The app.yaml
file defines your configuration settings for your runtime as well
as general app, network, and other resource settings.
Do not add app.yaml
to the .gcloudignore
file. app.yaml
might be required for deployment, and adding it to
.gcloudignore
will cause the deployment to fail.
Syntax
The syntax of the app.yaml
file is the YAML format.
The YAML format supports comments, where any line that begins with the hash
symbol (#
) character is ignored, for example:
# This is a comment.
URL and file path patterns use POSIX extended regular expression
syntax, excluding collating
elements and collation classes. Back-references to grouped matches (e.g. \1
)
are supported, as are these Perl extensions: \w \W \s \S \d \D
.
General settings
An app.yaml
file can include these general settings. Note that some of them
are required:
Name | Description |
---|---|
build_env_variables
|
Optional. If you are using a runtime that supports
buildpacks, you
can define build environment variables in your
To learn more, see Using build environment variables. |
runtime |
Required. The name of the runtime environment that is used by your app. For example, to specify the runtime environment, use: runtime: java
To specify a supported version of Java or to use the new Java runtimes, see the
|
runtime_config |
Specifies the Java version. Starting in Java version 11, you must specify
the version of the operating system.
runtime_config: operating_system: "ubuntu22" runtime_version: "21"
|
env: flex |
Required: Select the flexible environment. |
service: service_name |
Required if creating a service. Optional for the default service. Each
service and each version must have a name. A name can contain numbers,
letters, and hyphens. In the flexible environment, the combined length of
VERSION-dot-SERVICE-dot-PROJECT_ID
(where VERSION is the name of your version,
SERVICE is the name of your service, and
PROJECT_ID is your project ID) cannot be longer
than 63 characters and cannot start or end with a hyphen.
If you deploy without specifying a service name, then a new version of the default service is created. If you deploy with a service name that already exists, a new version of that service is created. If you deploy with a new service name that doesn't exist, a new service and version are created. We recommend using a unique name for each service-version combination. Note: Services were previously called "modules." |
service_account |
Optional. The The service account must be provided in the following format: service_account: [SERVICE_ACCOUNT_NAME]@[PROJECT_ID].iam.gserviceaccount.com |
skip_files |
Optional.
The
For example, to skip files whose names end in skip_files: - ^.*\.bak$ |
Runtime-specific settings
See the Java
runtime page to learn more about specifying a Java version using the
runtime_config
settings.
Network settings
You can specify network settings in your app.yaml
configuration file, for
example:
network: name: NETWORK_NAME instance_ip_mode: INSTANCE_IP_MODE instance_tag: TAG_NAME subnetwork_name: SUBNETWORK_NAME session_affinity: true forwarded_ports: - PORT - HOST_PORT:CONTAINER_PORT - PORT/tcp - HOST_PORT:CONTAINER_PORT/udp
You can use the following options when configuring network settings:
Option | Description |
---|---|
name |
Every VM instance in the flexible environment is assigned to a Google Compute Engine network when it is created. Use this setting to specify a network name. Give the short name, not the resource path (for example, default rather than https://www.googleapis.com/compute/v1/projects/my-project/global/networks/default ). If you do not specify a network name, instances are assigned to the project's default network (which has the name default ). If you want to specify a subnetwork name, you must specify a network name. |
instance_ip_mode |
Optional. To prevent instances from receiving an ephemeral external IP address, set to internal and enable Private Google Access. If your instance was previously deployed without this setting, or was deployed with this set to external , redeploying with it set to internal removes ephemeral external IP addresses from your instances. The internal setting has limitations. Default is external . |
instance_tag |
Optional. A tag with that name is assigned to each instance of the service when it is created. Tags can be useful in gcloud commands to target an action to a group of instances. For example, see the use of the --source-tags and --target-tags flags in the compute firewalls-create command. If not specified, the instance is tagged with aef-INSTANCE_ID when Shared VPC is not used. If Shared VPC is used, the instance is tagged with both aef-INSTANCE_ID |
subnetwork_name |
Optional. You can segment your network and use a custom subnetwork. Ensure that the network name is specified. Give the short name, not the resource path (for example, default rather than https://www.googleapis.com/compute/v1/projects/my-project/global/networks/default/subnetworks/default ).The subnetwork must be in the same region as the application. |
