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Knative - deploy, and manage modern
container-based serverless workloads
Elad Hirsch, Agmatix
Growing data
for Impact
WHOAMI
https://github.com/eladh
linkedin.com/in/eladhirsch
eladh@agmatix.com
CTO @ Agmatix
Let’s simplify things
Write once, run anywhere
Function as a Service
Service based
Event driven
Open API
No infra management
Managed security
Pay only for usage
Developer Operator
The serverless model
Where we really need serverless
AWS support for Docker lambda
Serverless is much more than
Total of 2,208,407 stars, market cap of $15.5T
and funding of $65.42B
Total of 2,208,407 stars, market cap of $15.5T
and funding of $65.42B
Kubernetes for serverless
Write
Kubernetes for serverless
Write
Build a container image
Deploy the application
Expose at an endpoint
Request-level load balancing
Set up SSL/TLS
Scale up based on demand
Scale down to zero
Canary deployments
Monitor metrics
In
real life
Kubernetes for serverless
Write
Build a container image
Deploy the application
Expose at an endpoint
Request-level load balancing
Set up SSL/TLS
Scale up based on demand
Scale down to zero
Canary deployments
Monitor metrics
In
real life
No infrastructure
What Kubernetes missing ?
Source-to-URL deploys
Canary deployments, rollouts/rollbacks
Kubernetes needs container images built/pushed
Kubernetes has no notion of immutable revisions to cleanly rollback
Manage application traffic
Kubernetes cannot natively split traffic (lack of L7 HTTP load balancing)
Out-of-the box monitoring
Kubernetes doesn’t provide monitoring signals beyond CPU/memory
Scale-to-zero
Kubernetes cannot do natively
Kubernetes ecosystem
K8s is a platform to build a platform
open source building blocks
for serverless on Kubernetes
Kubernetes
Knative
Service Mesh
Build code
Deploy and manage
Users/Systems (IoT)
OSS Contribute
Knative Partners
Serving/Eventing/CLI
Serving
Knative serving - Object Model
Service
(my-function)
Configuration
Revision
Revision
Revision
Route
(name)
routes
traffic to
records
history of
manages
Deployment
kn - your door to
Knative wonderland
Deployment - CLI
# Knative Client:
# github.com/knative/client
$ kn service create my-service 
--image registry/image-name
Deployment - K8s
$ kubectl apply -f service.yaml
apiVersion: serving.knative.dev/v1
kind: Service
metadata:
name: service-name
spec:
template:
spec:
containers:
- image: registry/image-name:v1
New version
HTTP
N-1
N
New revision
new version - K8s
apiVersion: serving.knative.dev/v1
kind: Service
metadata:
name: service-name
spec:
template:
spec:
containers:
- image: registry/image-name:v2
$ kn service update -n knativetutorial
blue-green-canary
--tag=blue-green-canary-xjygh-1=blue
Service
HTTP
N-1
N
N+1
New revision
NAME SERVICE TRAFFIC TAGS GENERATION AGE CONDITIONS READY
helloworld-go-cvclp-2 helloworld-go 100% 2 40s 4 OK / 4 True
helloworld-go-pyqqz-1 helloworld-go 1 6m29s 3 OK / 4 True
$ kn revision list
Name: helloworld-go-cvclp-2
Namespace: default
Age: 3m
Image: knative-sample/helloworld-go:160e4dc8 (pinned to 032b80)
Env: TARGET=knative
Service: helloworld-go
Conditions:
OK TYPE AGE REASON
++ Ready 3m
++ ContainerHealthy 3m
++ ResourcesAvailable 3m
I Active 2m NoTraffic
$ kn revision describe helloworld-go-cvclp-2
How to handle bursty traffic ?
HTTP
N-1
N
Request-based autoscaling
Service
(my-function)
Configuration
Revision
Route
(name)
PodAutoscaler
RPS vs. Concurrency
/S
Requests per second
reaching the pod
The number of requests
in-flight in any time
apiVersion: serving.knative.dev/v1
kind: Service
metadata:
name: service-name
namespace: default
spec:
template:
metadata:
annotations:
# Knative concurrency-based autoscaling (default).
autoscaling.knative.dev/class: kpa.autoscaling.knative.dev
autoscaling.knative.dev/metric: concurrency
autoscaling.knative.dev/target: "6"
autoscaling.knative.dev/targetUtilizationPresentege: "70"
KPA - Request based auto scaling
How to handle bursty traffic ?
