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AWS Lambda Custom Runtime for PHP: A Practical Example

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By Michael Moussa, APN Ambassador at Rackspace

This year’s AWS re:Invent was a nonstop, high-powered firehose of exciting new features and products.

Native PHP support on Lambda wasn’t one of those features, but the new AWS Lambda runtime API and layers capabilities give us the ability to build a clean, supportable implementation of PHP on Lambda of our own.

In this post, we’ll take a brief look at the overall workflow and runtime lifecycle, and then I’ll show you one way to build a PHP runtime to start powering your PHP applications on AWS Lambda.

Not a PHP developer? You can adapt the examples in this guide to build a custom runtime in your language of choice.

Overview of AWS Lambda Custom Runtimes and Layers

Before we get started, we should take a moment to consider how native language support on Lambda behaves and how the custom runtime API differs.

At a high level, selecting a natively-supported language when creating your Lambda function defines the environment that Amazon Web Services (AWS) will use to execute your function code. The environment has the language runtime (Python, Node, etc.) built in, as well as an implementation of the Lambda Runtime API that manages the execution lifecycle of the environment and invocations of the function itself.

The design of the custom runtime API separates these responsibilities and puts control of the runtime completely in our hands. The environment’s only responsibilities now are starting and shutting down our custom runtime.

The lifecycle of the runtime itself is composed of an Init phase and any number of Invoke phases. The Init phase spans the period of time between when the environment starts our custom runtime, and the time when our actual Lambda function code is executed. The Init phase code will execute only once during the environment lifecycle, during which we can prepare our custom runtime to handle all future Lambda function invocations.

At the conclusion of the Init phase, our runtime sits in the Invoke phase and will continuously ask for and execute additional work until the environment shuts it down entirely.

In addition to being able to define custom runtimes for our Lambda functions, we now have the ability to incorporate reusable components into our Lambda functions in the form of layers. If you’ve written Lambda functions in the past using Node.js, you should be familiar with the practice of packaging the entirety of a node_modulesdirectory with every individual function you create, even if there are no differences between the contents of those node_modules across your overall application.

This tends to be a slow process, which can result in very long build times for large applications consisting of many Lambda functions, especially if some of those Lambda functions didn’t depend on all of the node_modules in the first place.

With the new layering capability, we can publish reusable layers to share among different Lambda functions. For example, we can publish one layer consisting solely of our custom runtime code, and another layer consisting of library code or other dependencies, and then configure our Lambda functions to make the contents of those two previously-published layers available to our function code as needed.

Getting Started

We’ll get to the actual code for the custom runtime later. First, we need to make sure the underlying Lambda Execution Environment is able to execute the PHP code we’ll be writing.

Since there’s no native support for PHP in Lambda, we’ll need to provide the PHP binary for Lambda to use so that we acn execute our custom runtime code. The best way to go about this is to compile the desired version of PHP in an Amazon Linux environment compatible with the same environment in which the Lambda will be executing.

If you’re already familiar with the process of launching an Amazon Elastic Compute Cloud (Amazon EC2) instance, launch one now using the same Amazon Machine Image (AMI) from the underlying Lambda Execution Environment (amzn-ami-hvm-2017.03.1.20170812-x86_64-gp2 at the time of this writing), and ensure it has an AWS Identity and Access Management (IAM) Instance Profile that will allow it to create IAM Roles and manage Lambda functions.

Once this is ready, log into it using SSH. If you haven’t done that sort of thing before, there’s a fantastic step-by-step guide to doing this for PHP 7.0.7. However, since support for PHP 7.0.x has ended at the time of this writing, we’ll be using PHP 7.3.0 for this example.

Follow the instructions in the guide linked above up up to the Setting up PHP on the instance step, and then… read on!

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Compiling PHP

Now compile PHP by running the following commands:

# Update packages and install needed compilation dependencies
sudo yum update -y
sudo yum install autoconf bison gcc gcc-c++ libcurl-devel libxml2-devel -y

# Compile OpenSSL v1.0.1 from source, as Amazon Linux uses a newer version than the Lambda Execution Environment, which
# would otherwise produce an incompatible binary.
curl -sL | tar -xvz
cd openssl-1.0.1k
./config && make && sudo make install
cd ~

# Download the PHP 7.3.0 source
mkdir ~/php-7-bin
curl -sL | tar -xvz
cd php-src-php-7.3.0

# Compile PHP 7.3.0 with OpenSSL 1.0.1 support, and install to /home/ec2-user/php-7-bin
./buildconf --force
./configure --prefix=/home/ec2-user/php-7-bin/ --with-openssl=/usr/local/ssl --with-curl --with-zlib
make install

