This document outlines strategies for resolving problems and ensuring high availability in enterprise PHP applications, featuring key topics like monitoring for faults, fault diagnosis, and optimizing scalability through clustering. It emphasizes the importance of maintaining a good reputation by minimizing performance degradation and application downtime while providing insights into effective monitoring and debugging techniques. The session also includes a Q&A section and promotes upcoming webinars on performance optimization.

1. Building the perfect PHP app for the enterprise
Episode 3: Resolving
problems & high availability
Clark Everetts
September 28, 2016

2. 2
Series overview
Now: Resolving problems and high availability
October 13: Optimizing performance (revised date)
Keep users on your site by learning how to use background jobs and caching,
measure performance, and make data-driven decisions.

3. Clark Everetts
Professional services
Rogue Wave Software

4. 4
Agenda
1. How’s your reputation?
2. Monitoring: Know you have a problem
3. Fault diagnosis / Root cause analysis
4. Optimizing scale: Cluster management
5. Synchronizing session data
6. Conclusion
7. Q&A

5. How’s your
reputation?

6. 6
The cost of a bad rep
Complexity
Scale
ROI
DIY
Ideal enterprise
Volume
scales
beyond
servers
Performance
degradation
Administrativ
e costs
Not so good reputation
• Page delays
• Application
downtime
Good reputation
• Responsive under load
• Application availability

7. Monitoring:
Know you have a
problem

8. 8
Potential faults
“Issues are discussing, problems are for solving.”
- Me
Fatal
PHP errors
Out of memory
Failed database queries or
updates
Network connectivity
(no connection)
Application
Non-fatal
PHP notices, warnings
Slow functions or request
executions
High memory consumption
Network (degraded)
Application logic

9. 9
The problem with problem resolution
• Most problem resolution time is spent identifying root cause
• Problem reproduction is often difficult and time-consuming
• Many possible sources: server load, input data, database state, etc.

10. 10
Problem identification
• Do you know you have a problem?
– Your phone is ringing?
– Getting emails?
– Monitoring tools or services?
• Is a problem brewing that customers don’t see … yet?
Analyze
information
• Debugging
• Logging (files, events
database, application
level logs)
Recreate
problem
With enough relevant
information:
• Reproduce in order to
troubleshoot and verify a
fix
• Can we identify the
cause without having to
reproduce?
Gather
information
• What information can
you collect?

11. 11
Monitoring for faults
• Scan log files (not manually!)
– Web server access and error logs
– PHP error log (php.log)
– Application-specific logs (filesystem, database)
• Don’t log noise
• Avoid logging to php.log
• ZendLog, Monolog, error_log()
• Event-based monitoring
– Recorded in event database, visible in UI, accessible via API
– Optional automatic notification via email alerts
– Optional callback URIs for integration with other monitoring tools

12. 12
Monitoring events

13. 13
Event rules

14. 14
Sampling of event types
• Custom event
• Database error
• Function error
• High memory usage
• Inconsistent output size
• Job execution delay/error
• Job logical failure
• PHP error
• Slow function execution
• Slow query execution
• Slow request execution
• Zend Framework exception

15. 15
Example
Results:
Users never experienced a problem
Development team solidified “trust factor” with management
Requirements:
Stale data is unusable data
“Soft” performance criteria
(user’s say when “good enough”)
Problem:
New feature of internal application
suffered slow performance due to
large database result sets from
complex queries.
Challenge:
Prior to rollout, isolate which queries
were experiencing the slowest
response times, make improvements,
& cache results if possible
Used:
Zend Server Monitoring,
IBM i DB2 index analyzer, and
Zend Server Data Cache

16. Poll #1
How do you discover problems in
your applications?
- Notified by a person (phone call, email, cubicle visit)
- Notified by an in-house automated tool
- Notified by commercial automated tool (Zend, New Relic)

17. Fault diagnosis /
Root cause analysis

18. 18
Root cause analysis
• Log files
– Can both indicate a problem, and contain necessary diagnostics
• Monitoring tools may provide further info on:
– Failed function call arguments
– High memory consumption
– Etc.
• printf() and var_dump()
• Debuggers (Xdebug, Zend Debugger, phpdbg)
• Code tracing pinpoints in the request execution what triggered the
problem
• Z-Ray: request details right in the developer’s web browser (code trace-
like)

19. 19
Event details

20. 20
Debugging

21. Poll #2
What is your primary means of root
cause analysis?
- printf(), var_dump()
- Logging data to files
- Xdebug
- Zend debugger
- phpdbg

22. Optimizing scale:
Cluster management

23. 23
What is a cluster?

24. 24
Why cluster?
• Long-term demand is increasing
– Growing population of mobile devices
– Machine-to-machine traffic (bots, B2B, APIs) on the rise
• Demand is both predictable and unpredictable
– “The Witching Hour” and other periodic processing
spikes
• Resilience when failures occur
Clustering allows you to
• Adapt to changing demand
• Manage infrastructure costs
• Provide redundancy in the face of failures

25. 25
Cluster overview
Requests
Responses

26. 26
Cluster characteristics
• Nodes are the same
– Any node can do the same work as all others
– Same specs
• Operating system, installed software base
• Hardware (RAM, disk, etc.)
• Virtual machines
– Containerization and provisioning (Docker, Rocket, Puppet, Chef,
Ansible, SaltStack, Fabric, Capistrano, etc.)
Provides for:
• Scaling out/in as traffic increases/decreases
• Redundancy in the face of failures

27. Synchronizing
session data

28. 28
Load balancing and sessions
Session Affinity
(Sticky Sessions)

29. 29
Session clustering

30. 30
Session clustering

31. 31
Session clustering

32. 32
Best practices
How do you know? • Monitoring
How do you diagnose?
• Log files
• Code tracing
• Z-Ray
How do you prevent? • Testing!
• Load balancing
• Clustering
How do you minimize downtime? • Support

33. Poll #3
How do you currently implement
high availability sessions in a
clustered environment?
- Central database (MySQL, PostgreSQL, Oracle, MariaDB)
- Memcached
- Redis
- Zend Server
- Other/We’re not clustered

34. 34
Conclusion
• Reputation = f(reliability) + f(availability)
• Monitor for faults: know quickly when you have a problem
• Fault diagnosis is all about using the right tools
• Q: Scalability? A: Clustering!
• Sessions in clusters
Visit www.zend.com/en/resources/webinars for webinars
Visit devzone.zend.com for the Zend Developer Zone

35. Q & A

36. 36
The fastest way to enterprise PHP
Free trial
www.zend.com
• Full, tested, secure PHP stack
• Z-Ray vision deep into your app
• Code tracing
• Job queuing and caching
• Deployment and DevOps
• High availability session clustering
• Backed by support & services

37. 37
Series overview
October 13: Optimizing performance (revised date)
Keep users on your site by learning how to use background jobs and caching,
measure performance, and make data-driven decisions.

38. 38
Don’t miss this premiere PHP event!
Register at zendcon.com
Visit with sponsors 90+ sessions in 6 tracks

39. 39
Watch on demand
• Watch this webinar on demand
• Read the recap blog to see the results of the
polls and Q&A session

40. Building the perfect PHP app for the enterprise
Episode 3: Resolving
Problems & High Availability
Clark Everetts
September 28, 2016