The engineering team implemented several best practices that improved the organization. These included clickable mocks, coding standards, code reviews, architecture reviews, automated deployments, runbooks, quality engineering, RESTful APIs, user acceptance testing, build/release processes, and onboarding. The changes led to fewer bugs, better guidance for engineers, standardized decisions, faster iterations with customers, increased development speed, and more. Stakeholders saw the team as being far ahead thanks to the engineering improvements.

1. ENGINEERING BEST
PRACTICES IMPLEMENTED
GAURAV KUMKAR

2. TEAM BEFORE
• Inherited disorganized or no engineering team
• Late releases riddled with bugs
• Junior engineers directly reporting to senior management
• No mentorship or guidance for technical engineers
• Code was hacked together for every release
• Infrastructure was not maintained (non-static ips)
• No consistency in architectural decisions (e.g. mongo db vs sql server)

3. AFTER BEST PRACTICES IMPLEMENTATION
• Clickable mocks
• Coding standards
• Daily code reviews
• Architecture and design reviews
• Automated deployments and testing
• Runbooks
• Quality Engineering
• Interactive Restful API
• User Acceptance Testing
• Build and release process
• Onboarding process

4. Clickable Mock vs Wireframes
• Early visual snapshot to customers
• Cost to make adjustments on mock were
cheaper than actual product
• Lot of rapid iterations could take place
• Business team tried out multiple alternatives
before decided the look and feel and flow of
the product
• Final product was identical to clickable mock

5. Design Toolkit
• Speed of development
• Reusability
• Standardization

6. Best Standards
• Coding Standards
• Code reviews

7. Architecture & Design
• Micro services APIs
• MVC architecture
• Design Patterns (Factories / Singletons)
• Restful APIs with error codes
• Better communication between frontend
and backend teams
• Network Architecture Diagrams / UML

8. Build & Release Process
Automation
• Saved 30-45 minutes daily engineering time
from manual deployment
• Great communication between QA / Engineers
with version numbers
• DB, Frontend, Backend versions separated for
loose coupling
• One click deployments for dev, test, stage and
production

9. Quality Engineering
• Manual testing
• QA Plan
• Requirements Traceability Matrix
• Extensive Test cases
• Automation testing
• Selenium
• Local environment
• Load Testing

10. Load Testing
Number of simultaneous
users
Error % Overall requests per
second
Comments
10 0.01 % 6.33 With a very small number of users in the system, the server performs
very well. Very few errors with a good number of requests made every
second.
100 0.01 % 58.49 With 100 users, the error rate is kept low and it has a decent RPS.
500 0.02 % 123.12 Keep adding more simultaneous users to the system decreases the
performance. On a bright side, the error rate is still very low.
1000 0.02 % 127.42 From 500 users to 1000 users, we can see that the overall RPS does not
increase a lot.
We are close to hitting the server limit on handling requests.
Throughout the test, the primary DB server has max out the CPU usage.

11. Agile Software Development

12. Monitoring
• Production application monitoring
• System level
• Application level
• Email Alerts

13. Security & Risk Management
• Implemented security for OWASP top 10 Vulnerabilities
• Injection attack
• Weak Authentication and session management
• CSRF Vulnerabilities
• Path Manipulation Vulnerabilities
• Resource Leaks
• Security Credentials short

14. Analytics & User Engagement
• Google Analytics Integration
• Understanding user behavior in depth

15. THANK YOU
• We are light years ahead with all the engineering best practices improvement
• VP Operations (customer)
Stakeholders Testimonial
•We are light years ahead with all the engineering
best practices improvement
VP Business Operations