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6003 views · 3 years ago
Web Sockets in PHP

In his talk Websockets in PHP, John Fransler walks us through the use of WebSockets in PHP.

While discussing bi-directional real-time application development, John notes that PHP is often not invited to the table due to its lack of native support. Of all the possible attempts to bring in PHP on this stage of real-time development, Ratchet, a PHP WebSocket library, comes closest. "Ratchet is a loosely coupled PHP library providing developers with tools to create real-time, bi-directional applications between clients and servers over WebSockets."* Ahem!

Today's dynamic world


In today's dynamic content world of the internet, it is required to serve real-time bi-directional messages between clients and servers. WebSockets are simple, full-duplex, and persistent. They work over Http and are a standard today.

WebSockets have compatibility with 96.5% of clients globally

There's a very high chance your client has the necessary plumbing to access your content via WebSockets. WebSockets gives the ability to have real-time data on to your clients without the need for polling.

To understand WebSockets, John takes an example of a Javascript client and Ratchet Server. Javascript has everything built in to allow access to a socket. For example, you can use the send method on a WebSocket variable to send a message to the server, or if you want to respond to a message from the server, you use the OnConnection method.

While on the Server, John uses Ratchet, which is built on React PHP. A server script is then configured and set up to run and listen on a port for incoming HTTP requests. For messages, JSON is used, and to find public methods, a router is set up. He then goes on to instantiate the server-side script in Ratchet.

There are four functions of a Ratchets message component interface that are used in this example:

OnOpen gets called when a new connection is made.

OnClose gets called when a client quits. It's essential to keep an eye on memory management, and essential to keep tidying up as you move through the code.

OnError gets called when there is an exception faced by the user.

OnMessage gives the text of the JSON message, which is being exchanged with the client.

For Initialization, Jason continues to walk through the example. He shows how one can loop through the clients, both inside the server and outside the server. Outside the server, it’s a feature of React PHP. On database access, and with traditional standard synchronous MySQL in PHP, what usually happens is that it forces the code to wait for the query to return a result and do nothing — Fortunately, with Asynchronous MySQLi, that is not the case.

John gets into the details explaining Variables, References & Pointers. He also gives a demo where a central site has updated information on the Bitcoin and ether prices. A client terminal reflects the last values. Now the client doesn't have to poll the server for new values. When there is a change in the Bitcoin or ether values, the server pushes down the client's update. No polling helps with a lot of overheads and gets closer to real-time.

Using Supervisord


For Long-running applications - Jason recommends running a supervisord, use proxy to expose the port, and add a site certificate. Supervisord keeps an eye out for the server running the service; it can be used to restart the service and log any service issues. Recommended proxies are AWS load balancer, Nginx, and HA Proxy. For scalability, use multiple smaller WebSocket servers and a smaller number of clients per server used and load balancing. If one has to support a chat feature to allow clients to talk to each other in near real-time, it is recommended to use Redis. The Redis server proxies the messages between the server nodes.

The talk concludes with John summarizing best practices on error handling and takes QnA on various aspects of WebSockets such as handling load balancers and asynchronous calls to MSQLi.

The presentation for this video, along with the code, is hosted at John Curt's GitHub. More info about John's current areas of interest can be found on John's Blog.

Watch the video now


Related videos
10970 views · 3 years ago


It took me quite some time to settle on my first blog post in this series and I found myself thinking about the most requested functionality in my career – The good ‘ol Custom CMS – typically geared towards clients that want a straight forward, secure solution that can be expanded upon in a modular format and that’s their IP.

This will be our starting point. A blank slate to build something epic with clean code and even cleaner design. And in the spirit of building from scratch, I will refrain from using classes or a framework. The main reasoning behind this is to truly get everyone acquainted with and excited about PHP development.

Join me as I transform rudimentary code into something extraordinary that can be morphed into just about any Content, PHP, and MySQL driven project. So without further ado, let’s jump into it!

The bare necessities


If you’re just getting started with development, there’s a nifty bite sized server called UniformServer that will be your best friend throughout your coding career. PHPMyAdmin (an awesome visual db management tool) comes built in so if you’re looking for a work right out of the box solution, this is it.

