Php & cloud computing

PHP & Cloud Computing
PHPTOSTART 2013
Walter Dal Mut - @walterdalmut - @corleycloud

Whoami
• Walter Dal Mut • Corley S.r.l.
• Startupper • Scalable CMS
• Corley S.r.l.
• http://www.corley.it/ • www.xitecms.it
• UpCloo Ltd. • Load and Stress tests
• http://www.upcloo.com/
• Electronic Engineer
• www.corley.it
• Polytechnic of Turin • Consultancy
• Social • PHP
• @walterdalmut - @corleycloud - @upcloo • AWS
• Websites • Distributed Systems
• walterdalmut.com – corley.it – upcloo.com • Scalable Systems

Walter Dal Mut walter.dalmut@gmail.com @walterdalmut
@corleycloud @upcloo

AWS - Application Management Solutions


Why scalability

Source Jeff Barr AWS
slideshare.net/…

Also daily…


Provision with fixed hardware


Thanks to Cloud Computing


Are you wasting monies?


Scalability effects on your business
• Scale capacity on demand
• Turn fixed costs into variable costs
• Always available
• Rock-solid reliability
• Cost-effective
• Reduce time to market
• Focus on product and core competencies


Scalable PHP environments – Initial Step

Web
89.30.31.32/32 MySQL
Instance


Scalable PHP environments –
autoscaling

MySQL

Web
Elastic Load Balancer
Instance


autoscaling

Web
Instance
MySQL

Web
Instance


autoscaling

Web
Instance
MySQL

Web
Instance

Web
Instance MySQL
Read Replica


AWS (Elastic) Load Balancer
• You can distribute incoming traffic across your web instances
• When it detects unhealthy load-balanced web instances, it no longer
routes traffic to those web instances and spreads the load across the
remaining healthy web instances.

• Elastic?
• automatically scales its request handling capacity in response to incoming
application traffic.


Autoscaling
• Scale out web instances seamlessly and automatically when demand
increases
• Replace unhealthy or unreachable instances to maintain higher
availability of your applications.
• Scale dynamically based on your Cloud Watch metrics, or predictably
according to a schedule that you define..
• Run on-demand or spot instances


Metrics and Autoscaling

EC2 Instance CloudWatch

Scaling rules

Autoscaling




Scaling rules

Autoscaling

EC2 Instance

Alarms




Scaling rules

Autoscaling

EC2 Instance


Scale with metrics, scheduled or both?
• How to scale? It depends by your application
• Scheduled scale operations are useful when you have predictable spikes
• Metrics when you have heavy spike application and you need to adjust your
infrastructure automatically
• Mix previous in mixed scenarios
• Which metric use in order to scale?
• It depends by your application design
• CPU heavy scale on CPU load metric
• Network heavy scale on network load metric
• Etc.
• Remember that applications don’t consume only CPU but also other
resources

We have to discuss about:
• Session Management
• If we open and close servers runtime we have to maintain PHP sessions in
order to handle user logins and other application features related to the end
user session.
• Database connections
• All MySQL connectors (PDO, MySQLi, [mysql_*]) handle just one connection…
No “x” RDB connection at the same time
• Software maintenance
• How we can ran the same application version on all our infrastructure?
• What about logs? How we can collect VM logs in order to centralize
the log management?

Session Management
• Fortunately with PHP you can use different strategies to centralize
sessions
• Memcache/Memcached (AWS ElastiCache)
• Redis
• DynamoDB (AWS)
• Etc.
• We can modify the session_handler in order to use a different
storage (php.ini, your application bootstrap, etc.)
session.save_handler = memcache
session.save_path = “tcp://1.cache.group.domain.tld:11211”


MySQL – Master/Slave?
• Master/Slave is a model of communication where one device or
process has unidirectional control over one or more other devices
• MySQL can scales out all your read (SELECT) operations on different slave
servers.

• AWS RDS (Relational Database Service) helps you to create read
replicas directly in AWS web console with a couple of clicks!


