Big Data Expo 2015 - Savision Optimizing IT Operations
- 1. Optimizing IT Operations with Big Data analytics Dennis Rietvink, co-Founder & VP of Product Management
- 2. Agenda About Savision About You IT Operations Realities Market Trends in IT Operations How We Solve Big Data Problems Questions 2
- 3. About Savision Market leader in Business Service Management solutions for Microsoft System Center Founded in the Netherlands HQ in Amsterdam, offices in Dallas & Ottawa 3
- 4. 4 Customers
- 6. About You A: Interesting B: Couldn’t tell, I just got in C: Too much data already D: Better than a day in the office 6 What do you think of the event so far? A B C D 0A B C D
- 7. About You A: IT Pro B: Developer C> Analyst C: IT Management D: C-Level Management D: Other 7 What describes your current role best? A B C D E 0A B C D E F F
- 8. About You A: 1 - 100 B: 101 - 500 C: 501 - 5000 D: > 5000 8 What is the size of your organization? A B C D 0A B C D
- 9. About You A: 1 B: 2 - 10 C: 11- 20 D: > 20 E: Don’t know 9 How many monitoring tools are used in your organization? A B C D 0A B C D E E
- 10. About You 10 Meeting SLAs Balancing budget Moving workloads to the cloud Just keeping the lights on Balancing new initiatives with current operations What keeps you up at night? A B C D E 0A B C D E
- 11. IT Operations Realities On average more than 10 monitoring tools Producing over 1 million events per year Cloud increases IT operations complexity Number of managed devices will increase exponentially - 2015: 4.9 billion connected “Things” - 2020: 25 billion connected “Things” Ongoing information GAP between business and IT operations 11
- 12. IT Operations Realities On average more the 10 monitoring tools Producing over 1 million events per year Cloud increases IT operations complexity Ongoing information GAP between business and operations Number of managed devices will increase exponentially - 2015: 4.9 billion connected “Things” - 2020: 25 billion connected “Things” 12
- 13. Market Trends in IT Operations Intelligent discovery and transaction monitoring (APM) - Good: Auto discovery and problem detection, great for devops - Bad: Less focused on future problems and lack of domain knowledge Centralize machine data, then analyze (ITOA) - Good: Analyze patterns across data sets, quick search of datasets - Bad: Lack of domain knowledge and still need to add context 13
- 14. How We Solve Big Data Problems Combine forces using best of breed tools 14
- 15. How We Solve Big Data Problems 15 Business Service Model InfrastructureApplicationEnd User SocialBPM Outage Cost Incidents Changes Service Levels Business Service Business Service Dependencies Introduce a ‘new’ language for business and IT
- 16. How We Solve Big Data Problems 16 Business Service InfrastructureApplicationEnd User SocialBPM Outage Cost Incidents Changes Service Levels Business Service Business Service Dependencies Introduce a ‘new’ language for business and IT
- 17. How We Solve Big Data Problems 17 Business Service InfrastructureApplicationEnd User SocialBPM Outage Cost Incidents Changes Service Levels Business Service Business Service Dependencies Introduce a ‘new’ language for business and IT
- 18. How We Solve Big Data Problems 18 Fabric Model NetworkingVMsClusters IAASChanges PAAS Containers Storage Service Levels Introduce a ‘new’ language for business and IT Business Service Pivot
- 19. How We Solve Big Data Problems 19 Consumerize IT Ops
- 20. Availability 20 Today: Microsoft System Center + ServiceNow 2016 Q1: Microsoft System Center + Solarwinds + ServiceNow
- 21. Participate and win Scan your badge at our Booth #39 and participate in a draw to win a 21 Store all your BIG DATA!
- 22. Questions? 22 www.savision.com @Savision SavisionBV Savision For more information: Dennis Rietvink – Founder & VP of Product Management Dennis.Rietvink@savision.com Sales inquiries sales@savision.com Meet us at our booth #39!