Can I use docker to automatically spawn instances of whole microservices? - docker

I have a microservice with about 6 seperate components.
I am looking to sell instances of this microservice to people who need dedicated versions of it for their project.
Docker seems to be the solution to doing this as easily as possible.
What is still very unclear to me is, is it possible to use docker to deploy whole instances of microservices within a cloud service like GCP or AWS?
Is this something more specific to the Cloud provider itself?
Basicly in the end, I'd like to be able to, via code, start up a whole new instance of my microservice within its own network having each component be able to speak to eachother.
One big problem I see is assigning IP's to the containers so that they will find each other, independent of which network they are in. Is this even possible or is this not yet feasible with current cloud techonology?
Thanks a lot in advance, I know this is a big one...

They is definitely feasible and is nowadays one of the most popular ways to ship and deploy applications. However, the procedure to deploy varies slightly based on the cloud provider that you choose.
The good news is that the packaging of your microservices with Docker is independent from the cloud provider you use. You basically need to package each component in a Docker image, and deploy these images to a cloud platform.
All popular cloud platforms nowadays support deployment of docker containers. You can use in addition popular frameworks such as Docker swarm or Kubernetes on these cloud platforms to orchestrate the microservices deployment.

Related

Does a simple monolith application need kubernetes to manage

I'm very new to the infrastructure so I built a simple monolith application and I use docker for building a container and deploy it on my linux server. My question is, do I need to install kubernetes for a single container and if no how can I scale or do the load balancing.
"... do I need to install kubernetes for a single container" - No, it is not mandatory. One can use docker to manage applications. Kubernetes is a platform that can be used to orchestrate containerized applications. It offers tools and concepts like autoscaling based on load, isolation through namespaces, network access management through services and ingresses, and much more. But Kubernetes is not the only platform for orchestration. There are others, for example OpenShift, docker swarm, rancher. All those are optional platforms with additional tooling and concepts that can be used if necessary.
"how can I scale or do the load balancing." - We can, for example, define the replicas through the replicas variable in a docker-compose file. All containers defined under a service are accessed through this service's name. How exactly the balancing is done can also be configured through the endpoint_mode configuration. If we need even more control, we can deploy a separate load balancer, e.g. nginx. A possible configuration is described in this medium article.
For future posts, please limit yourself to one question per post.

Automated deployment of a dockerized application on a single machine

I have a web application consisting of a few services - web, DB and a job queue/worker. I host everything on a single Google VM and my deployment process is very simple and naive:
I manually install all services like the database on the VM
a bash script scheduled by crontab polls a remote git repository for changes every N minutes
if there were changes, it would simply restart all services using supervisord (job queue, web, etc)
Now, I am starting a new web project where I enjoy using docker-compose for local development. However, I seem to suck in analysis paralysis deciding between available options for production deployment - I looked at Kubernetes, Swarm, docker-compose, container registries and etc.
I am looking for a recipe that will keep me productive with a single machine deployment. Ideally, I should be able to scale it to multiple machines when the time comes, but simplicity and staying frugal (one machine) is more important for now. I want to consider 2 options - when the VM already exists and when a new bare VM can be allocated specifically for this application.
I wonder if docker-compose is a reasonable choice for a simple web application. Do people use it in production and if so, how does the entire process look like from bare VM to rolling out an updated application? Do people use Kubernetes or Swarm for a simple single-machine deployment or is it an overkill?
I wonder if docker-compose is a reasonable choice for a simple web application.
It can be, sure, if the development time is best spent focused on the web application and less on the non-web stuff such as the job queue and database. The other asterisk is whether the development environment works ok with hot-reloads or port-forwarding and that kind of jazz. I say it's a reasonable choice because 99% of the work of creating an application suitable for use in a clustered environment is the work of containerizing the application. So if the app already works under docker-compose, then it is with high likelihood that you can take the docker image that is constructed on behalf of docker-compose and roll it out to the cluster.
Do people use it in production
I hope not; I am sure there are people who use docker-compose to run in production, just like there are people that use Windows batch files to deploy, but don't be that person.
Do people use Kubernetes or Swarm for a simple single-machine deployment or is it an overkill?
Similarly, don't be a person that deploys the entire application on a single virtual machine or be mentally prepared for one failure to wipe out everything that you value. That's part of what clustering technologies are designed to protect against: one mistake taking down the entirety of the application, web, queuing, and persistence all in one fell swoop.
Now whether deploying kubernetes for your situation is "overkill" or not depends on whether you get benefit from the other things that kubernetes brings aside from mere scaling. We get benefit from developer empowerment, log aggregation, CPU and resource limits, the ability to take down one Node without introducing any drama, secrets management, configuration management, using a small number of Nodes for a large number of hosted applications (unlike creating a single virtual machine per deployed application because the deployments have no discipline over the placement of config file or ports or whatever). I can keep going, because kubernetes is truly magical; but, as many people will point out, it is not zero human cost to successfully run a cluster.
Many companies I have worked with are shifting their entire production environment towards Kubernetes. That makes sense because all cloud providers are currently pushing Kubernetes and we can be quite positive about Kubernetes being the future of cloud-based deployment. If your application is meant to run in any private or public cloud, I would personally choose Kubernetes as operating platform for it. If you plan to add additional services, you will be easily able to connect them and scale your infrastructure with a growing number of requests to your application. However, if you already know that you do not expect to scale your application, it may be over-powered to use a Kubernetes cluster to run it although Google Cloud etc. make it fairly easy to setup such a cluster with a few clicks.
Regarding an automated development workflow for Kubernetes, you can take a look at my answer to this question: How to best utilize Kubernetes/minikube DNS for local development

