Scaling a Laravel Application with Memcache on DigitalOcean

In this tutorial, we’re going to use Digital Ocean’s pre-build LEMP stack image to deploy a simple Laravel application and demonstrate how to use Memcache to improve application performance. (LEMP is Linux + Nginx + MySQL + PHP.)

Memcache is a fast caching layer that sits behind web applications and mobile application backends. It can be used to cache the results of database queries, page or page fragment renders, or the results of any other long-running computation that your application might need to reuse for multiple client requests. Using Memcache can help speed up responses to client requests and can help with horizontal scaling by reducing the load on database backends and application servers.

Prerequisites

The prerequisites for this tutorial are minimal, since we’re going to do everything on a single DigitalOcean droplet that we’ll set up from scratch.

You will need a DigitalOcean account and some familiarity with PHP and Laravel (I used version 5.8 for this tutorial), but that’s about all. (You’ll also need an SSH key to set up the droplet.)

Let’s get started.

Setting up a DigitalOcean droplet

In this section, we’ll do the initial setup of our DigitalOcean droplet.

Launch droplet from LEMP Ubuntu 18.04 image

From the DigitalOcean dashboard, launch a single droplet using the following configuration choices:

  • Image Under the “Choose an image” heading on the drop launch page, choose the “Marketplace” tab and select the “LEMP on 18.04” image. DigitalOcean provides a range of images in their marketplace that have common software stacks pre-installed. This can save a lot of time: instead of installing Nginx, MySQL and PHP yourself (and setting them up), you launch a droplet from the LEMP image and you have everything there ready to go.
  • Plan Choose the smallest droplet size for this tutorial: you don’t need anything larger. (Currently the smallest droplet size is a 1 Gb “Standard” droplet, which costs $5/month.)
  • Datacenter Choose a data center that’s geographically close to where you are. For this tutorial, it doesn’t matter which one.
  • SSH key If you’ve used DigitalOcean before, you probably already have an SSH key set up that you can choose to use in this part of the droplet setup page. If not, choose “New SSH Key”, paste your public key into the dialog that pops up and give the SSH key a name. Once the droplet is created, this public key will end up in the /root/.ssh/authorized_keys file on the droplet, allowing you to SSH into the droplet as the root user. (We’ll set up an application user once the droplet is running so that we don’t need to use the root user.)
  • Other options Leave all the other options at their default values, give your droplet a name (lemp-test or something like that), and hit the “Create” button.

SSH into droplet as root

It takes a minute or two to create your droplet. Once the droplet is there, you can view it in the DigitalOcean dashboard. From the droplet view, you can copy the IP address of the droplet. You can then SSH into the droplet as

where <ip-address> is the droplet’s IP address from the dashboard view. (If you’re using an SSH key other than your normal one, you might need to add the key to your SSH key management agent, or use the -i flag to ssh to tell it which key to use.)

If everything is set up right, you’ll end up with a root shell prompt on your new droplet.

In this tutorial, we’re just going to refer to our droplet using its IP address. If we were doing all this for real, we would set up a DNS name to point to the droplet. (We’re also not going to set up HTTPS, which is something that you should do for all production systems.)

Set up demo user

We don’t want to use the root user for further steps, so we’ll create a user called demo. There are a few steps to this, to make things convenient in what follows. As the root user on your droplet, do the following:

First, create the demo user account (the options here are mostly to fill in default values for some uninteresting fields in the password file):

Then copy the SSH keys from root to the demo user so that we can use the same SSH keys to log in as demo:

Allow the demo user to use sudo, and modify the sudo configuration to allow members of the sudo user group to use sudo without supplying a password:

At this point, the demo user is set up, so log out of the droplet and log back in as demo:

From here on, all commands should be run as the demo user on the droplet.

Setting up the application

The next step is to set up our basic Laravel application. We’re going to use a simple task list based on the Laravel tutorial. The code for this is in a GitHub repo, with one branch each for a version with no caching and one with database query caching.

OS package installation

We need a few extra operating system packages beyond those installed by default in the DigitalOcean LEMP image. We can install these by doing:

Install Composer

We’ll manage PHP dependencies using the Composer tool. We can install this by doing the following:

Once this is done, just running the composer command should give you Composer’s help message.

Set up to run application from Nginx

We’re going to be running our Laravel code using PHP-FPM behind Nginx. This is already set up in the LEMP stack, but we need to do a few things to make Nginx play nicely with our application code.

First we’ll create a directory to put our application in:

Next, we need to change some of the configuration settings for Nginx to make it default to looking in our application directory to serve our application views, and to use an index.php file without clients needing to add it to the URL. The following sed commands make the necessary changes (and then we force Nginx to reload its configuration data). If you prefer to edit the /etc/nginx/sites-available/digitalocean file by hand, go ahead and do that:

Set up application code

We don’t have any application code in place yet, so in the /var/www/html/demo directory, we next clone the tutorial repository and switch to the branch that doesn’t have any caching set up:

Now we install the PHP dependencies using Composer, and set some permissions to allow the PHP-FPM process to write logs and other data (this step is important and nothing will work if you don’t do it!):

Laravel reads a number of configuration settings from a .env file that we need to set up. Replace <ip-address> in the following with the IP address of your droplet:

All the possible configuration settings are explained in the Laravel documentation, but what we have here is a minimal sort of configuration to allow us to connect to a local MySQL server. We’ll create the database next.

