I'm pretty new to Docker orchestration and managing a fleet of containers. I'm wanting to build an app that would give the user a container when they ran a command. What is the best tool and best way to accomplish this?
I plan on having a pool of CoreOS servers to run the containers on and I'm imagining the scheduler to have an API that I can just call to create the container.
Most of what I have seen with Nomad, Kubernetes, Docker Swarm, etc is how to provision multiple clusters of containers all doing the same thing. I'm wanting to be able to create a single container based on a users command and then be able to communicate with an API on that container. Anyone have experience with this?
I'd look at Kubernetes + the Jobs API (short lived) or Deployments (long lived)
I'm not sure exactly what you mean by command, but I'll assume its some sort of dev env triggered by a CLI, make-dev.
User triggers make-dev, which sends a webhook to your app sitting in front of the Jobs API, ideally doing rate-limiting and/or auth.
Your app takes the command, sanity checks it, then fires off a Job/Deployment request + an Ingress rule + Service
Kubernetes will schedule it out across your fleet of machines
Your app waits for the pod to start, then returns back the address of the API with a unique identifier (the same thing in the ingress rule) like devclusters.com/foobar123
User now accesses their service at that address. Internally Kubernetes uses the ingress and service to route the requests to your pod
This should scale well, and if your different environments use the same base container image, they should start really fast.
Plug: If you want an easy CoreOS + Kubernetes cluster plus a UI try https://coreos.com/tectonic
I plan on having a pool of CoreOS servers to run the containers on and I'm imagining the scheduler to have an API that I can just call to create the container
kubernetes comes with a RESTful API that you can use to directly create pods (the unit of work in kubernetes which contains one or more containers) within your cluster.
The command line utility kubectl also interacts with the cluster in the exact same way, via the api. There are client libraries written in golang, Java, and Python at the moment with others on the way to help communicate with the cluster.
If you later want a higher level abstraction to manage pods, update them and manage their lifetimes, looking at one of the controllers (replicaset, replication controller, deployment, statefulset) should help.
Related
This question illustrates the theoretical differences between docker run and docker service.
What I don't understand is when would one need to use the exact same container replicated multiple times (as per the Docker documentation example)?
There, they run the same web app replicated 5 times.
Is deployment on Kubernetes (for example) a potential use case, where the developer does not want to centralize the app on one host, in order to make it more resilient, hence why 5 replicas are created?
To understand, can someone please please with an example use case, where the docker service is useful?
swarm is an orchestrator just like kubernetes. docker service deploys services to swarm just as you deploy your services to kubernetes using kubectl.
swarm is essentially built-in primitive orchestrator. One possible case for replicas is running a proxy that directs requests to proper containers. You could expose multiple machines and have one take place of another in case another fails. Or any other high availability case you could think of.
Your question could be rephrased as "What's the difference between running a single container and running containers in a cluster?", which would be another question altogether, but that rephrasing might help illustrate what docker service does.
If you want to scale your application, you can run multiple instances of it (horizontal scaling) or you beef up the machine(s) that it runs on (vertical scaling). For the first, you would have to put a load balancer in front of your application so that the traffic is evenly distributed between the different instances. The idea is that those instances run on different hosts, so if one goes down, your application is still up. Some controlling instance (a Kubernetes service, for example) will notice that one of your instances has gone south and won't direct any more traffic to it. Nowadays, with all the cloud stuff going on, this is typically the way to go.
You don't need Kubernetes for such a setup, but you're right, this would be a typical use case for it. At least if you run your application in a Docker container.
Once use case is running on Docker swarm which consists of n number of nodes in your swarm cluster. You can run replicas of your application on the swarm cluster with a load balancer/reverse proxy to load balance your setup. If any one of the nodes goes down the application can still run.
But the exact use case for running multiple instances is scalabilty. Suppose you know that one instance of your app can serve 10000 users (Assume Bank authentication) at a time.
If you want your application to serve 50K users just run 5 replicas(using docker service create) .
I a want to run a web page similar like kubernetes dashboard.The web page takes input from the user and generates a small file but i want the web page to be loaded without using any server. kubernetes is deploying a pod and bringing up the web page i want to do the same.If kubernetes is also using a server how is it using it(is it directly downloading it with the OS in the pod or how is kubernetes doing it).
Overview I want to know how kubernetes dashboard is getting deployed is it using a server if so how is it getting the server installed in the kubernetes pod else how is it bring up the UI.
Actually, Kubernetes plays the role as an orchestrator and provides sufficient way for building communication channels between containers in the cluster and uses Docker by default as a container runtime.
