I have a running keycloak 8's docker but whenever I restart it, all non-offline session disappears. Result, all users are being disconnected whenever I come to update keycloak.
Causes:
I've read this thread here and understood why access token aren't persisted (mainly performance issue).
As solution I've wanted to use Clusters (as recommended here), and I understood, that the core part is only well managing Infinispan.
Ideas:
I first wanted to store that infinispan outside docker container (in a volume), then search where does the JBoss saves Infinispan in a docker, but i didn't found anything.
Secondly I thought about an SPI to manage user sessions externally, but it seems not to be the right solution, as infinispan does already a good Job.
Setting up then a cluster, helped by this article about Cross-Datacenter support in Keycloak and this other one about Keycloak Cross Data Center Setup in AWS seemed to be a good starting point, but I'm still actually using dockers and I not sure if it's a better idea for me to build docker images from those tutorials.
Any more Idea would be welcome :)
Just yet I've tried using docker cluster a second time, but now using docker swarm with the info from here:
The PING discovery protocol is used by default in udp stack (which is used by default in standalone-ha.xml). Since the Keycloak image runs in clustered mode by default, all you need to do is to run it:
docker run jboss/keycloak
If you run two instances of it locally, you will notice that they form a cluster.
I've deployed very simply 3 instances of keycloak in clustered mode with an external database (postgres) using docker stack and it worked well.
Simpler said, keycloak docker does already handle this use-case when using clusters.
For more about the cluster use-case, please refer to this tutorial about how to setup Keycloak Cluster
Related
Can somebody explain it with some examples? Why multi-container docker apps are built? while you can contain your app in a single docker container.
When you make a multi-container app you have to do networking. Is not it easy to run a single image of a single container rather than two images of two containers?
There are several good reasons for this:
It's easier to reuse prebuilt images. If you need MySQL, or Redis, or an Nginx reverse proxy, these all exist as standard images on Docker Hub, and you can just include them in a multi-container Docker Compose setup. If you tried to put them into a single image, you'd have to install and configure them yourself.
The Docker tooling is built for single-purpose containers. If you want the logs of a multi-process container, docker logs will generally print out the supervisord logs, which aren't what you want; if you want to restart one of those containers, the docker stop; docker rm; docker run sequence will delete the whole thing. Instead with a multi-process container you need to use debugging tools like docker exec to do anything, which is harder to manage.
You can upgrade one part without affecting the rest. Upgrading the code in a container usually involves building a new image, stopping and deleting the old container, and running a new container from the new image. The "deleting the old container" part is important, and routine; if you need to delete your database to upgrade your application, you risk losing data.
You can scale one part without affecting the rest. More applicable in a cluster environment like Docker Swarm or Kubernetes. If your application is overloaded (especially in production) you'd like to run multiple copies of it, but it's hard to run multiple copies of a standard relational database. That essentially requires you to run these separately, so you can run one proxy, five application servers, and one database.
Setting up a multi-container application shouldn't be especially difficult; the easiest way is to use Docker Compose, which will deal with things like creating a network for you.
For the sake of simplification, I would say you can run only one application with a public entry point (like API) in a single container. Actually, this approach is recommended by Docker official documentation.
Microservices
Because of this single constraint, you cannot run microservices that require their own entry points in a single docker container.
It could be more a discussion on the advantages of Monolith application vs Microservices.
Database
Even if you decide to run the Monolith application only, still you need to connect some database there. As you noticed, Docker has an additional network-configuration layer, so if you want to run Database and application locally, the easiest way is to use docker-compose to run both images (Database and your Application) inside one, automatically configured network.
# Application definition
application: <your app definition>
# Database definition
database:
image: mysql:5.7
In my example, you can just connect to your DB via https://database:<port> URL from your main app (plus credentials eventually) and it will work.
Scalability
However, why we should split images for the database from the application? One word - scalability. For development purposes, you want to have your local DB, maybe with docker because it is handy. For production purposes, you will put the application image to run somewhere (Kubernetes, Docker-Swarm, Azure App Services, etc.). To handle multiple requests at the same time, you want to run multiple instances of your application. However what about the database? You cannot connect to the internal instance of DB hosted in the same container, because other instances of your app in other containers will have a completely different set of data (without synchronization).
