Instances are the basic building blocks of App Engine, providing all the resources needed to successfully host your application. At any given time, your application can be running on one or many instances with requests being spread across all of them. Each instance includes a security layer to ensure that instances cannot inadvertently affect each other.
App Engine can automatically create and shut down instances as traffic fluctuates, or you can specify a number of instances to run regardless of the amount of traffic. To determine how and when new instances are created, you specify a scaling type for your app.
App Engine supports the following scaling types, which controls how and when instances are created:
You specify the scaling type in your app's
- Automatic scaling
- Automatic scaling creates instances based on request rate, response latencies, and other application metrics. You can specify thresholds for each of these metrics, as well as a minimum number instances to keep running at all times.
- Basic Scaling
- Basic scaling creates instances when your application receives requests. Each instance will be shut down when the application becomes idle. Basic scaling is ideal for work that is intermittent or driven by user activity.
- Manual scaling
- Manual scaling specifies the number of instances that continuously run regardless of the load level. This allows tasks such as complex initializations and applications that rely on the state of the memory over time.
|Feature||Automatic scaling||Basic scaling||Manual scaling|
10 minutes for HTTP requests and task queue tasks. If your app doesn't
return a request within this time limit, App Engine interrupts
the request handler and
an error for your code to handle.
For legacy runtimes (Java 8, PHP 5, and Python 2):
24 hours for HTTP requests and task queue tasks. If your app doesn't
return a request within this time limit, App Engine interrupts the
request handler and
an error for your code to handle.
A basic-scaled instance can choose to handle
|Same as basic scaling.|
|Background threads||Not allowed||Allowed||Allowed|
|Residence||Instances are shut down based on usage patterns.||
Instances are shut down based on the
Instances remain in memory and state is preserved across requests. When
instances are stopped, an
|Startup and shutdown||Instances are created on demand to handle requests and automatically turned down when idle.||
Instances are created on demand to handle requests and automatically
shut down when idle, based on the
Instances are sent a start request automatically by App Engine in the
form of an empty GET request to
|Instance addressability||Instances are anonymous.||
Instance "i" of version "v" of service "s" is addressable at the URL:
||Same as basic scaling.|
App Engine scales the number of instances automatically in response to
processing volume. This scaling factors in the
A service with basic scaling is configured by setting the maximum number
of instances in the
||You configure the number of instances of each version in that service's configuration file. The number of instances usually corresponds to the size of a dataset being held in memory or the desired throughput for offline work.|
Scaling dynamic instances
App Engine applications that use basic or automatic scaling are powered by any number of dynamic instances at a given time, depending on the volume of incoming requests. As requests for your application increase, the number of dynamic instances may increase as well.
Apps with basic scaling
If you use basic scaling, App Engine attempts to keep your cost low, even though that may result in higher latency as the volume of incoming requests increases.
When none of the existing instances are available to serve an incoming request, App Engine starts a new instance. Even after starting a new instance, some requests may need to be queued until the new instance completes its startup process. If you require the lowest latency possible consider using automatic scaling, which creates new instances preemptively to minimize latency.
Apps with automatic scaling
If you use automatic scaling, each instance in your app has its own queue for incoming requests. Before the queues become long enough to have a noticeable effect on your app's latency, App Engine automatically creates one or more new instances to handle the increasing load.
You can configure the settings for automatic scaling to achieve a trade-off between the performance you want and the cost you can incur. The following table describes these settings.
|Automatic scaling settings||Description|
|Target CPU Utilization||Sets the CPU utilization ratio threshold to specify the CPU usage threshold at which more instances will be started to handle traffic.|
|Target Throughput Utilization||Sets the throughput threshold for the number of concurrent requests after which more instances will be started to handle traffic.|
|Max Concurrent Requests||Sets the max concurrent requests an instance can accept before the scheduler spawns a new instance.|
Watch the App Engine New Scheduler Settings video to see the effects of these settings.
