WebCamp 2016: PHP.Алексей Петров.PHP at Scale: System Architect Toolbox Website: http://webcamp.in.ua/devops.html#theme Facebook: https://www.facebook.com/WebCamp/ VK: https://vk.com/webcamp Twitter: https://twitter.com/WebCampOdessa Youtube: http://bit.ly/2bsQ0LO

2. Who am I
System Architect
Team Lead
PHP Developer
Find me on
@alexhelkar
alexhelkar
https://github.com/alexhelkar

3. Performance
Story

4. Canvas
PHP 7.0.8
Digital Ocean 5$ Droplet
Symfony 3 Demo Application
Yandex Tank

5. [phantom]
address=555.166.5.74 ; fake ip
port=80 ;target port
rps_schedule=step(20, 60, 10, 30s) const(1, 30s) ;load scheme
uris = /ru/blog/
Yandex Tank Config

6. Results

7. Results
Max. stable RPS: 50
Response time: ~20ms

8. PHP 7 facts
isset 1.55 times faster than array_key_exists
is_file 26 times faster than file_exists
single quotes slower that double quotes
instanceof faster is_a
etc.
Code performance?

9. Blackfire.io profile
Current results:
Total request time: 18.4 ms
file_exists called: 7 times
Exec. time for file_exists: 460 µs
Expected results:
Exec/ time: ~17.6 µs
Total request time: ~18.3996 ms

10. Perfomance
Response time?
Requests per second?

11. PHP lang performance
...овно?
OR
...амно?

12. SLA
Story

13. Demo App
recall with $$
Infrastructures scaling

14. 5$
RAM: 512
CPU: 1
HDD: 20
50 RPS
App Server

15. 10$
50 RPS
App Server
RAM: 1024
CPU: 1
HDD: 30
50 RPS
App Server
RAM: 512
CPU: 1
HDD: 20
LB Server
RAM: 512
CPU: 1
HDD: 20

16. 15$
100 RPS
App Server
50 RPS
App Server LB Server
5$
App Server
RAM: 512
CPU: 1
HDD: 20
RAM: 512
CPU: 1
HDD: 20
RAM: 512
CPU: 1
HDD: 20
RAM: 1024
CPU: 1
HDD: 30

17. 20$
160 RPS
App Server
120 RPS
App Server LB Server
App Server
App Server
RAM: 2048
CPU: 2
HDD: 40
RAM: 512
CPU: 1
HDD: 20
RAM: 512
CPU: 1
HDD: 20
RAM: 512
CPU: 1
HDD: 20
RAM: 512
CPU: 1
HDD: 20

18. Summary
Often hardware is cheaper than software
Often scaling is cheaper than tuning
Often horizontal scaling wins vertical scaling
Often applications are not scalable :(

20. Load Balancer Pattern

21. Examples
Kubernetes Services
Microservices
etc

22. Good to know
HAProxy TCP and HTTP Load Balancing
Nginx HTTP Load Balancing
Message Queue-Based Load Balancing

23. MQ Balancing
Story

24. MQ Balancing

25. Consumer retries

26. API Gateway

27. Benefits we've got
Advanced routing of requests
Advanced routing of responses
Workers could be added dynamically without LB
reconfig
Buffer size by queue limit
Back pressure by message TTL

28. Scaling out
Story

29. Generic Web App

30. Perfomance
Requests per second
(concurrency)

31. DNS Load Distribution

32. DNS Load Distribution

33. DNS Cache

34. Rule of Thumb: Add LB

35. What if?

36. Floating IP

37. Perfomance
Response time
(reads)

38. Reads Flow

39. DB Cache

40. Application Cache

41. Application Cache Candidates
Memcached (sessions, k/v data)
sessions
k/v data
Redis
k/v data
leaderboards
durability
replication
* Manual sharding both cases

42. Web Cache

43. Cache: Rule of thumb
IF Application is SLOW
Enable Caching
IF Application has GLITCHES
Disable Caching

44. Perfomance
Response time
(writes)

45. Cirquit Breaker

46. Fire & Forget

47. MySQL
Database Perfomance

48. MySQL
Story of 100 servers

49. MongoDB
Chose correct sharding key

50. Apache Cassandra
Linear writes

51. Apache Cassandra
Life story

52. Apache Kafka
2 billions messages on 3
machines

53. Distributed Locks
Consul || etcd || Zookeeper

54. Instead Summary
Scalability as afterwords doesn't work
Database is not a queue
Database is not a lock system
Redis is not a queue
MySQL master is always SPOF
Load balancers as a must
Linear disk writes wins
Perfomance in PHP is done by everything except PHP
Being distributed is fucking hard

55. Questions?
Find me on
@alexhelkar
alexhelkar
https://github.com/alexhelkar