A presentation at Incontro DevOps Italia by Horacio Gonzalez
Kubernetes Operators: Operating Cloud Native services at scale Horacio Gonzalez 2021-02-05
Who are we? Introducing myself and introducing OVH OVHcloud
Horacio Gonzalez @LostInBrittany Spaniard lost in Brittany, developer, dreamer and all-around geek Flutter
OVHcloud: A global leader Web Cloud & Telcom 30 Data Centers in 12 locations 1 Million+ Servers produced since 1999 Private Cloud 34 Points of Presence on a 20 TBPS Bandwidth Network 1.5 Million Customers across 132 countries Public Cloud 2200 Employees worldwide 3.8 Million Websites hosting Storage 115K Private Cloud VMS running 1.5 Billion Euros Invested since 2016 300K Public Cloud instances running P.U.E. 1.09 Energy efficiency indicator 380K Physical Servers running in our data centers 20+ Years in Business Disrupting since 1999 Network & Security
High performance at affordable prices From bare-metal servers to public or private cloud
Kubernetes Operators Helping to tame the complexity of K8s Ops
Taming microservices with Kubernetes
What about complex deployments
Specially at scale Lots of clusters with lots and lots of deployments
That’s just our case We both use Kubernetes and operate a Managed Kubernetes platform
Built over our Openstack based Public Cloud
We need to tame the complexity
Taming the complexity
Helm Charts are configuration Operating is more than installs & upgrades
Kubernetes is about automation How about automating human operators?
Kubernetes Operators A Kubernetes version of the human operator
Building operators Basic K8s elements: Controllers and Custom Resources
Kubernetes Controllers Keeping an eye on the resources
A control loop They watch the state of the cluster, and make or request changes where needed
A reconcile loop Strives to reconcile current state and desired state
Custom Resource Definitions Extending Kubernetes API
Extending Kubernetes API By defining new types of resources
Kubernetes Operator Automating operations
What’s a Kubernetes Operator?
Example: databases Things like adding an instance to a pool, doing a backup, sharding…
Knowledge encoded in CRDs and Controllers
Custom Controllers for Custom Resources Operators implement and manage Custom Resources using custom reconciliation logic
Operator Capability Model Gauging the operator maturity
How to write an Operator
Kubebuilder SDK for building Kubernetes APIs using CRDs
The Operator Framework Open source framework to accelerate the development of an Operator
Operator SDK Three different ways to build an Operator
Operator SDK and Capability Model
Operator Lifecycle Manager
OperatorHub.io
Harbor Operator Managing private registries at scale
We wanted to build a new product OVHcloud Managed Private Registry
Looking at the Open Source world Two main alternatives around Docker Registry
Harbor has more community traction Two main alternatives
Harbor has lots of components
But it has a Helm Chart It should be easy to install, isn’t it? $ helm install harbor What about configuration? Installing a 200 GB K8s volume? Nginx pods for routing requests? One DB instance per customer? Managing pods all around the cluster?
We wanted a Managed Private Registry
Using the platform Kubernetes tooling to the rescue
Let’s automate it We needed an operator… and there wasn’t any
Working with the community Harbor community also needed the operator
The challenge: reconciliation loop
The Harbor Operator
It’s Open Source https://github.com/goharbor/harbor-operator
LoadBalancer Operator A managed LoadBalancer at scale
Load Balancer: a critical cog Cornerstone of any Cloud Provider’s infrastructure
Our legacy Load Balancer stack ● Excellent performances ○ Built on bare metal servers + BGP ○ Custom made servers tuned for network traffic ● Carry the TLS termination ○ SSL / LetsEncrypt ● Not cloud ready ○ Piloted by configuration files ○ Long configuration loading time ● Custom made hardware ○ Slower to build ○ Needs to be deployed on 30 datacenters
Our needs for a new Load Balancer ● Supporting mass update ● Quickly reconfigurable ● Available anywhere quickly ● Easily operable ● Integrated into our Public Cloud
Building it on Kubernetes
A Load Balancer in a pod
Orchestrating one million LBs… kubectl apply -f lb is not an option!
We needed an Operator
Network: multus-cni Attaching multiple network interfaces to pods: Bridge + Host-local
Adding network interfaces on the fly Using annotations to add interfaces to pod
Config management Using Config Map How to detect a change on Config Map files? Watch + Trigger? More information on Config Map working martensson.io/go-fsnotify-and-kubernetes-configmaps
A Controller to watch and trigger
Observability Tried Prometheus Operator, limited to one container per pod Switched to Warp 10 with Beamium Operator
That’s all, folks! Thank you all!
Operators are extensions to Kubernetes that simplify application install and management by leveraging on manage applications Custom Resources.
The Kubernetes Operator pattern tries the emulate the role of an human operator, who uses their deep knowledge of the application to install, operate and debug it. The Kubernetes Operators search to automate these tasks and facilitate the whole application life-cycle.
In this talk, we will explain how do we use Kubernetes Operators at OVHcloud, and how the help us to operate our Managed Kubernetes service at scale.
We will illustrate the talks with three concrete examples: Harbor Operator, LoadBalancing Operator and our incoming NodePool operator.
The following resources were mentioned during the presentation or are useful additional information.