Most often you are electing to use a separate Database server - no matter if running it on the container or fully manged databases (like Azure CosmosDB or Mongo Atlas), but with your own configuration, scaling, and synchronization dedicated for DB only. Your app just needs to worry about the proper URL to that. Most cloud providers are exposing such services out of the box, so you are not worrying about the configuration by yourself.
Easy to change
Last but not least argument is about changing the initial setup overtime. You might change the database provider, or upgrade the version of the image in the future (such things are required from time to time). When you separate images, you can modify one without touching others. It is decreasing the cost of maintenance significantly.
Also, you can add additional services very easy - different logging aggregator? No Problem, additional microservice running out-of-the-box? Easy.
I currently have six docker containers that were triggered by a docker-compose file. Now I wish to move some of them to a remote machine and enable remote communication between them.
The problem now is that I also need to add a layer of security by encrypting their traffic.
This should be for a production website and needs to be very stable so I am unsure about which protocols/approaches could be better for this scenario.
I have used port forwarding using ssh and know that could also apply some stability through autossh. But I am unsure if there are other approaches that could help achieve the same idea by also taking into account stability and performance.
What protocols/approaches could help on this aim? How do they differ?
I would not recommend manually configuring docker container connections across physical servers because docker already contains a solution for that called Docker Swarm. Follow this documentation to configure your containers to use a docker swarm. I've done it and it's very cool!
I've working with Docker containers. What Ive done is lunching 5 containers running the same application, I use HAProxy to redirect requests to them, I added a volume to preserve data and set restart policy as Always.
It works. (So far this is my load balancing aproach)But sometimes I need another container to join the pool as there might be more requests, or maybe at first I don't need 5 containers.
This is provided by the Swarm Mode addition in Docker 1.12. It includes orchestration that lets you not only scale your service up or down, but recover from an outage by automatically rescheduling the jobs to run on other nodes.
If you don't want to use Docker 1.12 (yet!), you can also use a Service Discovery like Consul, register your containers inside and use a tool like Consul Template to regenerate your load balancer configuration accordingly.
I made a talk 6 months ago about it. You can find the code and the configuration I used during my demo here: https://github.com/bargenson/dockerdemo
I’m using Amazon ECS to auto deploy my containers on uat/production.
What is the best way to do that?
I have a REST api with a several front-end clients
Should I package my api container with nginx in the same container?
And do the same thing with the others front end clients.
Or I have to write a big task definition to bring together all my containers(db, nginx, php, api, clients) :(, but that's mean that I should redeploy all my infrastructure at each push uat/prod
I'm very confusing.
I would avoid including too much in a single container. Try and distill your containers down to one process doing one thing. If all you're doing is serving up a REST API for consumption by your front end, just put the essential pieces in for that and no more.
In my experience you also want your ECS tasks to be able to handle failure gracefully and restart, and the more complicated your containers are the harder this is to get right.
Depending on your requirements I would look into using ELB instead of nginx, you can have your ECS cluster point at an ELB and not have to deal with that piece at all.
Do not use ECS - it's too crude. I was using it as a platform for our staging/production environments and had odd problems during deployments - sometimes it worked well, sometimes - not (with the same Docker images). ECS provides not clear model of container deployment and maintenance.
There is another good, stable and predictive option - Docker Cloud service. It's new tool (a.k.a. Tutum) that was acquired by Docker. I switched the CI/CD to use it and we're happy with it.
Bind Amazon user credentials to Docker Cloud account. Docker Cloud uses AWS (or other provider) API for creating appropriate computer instances.
Create Node. Select Amazon EC2 instance type and parameters of storage, security group and so on. New instance will contain installed docker software and managing container that handles messages from Docker Cloud (deploy, destroy and others).
Create Stackfile, see https://docs.docker.com/docker-cloud/apps/stack-yaml-reference/. Stackfile is a definition of container group you required. You can define different scaling/distribution models for your containers using specific Stackfile options like deployment strategy, see https://docs.docker.com/docker-cloud/apps/stack-yaml-reference/#deployment-strategy-1.