Alternatively, you can opt for XAMPP or use an alternative server of your choice.

Now here’s where the exciting stuff begins, mapping things out.


I don’t see this done/encouraged often enough. Feel free to grab a piece of paper to logically map out your steps or produce a rough draft of where you’d like this project to go.

In this tutorial, I would like to achieve the following:



DB, DB, Set up your DB.


This requires a bit of planning but let’s start of with the basic structure we need to see this through.

We are going to need a user table and a content table and are a few ways to tackle this.

If you’re using the PHPMyAdmin tool you can create your database, add user permissions (Click on Permissions after creating your database), and create a table with ease.



If you’re like me and prefer to look at good ‘ol SQL then writing an SQL statement is the preferred approach.


CREATE TABLE <code>mydbname</code>.<code>content</code> ( <code>ID</code> INT(11) NOT NULL AUTO_INCREMENT , <code>title</code> VARCHAR(100) NOT NULL , <code>content</code> LONGTEXT NOT NULL , <code>author</code> VARCHAR(50) NOT NULL , PRIMARY KEY (<code>ID</code>)) ENGINE = MyISAM COMMENT = 'content table';


Understanding the SQL statement

In a nutshell we are creating a table with important fields. Namely:

####

ID | Title | Content | Author

#######

The ID field is our unique identifier.Now we can move on to the file structure.

Everything has a place in the file structure game


You can use a structure that speaks to your coding style / memory.

I tend to use the following:



Choose a name for your CMS, which should be placed at the webroot of your localhost/server.

Replicate the folder structure as per the above example.

Next, we’re going to create a basic connection file.


You can create a conn.php file in your root/includes folder.

The connection file will provide crucial information to connect to the database.

Type the following into your conn.php file, remember to include your own database credentials.


<?php

$letsconnect = new mysqli("localhost","dbuser","dbpass","dbname");

?>


Let’s go to the homepage (index.php)


Create a file called index.php at the root of your CMS folder.

I will be adding comments in my code to help you understand what each line does.

Comments are a useful tool for developers to add important notes private to their code.

We need to pull information from the database so it’s imperative that we include our connection file.


<?php

include('includes/conn.php');

if ($letsconnect -> connect_errno) { echo "Error " . $letsconnect -> connect_error;

}else{

$getmydata=$letsconnect -> query("SELECT * FROM content");

foreach($getmydata as $mydata){ echo "Title: "; echo $mydata['title']; echo "<br/>"; echo "Content: "; echo $mydata['content']; echo "<br/>"; echo "Author: "; echo $mydata['author']; echo "<br/>"; echo "<br/>";

}

}

$letsconnect -> close();

?>


Let’s get a (very) basic backend up and running


Create a file called index.php in your backend folder.

We need to create a basic form to capture our data.

Let’s code some HTML!


<html>

<head><title>Backend - Capture Content</title></head>

<body>

<form action="<?php $_SERVER[‘PHP_SELF’];?>" method="post">

<input type="text" name="title" placeholder="Content Title here" required/>

<textarea name="content">Content Here</textarea>

<input type="text" name="author" placeholder="Author" required/>

<input type="submit" value="Save My Data" name="savedata"/>

</form>

</body>

</html>


Next, we need to process the form data.


Type the following just above the
<form> 
tag.


<?php

if(isset($_POST['savedata'])){

include('../includes/conn.php');

if ($letsconnect->connect_error) {

die("Your Connection failed: " . $letsconnect->connect_error);

}else{

$sql = "INSERT INTO content(title,content,author)VALUES ('".$_POST["title"]."', '".$_POST["content"]."', '".$_POST["author"]."')";

if (mysqli_query($letsconnect, $sql)) {

echo "Your data was saved successfully!";

} else { echo "Error: " . $sql . "" . mysqli_error($letsconnect);

} $letsconnect->close();

}

}

?>


Note, this is a basic MySQL query to insert data. However, before using this in production it's important to add proper escaping and security to prevent SQL injections. This will be covered in the next article.


