Thanks for attending this workshop about building Kubernetes operators!
My name is Luke Bond, and I work for the UK government as a DevOps engineer, working with Docker and Kubernetes.
Any questions or follow-up, you can reach me at @lukeb0nd on Twitter, or you can email me at [email protected].
Here is what we're going to cover:
- A brief introduction to the concept of operators
- An overview of CoreOS's Etcd operator, as an example and a model for us to follow
- The practical workshop:
- Preliminaries: getting the code, using Katacoda, minikube, etc.
- Third party resources
- Watching for events
- Working towards a skeleton Postgres operator
The codebase with which we're working is based directly on the Etcd operator. I've basically stripped it down to its most basic form, removing anything Etcd- specific, and put in placeholders for Postgres functionality, in order to demonstrate what's common to the operator pattern. This isn't original code, it's mostly copy-paste!
We only have a few hours! Since this is a short workshop, I'm not able to take you from zero to a production-ready Postgres operator in that time.
The Etcd operator is written in Golang, and therefore so will our workshop be. This is not a Golang workshop, and I'm not a Golang expert. If there is one thing I want you to take away from this, it's the demystification of operators; a conceptual understanding of what's involved in building one.
I expect you to have:
- Some coding experience; at least enough to be able to read code and have an idea of what it's doing
- Ability to use a terminal and a text editor
- Basic Git skills
- Basic Docker experience
- A basic working knowledge of Kubernetes core concepts and familiarity
with
kubectl
If you don't have some, or any, of these, don't panic. I think there is some value to be gained from being here, reading the material and looking at the code. After all, the main take-away is about comprehension, not coding.
You will need to have a working Minikube environment, as well as Git and kubectl:
https://kubernetes.io/docs/tasks/tools/install-minikube/ https://kubernetes.io/docs/tasks/tools/install-kubectl/
Kubernetes' job is to run containerised applications and to manage their configuration, storage, load balancing, service discovery and scaling. Kubernetes is entirely API-driven: whatever Kubernetes itself can do, you can also do using the API. The API is also highly extensible.
The above reveals the fact that Kubernetes was designed with automation in mind from day one. Just as API-powered cloud providers made possible the era of infrastructure-as-code and the automation of previously manual infrastrucure tasks, so does Kubernetes make possible "no-ops", or the complete automation of the deployment and management of containerised software on Kubernetes, once the domain of high bus-factor sysadmins.
Getting the concept of operators can be difficult at first, because of the amount of DevOps and Kubernetes jargon involved, but the concept is actually quite simple: it is the automation of operational and maintenance tasks on a Kubernetes cluster.
Kubernetes does a lot for you in terms of launching your applications and keeping them running, but what it can't or won't do for you is application- specific things like database node failover and backups. Basically, anything that falls outside the 12-Factor App philosophy (i.e. stateful applications). This could be databases or "legacy" stateful applications that don't like to be moved about (perhaps they store files on disk).
Databases are very specialised applications. Most of them were written before the era of PaaS and containers. The process expects its data on disk to persist across executions. They don't expect to be moved from one host to another. In short, they're not cloud-native. Aside from their storage requirements, they also differ widely from one database to the next: operations such as node fail-over and backup are not the same for any two databases, and the knowledge of how to perform these operations resides, by and large, in the heads and run-books of sysadmins.
Kubernetes allows us to extend the API to define our high-maintenance, stateful apps as resource types that Kubernetes recognises, and we can then write code against the Kubernetes API to monitor and manipulate these resources. This is a powerful concept. The astute will understand that the gap between having Kubernetes APIs available on the one hand and replacing experienced sysadmins with a few lines of Golang on the other is a veritable chasm, but we can benefit a lot from the simplest of operators.
For a more detailed introduction to operators, see my slides from a recent talk on the subject:
https://github.com/lukebond/coreos-london-operators-20170124
CoreOS were the first to introduce the concept of the operator, with the announcement of the release of the Etcd operator in November 2016. The announcement blog post serves as a vision statement for the future of operations as well as a set of guidelines for how to build Kubernetes automation software that follows the operator pattern.
The core of the operator pattern is the "observe, analyse, act" cycle, which aligns nicely with the declarative nature of Kubernetes resources such as ReplicaSets.
