cloudcoil-models-keda
Versioned keda models for cloudcoil.
🔧 Installation
Using uv (recommended):
# Install with KEDA support
uv add cloudcoil.models.keda
Using pip:
pip install cloudcoil.models.keda
💡 Examples
Using KEDA Models
from cloudcoil import apimachinery
import cloudcoil.models.keda.v1alpha1 as keda
# Create a ScaledObject
scaled_object = keda.ScaledObject(
metadata=apimachinery.ObjectMeta(name="rabbitmq-scaler"),
spec=keda.ScaledObjectSpec(
scale_target_ref=keda.ScaledObjectSpecScaleTargetRef(
name="my-deployment",
kind="Deployment",
api_version="apps/v1"
),
triggers=[
keda.ScaledObjectSpecTriggersItem(
type="rabbitmq",
metadata={
"queue_name": "hello",
"host": "amqp://guest:guest@rabbitmq:5672"
}
)
],
min_replica_count=1,
max_replica_count=10
)
).create()
# List ScaledObjects
for scaler in keda.ScaledObject.list():
print(f"Found scaler: {scaler.metadata.name}")
# Update a ScaledObject
scaled_object.spec.max_replica_count = 20
scaled_object.save()
# Delete resources
keda.ScaledObject.delete("rabbitmq-scaler")
Using the Fluent Builder API
from cloudcoil.models.keda.v1alpha1 import ScaledObject
# Create a ScaledObject using the fluent builder
scaled_object = (
ScaledObject.builder()
.metadata(lambda metadata: metadata
.name("prometheus-scaler")
.namespace("default")
)
.spec(lambda spec: spec
.scale_target_ref(lambda target: target
.name("my-deployment")
.kind("Deployment")
.api_version("apps/v1")
)
.min_replica_count(1)
.max_replica_count(10)
.triggers(lambda triggers: triggers.add(
lambda trigger: trigger.type("prometheus").metadata({
"server_address": "http://prometheus.monitoring.svc",
"metric_name": "http_requests_total",
"threshold": "100"
})
))
)
.build()
)
Using the Context Manager Builder API
from cloudcoil.models.keda.v1alpha1 import ScaledObject
# Create a ScaledObject using context managers
with ScaledObject.new() as cpu_scaler:
with cpu_scaler.metadata() as metadata:
metadata.name("cpu-scaler")
metadata.namespace("default")
with cpu_scaler.spec() as spec:
with spec.scale_target_ref() as target:
target.name("my-deployment")
target.kind("Deployment")
target.api_version("apps/v1")
spec.min_replica_count(1)
spec.max_replica_count(10)
with spec.triggers() as trigger_list:
with trigger_list.add() as trigger:
trigger.type("cpu")
trigger.metadata({
"type": "Utilization",
"value": "50"
})
final_scaler = cpu_scaler.build()
📚 Documentation
For complete documentation, visit cloudcoil.github.io/cloudcoil
📜 License
Apache License, Version 2.0 - see LICENSE
Metadata
Release files for cloudcoil.models.keda 2.20.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| cloudcoil_models_keda-2.20.2.0.tar.gz | 245.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| cloudcoil_models_keda-2.20.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 429.8 kB
Release files / cloudcoil_models_keda-2.20.2.0.tar.gz
| Download URL | cloudcoil_models_keda-2.20.2.0.tar.gz |
|---|---|
| Size | 245.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Download URL | cloudcoil_models_keda-2.20.2.0-py3-none-any.whl |
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| Size | 184.6 kB |
| Tags | Python 3 |
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| Uploaded via |
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|
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