appsphere 15 - application analytics helping devops with data driven decision making
TRANSCRIPT
Application Analytics helping DevOps with data driven decision making Amod Gupta, Sr. Principal Product Manager Mike Anand, Director of Product Marketing
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Software defined business
Software agility drives rapid business velocity IT needs to respond in real-time
deliver great customer experience
ensure zero downtime this holiday season
reduce customer churn rates
understand changing usage patterns
stay ahead of performance problems
release new features faster
When business wants to… IT needs to…
“What do you need to get these done?”
“Understand business and software performance correlation in REAL-TIME!”
PM, Marketing, Sales, Customer Success
Ops, Dev
Business data Marketing data Operations data
Traditional approach to analytics IT cannot respond in real-time
Revenue
New Customer Growth
Churn
User preferences
Conversions
Campaign performance
Brower/Mobile performance
App performance
Infrastructure performance
Drop off rates
Loyalty Tiers
Product mix
Revenue per user
Revenue per tier
SEO Performance
Geo locations
Mobile usage
Network performance
Browser performance
Database performance
Network carrier performance
How much revenue was lost today from Tier-1 users not converting because they experienced poor app performance?
Enter custom big-data analytics….
5. ANALYZE 4. CORRELATE 3. STORE DATA 1. CHANGE CODE 2. COLLECT DATA
Slow and iterative Cannot keep up with today’s agile apps
Hard to maintain for fast changing apps
High costs – time, people, software, hardware
Backwards looking
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IT is unable to unlock the data potential
Need specialists to understand and analyze data
Any new business report request is a dev project
Business insights are never current nor granular enough
BIZ ANALYST
MKTG OPS IT OPS
What if you knew in real-time… Shopping & Merchandise Categories
Ticket Sales
Average Response Time
$232,390 Revenue impact of poor performance
Shops/Merch generating highest revenue
Revenue generated by ticket sales
Revenue Impact of Poor Performance
This is the timestamp when performance issue started
5 MIN
Wait Time
Dining Pass Sales
Users on each ride
Top Park Rides
What if you knew in real-time… Merchandise Categories
Ticket Sales
Average Response Time
$232,390 Revenue impact of poor performance
Merchandise generating highest revenue
Users on each ride
Breakdown of ticket sales
Revenue Impact of Poor Performance
Top Park Rides
This is the timestamp when performance issue started
24 MIN
Wait Time
Age of Customers
Three common use cases
Advanced performance analytics
Usage analytics
Business impact analytics
Business impact analytics Identify failed individual transactions and respond within minutes
Business and IT collaborate to run win-back campaigns
Capture all slow and failed transactions + revenue impact
List impacted platinum customers
Marketing runs win-back campaigns
10% off
Log
Platinum customer
British Airways API
Flight to London
Total cost $1,800
Kevin Gold IOS
AT&T
Laura Lewis iPad
T-Mobile
Poor experience
Flight to New York
Code level issue
Silver customer
Total cost $712
Matt Jacobs IOS
AT&T
Good experience
Gold customer Flight to
Miami
Total cost $650
Database issue
Tracy Kraft iPhone 6
AT&T
Poor experience
Silver customer
Code level issue
Flight to Tokyo
Total cost $1,100
Libby Halll iPad
T-Mobile
Poor experience
Platinum customer
Code level issue
Flight to New York
Total cost $850
Jude Germangy
Platinum customer
Book Flight
Flight to London
Travel Airways API
Total cost $1,800
Ready for real-time insights
Automatically collected
Fully correlated
Platinum customer, Jude Germangy, failed while booking a flight to London for $1,800 while using a browser due to issues with the Travel Airways API
Answer individual user questions in real-time
Log
Platinum customer
British Airways API
Flight to London
Total cost $1,800
Kevin Gold IOS
AT&T
Laura Lewis iPad
T-Mobile
Poor experience
Flight to New York
Code level issue
Silver customer
Total cost $712
Matt Jacobs IOS
AT&T
Good experience
Gold customer Flight to
Miami
Total cost $650
Database issue
Tracy Kraft iPhone 6
AT&T
Poor experience