Once that’s all completed, run /home/ec2-user/php-7-bin/bin/php -v to verify all went well. You should see some variation of the following, depending on the version you installed:

PHP 7.3.0 (cli) (built: Dec 11 2018 17:45:29) ( NTS )
Copyright (c) 1997-2018 The PHP Group
Zend Engine v3.3.0-dev, Copyright (c) 1998-2018 Zend Technologies

Preparing to Write Some Code

Next, let’s set up a working directory to package up and deploy our example:

mkdir -p ~/php-example/{bin,src}/
cd ~/php-example
touch ./src/{hello,goodbye}.php
touch ./bootstrap && chmod +x ./bootstrap
cp ~/php-7-bin/bin/php ./bin

Which gives us this initial directory structure:

+-- bin/
|   +-- php*
|-- bootstrap*
+-- src/
    +-- goodbye.php
    +-- hello.php
2 directories, 4 files

We now have some empty PHP script files where our function code will live, as well as an empty, executable bootstrap file. Let’s talk about bootstrap first.

Since the Lambda environment’s responsibility will be limited to simply starting and shutting down our custom runtime API, it’s up to us to define what is actually going to happen in the Lambda environment once that runtime API starts up. The bootstrap script will be what handles these Init and Invoke phases.

We’ll work on the bootstrap script first, but before we can do that we have one more setup task to complete. Implementing the custom runtime API will involve making a number of HTTP requests and parsing response headers, which can be very cumbersome to do in PHP using natively-available utilities like the various curl_* functions.

Rather than go that route, we’ll use the Composer package manager to install the popular Guzzle PHP HTTP client and simplify our custom runtime API implementation. Since any non-trivial PHP application is almost certainly going to be making use of other open source libraries or frameworks, completing this step will give us the added bonus of having a mechanism available for incorporating additional dependencies as our application evolves.

First, install Composer:

curl -sS | ./bin/php

Which should output something like this:

All settings correct for using Composer

Composer (version 1.8.0) successfully installed to: /home/ec2-user/php-example/composer.phar
Use it: php composer.phar

Next, install Guzzle:

./bin/php composer.phar require guzzlehttp/guzzle

Which gives us this:

Using version ^6.3 for guzzlehttp/guzzle
./composer.json has been updated
Loading composer repositories with package information
Updating dependencies (including require-dev)
Package operations: 5 installs, 0 updates, 0 removals
 - Installing guzzlehttp/promises (v1.3.1): Loading from cache
 - Installing ralouphie/getallheaders (2.0.5): Loading from cache
 - Installing psr/http-message (1.0.1): Loading from cache
 - Installing guzzlehttp/psr7 (1.5.2): Loading from cache
 - Installing guzzlehttp/guzzle (6.3.3): Loading from cache
guzzlehttp/guzzle suggests installing psr/log (Required for using the Log middleware)
Writing lock file
Generating autoload files

Building the Custom Runtime

We’re now ready to implement the custom runtime API and build a couple of example Lambda functions. Let’s start with the bootstrap.

The bootstrap is the main engine that will drive our example; it can be written in any language that Lambda’s underlying Amazon Linux environment is able to run. Since this is a PHP example, both the custom runtime and the bootstrap script itself are written in PHP, and they will be executed using the PHP binary we compiled earlier for Amazon Linux.

Lambda will place the files from our various layers under /opt, so our /home/ec2-user/php-example/bin/php file will ultimately end up being /opt/bin/php. The #!/opt/bin/php shebang declaration at the top of our bootstrap will instruct the program loader to use our PHP binary to execute the remainder of the code.

Here’s what our initial bootstrap script looks like:


// This invokes Composer's autoloader so that we'll be able to use Guzzle and any other 3rd party libraries we need.
require __DIR__ . '/vendor/autoload.php';

// This is the request processing loop. Barring unrecoverable failure, this loop runs until the environment shuts down.
do {
    // Ask the runtime API for a request to handle.
    $request = getNextRequest();

    // Obtain the function name from the _HANDLER environment variable and ensure the function's code is available.
    $handlerFunction = array_slice(explode('.', $_ENV['_HANDLER']), -1)[0];
    require_once $_ENV['LAMBDA_TASK_ROOT'] . '/src/' . $handlerFunction . '.php';

    // Execute the desired function and obtain the response.
    $response = $handlerFunction($request['payload']);

    // Submit the response back to the runtime API.
    sendResponse($request['invocationId'], $response);
} while (true);

The overall flow of things is fairly straightforward. We obtain the next request that needs to be handled, execute the code to handle it, submit a response, then repeat the process.

