I came across this article http://www.networkworld.com/article/3100383/cloud-computing/the-worlds-of-openstack-and-containers-are-colliding.html. It talks about openstack running atop kubernetes. What does that actually mean? Going by what they do, openstack is more lower level (IAAS) compared to kubernetes (between IAAS and PAAS), as per my understanding.
There are many ways containers and OpenStack are being mixed. The article you quoted refers to a new-ish approach of running OpenStack servers inside containers. The advantage is for maintainability and scalability. Basically, kubernetes is in charge of orchestrating the various pieces that make an OpenStack service, instead of the more general approach of installing OpenStack services on bare metal or VM (see TripleO).
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I’m trying to figure out and learn the patterns and best practices on moving a bunch of Docker containers I have for an application into Kubernetes. Things like, pod design, services, deployments, etc. For example, I could create a Pod with the single web and application containers in them, but that’d not be a good design.
Searching for things like architecture and design with Kubernetes just seems to yield topics on the product’s architecture or how to implement a Kubernetes cluster, and not the overlay of designing the pods, services, etc.
What does the community generally refer to this application later design in the Kubernetes world, and can anyone refer me to a 101 on this topic please?
Thanks.
Kubernetes is a complex system, and learning step by step is the best way to gain expertise. What I recommend you is documentation about Kubernetes, from where you can learn about each of components.
Another good option is to review 70 best K8S tutorials, which are categorized in many ways.
Designing and running applications with scalability, portability, and robustness in mind can be challenging. Here are great resources about it:
Architecting applications for Kubernetes
Using Kubernetes in production, lessons learned
Kubernetes Design Principles from Google
Well, there's no Kubernetes approach but rather a Cloud Native one: I would suggest you Designing Distributed Systems: patterns and paradigms by Brendan Burns.
It's really good because it provides several scenarios along with pattern approached and related code.
Most of the examples are obviously based on Kubernetes but I think that the implementation is not so important, since you have to understand why and when to use an Ambassador pattern or a FaaS according to the application needs.
The answer to this can be quite complex and that's why it is important that software/platform architects understand K8s well.
Mostly you will find an answer on that which tells you "put each application component in a single pod". And basically that's correct as the main reason for K8s is high availability, fault tolerance of the infrastructure and things like this. This leads us to, if you put every single component to a single pod and make it with a replica higher than 2 its will reach a batter availability.
But you also need to know why you want to go to K8s. At the moment it is a trending topic. But if you don't want to Ops a cluster and actually don't need HA or so, why you don't run on stuff like AWS ECS, Digital Ocean droplets and co?
Best answers you will currently find are all around how to design and cut microservices as each microservice could be represented in a pod. Also, a good starting point is from RedHat Principles of container-based Application Design
or InfoQ.
Un kubernetes cluster is composed of:
A master server called control plane
Nodes: nodes which execute the applications / Containers or pods
By design, a production kubernetes cluster must have at least a master server and 2 nodes according to the kubernetes documentation.
Here is a summary of the components of a kubernetes cluster:
Master = control plane:
kube-api-server: expose the kubernetes api
etcd: key values store for the cluster
kube-scheduler: distributed the pods on the nodes
kube-controller-manager: controller of nodes, pods, cluster components.
Nodes = Servers that run applications
Kubelet: runs on each node, It makes sure that the containers are running in a pod.
kube-proxy: Allows the pods to communicate in the cluster and outside
Runtine container: allows to run the containers / pods
Complementary modules = addons
DNS: DNS server that serves DNS records for Kubernetes services.
Webui: Graphical dashboard for the cluster
Container Resource Monitoring: Records metrics on containers in a central DB, provides UI to browse them
Cluster-level Logging: Records container logs in a central log with a search / browse interface.
I am evaluating Kubernetes (with Docker containers, not Kubernetes) and Docker Swarm and could use your input.
If I'm looking at 3 (8.76 hours) or 4 (52 min) 9's reliability in a server farm that is < 100 servers, would Kubernetes be overkill due to its complexity? Would Docker Swarm suffice?
Docker swarm will be able to meet your requirements. I recommend you start with Docker swarm as it is robust and very straightforward to use for anyone who has used Docker before.
For a Docker user, there are many new concepts that you need to learn to be able to use Kubernetes. Moreover, setting up Kubernetes on premise without using a preconfigured cloud platform is not straightforward
On the other hand, Kubernetes is more flexible and extensible. Kubernetes is older than Docker swarm and the community for kubernetes community is really big.
It really depends on your real needs, Kubernetes or Swarm orchestrators are not silver bullets. To take real advantage from the container technology, the applications have to be properly designed. A design guideline for these cloud native apps are the Twelve Factor app principles made by Heroku.
In case you want to scale and achieve global scaling, Kubernetes is a great framework to run distributed apps at scale. In case you have a lot of Java apps, maybe containerized traditional applications then Swarm is a best option.
The business requirements can drive you to make the right choice.
Hope this helps!
