Cloud Functions has been renamed to Cloud Run functions. For more information, see the Cloud Run functions blog post.

Tips & Tricks

This document describes best practices for designing, implementing, testing, and deploying Cloud Run functions.

Correctness

This section describes general best practices for designing and implementing Cloud Run functions.

Write idempotent functions

Your functions should produce the same result even if they are called multiple times. This lets you retry an invocation if the previous invocation fails part way through your code. For more information, see retrying event-driven functions.

Ensure HTTP functions send an HTTP response

If your function is HTTP-triggered, remember to send an HTTP response, as shown below. Failing to do so can result in your function executing until timeout. If this occurs, you will be charged for the entire timeout time. Timeouts may also cause unpredictable behavior or cold starts on subsequent invocations, resulting in unpredictable behavior or additional latency.

Node.js

const functions = require('@google-cloud/functions-framework');
const escapeHtml = require('escape-html');

/**
 * Responds to an HTTP request using data from the request body parsed according
 * to the "content-type" header.
 *
 * @param {Object} req Cloud Function request context.
 * @param {Object} res Cloud Function response context.
 */
functions.http('helloHttp', (req, res) => {
  res.send(`Hello ${escapeHtml(req.query.name || req.body.name || 'World')}!`);
});

Python


import functions_framework


from markupsafe import escape

@functions_framework.http
def hello_http(request):
    """HTTP Cloud Function.
    Args:
        request (flask.Request): The request object.
        <https://flask.palletsprojects.com/en/1.1.x/api/#incoming-request-data>
    Returns:
        The response text, or any set of values that can be turned into a
        Response object using `make_response`
        <https://flask.palletsprojects.com/en/1.1.x/api/#flask.make_response>.
    """
    request_json = request.get_json(silent=True)
    request_args = request.args

    if request_json and "name" in request_json:
        name = request_json["name"]
    elif request_args and "name" in request_args:
        name = request_args["name"]
    else:
        name = "World"
    return f"Hello {escape(name)}!"

Go


// Package helloworld provides a set of Cloud Functions samples.
package helloworld

import (
	"encoding/json"
	"fmt"
	"html"
	"net/http"

	"github.com/GoogleCloudPlatform/functions-framework-go/functions"
)

func init() {
	functions.HTTP("HelloHTTP", HelloHTTP)
}

// HelloHTTP is an HTTP Cloud Function with a request parameter.
func HelloHTTP(w http.ResponseWriter, r *http.Request) {
	var d struct {
		Name string `json:"name"`
	}
	if err := json.NewDecoder(r.Body).Decode(&d); err != nil {
		fmt.Fprint(w, "Hello, World!")
		return
	}
	if d.Name == "" {
		fmt.Fprint(w, "Hello, World!")
		return
	}
	fmt.Fprintf(w, "Hello, %s!", html.EscapeString(d.Name))
}

Java


import com.google.cloud.functions.HttpFunction;
import com.google.cloud.functions.HttpRequest;
import com.google.cloud.functions.HttpResponse;
import com.google.gson.Gson;
import com.google.gson.JsonElement;
import com.google.gson.JsonObject;
import com.google.gson.JsonParseException;
import java.io.IOException;
import java.io.PrintWriter;
import java.util.logging.Logger;

public class HelloHttp implements HttpFunction {
  private static final Logger logger = Logger.getLogger(HelloHttp.class.getName());

  private static final Gson gson = new Gson();

  @Override
  public void service(HttpRequest request, HttpResponse response)
      throws IOException {
    // Check URL parameters for "name" field
    // "world" is the default value
    String name = request.getFirstQueryParameter("name").orElse("world");

    // Parse JSON request and check for "name" field
    try {
      JsonElement requestParsed = gson.fromJson(request.getReader(), JsonElement.class);
      JsonObject requestJson = null;

      if (requestParsed != null && requestParsed.isJsonObject()) {
        requestJson = requestParsed.getAsJsonObject();
      }

      if (requestJson != null && requestJson.has("name")) {
        name = requestJson.get("name").getAsString();
      }
    } catch (JsonParseException e) {
      logger.severe("Error parsing JSON: " + e.getMessage());
    }

    var writer = new PrintWriter(response.getWriter());
    writer.printf("Hello %s!", name);
  }
}