session_affinity |
Optional. Set to true to configure App Engine to route multiple sequential requests for a given user to the same App Engine instance such as when storing user data locally during a session. Session affinity enables inspecting the value of a cookie to identify multiple requests by the same user and then directs all such requests to the same instance. If the instance is rebooted, unhealthy, overloaded or becomes unavailable when the number of instances has been scaled down, session affinity will be broken and further requests are then routed to a different instance. Note that enabling session affinity can affect your load balancing setup. This parameter is disabled by default. |
forwarded_ports |
Optional. You can forward ports from your instance (HOST_PORT ) to the Docker container (CONTAINER_PORT ). HOST_PORT must be between 1024 and 65535 and cannot conflict with the following ports: 22, 8080, 8090, 8443, 10000, 10001, 10400-10500, 11211, 24231. CONTAINER_PORT must be between 1 and 65535 and cannot conflict with the following ports: 22, 10001, 10400-10500, 11211. If you only specify a PORT , then App Engine assumes that it is the same port on the host and the container. By default, both TCP and UDP traffic are forwarded. Traffic must be directly addressed to the target instance's IP address rather than over the appspot.com domain or your custom domain. |
Advanced network configuration
You can segment your Compute Engine network into subnetworks. This allows you to enable VPN scenarios, such as accessing databases within your corporate network.
To enable subnetworks for your App Engine application:
Add the network name and subnetwork name to your
app.yaml
file, as specified above.To establish a simple VPN based on static routing, create a gateway and a tunnel for a custom subnet network. Otherwise, see how to create other types of VPNs.
Port forwarding
Port forwarding allows for direct connections to the Docker container on your instances. This traffic can travel over any protocol. Port forwarding is intended to help with situations where you might need to attach a debugger or profiler. Traffic must be directly addressed to the target instance's IP address rather than over the appspot.com domain or your custom domain.
By default, incoming traffic from outside your network is not allowed through
the Google Cloud Platform
firewalls.
After you have specified port forwarding in your app.yaml
file, you must add a
firewall rule that allows traffic from the ports you want opened.
You can specify a firewall rule in the Networking Firewall Rules page in the
Google Cloud console
or using gcloud
commands.
For example, if you want to forward TCP traffic from port 2222
:
In the network settings of your
app.yaml
, include:network: forwarded_ports: - 2222/tcp
If you use the Python runtime, modify the
app.yaml
to include:entrypoint: gunicorn -b :$PORT -b :2222 main:app
Specify a firewall rule in the Google Cloud console or using
gcloud compute firewall-rules create
to allow traffic from any source (0.0.0.0/0
) and fromtcp:2222
.
Resource settings
These settings control the computing resources. App Engine assigns a machine type based on the amount of CPU and memory you've specified. The machine is guaranteed to have at least the level of resources you've specified, it might have more.
You can specify up to eight volumes of tmpfs in the resource settings. You can then enable workloads that require shared memory via tmpfs and can improve file system I/O.
For example:
resources:
cpu: 2
memory_gb: 2.3
disk_size_gb: 10
volumes:
- name: ramdisk1
volume_type: tmpfs
size_gb: 0.5
You can use the following options when configuring resource settings:
Option | Description | Default |
---|---|---|
cpu |
The number of cores; it must be one, an even number between 2 and 32, or a multiple of 4 between 32 and 80. | 1 core |
memory_gb |
RAM in GB. The requested memory for your application, which does not include the ~0.4 GB of memory that is required for the overhead of some processes. Each CPU core requires a total memory between 1.0 and 6.5 GB. To calculate the requested memory:
For the example above where you have specified 2 cores, you can
request between 1.6 and 12.6 GB. The total amount of memory available to
the application is set by the runtime environment as the environment
variable |
0.6 GB |
disk_size_gb |
Size in GB. The minimum is 10 GB and the maximum is 10240 GB. | 13 GB |
name |
Required, if using volumes. Name of the volume. Names must be unique and
between 1 and 63 characters. Characters can be lowercase letters,
numbers, or dashes. The first character must be a letter, and the last
character cannot be a dash. The volume is mounted in the app container
as /mnt/NAME .
