AWS Auto Scaling Construct Library
This is a developer preview (public beta) module. Releases might lack important features and might have future breaking changes.
Application AutoScaling is used to configure autoscaling for all services other than scaling EC2 instances. For example, you will use this to scale ECS tasks, DynamoDB capacity, Spot Fleet sizes and more.
As a CDK user, you will probably not have to interact with this library directly; instead, it will be used by other construct libraries to offer AutoScaling features for their own constructs.
This document will describe the general autoscaling features and concepts; your particular service may offer only a subset of these.
AutoScaling basics
Resources can offer one or more attributes to autoscale, typically representing some capacity dimension of the underlying service. For example, a DynamoDB Table offers autoscaling of the read and write capacity of the table proper and its Global Secondary Indexes, an ECS Service offers autoscaling of its task count, an RDS Aurora cluster offers scaling of its replica count, and so on.
When you enable autoscaling for an attribute, you specify a minimum and a maximum value for the capacity. AutoScaling policies that respond to metrics will never go higher or lower than the indicated capacity (but scheduled scaling actions might, see below).
There are three ways to scale your capacity:
- In response to a metric (also known as step scaling); for example, you might want to scale out if the CPU usage across your cluster starts to rise, and scale in when it drops again.
- By trying to keep a certain metric around a given value (also known as target tracking scaling); you might want to automatically scale out an in to keep your CPU usage around 50%.
- On a schedule; you might want to organize your scaling around traffic flows you expect, by scaling out in the morning and scaling in in the evening.
The general pattern of autoscaling will look like this:
const capacity = resource.autoScaleCapacity({
minCapacity: 5,
maxCapacity: 100
});
// Enable a type of metric scaling and/or schedule scaling
capacity.scaleOnMetric(...);
capacity.scaleToTrackMetric(...);
capacity.scaleOnSchedule(...);
Step Scaling
This type of scaling scales in and out in deterministics steps that you configure, in response to metric values. For example, your scaling strategy to scale in response to CPU usage might look like this:
Scaling -1 (no change) +1 +3
│ │ │ │ │
├────────┼───────────────────────┼────────┼────────┤
│ │ │ │ │
CPU usage 0% 10% 50% 70% 100%
(Note that this is not necessarily a recommended scaling strategy, but it's a possible one. You will have to determine what thresholds are right for you).
You would configure it like this:
capacity.scaleOnMetric('ScaleToCPU', {
metric: service.metricCpuUtilization(),
scalingSteps: [
{ upper: 10, change: -1 },
{ lower: 50, change: +1 },
{ lower: 70, change: +3 },
],
// Change this to AdjustmentType.PercentChangeInCapacity to interpret the
// 'change' numbers before as percentages instead of capacity counts.
adjustmentType: autoscaling.AdjustmentType.ChangeInCapacity,
});
The AutoScaling construct library will create the required CloudWatch alarms and AutoScaling policies for you.
Target Tracking Scaling
This type of scaling scales in and out in order to keep a metric (typically representing utilization) around a value you prefer. This type of scaling is typically heavily service-dependent in what metric you can use, and so different services will have different methods here to set up target tracking scaling.
The following example configures the read capacity of a DynamoDB table to be around 60% utilization:
const readCapacity = table.autosScaleReadCapacity({
minCapacity: 10,
maxCapacity: 1000
});
readCapacity.scaleOnUtilization({
targetUtilizationPercent: 60
});
Scheduled Scaling
This type of scaling is used to change capacities based on time. It works
by changing the minCapacity and maxCapacity of the attribute, and so
can be used for two purposes:
- Scale in and out on a schedule by setting the
minCapacityhigh or themaxCapacitylow. - Still allow the regular scaling actions to do their job, but restrict
the range they can scale over (by setting both
minCapacityandmaxCapacitybut changing their range over time).
The following schedule expressions can be used:
at(yyyy-mm-ddThh:mm:ss)-- scale at a particular moment in timerate(value unit)-- scale every minute/hour/daycron(mm hh dd mm dow)-- scale on arbitrary schedules
Of these, the cron expression is the most useful but also the most
complicated. There is a Cron helper class to help build cron expressions.
The following example scales the fleet out in the morning, and lets natural scaling take over at night:
const capacity = resource.autoScaleCapacity({
minCapacity: 1,
maxCapacity: 50,
});
capacity.scaleOnSchedule('PrescaleInTheMorning', {
schedule: autoscaling.Cron.dailyUtc(8),
minCapacity: 20,
});
capacity.scaleOnSchedule('AllowDownscalingAtNight', {
schedule: autoscaling.Cron.dailyUtc(20),
minCapacity: 1
});
2 maintainers
Metadata
2 maintainers
Release files for aws-cdk.aws-applicationautoscaling 0.39.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| aws-cdk.aws-applicationautoscaling-0.39.0.tar.gz | 102.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| aws_cdk.aws_applicationautoscaling-0.39.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 203.8 kB
Release files / aws-cdk.aws-applicationautoscaling-0.39.0.tar.gz
| Download URL | aws-cdk.aws-applicationautoscaling-0.39.0.tar.gz |
|---|---|
| Size | 102.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
dbc89cf10f450f0b43b396ea25eabdbc160718e29f940b9f5842765c45fcf10f
|
|
BLAKE2b-256 checksum How to use checksums |
af561555e8e3836bf3c82b36a1cf8138120d36a6379ffd6cf69eb930aa936933
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/39.0.1 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/3.6.5
|
Release files / aws_cdk.aws_applicationautoscaling-0.39.0-py3-none-any.whl
| Download URL | aws_cdk.aws_applicationautoscaling-0.39.0-py3-none-any.whl |
|---|---|
| Size | 101.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
14d64c9d0f78c42e6c5fea392bb7afe18934eac4388e9e86bc1be470973d3451
|
|
BLAKE2b-256 checksum How to use checksums |
7b9f9b86961b05a476b13065e3eb3f120507b2c0f34c7354dc355c0fec230f4d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/39.0.1 requests-toolbelt/0.9.1 tqdm/4.32.2 CPython/3.6.5
|