C#

using Google.Cloud.Functions.Framework;
using Microsoft.AspNetCore.Http;
using Microsoft.Extensions.Logging;
using System.IO;
using System.Text.Json;
using System.Threading.Tasks;

namespace HelloHttp;

public class Function : IHttpFunction
{
    private readonly ILogger _logger;

    public Function(ILogger<Function> logger) =>
        _logger = logger;

    public async Task HandleAsync(HttpContext context)
    {
        HttpRequest request = context.Request;
        // Check URL parameters for "name" field
        // "world" is the default value
        string name = ((string) request.Query["name"]) ?? "world";

        // If there's a body, parse it as JSON and check for "name" field.
        using TextReader reader = new StreamReader(request.Body);
        string text = await reader.ReadToEndAsync();
        if (text.Length > 0)
        {
            try
            {
                JsonElement json = JsonSerializer.Deserialize<JsonElement>(text);
                if (json.TryGetProperty("name", out JsonElement nameElement) &&
                    nameElement.ValueKind == JsonValueKind.String)
                {
                    name = nameElement.GetString();
                }
            }
            catch (JsonException parseException)
            {
                _logger.LogError(parseException, "Error parsing JSON request");
            }
        }

        await context.Response.WriteAsync($"Hello {name}!", context.RequestAborted);
    }
}

Ruby

require "functions_framework"
require "cgi"
require "json"

FunctionsFramework.http "hello_http" do |request|
  # The request parameter is a Rack::Request object.
  # See https://www.rubydoc.info/gems/rack/Rack/Request
  name = request.params["name"] ||
         (request.body.rewind && JSON.parse(request.body.read)["name"] rescue nil) ||
         "World"
  # Return the response body as a string.
  # You can also return a Rack::Response object, a Rack response array, or
  # a hash which will be JSON-encoded into a response.
  "Hello #{CGI.escape_html name}!"
end

PHP

<?php

use Google\CloudFunctions\FunctionsFramework;
use Psr\Http\Message\ServerRequestInterface;

// Register the function with Functions Framework.
// This enables omitting the `FUNCTIONS_SIGNATURE_TYPE=http` environment
// variable when deploying. The `FUNCTION_TARGET` environment variable should
// match the first parameter.
FunctionsFramework::http('helloHttp', 'helloHttp');

function helloHttp(ServerRequestInterface $request): string
{
    $name = 'World';
    $body = $request->getBody()->getContents();
    if (!empty($body)) {
        $json = json_decode($body, true);
        if (json_last_error() != JSON_ERROR_NONE) {
            throw new RuntimeException(sprintf(
                'Could not parse body: %s',
                json_last_error_msg()
            ));
        }
        $name = $json['name'] ?? $name;
    }
    $queryString = $request->getQueryParams();
    $name = $queryString['name'] ?? $name;

    return sprintf('Hello, %s!', htmlspecialchars($name));
}

Do not start background activities

Background activity is anything that happens after your function has terminated. A function invocation finishes once the function returns or otherwise signals completion, such as by calling the callback argument in Node.js event-driven functions. Any code run after graceful termination cannot access the CPU and will not make any progress.

In addition, when a subsequent invocation is executed in the same environment, your background activity resumes, interfering with the new invocation. This may lead to unexpected behavior and errors that are hard to diagnose. Accessing the network after a function terminates usually leads to connections being reset (ECONNRESET error code).

Background activity can often be detected in logs from individual invocations, by finding anything that is logged after the line saying that the invocation finished. Background activity can sometimes be buried deeper in the code, especially when asynchronous operations such as callbacks or timers are present. Review your code to make sure all asynchronous operations finish before you terminate the function.

Always delete temporary files

Local disk storage in the temporary directory is an in-memory filesystem. Files that you write consume memory available to your function, and sometimes persist between invocations. Failing to explicitly delete these files may eventually lead to an out-of-memory error and a subsequent cold start.

You can see the memory used by an individual function by selecting it in the list of functions in the Google Cloud console and choosing the Memory usage plot.

If you need access to long term storage, consider using Cloud Run volume mounts with Cloud Storage or NFS volumes.

You can reduce memory requirements when processing larger files using pipelining. For example, you can process a file on Cloud Storage by creating a read stream, passing it through a stream-based process, and writing the output stream directly to Cloud Storage.

Functions Framework

To ensure that the same dependencies are installed consistently across environments, we recommend that you include the Functions Framework library in your package manager and pin the dependency to a specific version of Functions Framework.