Define ELB configurations in AWS for your new instances.
P.S. I'm not a member of Docker team and I like other AWS services :).
Here is my two cents on the topic, the question is not really related to ecs, it applies to any body deploying their apps on docker.
I would suggest separating the containers, one for nginx and one for API.
if they need to be co-located on the same instance, on ECS you can define them as part of the same task and on kubernetes you can make them part of same pod.
Define a docker link between the nginx and the api container. This will allow the nginx process to talk to api container without the api container exposing its ports to the host.
One advantage of using the container running platforms such as kubernetes and ecs is that they ensure each of the container run all the time and dynamically restart if one of the processes/containers go down.
Separating the containers will allow these platforms to monitor both the processes separately. When you combine the two into one container the docker container can only run with one of the processes in foreground, so you will loose the advantage of auto-healing for one of the processes.
Also moving from nginx to ELB is not a straightforward solution, you may have redirections and other things configured on the nginx, which are not available on ELB(As of date).
If you also need the ELB, there is no harm in forwarding the requests from the ELB to the nginx port.
I am new to both Docker and Consul, and am trying to get a feel for how containerized apps could use Consul for both service registry and KV pair config management ("configuration").
My understanding was that I could:
Create an image that runs Consul server, so something like this; then
Spin up three of these Docker-Consul containers (thus forming a cluster/quorum) on myvm01.example.com (an Ubuntu VM); then
Refactor my app to use Consul and create a Docker image that runs my app and Consul agent, with the agent configured to join the 3-node quorum at startup. On startup, my app uses the local Consul agent to pull down all of its configurations, stored as KV pairs. It also pulls in registered/healthy services, and uses a local load balancing tool to balance the services it integrates with.
Run my app's containers on, say, myvm02.example.com (another Ubuntu VM).
So to begin with, if any of this seems like I am misunderstanding the normal/proper uses of Docker and Consul (sans Registrator), please begin by correcting me!
Assuming I'm more or less correct, I recently stumbled across Registrator and am now even more confused. Registrator seems to be some middleman between your app containers and your Consul (or whatever registry you use) servers.
After reading their Quickstart tutorial, it sounds like what you're supposed to do is:
Deploy my Consul cluster/quorum containers to myvm01.example.com like before
Instead of "Dockerizing" my app to use Consul directly, I simply integrate it with Registrator
Then I deploy a Registrator container somewhere, and configure it to integrate with Consul
Then I deploy my app containers. They integrate with Registrator, and Registrator in turn integrates with Consul.
My concerns:
Is my understanding here correct or way off base? If so, how?
What is actually gained by the addition of Registrator. It doesn't seem (to the untrained eye at least) like anything more than a layer of indirection between the app and the service registry.
Will I still be able to leverage Consul's KV config service through Registrator?
Is my understanding here correct or way off base? If so, how?
It seems to me, that it's not a good solution, to have all cluster/quorum members running inside the same VM. It's not so bad if you use it for development or tetsing or something, where you don't care much about reliability, but not for production.
Once your VM dies, you'll loose all the advantages you have by creating a cluster. And even more, you can loose all the data you have in K/V store, because you are running Consul servers inside a docker containers, which should be additionaly configured to share the configuration between runs.
As for the rest, I see it the same as you.
What is actually gained by the addition of Registrator.
From my point of view, the main thing is, that you don't have to provide an instance of Consul Agent in every container you run. And the container with the image you run is responsible only for their main functions, not for registering itself somewhere. You may simply pull an image and just run a container with it, to make it's service available, without making additional work.
Will I still be able to leverage Consul's KV config service through Registrator?
Unfortunately, no. At least, we didn't find a solution to use it this way, when we were looking for something to make service discovering and configuration management. We came to conclusion, that Registrator is not a proxy for K/V store and is used only to automate service discovery. So you have to use some other logic to access consul's K/V store.
Update: furthermore, here is 2 articles: "Automatic Docker Service Announcement with Registrator" and "Automatic container registration with Consul and Registrator", I found usefull to understand Registrator role in service discovery process.