- Observe - fetch the state of the cluster (poll or watch)
- Analyse - compare the observed state with the desired state, and determine the actions that will bring the system to the desired state
- Act - perform the actions in order to bring the system towards the desired state
For example, an Etcd cluster may have a size of 3 before the operator is asked to scale it up to 5. The operator observes that there are 3 nodes, it analyses this information and concludes that it needs to act to spin up two more nodes.
The code for the Etcd operator can be found here:
The code we're working with today is taken from the Etcd operator codebase a
few months ago, at commit SHA 11d6afff17abd9708909b06324d4c272920701f2.
Ensure your minikube installation is functioning:
$ minikube status
minikubeVM: Running
localkube: Running
If you don't see this you may need to start one:
$ minikube start
If you have trouble getting it started, try a minikube delete before
running minikube start.
Clone my Postgres operator codebase:
$ git clone https://gitlab.com/lukebond/postgres-operator.git
Check that kubectl is pointing to your local cluster:
$ kubectl config current-context
minikube
$ kubectl get pods
No resources found
You don't need to be able to build and run the code in my repository as I've already built and pushed Docker images for the three stages of the workshop. Unless you're particularly interested in editing the code, you don't need to do the following steps. However, if you'd like to play with the code you can build it like so (you will need a working Golang build environment:
$ make build
On successful build it will create a Docker image locally on your laptop. To get that onto minikube, I find the easiest way is to export it from your laptop's Docker daemon and then import it into minikube.
$ docker save quay.io/lukebond/postgres-operator:workshop-01 -o postgres-operator-workshop-01.tar
$ minikube mount .
Mounting . into /mount-9p on the minikubeVM
This daemon process needs to stay alive for the mount to still be accessible...
ufs starting
^z
$ bg
$ minikube ssh
$ chmod 666 /mount-9p/postgres-operator-workshop-01.tar
$ docker load -i /mount-9p/postgres-operator-workshop-01.tar
This will load your latest built image into the Docker daemon in Minikube.
If you're familiar with Kubernetes you will have heard of Pods, Services, ReplicationControllers and the like. These are in-built Kubernetes Resources. They are entities in the Kubernetes API, with a schema, and there are various commands that can be performed on them.
Kubernetes allows us to define our own resources, which are called Third Party Resources (TPR). An operator's first task is to register a TPR for the service it is managing. For example, the Etcd operator registers a TPR called "EtcdCluster". We will be registering one called "PostgresOperator".
The Kubernetes client library in Golang makes it very simple to register a TPR:
func createTpr() error {
tpr := &v1beta1extensions.ThirdPartyResource{
ObjectMeta: v1.ObjectMeta{
Name: "postgres-cluster.lukeb0nd.com",
},
Versions: []v1beta1extensions.APIVersion{
{Name: "v1"},
},
Description: "Semi-automatic PostgreSQL cluster",
}
_, err := c.KubeCli.Extensions().ThirdPartyResources().Create(tpr)
if err != nil {
return err
}
return nil
}
This is the first step in building our operator. Check out the branch
workshop-01 to see the code for an operator that simply registers a TPR and
then stops.
$ git checkout workshop-01
Read through the code and try to understand it. There is a bit of boilerplate,
but start with main() in cmd/operator/main.go, see how the Kubernetes
client is configured and the operator is launched. Then focus on
pkg/controller/controller.go, in particular the call to
KubeCli.Extensions().ThirdPartyResources().Create(tpr).
This branch has been built into a container, tagged and pushed to a repository
on quay.io: quay.io/lukebond/postgres-operator:workshop-01.
We can run this on Minikube using the yaml file provided in the repository:
$ kubectl create -f kube/deployment.yaml
deployment "postgres-operator" created
We can see that a TPR has been created as a result:
$ kubectl get thirdpartyresources
NAME DESCRIPTION VERSION(S)
postgres-cluster.lukeb0nd.com Semi-automatic PostgreSQL cluster v1
To demonstrate that we've extended the Kubernetes API, we can observe that some new endpoints are now available:
$ kubectl proxy --port=8080 &
$ curl 127.0.0.1:8080/apis/lukeb0nd.com/v1
{
"kind": "APIResourceList",
"apiVersion": "v1",
"groupVersion": "lukeb0nd.com/v1",
"resources": [
{
"name": "postgresclusters",
"namespaced": true,
"kind": "PostgresCluster",
"verbs": [
"delete",
"deletecollection",
"get",
"list",
"patch",
"create",
"update",
"watch"
]
}
]
We'll be working with some of these endpoints in the upcoming sections.