To do this, include your preferred version in the relevant lock file (for example, package-lock.json for Node.js, or requirements.txt for Python).

If Functions Framework is not explicitly listed as a dependency, it will automatically be added during the build process using the latest available version.

Tools

This section provides guidelines on how to use tools to implement, test, and interact with Cloud Run functions.

Local development

Function deployment takes a bit of time, so it is often faster to test the code of your function locally.

Error reporting

In languages that use exception handling, do not throw uncaught exceptions, because they force cold starts in future invocations. See the Error Reporting guide for information on how to properly report errors.

Do not manually exit

Manually exiting can cause unexpected behavior. Please use the following language-specific idioms instead:

Node.js

Do not use process.exit(). HTTP functions should send a response with res.status(200).send(message), and event-driven functions will exit once they return (either implicitly or explicitly).

Python

Do not use sys.exit(). HTTP functions should explicitly return a response as a string, and event-driven functions will exit once they return a value (either implicitly or explicitly).

Go

Do not use os.Exit(). HTTP functions should explicitly return a response as a string, and event-driven functions will exit once they return a value (either implicitly or explicitly).

Java

Do not use System.exit(). HTTP functions should send a response with response.getWriter().write(message), and event-driven functions will exit once they return (either implicitly or explicitly).

C#

Do not use System.Environment.Exit(). HTTP functions should send a response with context.Response.WriteAsync(message), and event-driven functions will exit once they return (either implicitly or explicitly).

Ruby

Do not use exit() or abort(). HTTP functions should explicitly return a response as a string, and event-driven functions will exit once they return a value (either implicitly or explicitly).

PHP

Do not use exit() or die(). HTTP functions should explicitly return a response as a string, and event-driven functions will exit once they return a value (either implicitly or explicitly).

Use Sendgrid to send emails

Cloud Run functions does not allow outbound connections on port 25, so you cannot make non-secure connections to an SMTP server. The recommended way to send emails is to use a third party service such as SendGrid. You can find other options for sending email in the Sending Email from an Instance tutorial for Google Compute Engine.

Performance

This section describes best practices for optimizing performance.

Use dependencies wisely

Because functions are stateless, the execution environment is often initialized from scratch (during what is known as a cold start). When a cold start occurs, the global context of the function is evaluated.

If your functions import modules, the load time for those modules can add to the invocation latency during a cold start. You can reduce this latency, as well as the time needed to deploy your function, by loading dependencies correctly and not loading dependencies your function doesn't use.

Use global variables to reuse objects in future invocations

There is no guarantee that the state of a Cloud Run function will be preserved for future invocations. However, Cloud Run functions often recycles the execution environment of a previous invocation. If you declare a variable in global scope, its value can be reused in subsequent invocations without having to be recomputed.

This way you can cache objects that may be expensive to recreate on each function invocation. Moving such objects from the function body to global scope may result in significant performance improvements. The following example creates a heavy object only once per function instance, and shares it across all function invocations reaching the given instance:

Node.js

const functions = require('@google-cloud/functions-framework');

// TODO(developer): Define your own computations
const {lightComputation, heavyComputation} = require('./computations');

// Global (instance-wide) scope
// This computation runs once (at instance cold-start)
const instanceVar = heavyComputation();

/**
 * HTTP function that declares a variable.
 *
 * @param {Object} req request context.
 * @param {Object} res response context.
 */
functions.http('scopeDemo', (req, res) => {
  // Per-function scope
  // This computation runs every time this function is called
  const functionVar = lightComputation();

  res.send(`Per instance: ${instanceVar}, per function: ${functionVar}`);
});

Python

import time

import functions_framework


# Placeholder
def heavy_computation():
    return time.time()


# Placeholder
def light_computation():
    return time.time()


# Global (instance-wide) scope
# This computation runs at instance cold-start
instance_var = heavy_computation()


@functions_framework.http
def scope_demo(request):
    """
    HTTP Cloud Function that declares a variable.
    Args:
        request (flask.Request): The request object.
        <http://flask.pocoo.org/docs/1.0/api/#flask.Request>
    Returns:
        The response text, or any set of values that can be turned into a
        Response object using `make_response`
        <http://flask.pocoo.org/docs/1.0/api/#flask.Flask.make_response>.
    """

    # Per-function scope
    # This computation runs every time this function is called
    function_var = light_computation()
    return f"Instance: {instance_var}; function: {function_var}"