Congrats you made it to the end of tutorial 1!


Test out your creation, modify your content, and play around.

Go to your sitename/index.php to see your frontend after capturing data via sitename/backend/index.php

Next Up:


codewithme Now With Security, Functionality, and Aesthetics in mind.


Conclusion


Coding doesn’t have to be daunting and it’s my aim to divide a complex system into bitesized tutorials so you can truly use the knowledge you’ve acquired in your own projects.
25037 views · 4 years ago
Introduction to Gitlab CI for PHP developers
As a developer, you've probably at least heard something about CI - Continuous integration. And if you haven't - you better fix it ASAP, because that's something awesome to have on your skill list and can get extremely helpful in your everyday work. This post will focus on CI for PHP devs, and specifically, on CI implementation from Gitlab. I will suppose you know the basics of Git, PHP, PHPUnit, Docker and unix shell. Intended audience - intermediate PHP devs.
Adding something to your workflow must serve a purpose. In this case the goal is to automate routine tasks and achieve better quality control. Even a basic PHP project IMO needs the following:
* linter) checks (cannot merge changes that are invalid on the syntax level)
* Code style checks
* Unit and integration tests
All of those can be just run eventually, of course. But I prefer an automated CI approach even in my personal projects because it leads to a higher level of discipline, you simply can't avoid following a set of rules that you've developed. Also, it reduces a risk of releasing a bug or regression, thus improving quality.
Gitlab is as generous as giving you their CI for free, even for your private repos. At this point it is starting to look as advertising, therefore a quick comparison table for Gitlab, Github, Bitbucket. AFAIK, Github does not have a built-in solution, instead it is easily integrated with third parties, of which Travis CI seems to be the most popular - I will therefore mention Travis here.

Public repositories (OSS projects). All 3 providers have a free offer for the open-source community!


| Provider | Limits |
|---|---|
| Gitlab | 2,000 CI pipeline minutes per group per month, shared runners |
| Travis | Apparently unlimited |
| Bitbucket| 50 min/month, max 5 users, File storage <= 1Gb/month |

Private repositories


| Provider | Price | Limits |
|---|---|---|
| Gitlab | Free | 2,000 CI pipeline minutes per group per month, shared runners |
| Travis | $69/month | Unlimited builds, 1 job at a time |
| Bitbucket| Free | 50 min/month, max 5 users, File storage <= 1Gb/month |

Getting started

I made a small project based on Laravel framework and called it "ci-showcase". I work in Linux environment, and the commands I use in the examples, are for linux shell. They should be pretty much the same on Mac and nearly the same on Windows though.
composer create-project laravel/laravel ci-showcase

Next, I went to gitlab website and created a new public project: https://gitlab.com/crocodile2u/ci-showcase. Cloned the repo and copied all files and folders from the newly created project - the the new git repo. In the root folder, I placed a .gitignore file:
.idea
vendor
.env

Then the .env file:
APP_ENV=development

Then I generated the application encryption key: php artisan key:generate, and then I wanted to verify that the primary setup works as expected: ./vendor/bin/phpunit, which produced the output OK (2 tests, 2 assertions). Nice, time to commit this: git commit &amp;&amp; git push

At this point, we don't yet have any CI, let's do something about it!

Adding .gitlab-ci.yml

Everyone going to implement CI with Gitlab, is strongly encouraged to bookmark this page: https://docs.gitlab.com/ee/ci/README.html. I will simply provide a short introduction course here plus a bit of boilerplate code to get you started easier.
First QA check that we're going to add is PHP syntax check. PHP has a built-in linter, which you can invoke like this: php -l my-file.php. This is what we're going to use. Because the php -l command doesn't support multiple files as arguments, I've written a small wrapper shell script and saved it to ci/linter.sh:
#!/bin/sh
files=<code>sh ci/get-changed-php-files.sh | xargs</code>last_status=0
status=0
# Loop through changed PHP files and run php -l on each
for f in "$files" ; do message=<code>php -l $f</code> last_status="$?" if [ "$last_status" -ne "0" ]; then # Anything fails -> the whole thing fails echo "PHP Linter is not happy about $f: $message" status="$last_status" fi
done
if [ "$status" -ne "0" ]; then echo "PHP syntax validation failed!"
fi
exit $status

