Running an instance group with autoscaling using Terraform

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Yandex Cloud

Updated at October 2, 2024

Prepare your cloud
- Required paid resources
Create an infrastructure
Test your instance group and network load balancer
- Test autoscaling
How to delete the resources you created

To create an infrastructure for an instance group with an autoscaling policy using Terraform:

If you no longer need the resources you created, delete them.

Prepare your cloud

Go to the management console and log in to Yandex Cloud or create an account if you do not have one yet.
On the Yandex Cloud Billing page, make sure you have a billing account linked and it has the ACTIVE or TRIAL_ACTIVE status. If you do not have a billing account, create one.

If you have an active billing account, you can go to the cloud page to create or select a folder for your infrastructure to operate in.

Learn more about clouds and folders.

If you don't have the Yandex Cloud command line interface yet, install it.
For the scripts from the tutorial to run correctly, download and install the jq utility.
To check auto scaling, install the wrk benchmarking tool.

Required paid resources

The infrastructure cost includes:

Fee for continuously running VMs (see Compute Cloud pricing).
Fee for network load balancers and traffic balancing (see Network Load Balancer pricing).

Terraform allows you to quickly create a cloud infrastructure in Yandex Cloud and manage it using configuration files. Configuration files store the infrastructure description in the HashiCorp Configuration Language (HCL). Terraform and its providers are distributed under the Business Source License.

For more information about the provider resources, see the documentation on the Terraform website or the mirror.

If you change the configuration files, Terraform automatically detects which part of your configuration is already deployed, and what should be added or removed.

To create an infrastructure to automatically scale an instance group using Terraform:

Install Terraform and specify the source for installing the Yandex Cloud provider (see Configure a provider, step 1).

Prepare files with the infrastructure description:

Ready-made configuration

Manually

Clone the repository with configuration files:

git clone https://github.com/yandex-cloud-examples/yc-vm-group-with-autoscale.git

Go to the directory with the repository. Make sure it contains the following files:
- vm-autoscale.tf: New infrastructure configuration.
- declaration.yaml: Description of the Docker container with a web server that will be run on the VM to simulate the load on the service.
- config.tpl: Description of VM user parameters.
- vm-autoscale.auto.tfvars: User data.

Create a folder for configuration files.

In the folder, create:

vm-autoscale.tf configuration file

vm-autoscale.tf

# Declaring variables for confidential parameters

variable "folder_id" {
  type = string
}

variable "vm_user" {
  type = string
}

variable "ssh_key" {
  type      = string
  sensitive = true
}

# Setting up the provider

terraform {
  required_providers {
    yandex = {
      source = "yandex-cloud/yandex"
      version = ">= 0.47.0"
    }
  }
}

provider "yandex" {
  zone = "ru-central1-a"
}

# Creating a service account and assigning roles to it

resource "yandex_iam_service_account" "for-autoscale" {
  name = "for-autoscale"
}

resource "yandex_resourcemanager_folder_iam_member" "vm-autoscale-sa-role-compute" {
  folder_id = var.folder_id
  role      = "editor"
  member    = "serviceAccount:${yandex_iam_service_account.for-autoscale.id}"
}

# Creating a cloud network and subnets

resource "yandex_vpc_network" "vm-autoscale-network" {
  name = "vm-autoscale-network"
}

resource "yandex_vpc_subnet" "vm-autoscale-subnet-a" {
  name           = "vm-autoscale-subnet-a"
  zone           = "ru-central1-a"
  v4_cidr_blocks = ["192.168.1.0/24"]
  network_id     = yandex_vpc_network.vm-autoscale-network.id
}

resource "yandex_vpc_subnet" "vm-autoscale-subnet-b" {
  name           = "vm-autoscale-subnet-b"
  zone           = "ru-central1-b"
  v4_cidr_blocks = ["192.168.2.0/24"]
  network_id     = yandex_vpc_network.vm-autoscale-network.id
}

# Creating a security group

resource "yandex_vpc_security_group" "sg-1" {
  name                = "sg-autoscale"
  network_id          = yandex_vpc_network.vm-autoscale-network.id
  egress {
    protocol          = "ANY"
    description       = "any"
    v4_cidr_blocks    = ["0.0.0.0/0"]
  }
  ingress {
    protocol          = "TCP"
    description       = "ext-http"
    v4_cidr_blocks    = ["0.0.0.0/0"]
    port              = 80
  }
  ingress {
    protocol          = "TCP"
    description       = "healthchecks"
    predefined_target = "loadbalancer_healthchecks"
    port              = 80
  }
}