HTTP
N-1
N N N
CREATED A PAID CLUSTER
FORGOT TO CANCEL
BEFORE FREE TRIALS ENDS
Scale to zero
N-1
N
Scale to zero grace period
apiVersion: v1
kind: ConfigMap
metadata:
name: config-autoscaler
namespace: knative-serving
data:
scale-to-zero-grace-period: "40s"
Scale to zero
N-1
N
N+1
Canary deployments, rollouts/rollbacks
HTTP
N-1
N
Name: V1
100%
We got new version (Day 2-n/Blue)
HTTP
N-1
N
Name: V1
100%
N+1
Name: V2
0%
Blue/Green deployment
HTTP
N-1
N
Name: V1
50%
N+1
Name: V2
50%
apiVersion: serving.knative.dev/v1
kind: Route
spec:
spec:
traffic:
- tag: current
revisionName: bg-1
percent: 50
- tag: candidate
revisionName: bg-2
percent: 50
- tag: latest
latest Revision: true
percent: 0
Green deployment
HTTP
N-1
N
Name: V1
0%
N+1
Name: V2
100%
Rollback revision (Blue)
HTTP
N-1
N
Name: V1
100%
N+1
Name: V2
0%
$ kn service update blue-green-canary --traffic
blue=100,green=0,latest=0
NAME SERVICE TRAFFIC TAGS GENERATION AGE CONDITIONS READY
blue-green-canary-yzrwq-2 blue-green-canary latest,green 2 56m 4 OK / 4 True
blue-green-canary-xjygh-1 blue-green-canary 100% blue 1 83m 4 OK / 4 True
$ kn revision list
It’s still under the hood
Knative eventing
Describe event data in a common way
CloudEvents
IoT devices
Public clouds
Legacy systems
Private clouds
FaaS
SaaS
{
"specversion" : "1.0",
"id" : "b85d631a-101e-005a-02f2-cee7aa06f148",
"type" : "zohan.music.request",
"source" : "https://zohan.dev/music/",
"subject" : "zohan/music/requests/4322",
"time" : "2020-09-14T10:00:00Z",
"data" : {
"artist": "Gerardo",
"song": "Rico Suave"
}
}
Channel and Subscription
apiVersion: sources.eventing.knative.dev/v1alpha1
kind: CronJobSource
metadata:
name: source
spec:
schedule: "* * * * *"
data: '{"message": "Hello world from cron!"}'
sink:
apiVersion: serving.knative.dev/v1
kind: Service
name: service
apiVersion: serving.knative.dev/v1
kind: Service
metadata:
name: eventinghelloa
spec:
template:
metadata:
name: eventinghelloa-v1
annotations:
autoscaling.knative.dev/target: "1"
spec:
containers:
- image: registry/eventinghello:0.0.1
apiVersion: eventing.knative.dev/v1alpha1
kind: Channel
metadata:
name: eventinghello-ch
spec:
provisioner:
apiVersion: eventing.knative.dev/v1alpha1
kind: ClusterChannelProvisioner
name: in-memory-channel
apiVersion: sources.knative.dev/v1beta1
kind: PingSource
metadata:
name: event-greeter-ping-source
spec:
schedule: "*/2 * * * *"
jsonData: '{"msg": "Some msg"}'
sink:
ref:
apiVersion: messaging.knative.dev/v1
kind: Channel
name: eventinghello-ch
apiVersion: messaging.knative.dev/v1
kind: Subscription
metadata:
name: eventinghelloa-sub
spec:
channel:
apiVersion: messaging.knative.dev/v1
kind: Channel
name: eventinghello-ch
subscriber:
ref:
apiVersion: serving.knative.dev/v1
kind: Service
name: eventinghelloa
goal is to make developers more productive.
solves common problems like stand up a
scalable, secure, stateless service,
connecting systems together.
brings serverless deployment models to
Kubernetes.
keep in mind that it Knative is relatively new tool
which is still developing and evolving
THIS IS A
PLACEHOLDER
TEXT BOX FOR
A MEDIUM
SIZE MESSAGE
THANK YOU
Knative Offerings
Products
Knative
Service
Mesh
Platform
Knative ecosystem
demo
Demo
Kn
● Imperative management of Knative core entities (CRUD)
kn service|revision|route - Manage Knative services and revisions
kn trigger|subscription|broker|channel - Manage Knative eventing
kn source - Manage builtin-sources
● Declarative handling of Knative services
kn service apply - supporting 3-way merging of resources (like kubectl)
● Plugin architecture
Similar to kubectl
Inlining possible
● GitOps support
Tekton tasks
Offline generation of resource files
Knative build
Local build/push using Dockerfile
docker build -t user/app:version; docker push
Build Service (Cloud Build, GitHub Actions, GitLab, Jenkins…)
git tag ...; git push origin ...;
Cloud Native CI/CD ,On-cluster Build using Tekton Pipelines
kubectl apply -f task.yaml
Broker and Trigger
Simple delivery - Source to sink
Channel and Subscription with reply
● Did we market Knative wrong?
● Knative large footprint myth
● Advanced auto scaling techniques
● Why Are We Installing Istio?
● Knative with its own ingress
● CLI enhancements

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