Most of the time, you don't actually want to check each and every PHP file that you have. Instead, it's better to check only those files that have been changed. The Gitlab pipeline runs on every push to the repository, and there is a way to know which PHP files have been changed. Here's a simple script, meet ci/get-changed-php-files.sh:
#!/bin/sh
# What's happening here?
#
# 1. We get names and statuses of files that differ in current branch from their state in origin/master.
# These come in form (multiline)
# 2. The output from git diff is filtered by unix grep utility, we only need files with names ending in .php
# 3. One more filter: filter *out* (grep -v) all lines starting with R or D.
# D means "deleted", R means "renamed"
# 4. The filtered status-name list is passed on to awk command, which is instructed to take only the 2nd part
# of every line, thus just the filename
git diff --name-status origin/master | grep '\.php$' | grep -v "^[RD]" | awk '{ print }'

These scripts can easily be tested in your local environment ( at least if you have a Linux machine, that is ;-) ).
Now, as we have our first check, we'll finally create our .gitlab-ci.yml. This is where your pipeline is declared using YAML notation:
# we're using this beautiful tool for our pipeline: https://github.com/jakzal/phpqa
image: jakzal/phpqa:alpine
# For this sample pipeline, we'll only have 1 stage, in real-world you would like to also add at least "deploy"
stages: - QA
linter:
stage: QA
# this is the main part: what is actually executed
script: - sh ci/get-changed-php-files.sh | xargs sh ci/linter.sh

The first line is image: jakzal/phpqa:alpine and it's telling Gitlab that we want to run our pipeline using a PHP-QA utility by jakzal. It is a docker image containing PHP and a huge variety of QA-tools. We declare one stage - QA, and this stage by now has just a single job named linter. Every job can have it's own docker image, but we don't need that for the purpose of this tutorial. Our project reaches Step 2. Once I had pushed these changes, I immediately went to the project's CI/CD page. Aaaand.... the pipeline was already running! I clicked on the linter job and saw the following happy green output:
Running with gitlab-runner 11.9.0-rc2 (227934c0) on docker-auto-scale ed2dce3a
Using Docker executor with image jakzal/phpqa:alpine ...
Pulling docker image jakzal/phpqa:alpine ...
Using docker image sha256:12bab06185e59387a4bf9f6054e0de9e0d5394ef6400718332c272be8956218f for jakzal/phpqa:alpine ...
Running on runner-ed2dce3a-project-11318734-concurrent-0 via runner-ed2dce3a-srm-1552606379-07370f92...
Initialized empty Git repository in /builds/crocodile2u/ci-showcase/.git/
Fetching changes...
Created fresh repository.
From https://gitlab.com/crocodile2u/ci-showcase * [new branch] master -> origin/master * [new branch] step-1 -> origin/step-1 * [new branch] step-2 -> origin/step-2
Checking out 1651a4e3 as step-2...
Skipping Git submodules setup
$ sh ci/get-changed-php-files.sh | xargs sh ci/linter.sh
Job succeeded

It means that our pipeline was successfully created and run!

PHP Code Sniffer.

PHP Code Sniffer is a tool for keeping app of your PHP files in one uniform code style. It has a hell of customizations and settings, but here we will only perform simple check for compatibilty with PSR-2 standard. A good practice is to create a configuration XML file in your project. I will put it in the root folder. Code sniffer can use a few file names, of which I prefer phpcs.xml:
<?xml version="1.0"?>
/resources

I also will append another section to .gitlab-ci.yml:
code-style:	stage: QA	script:	# Variable $files will contain the list of PHP files that have changes	- files=<code>sh ci/get-changed-php-files.sh</code> # If this list is not empty, we execute the phpcs command on all of them - if [ ! -z "$files" ]; then echo $files | xargs phpcs; fi

Again, we check only those PHP files that differ from master branch, and pass their names to phpcs utility. That's it, Step 3 is finished! If you go to see the pipeline now, you will notice that linter and code-style jobs run in parallel.

