Concurrent requests in a single instance

Background

Function Compute is billed based on the total duration on instances. If three requests are processed in three instances and the latency to access a database is 10 seconds, the total duration is 30 seconds. If the three requests are concurrently processed in one instance, the total duration is only 10 seconds. Function Compute supports the feature of processing concurrent requests in one instance, which saves instance resources. Function Compute allows you to specify the InstanceConcurrency parameter for a function. This parameter limits the maximum number of requests that an instance can concurrently process. The following figure shows the differences between processing one request and concurrent requests in an instance.

Assume that three requests need to be concurrently processed. When the instance concurrency is set to 1, Function Compute must create three instances to process the three requests, and each instance processes one request. When the instance concurrency is set to 10 (one instance can process 10 requests concurrently), Function Compute can create only one instance to process the three requests.

Benefits

• Reduces the total duration and saves costs

  Functions that require input/output operations can process multiple requests in one instance to minimize the total duration on multiple instances.

• Provides shared state for requests

  Multiple requests in one instance can share the connection pool of the database to minimize the connections between requests and the database.

• Reduces the frequency of cold starts

  Fewer instances need to be created because multiple requests can be processed in one instance, which reduces the frequency of cold starts.

• Reduces the number of IP addresses used in a virtual private cloud (VPC)

  For a fixed number of requests to be processed, the number of occupied instances is reduced when each instance can handle multiple requests. Therefore, the number of IP addresses used in the VPC can be reduced.

Scenarios

Impacts

After you set InstanceConcurrency to a value greater than 1, it differs from the value 1 in the following aspects:

• Billing
  • Single request processing in a single instance
    A function instance can process only one request at a time. The billing duration starts when the first request starts and ends when the last request is complete.
  • Concurrent request processing in a single instance

    When an instance processes multiple requests concurrently, Function Compute calculates charges based on the duration on an instance. This duration begins when the first request starts and ends when the last request is complete.

    

  For more information, see Billing.

• Concurrent request limit

  Function Compute allows a maximum of 300 pay-as-you-go instances in a region by default. The maximum number of requests that can be concurrently processed in a region is 300 × InstanceConcurrency. For example, if InstanceConcurrency is set to 10, a maximum of 3,000 requests can be concurrently processed in a region. If the number of concurrent requests exceeds the maximum number of requests that Function Compute can process, the ResourceExhausted error occurs.

  Note If you want to increase the number of pay-as-you-go instances in a region, Contact us.
• Logs
  • When an instance processes one request, if you specify X-Fc-Log-Type: Tail in the HTTP header, Function Compute returns the function logs in the X-Fc-Log-Result field that is in the response header. When an instance processes multiple requests concurrently, the response header does not include function logs because the logs of a specific request cannot be obtained among concurrent requests.
  • For the Node.js runtime, the console.info() function is used to return the ID of the current request in the log. When an instance processes multiple requests concurrently, the console.info() function cannot display the correct IDs of all the requests. All the request IDs are changed to req 2. The following example shows a sample log:

    2019-11-06T14:23:37.587Z req1 [info] logger begin
    2019-11-06T14:23:37.587Z req1 [info] ctxlogger begin
    2019-11-06T14:23:37.587Z req2 [info] logger begin
    2019-11-06T14:23:37.587Z req2 [info] ctxlogger begin
    2019-11-06T14:23:40.587Z req1 [info] ctxlogger end
    2019-11-06T14:23:40.587Z req2 [info] ctxlogger end
    2019-11-06T14:23:37.587Z req2 [info] logger end
    2019-11-06T14:23:37.587Z req2 [info] logger end                    

    Therefore, the context.logger.info() function can be used to display logs. This ensures that the correct ID of a request is returned. The following example shows the sample code:

    exports.handler = (event, context, callback) => {
        console.info('logger begin');
        context.logger.info('ctxlogger begin');
    
        setTimeout(function() {
            context.logger.info('ctxlogger end');
            console.info('logger end');
            callback(null, 'hello world');
        }, 3000);
    };                   

• Error handling

  When an instance processes multiple requests concurrently, unexpected process quits caused by failed requests affect other concurrent requests. Therefore, you must compile troubleshooting logic to avoid impacts on other requests. The following example shows how to troubleshoot exceptions by using Node.js:

  exports.handler = (event, context, callback) => {
      try {
          JSON.parse(event);
      } catch (ex) {
          callback(ex);
      }
  
      callback(null, 'hello world');
  };                    

• Shared variables

  When an instance processes multiple requests concurrently, errors may occur if multiple requests attempt to modify the same variable at the same time. You must use the mutual exclusion method to avoid variable modifications that are not safe for threads when you define your functions. The following example shows the sample Java code:

  public class App implements StreamRequestHandler
  {
      private static int counter = 0;
  
      @Override
      public void handleRequest(InputStream inputStream, OutputStream outputStream, Context context) throws IOException {
          synchronized (this) {
              counter = counter + 1;
          }
          outputStream.write(new String("hello world").getBytes());
      }
  }                    

• Monitoring metrics
  After you specify the instance concurrency for your function, you can view that the number of used instances is reduced in the instance monitoring chart.

Limits

References

Specify the request concurrency in a single instance