You may have noticed there’s no error handling or abstractions of any kind in place. For this example, this is done purposely in the interest of brevity. In a real, object-oriented application, we’d have graceful error handling in place and be delegating things like input parsing, sanitization, request routing, and so on to an application framework.

Please consult the Runtime API documentation as you build your production custom runtimes in order to ensure that you’re handling all eventualities as gracefully as possible/ Otherwise, an unhandled error will cause the custom runtime to be terminated prematurely.

Now that we’ve got the overall structure of the request processing loop in place, let’s add the getNextRequest() and sendResponse() implementations to our bootstrap.

function getNextRequest()
    $client = new \GuzzleHttp\Client();
    $response = $client->get('http://' . $_ENV['AWS_LAMBDA_RUNTIME_API'] . '/2018-06-01/runtime/invocation/next');

    return [
      'invocationId' => $response->getHeader('Lambda-Runtime-Aws-Request-Id')[0],
      'payload' => json_decode((string) $response->getBody(), true)

Here, we’re making a GET request to the runtime API to obtain the next Lambda invocation that needs to be serviced. Each response will provide some information about the invocation in the response headers. For now, we’re just interested in the Invocation ID (Lambda-Runtime-Aws-Request-Id).

We’ll also grab the request payload to supply request parameters to our functions. We’ll retrieve those and return a simple associative array to make these values available to the caller.

function sendResponse($invocationId, $response)
    $client = new \GuzzleHttp\Client();
    'http://' . $_ENV['AWS_LAMBDA_RUNTIME_API'] . '/2018-06-01/runtime/invocation/' . $invocationId . '/response',
       ['body' => $response]

To send the response, we POST back to the runtime API with whatever output text our functions return.

Coding Our Example Functions

Let’s fill in the Lambda functions. We’ll just have two simple functions, hello() and goodbye(), which each expect an array of $data having a name key with a value that they will say “Hello” or “Goodbye” to.

Save the following to src/hello.php:


function hello($data)
    return "Hello, {$data['name']}!";

and save this to src/goodbye.php:


function goodbye($data)
    return "Goodbye, {$data['name']}!";

Before we create and test our custom runtime API and PHP functions, let’s take a quick inventory. By now you should have the following items:

  • PHP binary compiled on Amazon Linux
  • bootstrap file coded in PHP to handle the Init and ongoing Invoke phases
  • vendor directory with Guzzle’s source code
  • Two simple PHP functions: hello() and goodbye()


Let’s prepare our layers and function code for publication:

zip -r bin bootstrap
zip -r vendor/
zip src/hello.php
zip src/goodbye.php

Before publishing everything, we’ll need to make sure we’re on a recent enough version of the AWS Command Line Interface (CLI) that has the new Lambda capabilities available.

The easiest way to do this is to just update to the latest version:

sudo pip install --upgrade awscli

Now, we can publish our two layers. In my case, I’ve assigned an IAM instance profile to my Amazon EC2 instance that gives me access to the necessary AWS APIs to handle all publication from the instance. You can opt to do the same, or just download the four zip files and run them locally using your own IAM user credentials.

Naturally, you can also use the Amazon Web Console. To do this using the CLI, we’ll first need to create an execution role for our Lambda.

Save the following to /tmp/trust-policy.json:

  "Version": "2012-10-17",
  "Statement": [
    "Effect": "Allow",
    "Principal": {
      "Service": ""
   "Action": "sts:AssumeRole"

And then run:

aws iam create-role \
    --role-name LambdaPhpExample \
    --path "/service-role/" \
    --assume-role-policy-document file:///tmp/trust-policy.json

Make note of the Role.Arn output value (e.g. arn:aws:iam::XXXXXXXXXXXX:role/service-role/LambdaPhpExample), which you’ll need for the next steps.

Now, let’s create our runtime and vendorlayers:

aws lambda publish-layer-version \
    --layer-name php-example-runtime \
    --content fileb:// \
    --region us-east-1

aws lambda publish-layer-version \
    --layer-name php-example-vendor \
    --zip-file fileb:// \
    --region us-east-1

Make note of each command’s LayerVersionArn output value (e.g. arn:aws:lambda:us-east-1:XXXXXXXXXXXX:layer:php-example-runtime:1), which you’ll need for the next steps.