Adding PHPUnit

Unit and integration tests are essential for a successful and maintaiable modern software project. In PHP world, PHPUnit is de facto standard for these purposes. The PHPQA docker image already has PHPUnit, but that's not enough. Our project is based on Laravel, which means it depends on a bunch of third-party libraries, Laravel itself being one of them. Those are installed into vendor folder with composer. You might have noticed that our .gitignore file has vendor folder as one of it entries, which means that it is not managed by the Version Control System. Some prefer their dependencies to be part of their Git repository, I prefer to have only the composer.json declarations in Git. Makes the repo much much smaller than the other way round, also makes it easy to avoid bloating your production builds with libraries only needed for development.
Composer is also included into PHPQA docker image, and we can enrich our .gitlab-ci.yml:
test:	stage: QA	cache:	key: dependencies-including-dev	paths: - vendor/	script:	- composer install	- ./vendor/bin/phpunit

PHPUnit requires some configuration, but in the very beginning we used composer create-project to create our project boilerplate.laravel/laravel package has a lot of things included in it, and phpunit.xml is also one of them. All I had to do was to add another line to it:
xml

APP_KEY enironment variable is essential for Laravel to run, so I generated a key with php artisan key:generate.
git commit & git push, and we have all three jobs on theQA stage!

Checking that our checks work

In this branch I intentionally added changes that should fail all three job in our pipeline, take a look at git diff. And we have this out from the pipeline stages:Linter:
$ ci/linter.sh
PHP Linter is not happy about app/User.php:
Parse error: syntax error, unexpected 'syntax' (T_STRING), expecting function (T_FUNCTION) or const (T_CONST) in app/User.php on line 11
Errors parsing app/User.php
PHP syntax validation failed!
ERROR: Job failed: exit code 255

**Code-style**:
$ if [ ! -z "$files" ]; then echo $files | xargs phpcs; fi
FILE: ...ilds/crocodile2u/ci-showcase/app/Http/Controllers/Controller.php
----------------------------------------------------------------------
FOUND 0 ERRORS AND 1 WARNING AFFECTING 1 LINE
---------------------------------------------------------------------- 13 | WARNING | Line exceeds 120 characters; contains 129 characters
----------------------------------------------------------------------
Time: 39ms; Memory: 6MB
ERROR: Job failed: exit code 123

**test**:
$ ./vendor/bin/phpunit
PHPUnit 7.5.6 by Sebastian Bergmann and contributors.
F. 2 / 2 (100%)
Time: 102 ms, Memory: 14.00 MB
There was 1 failure:
1) Tests\Unit\ExampleTest::testBasicTest
This test is now failing
Failed asserting that false is true.
/builds/crocodile2u/ci-showcase/tests/Unit/ExampleTest.php:17
FAILURES!
Tests: 2, Assertions: 2, Failures: 1.
ERROR: Job failed: exit code 1

Congratulations, our pipeline is running, and we now have much less chance of messing up the result of our work.

Conclusion

Now you know how to set up a basic QA pipeline for your PHP project. There's still a lot to learn. Pipeline is a powerful tool. For instance, it can make deployments to different environments for you. Or it can build docker images, store artifacts and more! Sounds cool? Then spend 5 minutes of your time and leave a comment, you can also tell me if there is a pipeline topic you would like to be covered in next posts.
15281 views · 5 years ago
Create Alarm and Monitoring on Custom Memory and Disk Metrics for Amazon EC2

Today I am going write a blog on how to Monitor Memory and Disk custom metrics and creating alarm in Ubuntu.

To do this, we can use Amazon CloudWatch, which provides a flexible, scalable and reliable solution for monitoring our server.

Amazon Cloud Watch will allow us to collect the custom metrics from our applications that we will monitor to troubleshoot any issues, spot trends, and configure operational performance. CloudWatch functions display alarms, graphs, custom metrics data and including statistics.

Installing the Scripts


Before we start installing the scripts for monitoring, we should install all the dependent packages need to perform on Ubuntu.