Now that we have a TPR of our own, what to do with it? We can create an
instance of that resource as well as watch Etcd for changes to it. The
creation of an instance of this resource will come through as a change in
Etcd. In this part of the workshop we will create a monitor() function that
will detect and print out these changes.
Check out the branch and explore the code:
$ git checkout workshop-02
In particular, note the addition of the call to findAllClusters() in
initResource(), and the watchVersion value that it returns. This variable
is the Etcd version number of the latest version of our PostgresCluster
Kubernetes resource, which increases with each change made to our cluster. We
use it when watching Etcd for changes, as we are basically saying to Etcd
"tell me of all changes since this version". Therefore it's important to
determine it at startup.
Kubernetes uses Etcd natively to store information about the state of what's running in the cluster. Watching Etcd for changes is a common operation when writing code that interacts with Kubernetes, as operators do.
Also note the addition of the call to monitor() in the Run function in
the controller. This is the function that performs an Etcd watch based on the
version number fetched previously.
The monitor() function does an HTTP request to the Kubernetes API with
watch=true, which means an HTTP long poll. The HTTP body returned gets
parsed by a JSON decoder and unmarshalled into either an object of type
Status or Error, objects we've defined in controller.go.
The monitor() function uses an event and an error channel to communicate
events back to the calling function (Run()), where we print them out to the
console.
Notice that in the kube directory there is a new file
example-postgres-cluster.yaml. Running kubectl create -f on this file will
tell Kubernetes to create a new instance of type PostgresCluster that we
registered when we launch the operator. Eventually, this will actually
launch Postgres containers on the cluster, but for now we'll use it to trigger
the event monitoring we just added. It will result in the ADDED event being
logged by the operator, which is printed out in Run() in controller.go.
First remove what we previously deployed so that we have a clean slate:
$ kubectl delete deployment postgres-operator
$ kubectl delete thirdpartyresources postgres-cluster.lukeb0nd.com
Now deploy our new operator and then create a PostgresCluster:
$ kubectl create -f kube/deployment.yaml
deployment "postgres-operator" created
$ kubectl create -f kube/example-postgres-cluster.yaml
postgrescluster "example-postgresql-cluster" created
Now if we check the logs for our operator, we should see the ADDED message:
$ kubectl get pods
NAME READY STATUS RESTARTS AGE
postgres-operator-1337880999-ph9md 1/1 Running 1 11m
$ kubectl logs postgres-operator-1337880999-ph9md
Third-party resource already exists; continuing
Finding existing clusters...
Watch version: %s 4566
Controller initialised
Starting at watchVersion %v 0
Postgres cluster event: %v %v ADDED &{3 9.6.3 map[] false}
&{ADDED 0xc42034e5a0}
Let's modify the cluster and see what happens. Open up kube/example-postgres-cluster.yaml
in a text editor (e.g. vim) and change the cluster size to 5. Now post it
to Kubernetes:
$ kubectl replace -f kube/example-postgres-cluster.yaml
postgrescluster "example-postgresql-cluster" replaced
$ kubectl logs postgres-operator-1337880999-ph9md
Third-party resource already exists; continuing
Finding existing clusters...
Watch version: %s 4566
Controller initialised
Starting at watchVersion %v 0
Postgres cluster event: %v %v ADDED &{3 9.6.3 map[] false}
&{ADDED 0xc42034e5a0}
Postgres cluster event: %v %v MODIFIED &{5 9.6.3 map[] false}
&{MODIFIED 0xc42034eb40}
You can see that the new cluster size of 5 is available in the event that is printed out here. Our operator will use this information to reconcile the cluster size.
Now try deleting the cluster:
$ kubectl delete -f kube/example-postgres-cluster.yaml
postgrescluster "example-postgresql-cluster" deleted
$ kubectl logs postgres-operator-1337880999-ph9md
Third-party resource already exists; continuing
Finding existing clusters...
Watch version: %s 4566
Controller initialised
Starting at watchVersion %v 0
Postgres cluster event: %v %v ADDED &{3 9.6.3 map[] false}
&{ADDED 0xc42034e5a0}
Postgres cluster event: %v %v MODIFIED &{5 9.6.3 map[] false}
&{MODIFIED 0xc42034eb40}
Postgres cluster event: %v %v DELETED &{5 9.6.3 map[] false}
&{DELETED 0xc420136240}
We've learned the basics of watching Etcd for changes to our Third Party Resource. Let's look a bit more deeply into what's going on here, and extend it a little to show how an operator might reconcile a cluster to a desired configuration.