Next, let’s create our two functions (be sure to replace the XXXXXXXXXXXX with your account number):

aws lambda create-function \
    --function-name php-example-hello \
    --handler hello \
    --zip-file fileb://./ \
    --runtime provided \
    --role "arn:aws:iam::XXXXXXXXXXXX:role/service-role/LambdaPhpExample" \
    --region us-east-1 \
    --layers "arn:aws:lambda:us-east-1:XXXXXXXXXXXX:layer:php-example-runtime:1" \

aws lambda create-function \
    --function-name php-example-goodbye \
    --handler goodbye \
    --zip-file fileb://./ \
    --runtime provided \
    --role "arn:aws:iam::XXXXXXXXXXXX:role/service-role/LambdaPhpExample" \
    --region us-east-1 \
    --layers "arn:aws:lambda:us-east-1:XXXXXXXXXXXX:layer:php-example-runtime:1" \


And finally, let’s invoke them!

aws lambda invoke \
    --function-name php-example-hello \
    --region us-east-1 \
    --log-type Tail \
    --query 'LogResult' \
    --output text \
    --payload '{"name": "World"}' hello-output.txt | base64 --decode

aws lambda invoke \
    --function-name php-example-goodbye \
    --region us-east-1 \
    --log-type Tail \
    --query 'LogResult' \
    --output text \
    --payload '{"name": "World"}' goodbye-output.txt | base64 --decode

The --query 'LogResult' --output text parameters and | base64 --decode will display the logging output you’d normally see in Amazon CloudWatch Logs to the CLI.

If all goes well, the output should look something like this:

START RequestId: bf3a91af-f380-11e8-8a98-99a71fd9601e Version: $LATEST
END RequestId: bf3a91af-f380-11e8-8a98-99a71fd9601e
REPORT RequestId: bf3a91af-f380-11e8-8a98-99a71fd9601e  Init Duration: 141.20 ms Duration: 74.11 ms Billed Duration: 300 ms     Memory Size: 128 MB Max Memory Used: 38 MB

START RequestId: d14d2f9b-f380-11e8-8a98-99a71fd9601e Version: $LATEST
END RequestId: d14d2f9b-f380-11e8-8a98-99a71fd9601e
REPORT RequestId: d14d2f9b-f380-11e8-8a98-99a71fd9601e  Init Duration: 101.65 ms Duration: 77.20 ms Billed Duration: 200 ms     Memory Size: 128 MB Max Memory Used: 27 MB

Subsequent invocations of the same functions will not have Init phases (so long as there’s an active runtime waiting to process new work), and the duration of the Invoke phase will generally be lower.

For example:

REPORT RequestId: 4bbf021d-fd75-11e8-9129-574c933ae3eb  Duration: 4.41 ms Billed Duration: 100 ms Memory Size: 128 MB Max Memory Used: 38 MB
REPORT RequestId: 4c97876f-fd75-11e8-becf-a9bea4741119  Duration: 9.59 ms Billed Duration: 100 ms Memory Size: 128 MB Max Memory Used: 38 MB
REPORT RequestId: 4d298e9b-fd75-11e8-ac02-d96b0f356492  Duration: 2.68 ms Billed Duration: 100 ms Memory Size: 128 MB Max Memory Used: 38 MB
REPORT RequestId: 4d971d18-fd75-11e8-a534-73dd2a333b34  Duration: 1.94 ms Billed Duration: 100 ms Memory Size: 128 MB Max Memory Used: 38 MB

A quick cat of the hello-output.txt and goodbye-output.txt files will also reveal the Hello, World! and Goodbye, World! output, respectively.


In this post, you got a glimpse into what’s possible with the new Lambda custom runtime API and layering capabilities. From here, you can choose to incorporate API Gateway with Lambda integrationuse your Lambda functions as Application Load Balancer targets, or even use these functions as behind-the-scenes PHP workers to perform tasks asynchronously.

The new runtime APIs for Lambda make it possible to create runtimes for any programming language. You can see other examples for Rust and C++ that AWS has already open sourced.

As a Senior Product Architect at Rackspace, I’m excited about what these new capabilities could mean for PHP applications in 2019, and I look forward to seeing what you build with them.

If you build something you’d like to share, leave a comment below, or reach out to me on Twitter.

Next Steps

Are you excited about this and other recent AWS launch announcements? Schedule a free strategy session to discuss how Rackspace can assist in taking advantage of new AWS products and services.

Rackspace is an AWS Partner Network (APN) Premier Consulting Partner and Managed Service Provider (MSP) that holds more than 1,000 AWS Certifications. Rackspace has achieved AWS Competency status in seven key areas, including Financial Services, Migration, Storage, Microsoft Workloads, Oracle, DevOps, and Marketing and Commerce.

Rackspace has also been named an AWS Migration Acceleration Program (MAP) Partner and Public Sector Partner.

The content and opinions in this blog are those of the third party author and AWS is not responsible for the content or accuracy of this post.


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