First login to your AWS server, and from our terminal, install below packages

sudo apt-get update
sudo apt-get install unzip
sudo apt-get install libwww-perl libdatetime-perl


Now Install the Monitoring Scripts


Following are the steps to download and then unzip we need to configure the Cloud Watch Monitoring scripts on our server:
1. In the terminal, we need to change our directory and where we want to add our monitoring scripts.
2. Now run the below command and download the source:

curl https://aws-cloudwatch.s3.amazonaws.com/downloads/CloudWatchMonitoringScripts-1.2.2.zip -O

3. Now uncompress the currently downloaded sources using the following commands

unzip CloudWatchMonitoringScripts-1.2.2.zip && \

rm CloudWatchMonitoringScripts-1.2.2.zip && \

cd aws-scripts-mon


The directory will contain Perl scripts, because of the execution of these scripts only report memory run and disk space utilization metrics will run in our Ubuntu server.
Currently, our folder will contain the following files:
mon-get-instance-stats.pl - This Perl file is used to displaying the current utilization statistics reports for our AWS instance on which these file scripts will be executed.
mon-put-instance-data.pl - This Perl script file will be used for collecting the system metrics on our ubuntu server and which will send them to the Amazon Cloud Watch.
awscreds.template - This Perl script file will contain an example for AWS credentials keys and secret access key named with access key ID.
CloudWatchClient.pm - This Perl script file module will be used to simplify by calling Amazon Cloud Watch from using other scripts.
LICENSE.txt – This file contains the license details for Apache 2.0.
NOTICE.txt – This file contains will gives us information about Copyright notice.
4. For performing the Cloud Watch operations, we need to confirm that whether our scripts have corresponding permissions for the actions:

If we are associated with an IAM role with our EC2 Ubuntu instance, we need to verify that which will grant the permissions to perform the below-listed operations:

cloudwatch:GetMetricStatistics

cloudwatch:PutMetricData

ec2:DescribeTags

cloudwatch:ListMetrics


Now we need to copy the ‘awscreds.template’ file into ‘awscreds.conf’ by using the command below and which will update the file with details of the AWS credentials.

cp awscreds.template awscreds.conf

AWSAccessKeyId = my_access_key_id

AWSSecretKey = my_secret_access_key


Now we completed the configuration.

mon-put-instance-data.pl


This Perl script file will collect memory, disk space utilization data and swap the current system details and then it makes handling a remote call to Amazon Cloud Watch to reports details to the collected cloud watch data as a custom metrics.

We can perform a simple test run, by running the below without sending data to Amazon CloudWatch

./mon-put-instance-data.pl --mem-util --verify --verbose


Now we are going to set a cron for scheduling our metrics and we will send them to Amazon CloudWatch
1. Now we need to edit the crontab by using below command:

 crontab -e

2. Now we will update the file using the following query which will disk space utilization and report memory for particular paths to Amazon CloudWatch in every five minutes:

*/5 * * * * ~/STORAGE/cloudwatch/aws-scripts-mon/mon-put-instance-data.pl --mem-util --mem-avail --mem-used --disk-space-util --disk-space-avail --disk-space-used --disk-path=/ --disk-path=/STORAGE --from-cron


If there is an error, the scripts will write an error message in our system log.

Use of Options

--mem-used
The above command will collect the information about used memory and which will send the details of the reports in MBs into the MemoryUsed metrics. This will give us information about the metric counts memory allocated by applications and the OS as used.
--mem-util
The above command will collect the information about memory utilization in percentages and which will send the details of the Memory Utilization metrics and it will count the usage of the memory applications and the OS.
--disk-space-util
The above command will collect the information to collect the current utilized disk space and which will send the reports in percentages to the DiskSpaceUtilization for the metric and for the selected disks.
--mem-avail
The above command will collect the information about the available memory and which will send the reports in MBs to the MemoryAvailable metrics details. This is the metric counts memory allocated by the applications and the OS as used.
--disk-path=PATH
The above command will collect the information and will point out the which disk path to report disk space.
--disk-space-avail
The above command will collect the information about the available disk space and which will send the reports in GBs to the DiskSpaceAvailable metric for the selected disks.
--disk-space-used
The above command will collect the information about the disk space used and which will send the reports in GBs to the DiskSpaceUsed metric for the selected disks.