After the monitor() function has completed and pushed events onto the events
channel, we are currently iterating over them and printing them out. Let's
replace those printouts with some more detailed skeleton code.
One of the main additions is an event and error channel for each cluster.
Check out the branch:
$ git checkout workshop-03
Note the new code in the Run() function in controller.go, in the switch
statement. On ADDED, MODIFIED and DELETED events we are now calling out
to some new code. The new code in pkg/cluster/cluster.go in New(),
setup() and create() initialises the cluster state and then has a place-
holder printout that says "PLACEHOLDER: Launch seed Postgres node!". This is
where we'd start a Postgres container for the first node and bootstrap the
cluster from there. We won't get that far today.
In pkg/cluster/cluster.go we have new functions Update() and Delete()
that get called when the MODIFIED and DELETED events arrive. These two
functions just pushes the events onto the cluster's channel, using new event
types eventModifyCluster and eventDeleteCluster. These events are
handled in run() in pkg/cluster/cluster.go.
Have a read through the code I've pointed out and see if you can guess what you will see in the logs when you run it.
Once you're ready to find out, delete the previous operator to start from a clean slate:
$ kubectl delete deployment postgres-operator
$ kubectl delete thirdpartyresources postgres-cluster.lukeb0nd.com
Now deploy our new operator and then create a PostgresCluster:
$ kubectl create -f kube/deployment.yaml
deployment "postgres-operator" created
$ kubectl get thirdpartyresources
NAME DESCRIPTION VERSION(S)
postgres-cluster.lukeb0nd.com Semi-automatic PostgreSQL cluster v1
$ kubectl create -f kube/example-postgres-cluster.yaml
postgrescluster "example-postgresql-cluster" created
$ kubectl get pods
NAME READY STATUS RESTARTS AGE
postgres-operator-1449816488-xhs5d 1/1 Running 1 11m
$ kubectl logs postgres-operator-1449816488-xhs5d
Third-party resource already exists; continuing
Finding existing clusters...
Watch version: %s 15333
Controller initialised
Starting at watchVersion %v 0
Postgres cluster event: %v %v ADDED &{5 9.6.3 false map[] false}
&{ADDED 0xc420100480}
creating cluster with Spec (%#v), Status (%#v) &{5 9.6.3 false map[] false} <nil>
PLACEHOLDER: Launch seed Postgres node!
PLACEHOLDER: Start cluster!
Running: %v, pending: %v [] []
All Postgres pods are dead. Trying to recover from a previous backup
PLACEHOLDER: disaster recovery!
Was this close to what you expected?
What we're seeing here is a placeholder to create the seed Postgres node (but of course no such node was created), and then the operator declaring that the whole cluster is dead and needs to be restored from a backup.
If we had actually created the seed node we wouldn't have seen the disaster
message, but instead would have seen reconciliation related messages. Notice
that in the cluster run() function there is a timer to periodically
reconcile the cluster. It fetches the number of pods, compares it against the
desired state, and makes decisions about what to do.
This is the more complex part of the operator and you should spend some time reading the code and trying to understand it.
Or "homework" for the rest of us!
- Build the codebase yourself to create a Docker image for the operator
- Launch a seed Postgres node, using the Etcd operator as a guide, and a publically-available Postgres image (e.g. the official one)
- Reconcile the instance count to get a healthy cluster
- Simulate losing a node (hint: kubectl delete pod) and see if your operator can recover it
You've learned the basics of how to structure a Kubernetes operator written in Golang. It may seem that we didn't get very far towards a production-ready operator, but bear in mind that operators were only announced late last year, and there are only a handful of them that have been released. That fact that you're familiar with them and could start writing one soon already means you're ahead of most people!
Next time you're releasing stateful software onto Kubernetes, consider automating its operations by writing an operator.
For the sake of time I left out chaos monkey style testing for operators. CoreOS, in their guidelines for building operators, recommend these kind of tests. I discuss this in my recent talk, the link to which you can find above. It's really easy to add to your application, so do check it out!
Any questions or follow-up, you can reach me at @lukeb0nd on Twitter, or you can email me at [email protected].