# Specifying a ready-made VM image

data "yandex_compute_image" "autoscale-image" {
  family = "container-optimized-image"
}

# Creating an instance group

resource "yandex_compute_instance_group" "autoscale-group" {
  name                = "autoscale-vm-ig"
  folder_id           = var.folder_id
  service_account_id  = yandex_iam_service_account.for-autoscale.id
  instance_template {

    platform_id = "standard-v3"
    resources {
      memory = 2
      cores  = 2
    }

    boot_disk {
      mode = "READ_WRITE"
      initialize_params {
        image_id = data.yandex_compute_image.autoscale-image.id
        size     = 30
      }
    }

    network_interface {
      network_id = yandex_vpc_network.vm-autoscale-network.id
      subnet_ids = [
        yandex_vpc_subnet.vm-autoscale-subnet-a.id,
        yandex_vpc_subnet.vm-autoscale-subnet-b.id
      ]
      security_group_ids = [ yandex_vpc_security_group.sg-1.id ]
      nat                = true
    }

    metadata = {
      user-data = templatefile("config.tpl", {
        VM_USER = var.vm_user
        SSH_KEY = var.ssh_key
      })
      docker-container-declaration = file("declaration.yaml")
    }
  }

  scale_policy {
    auto_scale {
      initial_size           = 2
      measurement_duration   = 60
      cpu_utilization_target = 40
      min_zone_size          = 1
      max_size               = 6
      warmup_duration        = 120
    }
  }

  allocation_policy {
    zones = [
      "ru-central1-a",
      "ru-central1-b"
    ]
  }

  deploy_policy {
    max_unavailable = 1
    max_expansion   = 0
  }

  load_balancer {
    target_group_name        = "auto-group-tg"
    target_group_description = "load balancer target group"
  }
}

# Creating a network load balancer

resource "yandex_lb_network_load_balancer" "balancer" {
  name = "group-balancer"

  listener {
    name        = "http"
    port        = 80
    target_port = 80
  }

  attached_target_group {
    target_group_id = yandex_compute_instance_group.autoscale-group.load_balancer[0].target_group_id
    healthcheck {
      name = "tcp"
      tcp_options {
        port = 80
      }
    }
  }
}

declaration.yaml file describing the Docker container with a web server that will be run on the VM to simulate the load on the service.
declaration.yaml
```
spec:
containers:
- image: cr.yandex/yc/demo/web-app:v1
  securityContext:
    privileged: false
  tty: false
  stdin: false
```

config.tpl file with VM user parameters:

config.tpl

users:
  - name: "${VM_USER}"
    groups: sudo
    shell: /bin/bash
    sudo: 'ALL=(ALL) NOPASSWD:ALL'
    ssh_authorized_keys:
      - "${SSH_KEY}"

vm-autoscale.auto.tfvars user data file:

vm-autoscale.auto.tfvars

folder_id = "<folder_ID>"
vm_user   = "<VM_user_name>"
ssh_key   = "<public_SSH_key_contents>"

For more information about the parameters of resources used in Terraform, see the provider documentation:

In the vm-autoscale.auto.tfvars file, set the following user-defined parameters:
- folder_id: Folder ID.
- vm_user: VM user name.
- ssh_key: Contents of the file with a public SSH key to authenticate the user on the VM. For more information, see Creating an SSH key pair.
Create resources:
1. In the terminal, change to the folder where you edited the configuration file.
2. Make sure the configuration file is correct using the command:
```
terraform validate
```
  If the configuration is correct, the following message is returned:
```
Success! The configuration is valid.
```
3. Run the command:
```
terraform plan
```
  The terminal will display a list of resources with parameters. No changes are made at this step. If the configuration contains errors, Terraform will point them out.
4. Apply the configuration changes:
```
terraform apply
```
5. Confirm the changes: type yes in the terminal and press Enter.

After creating an infrastructure, test your VM group and network load balancer.

Test your instance group and network load balancer

Create a load on an instance.