Go


// h is in the global (instance-wide) scope.
var h string

// init runs during package initialization. So, this will only run during an
// an instance's cold start.
func init() {
	h = heavyComputation()
	functions.HTTP("ScopeDemo", ScopeDemo)
}

// ScopeDemo is an example of using globally and locally
// scoped variables in a function.
func ScopeDemo(w http.ResponseWriter, r *http.Request) {
	l := lightComputation()
	fmt.Fprintf(w, "Global: %q, Local: %q", h, l)
}

Java


import com.google.cloud.functions.HttpFunction;
import com.google.cloud.functions.HttpRequest;
import com.google.cloud.functions.HttpResponse;
import java.io.IOException;
import java.io.PrintWriter;
import java.util.Arrays;

public class Scopes implements HttpFunction {
  // Global (instance-wide) scope
  // This computation runs at instance cold-start.
  // Warning: Class variables used in functions code must be thread-safe.
  private static final int INSTANCE_VAR = heavyComputation();

  @Override
  public void service(HttpRequest request, HttpResponse response)
      throws IOException {
    // Per-function scope
    // This computation runs every time this function is called
    int functionVar = lightComputation();

    var writer = new PrintWriter(response.getWriter());
    writer.printf("Instance: %s; function: %s", INSTANCE_VAR, functionVar);
  }

  private static int lightComputation() {
    int[] numbers = new int[] { 1, 2, 3, 4, 5, 6, 7, 8, 9 };
    return Arrays.stream(numbers).sum();
  }

  private static int heavyComputation() {
    int[] numbers = new int[] { 1, 2, 3, 4, 5, 6, 7, 8, 9 };
    return Arrays.stream(numbers).reduce((t, x) -> t * x).getAsInt();
  }
}

C#

using Google.Cloud.Functions.Framework;
using Microsoft.AspNetCore.Http;
using System.Linq;
using System.Threading.Tasks;

namespace Scopes;

public class Function : IHttpFunction
{
    // Global (server-wide) scope.
    // This computation runs at server cold-start.
    // Warning: Class variables used in functions code must be thread-safe.
    private static readonly int GlobalVariable = HeavyComputation();

    // Note that one instance of this class (Function) is created per invocation,
    // so calling HeavyComputation in the constructor would not have the same
    // benefit.

    public async Task HandleAsync(HttpContext context)
    {
        // Per-function-invocation scope.
        // This computation runs every time this function is called.
        int functionVariable = LightComputation();

        await context.Response.WriteAsync(
            $"Global: {GlobalVariable}; function: {functionVariable}",
            context.RequestAborted);
    }

    private static int LightComputation()
    {
        int[] numbers = { 1, 2, 3, 4, 5, 6, 7, 8, 9 };
        return numbers.Sum();
    }

    private static int HeavyComputation()
    {
        int[] numbers = { 1, 2, 3, 4, 5, 6, 7, 8, 9 };
        return numbers.Aggregate((current, next) => current * next);
    }
}

Ruby

# Global (instance-wide) scope.
# This block runs on cold start, before any function is invoked.
#
# Note: It is usually best to run global initialization in an on_startup block
# instead at the top level of the Ruby file. This is because top-level code
# could be executed to verify the function during deployment, whereas an
# on_startup block is run only when an actual function instance is starting up.
FunctionsFramework.on_startup do
  instance_data = perform_heavy_computation

  # To pass data into function invocations, the best practice is to set a
  # key-value pair using the Ruby Function Framework's built-in "set_global"
  # method. Functions can call the "global" method to retrieve the data by key.
  # (You can also use Ruby global variables or "toplevel" local variables, but
  # they can make it difficult to isolate global data for testing.)
  set_global :my_instance_data, instance_data
end

FunctionsFramework.http "tips_scopes" do |_request|
  # Per-function scope.
  # This method is called every time this function is called.
  invocation_data = perform_light_computation

  # Retrieve the data computed by the on_startup block.
  instance_data = global :my_instance_data

  "instance: #{instance_data}; function: #{invocation_data}"
end

PHP


use Psr\Http\Message\ServerRequestInterface;

function scopeDemo(ServerRequestInterface $request): string
{
    // Heavy computations should be cached between invocations.
    // The PHP runtime does NOT preserve variables between invocations, so we
    // must write their values to a file or otherwise cache them.
    // (All writable directories in Cloud Functions are in-memory, so
    // file-based caching operations are typically fast.)
    // You can also use PSR-6 caching libraries for this task:
    // https://packagist.org/providers/psr/cache-implementation
    $cachePath = sys_get_temp_dir() . '/cached_value.txt';