Does it makes sense to manage Docker containers of a/few single hosts with Kubernetes?

I'm using docker on a bare metal server. I'm pretty happy with docker-compose to configure and setup applications.
Still some features are missing, like configuration management and monitoring maybe there are other solutions to solve this issues but I'm a bit overwhelmed by the feature set of Kubernetes and can't judge if it would help me here.
I'm also open for recommendations to solve the requirements separately:
Configuration / Secret management
Monitoring of my docker hostes applications (e.g. having some kind of dashboard)
Remot container control (SSH is okay with only one Server)
Being ready to scale my environment (based on multiple different Dockerized applications) to more than one server in future - already thinking about networking/service discovery issues with a pure docker-compose setup
I'm sure Kubernetes covers some of these features, but I have the feeling that it's too much focused on Cloud platforms where Machines are created on the fly (since I only have at most few bare metal Servers)
I hope the questions scope is not too broad, else please use the comment section and help me to narrow down the question.
Thanks.
I think the Kubernetes is absolutely much your requests and it is what you need.
Let's start one by one.
I have the feeling that it's too much focused on Cloud platforms where Machines are created on the fly (since I only have at most few bare metal Servers)
No, it is not focused on Clouds. Kubernates can be installed almost on any bare-metal platform (include ARM) and have many tools and instructions which can help you to do it. Also, it is easy to deploy it on your local PC using Minikube, which will prepare local cluster for you within VMs or right in your OS (only for Linux).
Configuration / Secret management
Kubernates has a powerful configuration and management based on special objects which can be attached to your containers. You can read more about configuration management in that article.
Moreover, some tools like Helm can provide you more automation and range of preconfigured applications, which you can install using a single command. And you can prepare your own charts for it.
Monitoring of my docker hostes applications (e.g. having some kind of dashboard)
Kubernetes has its own dashboard where you can get many kinds of information: current applications status, configuration, statistics and many more. Also, Kubernetes has great integration with Heapster which can be used with Grafana for powerful visualization of almost anything.
Remot container control (SSH is okay with only one Server)
Kubernetes controlling tool kubectl can get logs and connect to containers in the cluster without any problems. As an example, to connect a container "myapp" you just need to call kubectl exec -it myapp sh, and you will get sh session in the container. Also, you can connect to any application inside your cluster using kubectl proxy command, which will forward a port you need to your PC.
Being ready to scale my environment (based on multiple different Dockerized applications) to more than one server in future - already thinking about networking/service discovery issues with a pure docker-compose setup
Kubernetes can be scaled up to thousands of nodes. Or can have only one. It is your choice. Independent of a cluster size, you will get production-grade networking, service discovery and load balancing.
So, do not afraid, just try to use it locally with Minikube. It will make many of operation tasks more simple, not more complex.

Linking many containers in Docker

Let's say I have a Java EE application which requires a database + I would also like to use apache.
Now, is it better to make a single image containing all three pieces or 3 containers for each of these and use the docker networking (linking is deprecated, right?) to connect them?
You can also use built-in Docker swarm mode. This gives you built in encryption for passing your secrets around, such as the database login. Here's an official Docker sample app that shows how to do a Java Spring Boot app connecting to a database with each service separated.
Docker is a lightweight solution for isolating applications. So if you have 3 different applications, you will almost always run those in 3 separate containers. Some of the advantages that gives you are:
The ability to independently scale each component
The ability to run components on different hosts
The ability to independently upgrade one component without impacting the others
The only time I merge application components into a single container is when they cannot communicate through a networking API, and they really need filesystem- and process-level integration between the parts.

Container delivery on amazon ecs

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.

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