AppSphere 15 - Application Analytics helping DevOps with Data Driven Decision Making
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Every business is a software business: as companies embrace and embark on digital transformation the organization must become data-driven. Each decision is made based on data and key performance indicators along with analytical insights. Enterprise IT teams in this data-driven era must make decisions across multiple departments within an organizations based on these key insights. AppDynamics Application Analytics is a user and application-driven IT Operations Analytics (ITOA) platform. In this session, you will learn and see specific use cases in which AppDynamics Application Analytics applies to across your organization such as Business Impact Analytics, Usage Analytics & Advance Performance Analytics. This deck was originally presented at AppSphere 2015.
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AppSphere 15 - Application Analytics helping DevOps with Data Driven Decision Making
- 1. Application Analytics helping DevOps with data driven decision making Amod Gupta, Sr. Principal Product Manager Mike Anand, Director of Product Marketing
- 3. 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
- 4. 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?
- 5. Enter custom big-data analytics…. 5. ANALYZE4. CORRELATE3. STORE DATA1. 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 0110101101011010110101101 0110101101011010110101101 0110101101011010110101101 0110101101 0 1 0 1 0 11 0 1 01 0 1 0 101 011
- 6. 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
- 7. 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
- 8. 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
- 9. Three common use cases Advanced performance analytics Usage analytics Business impact analytics
- 10. 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
- 11. 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
- 12. 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 experiencePoor 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
- 13. Female Male New Existing ProductHome 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
- 14. {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
- 16. • 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
- 17. OPTION 1 SLIDE Under the hood Data Collection Data Collection Data Processing & Storage Data Visualization Controller Machines Java Agent A P M Events Service A N A L Y T I C S Transaction, Log and User Data EUM Processor Machine Agent .NET Agent Analytics Agent Machine Agent UI
- 18. OPTION 1 SLIDE Data Collection Data Processing & Storage Data VisualizationPlatform Architecture Event Service SaaS: Designed For Petabytes of Daily Data Volume On-Premises: Start Small & Scale Horizontally
- 20. SaaS numbers in last 24 hours (are we ok showing these? If we are, I can pull in more data from OA)
- 22. 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
- 23. Analytics Deep Dive Session Tomorrow’s session dives more in depth about our architecutre and upcoming features Copyright © 2015 AppDynamics. All rights reserved. 23
- 24. Thank You
- 25. 4.2 new data sources APM Transactions Browser Real-User Monitoring Mobile Real-User Monitoring Application & Infrastructure Logs 01101011010110101101011010110101100 01101011010110101101011010110101100 01101011010110101101011010110101100 AppDynamics Analytics Synthetic Monitoring Custom Events Logs and Transactions new
- 26. Dashboard Integration & Reporting Copyright © 2015 AppDynamics. All rights reserved. 26 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
- 27. 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
- 28. New and Improved Widgets Ranges and buckets Funnel Widget
- 29. Copyright © 2015 AppDynamics. All rights reserved. 29 Application Performance Business Performance AppDynamics Application Analytics Correlation in real time
- 30. 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