Serverless is a good pattern when it comes to saving infrastructure resources: why should you run apps when there’s nothing to do? The open source project Knative is often used to run functions as serverless apps in Kubernetes clusters. In this talk, you’ll see how to leverage Knative for Kubernetes apps, not only functions. Check out how to apply serverless patterns to an existing Spring Boot / Nodejs app (backend / frontend) with a live demo.

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Knative goes
beyond serverless
Alexandre Roman
Senior Solution Engineer, VMware Tanzu
November 2021

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@Alexandre_Roman 2
Alexandre Roman
Senior Solution Engineer, VMware Tanzu
@Alexandre_Roman
Welcome to this session!

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@Alexandre_Roman 3

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Pod Service
LoadBalancer
Ingress
Or?
Deployment
replicas
Not so easy
Deploying an application to Kubernetes

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The reality
Deploying an application to Kubernetes
TOO MUCH YAML

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We all agree, right?
What developers want
Write code
👍
Write infrastructure code
😵
💫

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An API simplifying the Kubernetes developer experience… and more
Introducing Knative

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apiVersion: serving.knative.dev/v1
kind: Service
metadata:
name: spring-on-k8s
spec:
template:
spec:
containers:
- image: alexandreroman/spring-on-k8s
A dream come true
A Kubernetes YAML descriptor that fits in a slide 😮
What you get as a result:
✅Pods running in your cluster
✅Managed by a Deployment / ReplicaSet
✅With “horizontal pod autoscaling”
✅Exposed a cluster internal service
✅Accessible through an ingress route
How cool is that?!?

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apiVersion: apps/v1
kind: Deployment
metadata:
name: spring-on-k8s
spec:
selector:
matchLabels:
role: app
template:
metadata:
labels:
role: app
spec:
containers:
- name: app
image: alexandreroman/spring-on-k8s:latest
imagePullPolicy: IfNotPresent
ports:
- name: http
containerPort: 8080
livenessProbe:
httpGet:
port: http
path: /actuator/health/liveness
readinessProbe:
httpGet:
port: http
path: /actuator/health/readiness
---
apiVersion: v1
kind: Service
metadata:
name: spring-on-k8s
spec:
type: ClusterIP
ports:
- port: 8080
protocol: TCP
targetPort: http
selector:
role: app
---
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: spring-on-k8s
spec:
rules:
- host: springonk8s.withtanzu.com
http:
paths:
- pathType: ImplementationSpecific
path: /
backend:
service:
name: spring-on-k8s
port:
number: 8080
---
apiVersion: autoscaling/v2beta2
kind: HorizontalPodAutoscaler
metadata:
name: spring-on-k8s
spec:
minReplicas: 1
maxReplicas: 8
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: spring-on-k8s
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 60
apiVersion: serving.knative.dev/v1
kind: Service
metadata:
name: spring-on-k8s
spec:
template:
spec:
containers:
- image: alexandreroman/spring-on-k8s
VS
Which one do you prefer?

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Knative features

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Node
Pod
Pod
Pod
Auto Scaling
HTTP Router
LoadBalancer
Knative Pod
Autoscaler
Queue-Proxy
Concurrency=1
User container
Kubernetes
apiserver
Kubelet
ReplicaSet
Goal: Scale container replicas based on request
rate.
Scaling based on request rate provides an earlier
signal than CPU usage and aligns well with
concurrency limits.
Solution: custom autoscaler that collects request
information from queue-proxy.
Count = 3
Requests = 3

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Node
Pod
Scale-to-Zero
HTTP Router
LoadBalancer
Activator
Queue-Proxy User container
Kubernetes
apiserver
ReplicaSet
Goal: Support scale-to-zero.
When user containers are finished processing
requests, allow all of them to be shut down and
the activator used instead.
Solution: The Knative controller rewrites the
HTTP routing rules when scaling to count=0 to
add the Activator to the Kubernetes service.
Controller
Count = 0

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Node
Pod
Scale-From-Zero
HTTP Router
LoadBalancer
Activator
Queue-Proxy User container
Kubernetes
apiserver
Kubelet
ReplicaSet
Goal: Support scale-from-zero.
Be able to start the user container on demand
when a request arrives for it.
Solution: The activator component stalls the
HTTP request until a user Pod is available to
handle it.
GET / HTTP/1.1

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Node
Pod
Pod
Advanced Rollout Support
HTTP Router
LoadBalancer
Queue-Proxy User container
ReplicaSet
Goal: Support percentage rollout of new features.
Small services may only receive enough traffic to
use one or two Pods. This makes it difficult to do a
good progressive rollout.
Solution: Knative supports percentage-based
traffic assignment to Revisions of a Service.
Node
Pod
Queue-Proxy User container
ReplicaSet
Percent = 10
Percent = 90

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Standardized Event Notifications
Goal: Support routing events from an external system to one or more functions.
This is the core of building an event-driven system – delivering event notifications from systems
that produce them (examples: object.create from an object store like S3 or vm.delete from
vCenter) to components that consume them.
Solution: Knative uses a standard delivery protocol, pushed CloudEvents over HTTP, for passing
the event notification from one component to the next.
External
System
𝒇(𝒙)
Destination
(Knative Service)
?

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Easy to Support Many External System Events
External
System
Source Adapter
𝒇(𝒙)
Destination
(Knative Service)
Goal: Support delivering events from many different external systems.
There are many external systems which already exist and can deliver event notifications in some
way (GitHub webhooks, tailing a log, pubsub notifications over various protocols). Configuring
and receiving these event notifications is custom for each system, however.
Solution: Build a source adapter per system (typically, a small Kubernetes custom resource and
a backing container) to translate subscription requests to event deliveries.
?

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Easy to Map Events to Destinations
External
System
Source Adapter Broker
Trigger 𝒇(𝒙)
Trigger
Destination
(Knative Service)
Goal: Support delivering specific events from a broker to different destinations.
Broker acts as a central hub for events, accepting and persisting event notifications in a durable
way and performing fan-out of stored event notifications to multiple destinations.
Solution: Triggers provide content-based filtering (currently simple string-matching) against
CloudEvents attributes in the event notification. Only events which match the filter are passed to
the destination.

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Your application is stateless: Knative will kill your pods when there’s no traffic
You rely on eventing, leveraging brokers such as Kafka and RabbitMQ
You need a cross-platform serverless framework – deploy to any Kubernetes
You need proportional phase releases – like “A/B testing”
You want to optimize the resources of your cluster – autoscaling FTW
My advices to simplify your Kubernetes developer experience
Use Knative for your next application if…
🔥

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Wanna try and learn Knative?
learn.tanzu.io – free workshops including live K8s clusters with Knative enabled
Tips and tricks?
knative.tips
My demo app
github.com/alexandreroman/kn-todo-app
It’s dangerous to go alone: take this.
Resources
👍

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Thank You