    $response = '';
    if (file_exists($cachePath)) {
        // Read cached value from file, using file locking to prevent race
        // conditions between function executions.
        $response .= 'Reading cached value.' . PHP_EOL;
        $fh = fopen($cachePath, 'r');
        flock($fh, LOCK_EX);
        $instanceVar = stream_get_contents($fh);
        flock($fh, LOCK_UN);
    } else {
        // Compute cached value + write to file, using file locking to prevent
        // race conditions between function executions.
        $response .= 'Cache empty, computing value.' . PHP_EOL;
        $instanceVar = _heavyComputation();
        file_put_contents($cachePath, $instanceVar, LOCK_EX);
    }

    // Lighter computations can re-run on each function invocation.
    $functionVar = _lightComputation();

    $response .= 'Per instance: ' . $instanceVar . PHP_EOL;
    $response .= 'Per function: ' . $functionVar . PHP_EOL;

    return $response;
}

It is particularly important to cache network connections, library references, and API client objects in global scope. See Optimizing Networking for examples.

Do lazy initialization of global variables

If you initialize variables in global scope, the initialization code will always be executed via a cold start invocation, increasing your function's latency. In certain cases, this causes intermittent timeouts to the services being called if they are not handled appropriately in a try/catch block. If some objects are not used in all code paths, consider initializing them lazily on demand:

Node.js

const functions = require('@google-cloud/functions-framework');

// Always initialized (at cold-start)
const nonLazyGlobal = fileWideComputation();

// Declared at cold-start, but only initialized if/when the function executes
let lazyGlobal;

/**
 * HTTP function that uses lazy-initialized globals
 *
 * @param {Object} req request context.
 * @param {Object} res response context.
 */
functions.http('lazyGlobals', (req, res) => {
  // This value is initialized only if (and when) the function is called
  lazyGlobal = lazyGlobal || functionSpecificComputation();

  res.send(`Lazy global: ${lazyGlobal}, non-lazy global: ${nonLazyGlobal}`);
});

Python

import functions_framework

# Always initialized (at cold-start)
non_lazy_global = file_wide_computation()

# Declared at cold-start, but only initialized if/when the function executes
lazy_global = None


@functions_framework.http
def lazy_globals(request):
    """
    HTTP Cloud Function that uses lazily-initialized globals.
    Args:
        request (flask.Request): The request object.
        <http://flask.pocoo.org/docs/1.0/api/#flask.Request>
    Returns:
        The response text, or any set of values that can be turned into a
        Response object using `make_response`
        <http://flask.pocoo.org/docs/1.0/api/#flask.Flask.make_response>.
    """
    global lazy_global, non_lazy_global

    # This value is initialized only if (and when) the function is called
    if not lazy_global:
        lazy_global = function_specific_computation()

    return f"Lazy: {lazy_global}, non-lazy: {non_lazy_global}."

Go


// Package tips contains tips for writing Cloud Functions in Go.
package tips

import (
	"context"
	"log"
	"net/http"
	"sync"

	"cloud.google.com/go/storage"
	"github.com/GoogleCloudPlatform/functions-framework-go/functions"
)

// client is lazily initialized by LazyGlobal.
var client *storage.Client
var clientOnce sync.Once

func init() {
	functions.HTTP("LazyGlobal", LazyGlobal)
}

// LazyGlobal is an example of lazily initializing a Google Cloud Storage client.
func LazyGlobal(w http.ResponseWriter, r *http.Request) {
	// You may wish to add different checks to see if the client is needed for
	// this request.
	clientOnce.Do(func() {
		// Pre-declare an err variable to avoid shadowing client.
		var err error
		client, err = storage.NewClient(context.Background())
		if err != nil {
			http.Error(w, "Internal error", http.StatusInternalServerError)
			log.Printf("storage.NewClient: %v", err)
			return
		}
	})
	// Use client.
}

Java


import com.google.cloud.functions.HttpFunction;
import com.google.cloud.functions.HttpRequest;
import com.google.cloud.functions.HttpResponse;
import java.io.IOException;
import java.io.PrintWriter;
import java.util.Arrays;

public class LazyFields implements HttpFunction {
  // Always initialized (at cold-start)
  // Warning: Class variables used in Servlet classes must be thread-safe,
  // or else might introduce race conditions in your code.
  private static final int NON_LAZY_GLOBAL = fileWideComputation();