|
|
volume_type |
Required, if using volumes. Must be tmpfs . |
|
size_gb |
Required, if using volumes. Size of the volume, in GB. The minimum is 0.001 GB and the maximum is the amount of memory available in the application container and on the underlying device. Google does not add additional RAM to your system to satisfy the disk requirements. RAM allocated for tmpfs volumes will be subtracted from memory available to the app container. The precision is system dependent. |
Split health checks
By default, split health checks are enabled. You can use periodic health check requests to confirm that a VM instance has been successfully deployed, and to check that a running instance maintains a healthy status. Each health check must be answered within a specified time interval.
An instance is unhealthy when it fails to respond to a specified number of consecutive health check requests. If an instance is not live, then it is restarted. If an instance is not ready, then it will not receive any client requests. A health check can also fail if there is no free disk space.
There are two types of health checks that you can use:
- Liveness checks confirm that the VM and Docker container are running. App Engine restarts unhealthy instances.
- Readiness checks confirm your instance is ready to accept incoming requests. Instances that fail the readiness check are not added to the pool of available instances.
By default, HTTP requests from health checks are not forwarded to your
application container. If you want to extend health checks to your application,
then specify a path for liveness checks or
readiness checks. A customized health check to your
application is considered successful if it returns a 200 OK
response code.
Liveness checks
Liveness checks confirm that the VM and the Docker container are running. Instances that are deemed unhealthy are restarted.
You can customize liveness check requests by adding an optional liveness_check
section to your app.yaml
file, for example:
liveness_check:
path: "/liveness_check"
check_interval_sec: 30
timeout_sec: 4
failure_threshold: 2
success_threshold: 2
The following settings are available for liveness checks:
Field | Default | Range (Minimum-Maximum) | Description |
---|---|---|---|
path |
None | If you want liveness checks to be forwarded to your application
container, specify a URL path, such as "/liveness_check" |
|
timeout_sec |
4 seconds | 1-300 | Timeout interval for each request, in seconds. |
check_interval_sec |
30 seconds | 1-300 | Time interval between checks, in seconds. Note that this value must be greater than timeout_sec. |
failure_threshold |
4 checks | 1-10 | An instance is unhealthy after failing this number of consecutive checks. |
success_threshold |
2 checks | 1-10 | An unhealthy instance becomes healthy again after successfully responding to this number of consecutive checks. |
initial_delay_sec |
300 seconds | 0-3600 | The delay, in seconds, after the instance starts during which health check responses are ignored. This setting applies to each newly created instance and can allow a new instance more time to get up and running. The setting delays autohealing from checking on and potentially prematurely recreating the instance if the instance is in the process of starting up. The initial delay timer starts when the instance is in RUNNING mode. For example, you may want to increase the delay if your application has initialization tasks that take a long time before it is ready to serve traffic. |
Readiness checks
Readiness checks confirm that an instance can accept incoming requests. Instances that don't pass the readiness check are not added to the pool of available instances.
