You can scale an app with Autoscaler in your TAS for VMs deployment based on a Custom App Metric.
In a VMware Tanzu Application Service for VMs (TAS for VMs) deployment, Autoscaler can scale apps based on Custom App Metrics. The table describes the main components involved in this workflow and how they correspond to steps in this tutorial.
Component | Description | Related Tutorial Steps |
---|---|---|
App | The app must emit Custom App Metrics by exposing a Prometheus endpoint. This tutorial includes a sample Spring app, java-spring-security , that emits such metrics. For more information about Prometheus, see the Prometheus documentation. |
Review the sample app and Push the sample app |
Metric Registrar | The Metric Registrar is a component of TAS for VMs through which you can export custom app metrics to Loggregator. You issue commands to the Metric Registrar through the Metric Registrar CLI plug-in. For more information about the Metric Registrar, see Metric registrar and custom app metrics. | Register a Custom App Metrics endpoint |
App Autoscaler | Autoscaler is a service integrated with Apps Manager that automatically scales apps in your TAS for VMs deployment based on the scaling metrics or schedule that you configure. For more information, see Scaling an app using App Autoscaler. | Create and Autoscaling Rule and Trigger Scaling |
This tutorial requires the following:
Important You must have SpaceDeveloper
permissions in at least one space.
To review the code for the sample app, java-spring-security
, see the metric-registrar-examples repository on GitHub. This sample app is a Spring app with a user interface (UI) that includes several buttons to call different endpoints. Some of these endpoints are instrumented to produce metrics.
You can see what the UI looks like in the Push the sample app section, which includes a screenshot. The following sections provide some details about the code.
You can view the app dependencies in the build.gradle file.
The dependencies include Micrometer Prometheus, which creates a prometheus metrics endpoint at /actuator/prometheus
that can be scraped by Metric Registrar.
This section describes how the app is instrumented. Instrumentation refers to how metrics were added for a particular function.
See the ExampleController.java file from the sample app code:
The ExampleController
class includes a MeterRegistry
object, which is passed and set in the constructor.
private MeterRegistry registry;
private AtomicLong custom;
public ExampleController(MeterRegistry registry) {
this.registry = registry;
this.custom = new AtomicLong(0L);
}
It also includes a custom
variable that is initialized in the constructor. In the customMetric handler, this variable gets passed to the registry and incremented or decremented.
public ResponseEntity<String> customMetric(@RequestParam(value="inc", defaultValue="") String increment) {
AtomicLong customGauge = registry.gauge("custom", this.custom);
if (!"".equals(increment)) {
customGauge.incrementAndGet();
} else {
customGauge.decrementAndGet();
}
The App Autoscaler only scales on a gauge, or metric, that can go up and down. The standard metrics of CPU Processor Utilization, Container Memory Utilization, HTTP Request Throughput, and HTTP Request Latency are all gauges.
To push the sample app:
Open a terminal window and clone the git repository that contains the sample app:
git clone https://github.com/pivotal-cf/metric-registrar-examples.git
Navigate to the java-spring-security
app directory:
cd metric-registrar-examples/java-spring-security
Build the app by running:
./gradlew build
Push the app with a random route:
cf push java-spring-security --random-route
The command returns output similar to the following example:
Waiting for app to start... Uploaded droplet (60.5M) Uploading complete Cell 333e7fdf-806e-424d-b3a0-78967ecb6d28 stopping instance 6f345835-8beb-48a5-b578-921f5de442c6 name: java-spring-security requested state: started routes: java-spring-security-random-route.cfapps.io last uploaded: Wed 28 Aug 11:02:33 PDT 2019
From the routes
section of the terminal output, record the URL of the java-spring-security
app. In the example output in the previous step, this URL is tutorial-example-random-route.cfapps.io
.
In a browser, navigate to the app URL you recorded in the previous step. The app UI looks like what you see in the image that follows.
It has the following buttons:
custom
metric to increase by a value of 1
. You use this button in Trigger scaling.custom
metric to decrease by a value of 1
./actuator/prometheus
in your browser. The Metric Registrar uses this page to collect metrics. You can use this page to view the values of the custom
metric and all metrics from the Micrometer Prometheus library.When you want to your app to emit Custom App Metrics, you register the app as a metric source with the Metric Registrar.
To register a Custom App Metrics endpoint for the app:
Install the Metric Registrar CLI:
cf install-plugin -r CF-Community "metric-registrar"
Register the metrics endpoint of the java-spring-security
app by running:
cf register-metrics-endpoint java-spring-security /actuator/prometheus --insecure
Because the app dependencies include the Micrometer Prometheus library, there is automatically a metrics endpoint at /actuator/prometheus
.
Caution When you include the --insecure
flag in the above command, the Metric Registrar scrapes the metrics endpoint on the default app port. Exposing metrics on the default app port makes the metrics available to anyone with access to the app. VMware recommends that you do not use the --insecure
flag in a production environment. Instead, specify an alternative port by including the --internal-port
flag. Specifying an alternative port the --internal-port
flag exposes the metrics endpoint on that port and limits access to the app.
Install the Log Cache CLI by running:
cf install-plugin -r CF-Community "log-cache"
Log Cache is a component of TAS for VMs that caches logs and metrics from across the platform.
View the app metrics as they are emitted running the command that follows. The --follow
flag appends output as metrics are emitted.
cf tail java-spring-security --envelope-class metrics --follow
The output looks similar to the following example. The custom
metric displays in the output.
Retrieving logs for app in org sandbox / space development as example@user... 2019-08-28T09:17:56.28-0700 [tutorial-example/1] GAUGE cpu:0.289158 percentage disk:135716864.000000 bytes disk_quota:1073741824.000000 bytes memory:399979315.000000 bytes memory_quota:2147483648.000000 bytes 2019-08-28T09:17:56.50-0700 [tutorial-example/0] GAUGE custom:1.000000
In the java-spring-security
app UI, you must click Increment Custom gauge at least one time to cause the app to emit the custom
metric.
Autoscaler is integrated with Apps Manager. You can create autoscaling rules in Apps Manager.
To create an autoscaling rule for the java-spring-security
app that uses the custom
metric as its scaling metric:
Log in to Apps Manager. For more information, see Logging in to Apps Manager.
In Apps Manager, go to the java-spring-security
app overview. For more information, see View app overview in Managing apps and service instances using Apps Manager.
Click Enable Autoscaling.
Click Manage Autoscaling.
Under Instance Limits, configure upper and lower scaling limits for the java-spring-security
app:
1
.5
.To create an autoscaling rule:
Custom
.2
. If the average value of the custom
metric falls below this number, Autoscaler scales the number of app instances down.5
. If the average value of the custom
metric rises above this number, Autoscaler scales the number of app instances up.custom
.Click Save.
Now that you pushed an app that emits a Custom App Metric and configured autoscaling rules, you can trigger a scaling action. App Autoscaler scales the app when the Custom App Metric goes above or below the threshold specified in the scaling rule.
To trigger scaling:
Go to the web UI of the app. Use the same URL from Push the sample app.
Click Increment Custom gauge enough times to bring the Custom App Metric over the threshold of 5
that you set in the scaling rule. You can see the value of the custom
metric using the See Metrics button.
Monitor the app page in Apps Manager for about two minutes. App Autoscaler begins to scale the app. It adds one instance at a time until it reaches the Maximum instance limit of 5
.
Now that you have completed this tutorial, explore the app, emitting Custom App Metrics and creating scaling rules with your own app. After you instrument your app to emit Custom App Metrics, you can follow the steps outlined in this tutorial to scale based on those metrics.