Create database

The LEMP stack includes a pre-configured MySQL installation, so we just need to create a database for our application. The DigitalOcean droplet setup code puts the root password for the MySQL server into a file on the droplet (/root/.digitalocean_password), so we can cut and paste the password from there to log into the MySQL server:

Now paste in the MySQL root password. The following commands are then run from the MySQL prompt:

At this point we have a database called demo accessible by the Linux demo user using password demopassword, all of which match what we wrote in the .env configuration file.

We now use the Artisan tool to run the database migrations to set up the application’s model tables:

(We need to say --force because we’re setting this up as a production application.) Note that Artisan also picks up the database name and credentials from the .env file.

Test basic Laravel app

At this point, the basic Laravel application should be working. If you visit http://<ip-address>/ in your browser (replace <ip-address> with your droplet’s IP address), you should see a (very simple) task manager application.

If you follow all the steps above, this should work, and you should be able to add and delete tasks. If things don’t work, you can look in the Laravel logs (in /var/www/html/demo/storage/logs) or the Nginx logs (in /var/log/nginx) to see what’s going on.

In the source for the application, you might want to take a look at:

  • resources/views/tasks.blade.php: the view for the task list;
  • routes/web.php: contains all the controller code for the task list, with routes to list all tasks, create a new task and delete an existing task;
  • database/migrations/2019_..._create_tasks_table.php: the database migration to create the task table.

Next, we’ll extend the controller code to make use of a Memcache cache to cache the results of our task list database query.

Caching with Laravel and MemCachier

Now that we have a working application, it’s time to explore some caching options. In this section, we’re going to set up a MemCachier cache and add the relevant configuration to our Laravel application to use the cache, then we’ll demonstrate how to cache the results of database queries, and to invalidate cached values at the appropriate time.

Cache configuration

The code demonstrating database caching is on the db-caching branch in the repository, so in the /var/www/html/demo directory, switch to this branch with:

We now need to install the PHP requirements to work with Memcache:

Installing the php-memcached package changes the PHP configuration under the /etc/php directory to include the shared object files needed for the PHP interpreter to talk to Memcache. We need to restart the PHP-FPM process to pick up this change in configuration, by doing

This step is important: caching will not work without doing it, and you will see lots of errors in the Laravel logs about not being able to find things called Memcached::something.

We can now create a cache on MemCachier: create an account, then add a free development cache (25 Mb in size, plenty big enough for experimentation), on DigitalOcean and in the same region as the droplet you created earlier.

Your MemCachier dashboard will show you the server name and credentials to use to connect to your cache. Add these to your .env file:

(Fill in the ... from the values provided by MemCachier.)

The Laravel configuration changes needed to enable Memcache support can be seen here. The configuration options shown there are good choices for operation with MemCachier.

Caching database queries

One of the most common uses for a caching layer like Memcache is to cache the results of expensive database queries that are needed by multiple client requests. For example, a news site might show the last ten stories on its front page, and all clients viewing the front page need to see the same set of stories. In this case, it makes sense to cache the result of the query used to make the story list so that it can be reused by multiple client requests without needing to touch the database again.

Let’s do something like this for the task list. Although the database query there is very simple and low-cost, we can demonstrate how caching works.

The changes to make this work are all in the routes/web.php file. First, we use the Cache::rememberForever function in the GET route to handle the caching:

The rememberForever function takes as arguments a cache key to identify the information we’re caching, and a function to generate the data we want to cache. Here, we use “all_tasks” as the cache key, and use the same database query as in the non-caching code to get the query results. When the rememberForever function is called, it checks the cache to see if there is data stored under the all_tasks key. If there is data there, it’s returned immediately (so no database query is needed). If the data is not found in the cache, the database query is run and the result is stored in the cache. This means that the database query is only run once.

To make the behaviour of the caching code visible, we include some statistics in the task list view, which we retrieve and pass into the view. This allows us to see count how often data is found in the cache (“a cache hit”) and when the database query has to be run (“a cache miss”).

Of course, if we change the list of tasks by creating a new one or deleting and existing one, the cached task list data becomes invalid. We thus need a way to clear the cached data whenever these changes happen. We can do this using the Cache::forget function, which we add to the POST and DELETE routes:

This need to invalidate cached data is often the greatest difficulty in including a caching layer into an existing application. Here the invalidation logic is simple (invalidate any time the task list has an entry added or removed), but in more complicated cases it can require some thought.

Using the code on the db-caching branch, we can view the task list and add and remove tasks as before. The behaviour of the application is substantially unchanged, but behind the scenes, far fewer database queries are happening. Any time we reload the task list page, the task list is served directly from the cached data, not the database. The effect of adding or deleting tasks on the cache behaviour can be seen by looking at the “Set commands”, “Get hits” and “Get misses” counters at the bottom of the page.

Clean up and conclusions

The only cleanup needed after this tutorial is to destroy the DigitalOcean droplet you created at the beginning (go to the “Destroy” tab on the droplet view in the DigitalOcean dashboard).

Here, we’ve demonstrated only the most common use caching, to avoid rerunning expensive database queries. However, caching can be used in any situation where you have an expensive computation whose result you might want to reuse.

For example, a second common use of a caching layer is to cache fragments of rendered pages. As an example, think of a microblogging site like Twitter, where individual posts need to be rendered to HTML and displayed in different settings on many different pages (different users’ timelines, search results, results of hashtag queries, and so on). Depending on the exact performance of the rendering code, it may make sense to render each individual post once, cache the renders, then serve the cached renders to make the composite pages that users see. (This can be achieved using the laravel-partialcache package.)

Laravel’s caching API is flexible enough to support both these common use cases and more unusual applications.

Further reading and resources