The PATH can specify to point or any of the files can be located on which are mounted point for the filesystem which needs to be reported.

If we want to points to the multiple disks, then specify both of the disks like below:

--disk-path=/ --disk-path=/home


Setting an Alarm for Custom Metrics


Before we are going to running our Perl Scripts, then we need to create an alarm that will be listed in our default metrics except for the custom metrics. You can see some default metrics are listed in below image:



Once we completed setting the cron, then the custom metrics will be located in Linux System Metrics.

Now we are going to creating the alarm for our custom metrics
1. We need to open the cloudwatch console panel at https://console.aws.amazon.com/cloudwatch/home
2. Now navigate to the navigation panel, we need to click on Alarm and we can Create Alarm.
3. This will open a popup which with the list of the CloudWatch metrics by category.
4. Now click on the Linux System Metrics . This will be listed out with custom metrics you can see in the below pictures






5. Now we need to select metric details and we need to click on the NEXT button. Now we need to navigate to Define Alarm step.



6. Now we need to define an Alarm with required fields

Now we need to enter the Alarm name for identifying them. Then we need to give a description of our alarm.

Next, we need to give the condition with the maximum limit of bytes count or percentage when it notifies the alarm. If the condition satisfies, then the alarm will start trigger.

We need to provide a piece of additional information about for our alarm.

We need to define what are the actions to be taken when our alarm changes it state.

We need to select or create a new topic with emails needed for sending notification about alarm state.
7. Finally, we need to choose the Create Alarm.

So its completed. Now the alarm is created for our selected custom metrics.

Finished!

Now the alarm will be listed out under the selected state in our AWS panel. Now we need to select an alarm from the list seen and we can see the details and history of our alarm.
15992 views · 5 years ago
PHP IPC with Daemon Service using Message Queues, Shared Memory and Semaphores

Introduction

In a previous article we learned about Creating a PHP Daemon Service. Now we are going to learn how to use methods to perform IPC - Inter-Process Communication - to communicate with daemon processes.

Message Queues

In the world of UNIX, there is an incredible variety of ways to send a message or a command to a daemon script and vice versa. But first I want to talk only about message queues - "System V IPC Messages Queues".

A long time ago I learned that a queue can be either in the System V IPC implementation, or in the POSIX implementation. I want to comment only about the System V implementation, as I know it better.

Lets get started. At the "normal" operating system level, queues are stored in memory. Queue data structures are available to all system programs. Just as in the file system, it is possible to configure queues access rights and message size. Usually a queue message size is small, less than 8 KB.

This introductory part is over. Lets move on to the practice with same example scripts.queue-send.php
$key = ftok(__FILE__, 'A'); 
$queue = msg_get_queue($key);

msg_send($queue, 1, 'message, type 1');
msg_send($queue, 2, 'message, type 2');
msg_send($queue, 3, 'message, type 3');
msg_send($queue, 1, 'message, type 1');

echo "send 4 messages
";

queue-receive.php
$key = ftok('queue-send.php', 'A');
$queue = msg_get_queue($key);

for ($i = 1; $i <= 3; $i++) {
echo "type: {$i}
";

while ( msg_receive($queue, $i, $msgtype, 4096, $message, false, MSG_IPC_NOWAIT) ) {
echo "type: {$i}, msgtype: {$msgtype}, message: {$message}
";
}
}


Lets run on the first stage of the file queue-send.php, and then queue-receive.php.
u% php queue-send.php
send 4 messages
u% php queue-receive.php
type: 1
type: 1, msgtype: 1, message: s:15:"message, type 1";
type: 1, msgtype: 1, message: s:15:"message, type 1";
type: 2
type: 2, msgtype: 2, message: s:15:"message, type 2";
type: 3
type: 3, msgtype: 3, message: s:15:"message, type 3";


You may notice that the messages have been grouped. The first group gathered 2 messages of the first type, and then the remaining messages.