I have been looking into Docker containerization for a while now but few things are still confusing to me. I understand that all the containers are grouped into a cluster and cluster management tools like Docker Swarm, DC/OS, Kubernetes or Rancher can be used to manage docker containers. I have been testing out Container cluster management with DC/OS and Kubernetes, but still a few questions remain unanswered to me.
How does auto scaling in container level help us in production servers? How does the application serve traffic from multiple containers?
Suppose we have deployed a web application using containers and they have auto scaled. How does the traffic flow to the containers? How are the sessions managed?
What metrics are calculated for autoscaling containers?
The autoscaling in DC/OS (note: Mesosphere is the company, DC/OS the open source project) the autoscaling is described in detail in the docs. Essentially the same as with Kubernetes, you can use either low-level metrics such as CPU utilization to decide when to increase the number of instances of an app or higher-level stuff like app throughput, for example using the Microscaling approach.
Regarding your question how the routing works (how are requests forwarded to an instance, that is a single container running): you need a load balancer and again, DC/OS provides you with this out of the box. And again, the options are detailed out in the docs, essentially: HAProxy-based North-South or IPtables-based, East-West (cluster internal) load balancers.
Kubernetes has concept called service. A Kubernetes Service is an abstraction which defines a logical set of Pods and a policy by which to access them. Kubernetes uses services to serve traffic from multiple containers. You can read more about services here.
AFAIK, Sessions are managed outside kubernetes, but Client-IP based session affinity can be selected by setting service.spec.sessionAffinity to "ClientIP". You can read more about Service and session affinity here
Multiple metrics like cpu and memory can be used for autoscaling containers. There is a good blog you can read about autoscaling, when and how.
Recently some alternatives for running docker containers or even the app container have developed.
I know that there is rkt from coreos (https://coreos.com/blog/rocket/) and triton from joyent (https://www.joyent.com/)
How do these two approaches compare?
Edit
Maybe I should re-phrase my question after these good comments from # Lakatos Gyula
How does Triton compare to coreos or kubernetes for running docker-containers at scale?
So in a way, this is an apples to oranges to grapes comparison. CoreOS is an operating system, Kubernetes is open source container orchestration software, and Triton is a PaaS.
So CoreOS, it's a minimal operating system with a focus on security. I've been using this in production for several months now at work, haven't found a reason to not like it yet. It does not have a package manager, but it comes preinstalled with both rkt and Docker. You can run both docker and rkt just fine on there. It also comes with Etcd, which is a distributed key-value store, and it happens that kubernetes is backed by it. It also comes with Flannel which is a networking program for networking between containers and machines in your cluster. CoreOS also ships with Fleet, which you can think of like a distributed version of systemd, which systemd is CoreOS' init system. And as of recently, CoreOS ships with Kubernetes itself.
Kubernetes is a container orchestration software that is made up of a few main components. There are masters, which use the APIServer, controller and scheduler to manage the cluster. And there are nodes which use the "kubelet" and kube-proxy". Through these components, Kubernetes schedules and manages where to run your containers on your cluster. As of v1.1 Kubernetes also can auto-scale your containers. I also have been using this in production as long as I have been using CoreOS, and the two go together very well.
Triton is Joyent's Paas for Docker. Think of it like Joyent's traditional service, but instead of BSD jails (similar concept to Linux containers) and at one point Solaris Zones (could be wrong on that one, that was just something I heard from word of mouth), you're using Docker containers. This does abstract away a lot of the work you'd have to do with setting up CoreOS and Kubernetes, that said there are services that'll do the same and use kubernetes under the hood. Now I haven't used Triton like I have used Kubernetes and CoreOS, but it definitely seems to be quite well engineered.
Ultimately, I'd say it's about your needs. Do you need flexibility and visibility, then something like CoreOS makes sense, particularly with Kubernetes. If you want that abstracted away and have these things handled for you, I'd say Triton makes sense.
From what I understand, Kubernetes/Mesosphere is a cluster manager and Docker Swarm is an orchestration tool. I am trying to understand how they are different? Is Docker Swarm analogous to the POSIX API in the Docker world while Kubernetes/Mesosphere are different implementations? Or are they different layers?
Disclosure: I'm a lead engineer on Kubernetes
Kubernetes is a cluster orchestration system inspired by the container orchestration that runs at Google. Built by many of the same engineers who built that system. It was designed from the ground up to be an environment for building distributed applications from containers. It includes primitives for replication and service discovery as core primitives, where-as such things are added via frameworks in Mesos. The primary goal of Kubernetes is a system for building, running and managing distributed systems.
Swarm is an effort by Docker to extend the existing Docker API to make a cluster of machines look like a single Docker API. Fundamentally, our experience at Google and elsewhere indicates that the node API is insufficient for a cluster API. You can see a bunch of discussion on this here: https://github.com/docker/docker/pull/8859 and here: https://github.com/docker/docker/issues/8781
Swarm is a very simple add-on to Docker. It currently does not provide all the features of Kubernetes. It is currently hard to predict how the ecosystem of these tools will play out, it's possible that Kubernetes will make use of Swarm.