To do this, save the script named request.sh to the home directory. The script will send a request to one of the VMs through the group-balancer load balancer. The request will utilize 100% CPU for 30 seconds.
```
EXTERNAL_IP=$(yc load-balancer network-load-balancer get group-balancer --format=json | jq -r .listeners[0].address)

curl "http://$EXTERNAL_IP/burn-cpu?time=30000&load=100"
```

Run the script:

CLI

sh request.sh

Result:

projects/b0g12ga82bcv********/zones/ru-central1-b

View the instance utilization:
Management console
1. In the management console, select the folder where you created the instance group.
2. Select Compute Cloud.
3. In the left-hand panel, click Instance groups.
4. Select auto-group.
5. Go to the Monitoring tab.
  
  The load balancer sent the request to an instance in the group. In the availability zone this instance belongs to, the average CPU utilization is higher than in other zones (see the Average CPU utilization in zone chart).

Test autoscaling

To test autoscaling for your instance group, increase the CPU utilization of each instance. In the specification.yaml file, the scale_policy.auto_scale.cpu_utilization_rule.utilization_target parameter is set to 40: it means that the target utilization level is 40% CPU. If you exceed the target utilization, the number of VMs in the group will increase.

Increase the utilization for the instance group.

To do this, save the script named load.sh to the home directory. The script sends requests to the instance group through 12 threads for 10 minutes. Each VM instance utilizes 20% CPU on each core that processes the request. The instance group utilization is 240% CPU at any given time. To be sure that requests are evenly distributed across the instances in the group, the script executes multiple parallel requests utilizing 20% CPU rather than one request utilizing 240% CPU.
```
EXTERNAL_IP=$(yc load-balancer network-load-balancer get group-balancer --format=json | jq -r .listeners[0].address)

wrk -H "Connection: close" -t12 -c12 -d10m "http://$EXTERNAL_IP/burn-cpu?time=5000&load=20"
```

Run the script:

CLI

sh load.sh

Result:

Running 10m test @ http://130.193.56.111/burn-cpu?time=5000&load=20
  12 threads and 12 connections
  Thread Stats   Avg      Stdev     Max   +/- Stdev
...
Requests/sec: 15.04
Transfer/sec: 3.20KB

View the utilization levels:
Management console
1. In the management console, select the folder where you created the auto-group instance group.
2. Select Compute Cloud.
3. In the panel on the left, click Instance groups.
4. Select auto-group.
5. Go to the Monitoring tab.
  The chart Number of instances in zone shows how the number of instances changed in each availability zone. The chart Average CPU utilization in zone shows average CPU utilization in each availability zone.
6. Go to the Logs tab.
  The page displays messages relating to the instance group autoscaling.
The total utilization of 240% CPU was evenly distributed between two instances in two availability zones and exceeded the target utilization of 40% CPU. Yandex Compute Cloud created one instance more in each availability zone to result in four instances in the group. When the script stopped utilizing the CPU, Compute Cloud automatically decreased the number of instances in the group to two.

How to delete the resources you created

To stop paying for the resources you created:

Open the vm-autoscale.tf configuration file and delete the description of the new infrastructure from it.
Apply the changes:
1. In the terminal, change to the folder where you edited the configuration file.
2. Make sure the configuration file is correct using the command:
```
terraform validate
```
  If the configuration is correct, the following message is returned:
```
Success! The configuration is valid.
```
3. Run the command:
```
terraform plan
```
  The terminal will display a list of resources with parameters. No changes are made at this step. If the configuration contains errors, Terraform will point them out.
4. Apply the configuration changes:
```
terraform apply
```
5. Confirm the changes: type yes in the terminal and press Enter.

Running an instance group with autoscaling using Terraform

Prepare your cloud

Required paid resources

Create an infrastructure

Test your instance group and network load balancer

Test autoscaling

How to delete the resources you created

See also

Was the article helpful?

Running an instance group with autoscaling using Terraform

Prepare your cloudPrepare your cloud

Required paid resourcesRequired paid resources

Create an infrastructureCreate an infrastructure

Test your instance group and network load balancerTest your instance group and network load balancer

Test autoscalingTest autoscaling

How to delete the resources you createdHow to delete the resources you created

See alsoSee also

Was the article helpful?

Prepare your cloud

Required paid resources

Create an infrastructure

Test your instance group and network load balancer

Test autoscaling

How to delete the resources you created

See also