If we would have indicated to receive messages of type 0, you would get all messages, regardless of the type.
while (msg_receive($queue, $i, $msgtype, 4096, $message, false, MSG_IPC_NOWAIT)) {


Here it is worth noting another feature of the queues: if we do not use the constant MSG_IPC_NOWAIT in the script and run the script queue-receive.php from a terminal, and then run periodically the file queue-send.php, we see how a daemon can effectively use this to wait jobs.queue-receive-wait.php
$key = ftok('queue-send.php', 'A');
$queue = msg_get_queue($key);

while ( msg_receive($queue, 0, $msgtype, 4096, $message) ) {
echo "msgtype: {$msgtype}, message: {$message}
";
}


Actually that is the most interesting information of all I have said. There are also functions to get statistics, disposal and checking for the existence of queues.

Lets now try to write a daemon listening to a queue:queue-daemon.php
$pid = pcntl_fork();
$key = ftok('queue-send.php', 'A');
$queue = msg_get_queue($key);

if ($pid == -1) {
exit;
} elseif ($pid) {
exit;
} else {
while ( msg_receive($queue, 0, $msgtype, 4096, $message) ) {
echo "msgtype: {$msgtype}, message: {$message}
";
}
}

posix_setsid();


Shared Memory

We have learned to work with queues, with which you can send small system messages. But then we may certainly be faced with the task of transmitting large amounts of data. My favorite type of system, System V, has solved the problem of rapid transmission and preservation of large data in memory using a mechanism calledShared Memory.

In short, the data in the Shared Memory lives until the system is rebooted. Since the data is in memory, it works much faster than if it was stored in a database somewhere in a file, or, God forgive me on a network share.

Lets try to write a simple example of data storage.shared-memory-write-base.php
$id = ftok(__FILE__, 'A');


$shmId = shm_attach($id);

$var = 1;

if (shm_has_var($shmId, $var)) {
$data = (array) shm_get_var($shmId, $var);
} else {
$data = array();
}

$data[time()] = file_get_contents(__FILE__);

shm_put_var($shmId, $var, $data);


Run this script several times to save the value in memory. Now lets write a script only to read from the memory.shared-memory-read-base.php
$id = ftok(__DIR__ . '/shared-memory-write-base.php', 'A');
$shmId = shm_attach($id);
$var = 1;

if (shm_has_var($shmId, $var)) {
$data = (array) shm_get_var($shmId, $var);
} else {
$data = array();
}

foreach ($data as $key => $value) {
$path = "/tmp/$key.php";
file_put_contents($path, $value);

echo $path . PHP_EOL;
}


Semaphores

So, in general terms, it should be clear for you by now how to work with shared memory. The only problems left to figure out are about a couple of nuances, such as: "What to do if two processes want to record one block of memory?" Or "How to store binary files of any size?".

To prevent simultaneous accesses we will use semaphores. Semaphores allow us to flag that we want to have exclusive access to some resource, like for instance a shared memory block. While that happens other processes will wait for their turn on semaphore.

In this code it explained clearly:shared-memory-semaphors.php

$id = ftok(__FILE__, 'A');

$semId = sem_get($id);

sem_acquire($semId);

$data = file_get_contents(__DIR__.'/06050396.JPG', FILE_BINARY);

$shmId = shm_attach($id, strlen($data)+4096);
$var = 1;

if (shm_has_var($shmId, $var)) {
$data = shm_get_var($shmId, $var);

$filename = '/tmp/' . time();
file_put_contents($filename, $data, FILE_BINARY);

shm_remove($shmId);
} else {
shm_put_var($shmId, $var, $data);
}

sem_release($semId);


Now you can use the md5sum command line utility to compare two files, the original and the saved file. Or, you can open the file in image editor or whatever prefer to compare the images.

With this we are done with shared memory and semaphores. As your homework I want to ask you to write code that a demon will use semaphores to access shared memory.

Conclusion

Exchanging data between the daemons is very simple. This article described two options for data exchange: message queues and shared memory.

Post a comment here if you have questions or comments about how to exchange data with daemon services in PHP.

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