Shobana Radhakrishnan discusses how Mindflash manages service integration and implements a microservices architecture to achieve high uptime and continuous deployment in a lean startup. Mindflash relies on many external services and has evolved its deployment process from monthly major releases with fallouts to near-continuous deployment with high automation and alignment between test and production environments. Mindflash implements a microservices architecture with independent services communicating through APIs to improve scalability, deployment speed, and allow incremental improvements. This approach helps Mindflash continuously upgrade services while maintaining high performance and uptime.

1. February 2015
Managing Service Integration for
High Uptime In a Lean Startup
Shobana Radhakrishnan
Vice President of Engineering, Mindflash

2. Agenda
• Introduction
• Managing External Service Integration
• Mindflash API
• Microservice Architecture at Mindflash
2

3. Mindflash At a Glance
3
Mindflash App
Mindflash
Customer API
Services
Course Videos
Player
Developer
ManagerTrainer/P
rospect

4. Some Numbers
• 1000+ Enterprise Customers
• Thousands of trainees/program
• 2 million courses completed
• Increasing mobile adoption
• Increasingly global programs
4

5. Lean Startup**
5
**Eric Weis: http://theleanstartup.com/principles

6. Lean Startup Principles at Mindflash
• Minimum Viable Product
(MVP)
• Ship Frequently
• Monitor Outcome
• Iterate
6

7. Questions
• How do you manage service deployment for
high uptime and quality?
• How can you guarantee high uptime when
relying on several external services?
• How can you do these in a lean startup?
7

8. 8
• Monthly releases
• Somewhat automated
• Multi-hour deployment, fall-out after releases
• Test vs. Production not completely aligned
2013 and
Prior

9. 9
• Ability to make multiple releases a day (Major
features still monthly)
• Highly automated
• Deployment in minutes, major fall-outs rare
• Test vs. Production more completely aligned
Mid 2014 on

10. 10
• Continuous feature releases
• Full deployment automation
• Deployment in minutes, major fall-outs rare
• Test vs. Production fully aligned
Next

11. Microservice Architecture
Microservices is a software design pattern, in
which complex applications are composed of
small, independent services communicating
with each other using highly decoupled
language-agnostic APIs
11

12. Architectural Difference
Monolithic App Microservice-based App
12
Presentation Layer (View)
Middleware/Business Logic Layer
(Controller)
Database
(Model)

13. Monolithic vs. Microservices
Monolithic
• N-tier Application
• Code dependencies
• Shared database
• Larger units of deployment
Microservices
• Independent services
• Easier to manage and
deploy
• Loose Coupling
13

14. When to Consider Microservices?
• Team working on the application
• Quick Ramp-up for new Team Members
• Continuous Deployment
• Take advantage of emerging technologies
14

15. Three Angles For Microservice
Architectures
15

16. Integration with SAAS/PAAS
Services
16

17. Exposing API
17

18. Internal Microservices
18

19. Mindflash External Service
Integration
19

20. Trends
• Growth of SaaS/PaaS Services
• Evolution of Hub and Data
Analysis Solutions
• Public API and Open Source
20

21. Architectural View
21

22. Services we Integrate With
22

23. Integration
• Building and Maintaining Component
• API Migration and Upgrades
• Security and Bug Patches
23

24. API Call Flow
24
API
Customer 1
API
Customer 2
API
Customer 3
API
Customer 4
API
Customer 5
Services Layer
API Gateway

25. API Considerations
• Heterogeneous Needs
• User release cycles vary
• Backwards compatibility
• Objects evolve continuously
25

26. Approach and Lessons Learned
26

27. Automate – BrowserStack,
Jenkins, Selenium
27

28. Fail Fast and Recover Quickly –
Pingdom, Crittercism, AWS
Monitoring and Alerting
28

29. Measure and Iterate – Optimizely,
Gainsight, Pingdom, Google
Analytics, KISSMetrics, Internal
reporting
29

30. Upgrade Continuously
30

31. Deploy Small and Continuously
31
Build
Deploy to
QA
Check in
Run Tests
Deploy to
PROD
Rule-based
subset that
needs to be
rebuilt/deplo
yed

32. Implementation Best Practices
• Loose Coupling
• Chain-of-responsibility pattern
• Single Responsibility Principle
• Defensive Programming
• Clear separation of real-time
vs. asynchronous
• Feature Flags
32

33. Real-time Vs. Asynchronous
33
MF
Trainers and
Prospects
Trainees
Hydra
Billing
RDS
Analytics
File
Conversion
Feature
Integration
Developers
MF
API
Gateway

34. Feature Flags – our implementation
• Feature Flags persisted in DB
• Set per account and pricing tier
• Common Uses
– Manage rollout for risky changes
– Adjust feature offering based on pricing tier
– Enable limited testing of a feature
34

35. Be Aware of Cultural Factors
35

36. Results
• Releases without fallout
• Shorter deployment cycles
• Much lower error rates
• Consistently high uptime
• Consistently low response
time
36

37. Internal Microservices
37

38. Our Initial Implementation
38
Emails
All Applications – TraineeWeb, TrainerWeb, Player etc.
Video
Conversion
Jobs
Async
updates with
Third Party
Systems

39. Characteristics
• High Performance and Uptime
• Easy Error Tracking
• Highly Scalable System
• Achieved Decoupling (sort of)
• Achieved independent deployment (again,
sort of)
• Independent code base (not really)
• Decoupled deployment (not really)
39

40. New Approach
• Independent Verticals ie. Services
• Hapi framework
• Common Services across Verticals
• Incremental code migration
• Integrate tools such as Docker, Stackato,
Ansible, Kubernetes
• More to come!
40

41. Coming Up
• Fully decoupled
microservice
implementation
• Integrate automated
container management
• Fully automated backward
compatibility testing
41

42. References
• Product Blog –
http://www.mindflash.com/blog
• Developer Blog –
http://www.mindflash.com/developers
42

43. Thank you!
• https://www.linkedin.com/in/shob
anaradhakrishnan
• Twitter: #shobanarad, #mindflash
• We’re hiring!
43

44. Questions?