You can customize health check requests by adding an optional readiness_check
section to your app.yaml
file, for example:
readiness_check:
path: "/readiness_check"
check_interval_sec: 5
timeout_sec: 4
failure_threshold: 2
success_threshold: 2
app_start_timeout_sec: 300
The following settings are available for readiness checks:
Field | Default | Range (Minimum-Maximum) | Description |
---|---|---|---|
path |
None | If you want readiness checks to be forwarded to your application
container, specify a URL path, such as "/readiness_check" |
|
timeout_sec |
4 seconds | 1-300 | Timeout interval for each request, in seconds. |
check_interval_sec |
5 seconds | 1-300 | Time interval between checks, in seconds. Note that this value must be greater than timeout_sec. |
failure_threshold |
2 checks | 1-10 | An instance is unhealthy after failing this number of consecutive checks. |
success_threshold |
2 checks | 1-10 | An unhealthy instance becomes healthy after successfully responding to this number of consecutive checks. |
app_start_timeout_sec |
300 seconds | 1-1800 | This setting applies to new deployments, not individual VMs. It specifies the maximum time in seconds allowed for a sufficient number of instances in a deployment to pass health checks. If this duration is exceeded then the deployment fails and is rolled back. The timer starts when the Compute Engine instances have been provisioned and the Load Balancer backend service has been created. For example, you might want to increase the timeout if you wish to provide longer timeouts during deployments for a sufficient number of instances to become healthy. |
Health check frequency
To ensure high availability, App Engine creates redundant copies of each health checker. If a health checker fails, a redundant one can take over with no delay.
If you examine the nginx.health_check
logs for your application, you might see
health check polling happening more frequently than you have configured, due to
the redundant health checkers that are also following your settings. These
redundant health checkers are created automatically and you cannot configure
them.
Service scaling settings
The keys used to control scaling of a service depend on the type of scaling you assign to the service.
You can use either automatic or manual scaling. The default is automatic scaling.
Automatic scaling
You can configure automatic scaling by adding an automatic_scaling
section to your app.yaml
file. For example:
automatic_scaling:
min_num_instances: 1
max_num_instances: 15
cool_down_period_sec: 180
cpu_utilization:
target_utilization: 0.6
target_concurrent_requests: 100
The following table lists the settings you can use with automatic scaling:
Name | Description |
---|---|
automatic_scaling |
Automatic scaling is assumed by default. Include this line if you are going to specify any of the automatic scaling settings. |
min_num_instances |
The minimum number of instances given to your service. When a service
is deployed, it is given this many instances and scales according
to traffic.
Must be 1 or greater, default is 2 to reduce
latency.
|
max_num_instances |
The maximum number of instances that your service
can scale up to. The maximum number of instances in
your project is limited by your project's
resource quota.
Default is 20 .
|
cool_down_period_sec |
The number of seconds that the autoscaler should wait before it
starts collecting information from a new instance. This prevents the
autoscaler from collecting information when the instance is initializing,
during which the collected usage would not be reliable. The cool-down
period must be greater than or equal to 60 seconds.
Default is 120 .
|
cpu_utilization |
Use this header if you are going to specify the target CPU utilization. |
target_utilization |
Target CPU utilization. CPU use is averaged
across all running instances and is used to decide when to reduce or
increase the number of instances. Note that instances are downscaled
irrespective of in-flight requests 25 seconds after an instance receives
the shutdown signal. Default is 0.5 .
|
target_concurrent_requests |
(Beta) Target number of concurrent connections per instance. If you specify a value for this parameter, then the autoscaler uses the average number of concurrent connections across all running instances to decide when to reduce or increase the number of instances. An instance is downscaled 25 seconds after it receives the shutdown signal, regardless of requests that are in process. If you don't specify a value for this parameter, then the autoscaler doesn't target a number of concurrent connections per instance. Connections are different from requests. A connection can be reused by a client to send multiple requests. |
Manual scaling
You can configure manual scaling by adding a manual_scaling
section to your app.yaml
file. For example:
manual_scaling:
instances: 5
The following table lists the settings you can use with manual scaling:
Name | Description |
---|---|
manual_scaling |
Required to enable manual scaling for a service. |
instances |
The number of instances to assign to the service. |
Defining environment variables
You can define environment variables in app.yaml
to make them available to
your app, for example:
env_variables:
MY_VAR: "my value"
where MY_VAR
and my value
are the name and value of the environment variable
that you want to define and each environment variable entry is indented two
spaces under the env_variables
element.
Using your environment variables
To retrieve and your environment variable for the Java runtime,
use System.getenv()
.
Also see the list of the latest Java
or Java 8 runtime
environment variables that cannot be overwritten. For example, all the
environment variables that are prefixed with GAE
are reserved
for system use.