#books/tech
Kubernetes was based on Borg, a container orchestrator used internally by Google.
This paper about Borg seems to be a valuable reading: https://research.google/pubs/pub43438.pdf
What makes Kubernetes so valuable?
Kubernetes do the things that the very best system administrator would do: automation, failover, centralized logging, monitoring. It takes what we've learned in the DevOps community and makes it the default, out of the box.
~ Kelsey Hightower
Oddly enough, despite the current excitement around Kubernetes, we may not be talking much about it in years to come. Many things that once were new and revolutionary are now so much part of the fabric of computing that we don't really think about them: microprocessors, the mouse, the internet.
Kubernetes, too, is likely to disappear and become part of the plumbing. It's boring, in a good way: once you learn what you need to know to deploy your application to Kubernetes, you're more or less done.
The future of Kubernetes is likely to lie largely in the realm of managed services. Virtualization, which was once an exciting new technology, has now simply become a utility. Most people rent virtual machines from a cloud provider rather than run their own virtualization platform, such as vSphere or Hyper-V.
In the same way, we think Kubernetes will become so much a standard part of the plumbing that you just won't know it's there anymore.
From "Cloud Native DevOps with Kubernetes" book.
(...) some things just aren't a good fit for Kubernetes (databases, for example).
While it's perfectly possible to run stateful workloads like databases in Kubernetes with enterprise-grade reliability, it requires a large investment of time and engineering that it may not make sense for your compatny to make. It's usually more cost-effective to use managed services instead.
By the time an engineering organization reaches ~75 people, there is almost certainly a central infrastructure team in place starting to build common substrate features required by product teams building microservices. But there comes a point at which the central infrastrucutre team can no longer both continue to build and operate the infrastructure critical to business success, while also maintaining the support burden of helping product teams with operational tasks.
~ Matt Klein
demo appRunning the demo container
docker container run \
-p 9999:8888 \
--name hello \
cloudnatived/demo:hello
And then access http://localhost:9999/
Building the demo image
The provided Dockerfile for the demo app (written in go) is interesting:
FROM golang:1.14-alpine AS build
WORKDIR /src/
COPY main.go go.* /src/
RUN CGO_ENABLED=0 go build -o /bin/demo
FROM scratch
COPY --from=build /bin/demo /bin/demo
ENTRYPOINT ["/bin/demo"]
It generates an image FROM scratch with only the demo binary. It is possible because "Go is a compiled language that can produce self-contained executables, it's ideal for writing minimal (scratch) containers."
git clone https://github.com/cloudnativedevops/demo
cd demo/hello
docker image build -t myhello .
# try to launch the image you've just created
docker container run -p 9999:8888 myhello
# test connection in localhost:9999
# creating a pod with the demo app
kubectl run demo \
--image=cloudnatived/demo:hello \
--labels app=demo
# get info about the pod
kubectl get all
kubectl describe pod/demo
# the demo by defaul is listening on port 8888
# let's make our machine listen on port 9999 and
# forward it to 8888
kubectl port-forward pod/demo 9999:8888
The cluster's brain is called the control plane.
Kubernetes Architecture
Components of a Master Node:
kube-apiserver: frontend server for the control plane, handling API requests.etcd: database where k8s stores all its information: what nodes exist, what resources exist on the cluster and so on.kube-scheduler: decides where to run newly created Pods.kube-controller-manager: responsible for running resource controllers, such as Deployments.The members of the cluster which run the control plane components are called master nodes.
Cluster members that run user workloads are called worker nodes.
Components of a Worker Node:
kubelet: responsible for driving the container runtime to start workloads that are scheduled on the node, and monitoring their status.kube-proxy: does the networking magic that routes request between Pods on differente nodes, and between Pods and the internet.