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2. 2 2 Jeff Hart M2 Technology IT Situational Awareness 2

3. 3 Theoretical model of situation awareness, Dr. Mica Endsley, 1995 Situational Awareness 3 Perception of Elements in Current Situation Comprehension of Current Situation Projection of Future Status

4. 4 Baseline Discovery Gathering Perception 4 Track Usage Inventory Software Inventory Hardware Identify Devices Discover Environment Recognize Applications

5. 5 Combining Top Down and Bottom Up Metrics Perceiving Current Status 5 N/WSYS Mission APPS Organization Other Server1ProcessDNSSwitch1 N/WSYSAPPS Othe r ProbeX Probe1 Probe2 Probe3 Status Mission Organization

6. 6 Beginning to define service models Perceiving Context 6

7. 7 Automated mapping of what you have and how it relates Automating Application Mapping 7 Layer 2-7 of the OSI Model AccountingCSOB2BOrderingRetail store Accounts receivable_app Accounts payable_app Customer support_app Order_appShipping_app Physical Data Center Business Process Model

8. 8 Building comprehension from perception Foundation of Comprehension 8 Run-time Service Model HP CMS 3 rd party CMDB Integrated/Federated Application Performance Management Infrastructure Performance Management

9. 9 Creating Context 9 Event mapping to CI‘s in the Run-Time service model –Relationship of events to dynamically updated CIs BSM Platform Events and discovery / topology data are brought together End-to-end visibility of infrastructure and alerts by showing relationships of events to CIs and business services that are impacted Shows CIs in context Event consolidation through OMi Run-time Service Model hosts auto- discovered CIs

10. Bringing Clarity to Complexity 10 TBEC – Topology Based Event Correlation Efficiency gains per advanced event causal correlation Use case addressed by TBEC: 1.Something goes wrong in your environment 2.Monitoring reports multiple problems via events 3.Usually just one of the events describes the CAUSE of the problem 4.Others are just SYMPTOMS 5.Fix the CAUSE and also the SYMPTOMS go away Use case addressed by TBEC: 1.Something goes wrong in your environment 2.Monitoring reports multiple problems via events 3.Usually just one of the events describes the CAUSE of the problem 4.Others are just SYMPTOMS 5.Fix the CAUSE and also the SYMPTOMS go away Cause Cause and Symptom Symptom

11. 11 Automating Correlation & Service Model Management 11 The “T“ in TBEC - rules based on topology –Adaptive correlation – support for dynamic environments without adding administrative burden Current discovered Topology utilized to correlate related events Related events analyzed to determine SYMPTOMS and CAUSE. As new CIs and relationships are automatically discovered, the TBEC rules are automatically applied. Experts define the rules ONCE and do NOT have to go back and update when the infrastructure changes Symptoms Cause

12. 12 Automatic prioritization of Events 12 Based on Business / Mission Context Event Priority is calculated based on severity and business / mission impact. Event that affects business service of criticality 4 gets higher priority than event that affects business service of criticality 2. CI business impact is calculated based on Business Criticality of all affected business services, applications and business process CIs and eg. SLAs.

13. 13 Customized console 13 Optimize use of staff resources –Optimized use of operations staff resources Operator Perspectives: Operator can configure his own operator console with the information he needs for his daily tasks Mash-up UI: Gallery allows user to compose new pages using provided components Role based consoles

14. 14 Projection of Future Status 14 HP Service Health Analyzer (SHA) 1.Anticipate problems before the business is impacted and prevent downtime 2.Automatically correlate information from multiple domains 3.Reduce cost of handling events by proactively investigating anomalies 4.Self learning system Predictive Analytics

15. © Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 15 Proactive Risk Reduction by fusing IA and Ops Operational Analytics #2 Provide Context #3 Act Appropriately Proactive Risk Reduction SECURITY User Provisioning Identity & Access Mgmt Database Encryption Anti-Virus, Endpoint Firewall, Email Security #1 SEE EVERYTHING IT OPERATIONS User Management App Lifecycle Mgmt Information Mgmt Operations Mgmt Network Mgmt #1 SEE EVERYTHING 15

16. 16 Operational Analytics 16 A unified approach to solving IT Operations Management (ITOM) problems Event Triage Log Management Advanced Analytics Advanced Correlation Unknown Problems Known Problems Reactive Monitoring Proactive Monitoring Operations Analytics

17. 17 Service Health Analyzer powered by RTSM 17 Run-time Service Model Comprehensive, automated and up-to-date model for dynamic services Infrastructure Performance Management Application Performance Management End-User Experience Transactions App Diagnostics Business metrics Server Network Virtualization 3 rd party

18. 18 Projection of Future Status 18 Early morning: Metric performing within baseline 11:00am: Metric violates threshold 10:30am - SHA detects an anomaly and sends out an alert\event SHA detected a problem and sent alert one full hour before the service failed 1 2 3 11:30am: Service is now unavailable… 4

19. 19 Implementing the Ops Bridge 19 Value to the Organization Experts Can focus on mission / business initiatives Less time spent on day to day operations tasks Less time spent on administration Are able to add incremental value to operations more rapidly Operations Are more effective at day to day operations activities Continued control of OpEx Higher efficiency – lower MTTR Higher Service levels  Spend less time working on day to day operations  Spend less time maintaining operational solutions  Optimize time engaged in evolving operational solutions  Maximize time spent on strategic activities  Reduce false alarms.  Work on causes and not symptoms.  Enable co- operative cross- domain working  Focus on what matters to the business  Handle a higher proportion of incidents without escalation  Fix issues more rapidly  Streamline incident management activities Tier 1 Operators Experts Workload Efficiency

20. © Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. Questions? Contact Information: Jeff Hart, M2 Technology Enterprise Software Specialist Jeff.hart@m2ti.com 202-595-1917

21. © Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. Thank you Contact Information: Jeff Hart, M2 Technology Enterprise Software Specialist Jeff.hart@m2ti.com 202-595-1917