When request volumes decrease, App Engine reduces the number of instances. This downward scaling helps ensure that all of your application's current instances are being used to optimal efficiency and cost effectiveness.
When an application is not being used at all, App Engine turns off its associated dynamic instances, but readily reloads them as soon as they are needed. Reloading instances can result in loading requests and additional latency for users.
You can specify a minimum number of idle instances. Setting an appropriate number of idle instances for your application based on request volume allows your application to serve every request with little latency, unless you are experiencing abnormally high request volume.
Scaling and batches of requests
If you are sending batches of requests to your services, for example, to a task queue for processing, a large number of instances will be created quickly. We recommend controlling this by rate limiting the number of request sent per second, if possible. For example, if you use Tasks, you can control the rate at which tasks are pushed.
Instance life cycle
An instance of an auto-scaled service is always running. However, an instance of a manual or basic scaled service can be either running or stopped. All instances of the same service and version share the same state. You change the state of your instances by managing your versions. You can:
- Use the Versions page in the Cloud Console
- Use the Cloud SDK
gcloud app versions start) and stop (
gcloud app versions stop) commands
- Use the Modules service
- Use the
appcfgcommands: start (
appcfg.sh start_module_version) and stop (
Each service instance is created in response to a start request, which is an
GET request to
/_ah/start. App Engine sends this request
to bring an instance into existence; users cannot send a request to
/_ah/start. Manual and basic scaling instances must respond to the start
request before they can handle another request. The start request can be used
for two purposes:
- To start a program that runs indefinitely, without accepting further requests.
- To initialize an instance before it receives additional traffic.
Manual, basic, and automatically scaling instances startup differently. When you
start a manual scaling instance, App Engine immediately sends a
/_ah/start request to each instance. When you start an instance of a basic
scaling service, App Engine allows it to accept traffic, but the
/_ah/start request is not sent to an instance until it receives its first user
request. Multiple basic scaling instances are only started as necessary, in
order to handle increased traffic. Automatically scaling instances do not
When an instance responds to the
/_ah/start request with an HTTP status code
404, it is considered to have successfully started and can
handle additional requests. Otherwise, App Engine terminates the
instance. Manual scaling instances are restarted immediately, while basic
scaling instances are restarted only when needed for serving traffic.
The shutdown process might be triggered by a variety of planned and unplanned events, such as:
- You manually stop an instance.
- You deploy an updated version to the service.
- The instance exceeds the maximum memory for its configured
- Your application runs out of Instance Hours quota.
- Your instance is moved to a different machine, either because the current machine that is running the instance is restarted, or App Engine moved your instance to improve load distribution.
When App Engine creates a new instance for your application, the instance must first load any libraries and resources required to handle the request. This happens during the first request to the instance, called a Loading Request. During a loading request, your application undergoes initialization which causes the request to take longer.
The following best practices allow you to reduce the duration of loading requests:
- Load only the code needed for startup.
- Access the disk as little as possible.
- In some cases, loading code from a zip or jar file is faster than loading from many separate files.
Warmup requests are a specific type of loading request that load application
code into an instance ahead of time, before any live requests are made.
Manual or basic scaling instances do not receive an
App Engine attempts to keep manual and basic scaling instances running indefinitely. However, at this time there is no guaranteed uptime for manual and basic scaling instances. Hardware and software failures that cause early termination or frequent restarts can occur without prior warning and can take considerable time to resolve; thus, you should construct your application in a way that tolerates these failures.
Here are some good strategies for avoiding downtime due to instance restarts:
- Reduce the amount of time it takes for your instances restart or for new ones to start.
- For long-running computations, periodically create checkpoints so that you can resume from that state.
- Your app should be "stateless" so that nothing is stored on the instance.
- Use queues for performing asynchronous task execution.
- If you configure your instances to manual scaling:
- Use load balancing across multiple instances.
- Configure more instances than required to handle normal traffic.
- Write fall-back logic that uses cached results when a manual scaling instance is unavailable.