Performance Engineering in 2020 is not going to be the same as it is now. Cloud, Microservices, Continuous Delivery and Self-Healing are some of the aspects that will shape the role and focus of performance engineering. Ram, currently working as a Lead Performance Engineer at REI, has seen both worlds and gives us insights on how to optimize performance engineering on your existing on premise applications with AppMon but how it has to evolve when moving to new architectures and cloud environments with Dynatrace. A perfect opportunity to evolve your performance engineering is when moving your apps to the cloud as this is the right time to evolve your tooling and processes as well. Join us and learn how Ram has been successfully doing it.

1. #Perform2018
Cloud innovation and automation
Evolving performance engineering for
the move to cloud, microservices,
continuous delivery and self-healing
Ram
Lead Performance Engineer
#Perform2018#Perform2018

2. EARLY 2015
TRANSFORMATION ERA
ON PREMISE - CLOUD

3. Our journey
Three Stages
EARLY 2015
Waterfall Model
Transformation Era
Agile
On Prem- Cloud
DevOps
1 2 3

4. TRANSFORMATION ERA
Our Journey and How did we do it?

5. PEChanges
Cloud Based Load
Testing Solution
Version Control with Bit
Bucket
Reporting to Atlassian
Tool Sets ( Confluence,
JIRA etc)
Performance to Left &
Right
Production Load Test
from multiple
Geography.
EvolutionofAPM
APM Selection using
Gartner Magic
Quadrant
APM Monitoring
Production &
Performance
Environments.
Full Stack Analysis (
Application, DB,
Network)
ProductionMonitoring
Alerts & Thresholds
Configurations.
Pro Active Alerting
using Slack & Service
Now Integration.

6. ON PREM - CLOUD

7. Cloud Adoptions
• AWS, Azure , Google
• Serverless Functions
• Auto Scaling
• Multi AZ Deployments
• RDS, No SQL
Performance Engineering
in the Cloud
• Scalability (Auto Scaling)
• Availability (Multi AZ
Failover)
• Serverless Tuning
• Monitoring Cloud native
apps
Tools Migration
• Cloud Based SAAS
APM Solutions.
• Ease of configurations
using OneAgent
Technology.
• Docker Monitoring
w/o customizing
docker images.

8. ON PREM DASHBOARDS & USE CASES

12. Slack Integration & Pro
active Problem
Resolution

13. Docker Monitoring
using Appmon

14. CLOUD APP DASHBOARDS & MONITORING
FOOTPRINT

15. Cloud Monitoring using
Cloud watch Metrics
Integration

16. Server less Functions
Deep Method Level
Analysis

17. Production Realtime TV
Dashboards

18. Slack Integration & Pro
active Problem
Resolution using
Dynatrace Managed (AI
Powered)

19. Auto Problem
Detection

20. Java/ Dot net Custom
Service Configurations
with Dynatrace
Managed

21. Detailed Service Flow
for Custom Services

23. Thank you