  // Declared at cold-start, but only initialized if/when the function executes
  // Uses the "initialization-on-demand holder" idiom
  // More information: https://en.wikipedia.org/wiki/Initialization-on-demand_holder_idiom
  private static class LazyGlobalHolder {
    // Making the default constructor private prohibits instantiation of this class
    private LazyGlobalHolder() {}

    // This value is initialized only if (and when) the getLazyGlobal() function below is called
    private static final Integer INSTANCE = functionSpecificComputation();

    private static Integer getInstance() {
      return LazyGlobalHolder.INSTANCE;
    }
  }

  @Override
  public void service(HttpRequest request, HttpResponse response)
      throws IOException {
    Integer lazyGlobal = LazyGlobalHolder.getInstance();

    var writer = new PrintWriter(response.getWriter());
    writer.printf("Lazy global: %s; non-lazy global: %s%n", lazyGlobal, NON_LAZY_GLOBAL);
  }

  private static int functionSpecificComputation() {
    int[] numbers = new int[] {1, 2, 3, 4, 5, 6, 7, 8, 9};
    return Arrays.stream(numbers).sum();
  }

  private static int fileWideComputation() {
    int[] numbers = new int[] {1, 2, 3, 4, 5, 6, 7, 8, 9};
    return Arrays.stream(numbers).reduce((t, x) -> t * x).getAsInt();
  }
}

C#

using Google.Cloud.Functions.Framework;
using Microsoft.AspNetCore.Http;
using System;
using System.Linq;
using System.Threading;
using System.Threading.Tasks;

namespace LazyFields;

public class Function : IHttpFunction
{
    // This computation runs at server cold-start.
    // Warning: Class variables used in functions code must be thread-safe.
    private static readonly int NonLazyGlobal = FileWideComputation();

    // This variable is initialized at server cold-start, but the
    // computation is only performed when the function needs the result.
    private static readonly Lazy<int> LazyGlobal = new Lazy<int>(
        FunctionSpecificComputation,
        LazyThreadSafetyMode.ExecutionAndPublication);

    public async Task HandleAsync(HttpContext context)
    {
        // In a more complex function, there might be some paths that use LazyGlobal.Value,
        // and others that don't. The computation is only performed when necessary, and
        // only once per server.
        await context.Response.WriteAsync(
            $"Lazy global: {LazyGlobal.Value}; non-lazy global: {NonLazyGlobal}",
            context.RequestAborted);
    }

    private static int FunctionSpecificComputation()
    {
        int[] numbers = { 1, 2, 3, 4, 5, 6, 7, 8, 9 };
        return numbers.Sum();
    }

    private static int FileWideComputation()
    {
        int[] numbers = { 1, 2, 3, 4, 5, 6, 7, 8, 9 };
        return numbers.Aggregate((current, next) => current * next);
    }
}

Ruby

FunctionsFramework.on_startup do
  # This method is called when the function is initialized, not on each
  # invocation.

  # Declare and set non_lazy_global
  set_global :non_lazy_global, file_wide_computation

  # Declare, but do not set, lazy_global
  set_global :lazy_global do
    function_specific_computation
  end
end

FunctionsFramework.http "tips_lazy" do |_request|
  # This method is called every time this function is called.

  "Lazy: #{global :lazy_global}; non_lazy: #{global :non_lazy_global}"
end

PHP

PHP functions cannot preserve variables between requests. The scopes sample above uses lazy loading to cache global variable values in a file.

This is particularly important if you define several functions in a single file, and different functions use different variables. Unless you use lazy initialization, you may waste resources on variables that are initialized but never used.

Reduce cold starts by setting a minimum number of instances

By default, Cloud Run functions scales the number of instances based on the number of incoming requests. You can change this default behavior by setting a minimum number of instances that Cloud Run functions must keep ready to serve requests. Setting a minimum number of instances reduces cold starts of your application. We recommend setting a minimum number of instances if your application is latency-sensitive.

To learn how to set a minimum number of instances, see Using minimum instances.

Additional resources

Find out more about optimizing performance in the "Google Cloud Performance Atlas" video Cloud Run functions Cold Boot Time.