Containers represent run-time environment for images, however images consist with OS layer and application binaries, a good explanation you can find here. In order to build own image you might consider two ways to afford this: create an image from existing one in Docker Hub or compose image from Dockerfile.To store the customized image might be the option to push it into Docker Hub repository or stand for some private isolated repo by deploying a Registry server.
When you are ready with an image, and you plan to implement application in Kubernetes cluster, that's a good time to create first microservice. Although, there are tons of materials about Kubernetes cluster and its run-time engine architecture in the globe, I would focus on the application deployment lifecycle.
Deployment is the main mechanism which defines how are Pods should to be implemented within a cluster and provides specific configuration for further application run-time workflow.
Service describes a way how the particular Pod will communicate with other resources within a cluster, providing endpoint IP address and port where your application will respond.
In general scenario with Kubernetes Dashboard, the method in use kubectl proxy will expose the application by proxying gateway between host and Kubernetes API, which is more like for testing purposes and not secure, in comparison with Nodeport type which brings more convenient way to make application accessible outside the cluster, as described in this Stack thread.
I encourage you to get some more learning stuff in the official Kubernetes documentation.
I am creating a docker container ( using docker run) in a kubernetes Environment by invoking a rest API.
I have mounted the docker.sock of the host machine and i am building an image and running that image from RESTAPI..
Now i need to connect to this container from some other container which is actually started by Kubectl from deployment.yml file.
But when used kubeclt describe pod (Pod name), my container created using Rest API is not there.. So where is this container running and how can i connect to it from some other container ?
Are you running the container in the same namespace as namespace with deployment.yml? One of the option to check that would be to run -
kubectl get pods --all-namespaces
If you are not able to find the docker container there than I would suggest performing below steps -
docker ps -a {verify running docker status}
Ensuring that while mounting docker.sock there are no permission errors
If there are permission errors, escalate privileges to the appropriate level
To answer the second question, connection between two containers should be possible by referencing cluster DNS in below format -
"<servicename>.<namespacename>.svc.cluster.local"
I would also request you to detail steps, codes and errors(if there are any) for me to better answer the question.
You probably shouldn't be directly accessing the Docker API from anywhere in Kubernetes. Kubernetes will be totally unaware of anything you manually docker run (or equivalent) and as you note normal administrative calls like kubectl get pods won't see it; the CPU and memory used by the pod won't be known about by the node interface and this could cause a node to become over utilized. The Kubernetes network environment is also pretty complicated, and unless you know the details of your specific CNI provider it'll be hard to make your container accessible at all, much less from a pod running on a different node.
A process running in a pod can access the Kubernetes API directly, though. That page notes that all of the official client libraries are aware of the conventions this uses. This means that you should be able to directly create a Job that launches your target pod, and a Service that connects to it, and get the normal Kubernetes features around this. (For example, servicename.namespacename.svc.cluster.local is a valid DNS name that reaches any Pod connected to the Service.)
You should also consider whether you actually need this sort of interface. For many applications, it will work just as well to deploy some sort of message-queue system (e.g., RabbitMQ) and then launch a pool of workers that connects to it. You can control the size of the worker queue using a Deployment. This is easier to develop since it avoids a hard dependency on Kubernetes, and easier to manage since it prevents a flood of dynamic jobs from overwhelming your cluster.
I know just the bare minimum of Kubernetes. However, I wanted to know if there would be any benefit in running 2 containers in a single pod:
1 Container running the application (e.g. a NodeJS app)
1 Container running the corresponding local database (e.g. a PouchDB database)
Would this would increase performance or the down-sides of coupling the two containers would overcome any benefits?
Pods, are designed to put together containers that share the same lifecyle. Containers inside the same pod, share some namespaces (like networking) and volumes.
This way, coupling an app with its database could look like a good idea, because the app could just connect to the database through localhost, etc. But it is not! As Diego Velez pointed out, one of the first limitations you could face is scaling your app. If you couple your app with your database, you are forced to scale your database whenever you scale your app, what is not optimal at all and prevents you from benefit of one of the main benefits of using a container orchestrator like kubernetes.
Some good use cases are:
Container with app + container with agent for app metrics, ci agents, etc.
CI/CD container (like jenkins agents) + container(s) with tools for CI/CD.
Container with app + container with proxy (like in istio making use of the sidecar pattern).
Lets say you neeed to scale your app (the pod), what would happen is that the DB will also be scaled, and that will cause an error because it is not set to be a cluster, just a single node.
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.