Abstract
- keda is Kubernetes Event-driven Autoscaling and it's been used wisely now. In this blog, it provides the way to create Keda scaledobject CRD as code using CDK8S typescript.
- With importing Keda CRDs and using CDK8S you can create Keda scaledobjects using your familiar programming languages such as typescript as scale.
Table Of Contents
- Pre-requisite
- Overview of Keda
- Import Keda CRDs
- Write code
- Build keda scaledobjects from code
- Apply and test
- Conclusion
🚀 Pre-requisite
- Install typescript, node, and cdk8s as well as projen (optional) which is a tool of managing project configuration as code.
- Getting started with cdk8s
🚀 Overview of Keda
- KEDA works alongside standard Kubernetes components like the Horizontal Pod Autoscaler and can extend functionality without overwriting or duplication.
- KEDA supports multiple triggers within an Scaledobject. Each trigger is exposed split as a metric and the HPA Controller does a MAX between all the metrics.
🚀 Import Keda CRDs
- Keda does not provide its CRDs separately so we can found the manifest in GH release section. Here I import the current latest version of keda v2.8.0 and output the
importsfolder insrc/imports
⚡ $ cdk8s import https://github.com/kedacore/keda/releases/download/v2.8.0/keda-2.8.0.yaml --output src/imports/
------------------------------------------------------------------------------------------------
A new version 2.0.88 of cdk8s-cli is available (current 2.0.13).
Run "npm install -g cdk8s-cli" to install the latest version on your system.
For additional installation methods, see https://cdk8s.io/docs/latest/getting-started
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Importing resources, this may take a few moments...
keda.sh
keda.sh/clustertriggerauthentication
keda.sh/scaledjob
keda.sh/scaledobject
keda.sh/triggerauthentication
- Import result ```
⚡ $ tree src/imports/
src/imports/
└── keda.sh.ts
0 directories, 1 file
## 🚀 **Write code** <a name="Write-code"></a>
- Overview of keda scaledObjects in this post
<img src=https://raw.githubusercontent.com/vumdao/keda-hands-on/master/docs/images/flow.png width=900>
- It's much more convinient to use visual code writing KEDA scaledobject in typescript language. We can read the document and find all references of construct, objects and properties of KEDA CRDs
- This blog provides the usecase of creating scaledObject (SO) for Apache airflow worker component. It contains 3 triggers (Scalers) in the SO
### 1. [Cron](https://keda.sh/docs/2.8/scalers/cron/) - Scale applications based on a cron schedule.
- Airflow server scheduled pipelines and worker components are scaled out at that time, but it takes time to start nodes, join node to cluster and Pod ready (about 2-3mins) so we use cron to pre-scale workers
### 2. [PostgreSQL](https://keda.sh/docs/2.8/scalers/postgresql/) - Scale applications based on a PostgreSQL query.
- This scaler bases on the output of query command to scaleout works, here we count the number of running/queued airflow task instances belongs to scheduled pipeline (eg. running reports). Divide the count number to Airflow worker concurrency (eg. 16 as default)
- `targetQueryValue: '1.5'` - The result of above calculation divide to this target value to decide how many pods will be scaled out
### 3. [CPU](https://keda.sh/docs/2.8/scalers/cpu/) - Scale applications based on cpu metrics
- This is optional as it ensure provisioning workers when CPU Utilization is higher than 80%
- PostgreSQL Scaler requires `TriggerAuthentication` to provide password of airflow user in order to query the database. The credential is get from K8S secret `airflow-secret` within the `airflow` namespace
const pgAuth = new TriggerAuthentication(this, 'KedaPostgresAuthentication', {
metadata: {
name: 'keda-airflow-postgresql-auth',
namespace: 'airflow',
},
spec: {
secretTargetRef: [{
parameter: 'password',
name: 'airflow-secret',
key: 'postgresql-password',
}],
},
});
- Some SO specs need to know
- `pollingInterval`: This is the interval to check each trigger on. By default KEDA will check each trigger source on every ScaledObject every 30 seconds. So to reduce the query connections/workload to airflow database we need to care this vaule.
- `cooldownPeriod`: The period to wait after the last trigger reported active before scaling the resource back to 0.
## 🚀 **Build keda scaledobjects from code** <a name="Build-keda-scaledobjects-from-code"></a>
- Source code:
⚡ $ tree src/
src/
├── imports
│ └── keda.sh.ts
├── keda-airflow.ts
└── main.ts
1 directory, 3 files
- Build resource
⚡ $ npx projen build
👾 build » default | ts-node --project tsconfig.dev.json .projenrc.ts
👾 build » compile | tsc --build
👾 build » post-compile » synth | cdk8s synth
No manifests synthesized
👾 build » test | jest --passWithNoTests --all --updateSnapshot
No tests found, exiting with code 0
----------|---------|----------|---------|---------|-------------------
File | % Stmts | % Branch | % Funcs | % Lines | Uncovered Line #s
----------|---------|----------|---------|---------|-------------------
All files | 0 | 0 | 0 | 0 |
----------|---------|----------|---------|---------|-------------------
👾 build » test » eslint | eslint --ext .ts,.tsx --fix --no-error-on-unmatched-pattern src test build-tools projenrc .projenrc.ts
- Manifest yaml file
⚡ $ tree dist/
dist/
└── keda
└── airflow-keda-so.yaml
1 directory, 1 file
## 🚀 **Apply and test** <a name="Apply-and-test">
- Apply manifest and check result
# k apply -f dist/keda/airflow-keda-so.yaml
# k get so -n airflow
NAME SCALETARGETKIND SCALETARGETNAME MIN MAX TRIGGERS AUTHENTICATION READY ACTIVE FALLBACK AGE
airflow-worker-1 apps/v1.StatefulSet airflow-worker 2 12 cron keda-airflow-postgresql-auth True True False 2d21h
# k get hpa -n airflow
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
keda-hpa-airflow-worker-1 StatefulSet/airflow-worker 500m/1 (avg), 500m/1 (avg) + 2 more... 2 12 2 2d21h
## 🚀 Conclusion <a name="Conclusion"></a>
- Within the Scaledobject class, you can jump to definition to understand the meaning of each properties and also know which required/optional attributes.
- We can create a custom construct and base on that to provision multiple KEDA scaledobjects with customize specs/meta such as min/max/desired replicas, triggers, trigger authentication, etc.
---
Top comments (2)
It is really useful for me. That is a great example. Thanks
. #KEDA and #Karpenter together help us scaling down to zero the Dev/Test clusters at non-working hours and scaling up automatically before working time.
Here is an example of scaling down/up Solr at 9PM/7AM
apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
name: solr1
spec:
minReplicaCount: 0
scaleTargetRef:
kind: StatefulSet
name: solr1
triggers:
- metadata:
desiredReplicas: "1"
end: 0 21 * * *
start: 0 7 * * *
timezone: Asia/Ho_Chi_Minh
type: cron