PHP Application MySQL READ
Replicas

SELECT ONLY
SLAVE 1
INSERT/UPDATE/
DELETE/SELECT
MASTER
Application

SELECT ONLY
SLAVE 2


MySQL Native Driver
• MySQL native driver?
• Available from PHP >= 5.3
• You have to compile your PHP with “mysqlnd” support
• --with-mysqli=mysqlnd --with-pdo=mysqlnd --with-mysql=mysqlnd

• Delegate to “mysqlnd_ms” the master/slave management
• http://php.net/manual/en/book.mysqlnd.php


Create the mysqlnd_ms configuration file
{
The simple JSON configuration is divided
"myapp": {
in two main section
"master": {
"master_0": {
• Master
"host": "localhost",
• Slaves
"port": "3306"
}
},
“myapp” is the hostname that we use
"slave": {
instead the real mysql host address.
"slave_0": {
"host": "192.168.2.27", Eg.
"port": "3306"
• mysql_connect(“myapp”, “user”,
“passwd”);
}
• new Mysqli(“myapp”, “user”,
}
“passwd”);
}
• new
} PDO(“mysql:dbname=testdb;host=my
app”);

Maintain softwares

Web
Instance


Maintain softwares

Web
Instance

Web
Instance


Maintain softwares

Web
Instance

Web
Instance

Web
Instance


Maintain softwares

Web
Instance


Web
Instance


Maintain softwares

Web
Instance



How we can stay fresh?
• If servers starts and stops continuously we have to find solutions to
stay updated also on software
• When a server starts, it has to create a valid environment in order to provides
web pages. Strategies?
• Compile and bundle all softwares in one instance image
• It is very simple but all software becomes old very quickly and when you have to release an
update you have to compile a new image and update all load balancers configurations. It is a
long and complex operation
• Use EC2_USER_DATA feature provided by AWS
• You can run a shell script when your instances bootstraps. It is more flexible because you can
create a skeleton (PHP + libraries) and download all software runtime during the boot
operation
• Typically you will use both in conjunction


Cool Up/Down – Inhibits alarms


Scales in action


Run commands on multiple servers
• If you ran many servers execute commands could be hard. You can
use tools to run commands on a server list
• Capistrano (Ruby)
• https://github.com/capistrano/capistrano
• Fabric (Python)
• https://github.com/fabric/fabric
• Use CLOTH for AWS EC2 instances
• https://github.com/garethr/cloth
• Chef
• Puppet
• Etc…


Fabric is very simple
#! /usr/bin/env python
from __future__ import with_statement
from fabric.api import *
EC2 instances are dynamic with don’t know
from fabric.contrib.console import confirm addresses, for that reason we can use tagging
system to execute commands on a group of
from cloth.tasks import * instances
env.user = "root" fab nodes:"^production.*" tail
env.directory = '/mnt/wordpress'
env.key_filename = ['/home/walter/Amazon/wp- Execute the “tail” command on all instances
cms.pem'] with a name that starts with “production.”
@task Eg.
def reload(): • production.web-1
"Reload Apache configuration" • production.log
run('/etc/init.d/apache2 reload') • production.mongodb

@task
def tail():
"Tail Apache logs"
run('tail /var/log/syslog') Walter Dal Mut walter.dalmut@gmail.com @walterdalmut

Centralize all logs
• We create and destroy instances thanks to alarms but when we
close an instance we lose immediately all instance/application logs
• How we can manage logs?
• The simplest way is to use Rsyslog clusters
• Rsyslog is an opensource software that forwarding log messages in
an IP network
• Rsyslog implement the basic syslog protol
• That means that we can configure apache logs to “syslog” instead using
normal text files.
• In this way we can collect all logs in one group of VM and work on these
files later thanks to other technologies


Log management
• Collecting logs is not the latest operation because you have to
analyse and reduce information
• Move logs to S3 bucket – Time based
• Analyze logs with Hadoop
• Map Reduce on the cloud with Elastic Map Reduce service (EMR)
• Use script languages on top of Hadoop in order to simply the log analysis
• HIVE – Data Warehouse infrastructure (data summarization)
• Pig – High level platform for creating MapReduce program


Cloud Conference 2013 – 18 April
• www.cloudconf.it
• @_CloudConf_
• https://www.facebook.com/pages/Cloud-Conf-Italia/140265592804313?ref=hl

• Data analysis
• Hadoop – MapReduce Framework
• Apache Pig – MapReduce Scripting Language for Hadoop
• Apache Hive – Data Warehouse System for Hadoop

PUG User Coupon Code:
pug-user

Thanks for listening

Any questions?


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