Silver customer
Code level issue
Flight to Tokyo
Total cost $1,100
Libby Halll iPad
T-Mobile
Poor experience
Platinum customer
Code level issue
Flight to New York
Total cost $850
Answer aggregate questions in real-time
Poor experience
Poor experience
Poor experience Poor
experience
Poor experience
Poor experience
Total cost $1,800
Total cost $850
Total cost $712
Total cost $1,100
Total cost $650
A total of $4,785 revenues were at risk due to poor experience while booking flights
Ready for real-time insights
Automatically collected
Fully correlated
Female Male
New Existing
Product Home Gallery Basket Checkout
Gender
Customer
Journey
Time of day
Personalized
Device
08:00 12:00
00:00 04:00
04:00- 08:00
12:00 16:00
16:00 20:00
Desktop Mobile
Yes No
Age 21-29 <21 30-45 45+
Usage analytics The what, who, where, and how of users
{Customer Name} User Experience {Customer Name} Cost to Serve
Diamond Customers Performance
Advanced performance analytics Performance views for specific customers and partners
Diamond Customers Requests
DIVING DEEPER Architecture
• Automatic • Structured &
Unstructured Data
• Infinitely Scalable • Real Time
• Visual Query Building
• Ad hoc analysis
OPTION 1 SLIDE
Conceptual Visualization Analytics under the covers
Data Collection
Data Processing& Storage
Data Visualization
OPTION 1 SLIDE
Under the hood Data Collection
Data Collection
Data Processing& Storage
Data Visualization
Controller
Mac
hine
s
Java Agent
APM
Events Service
ANALYTICS
Transaction, Log and User Data
EUM Processor
Machine Agent
.NET Agent
Analytics Agent
Machine Agent UI
OPTION 1 SLIDE
Data Collection
Data Processing& Storage
Data Visualization Platform Architecture
Event Service
SaaS: Designed For Petabytes of Daily Data Volume On-Premises: Start Small & Scale Horizontally
OPTION 1 SLIDE
Data Collection
Data Processing& Storage
Data Visualization Data Visualization
SaaS numbers in last 24 hours (are we ok showing these? If we are, I can pull in more data from OA)
WHAT’S NEW 4.2 Features
BTs (4.1)
Logs (4.1)
Browser RUM (GA)
Mobile RUM (GA)
Custom Events (New)
API (New) Richer Data Set
AppDynamics Query Language Advanced Search
Visualization & Reporting
Deeper Insights Auto-correlation between Business
Transactions & Logs Grok patters to include
Key Value Pairs
Custom Dashboard
Funnel Conversion
Multiple X and Y
Schedule Reporting
What’s new in 4.2
Security Role Based Access Control SSO
Analytics Deep Dive Session
Tomorrow’s session dives more in depth about our architecutre and upcoming features
Copyright © 2015 AppDynamics. All rights reserved. 23
Thank You
4.2 new data sources
APM Transactions
Browser Real-User Monitoring
Mobile Real-User Monitoring
Application & Infrastructure Logs
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AppDynamics Analytics
Synthetic Monitoring
Custom Events
Logs and Transactions
new
Dashboard Integration & Reporting
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Widgets from APM, EUEM & Analytics on same dashboard
Convert dashboards into daily, weekly reports
Interactive widgets – Move in and out of the dashboard
Custom time ranges for each widget
More 4.2 Goodness
Copyright © 2015 AppDynamics. All rights reserved. 27
Log Agent • Transaction and Log correlation • Support for more log formats
Security • Role based access control in analytics
Agent • Node.js agent supports transaction analytics
API • API support for data ingestion and extraction
New and Improved Widgets
Ranges and buckets Funnel Widget
Copyright © 2015 AppDynamics. All rights reserved. 29
Application Performance
Business Performance
AppDynamics Application Analytics
Correlation in real time
Copyright © 2015 AppDynamics. All rights reserved. 30
ADQL • Free text query language support • Programmatically search through your data
Dashboard & Reporting
• Save Analytics widgets to Custom Dashboards • Schedule reports
Improved UX • New Widgets – Funnel, Live stream, Percentile etc • Improvements to existing widgets – Multiple fields on X & Y axes
API • API for search and extraction • API for custom events ingestion
What’s new in 4.2
Security • Role based access control for Analytics
Log & Transaction • Correlation between logs and transaction using BT GUID • Enhancing log collection & parsing