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