Computer Genomics: Towards Self- Change and Configuration Management ( http://research.microsoft.com/sn/strider)

1. Computer Genomics: Towards Self- Change and Configuration Management(http://research.microsoft.com/sn/strider) Yi-Min Wang Senior Researcher & Group Manager Systems Management Research Group (http://research.microsoft.com/sm/)

2. OUTLINE • Change & Configuration Management • Genomics & Computer Genomics • What We’ve Learned From The Analogy • Systems Management • Configuration Troubleshooting • Patch Impact Analysis • Spyware Management • Towards Self-Management

3. … Spyware Download Setting Change Patching Change & Configuration Management • Problem Scope • Setting changes through Control Panel, program executions, etc. • Software installations, updates, and patching • Drive-by downloads of spyware … O(101) to O(102) processes … O(105) Registry entries and files

4. Persistent Configuration Settings Aging Volatile State Executable Files Process App Reinstallation System Restore OS Re-imaging Patching Configuration Errors • Persistent: cannot be solved by restart / reboot • A major contributor to Internet service unavailability and computer user frustration App Restart Rejuvenation Machine Reboot

5. Genomics & Computer Genomics • “A”, “C”, “G”, and “T” are the four DNA letters of the genetic alphabet • “1” and “0” are the binary letters of the computer genetic alphabet • 3 billion base pairs arranged into 24 distinct chromosomes • Windows Registry is typically 50MB (or 400 mega bits) arranged into several hives

6. Gene: a stretch of sequence in a specific position on a DNA strand • Computer gene: a Registry entry (a stretch of bit sequence) in a specific position of a hive identified by a hierarchical path name • Gene carries the instructions for making a particular protein through gene expression • Registry entry carries the instructions for configuring a particular process instantiation

7. Less than 2 percent of the human genome is made up of protein-coding sequences • The rest labeled as ‘junk’ DNA • A lot of Registry entries are not configuration settings, but rather “operational states” such as usage counts, most recently used files, etc. • They can be labeled as ‘junk’ entries as far as configuration management is concerned

8. Any two persons’ genome is >99.9% identical • Registry snapshots from two different days on the same machine typically have about 99% of the entries identical between them • Even between mouse and human genes, the similarities range from 70% to 90% • Even across different machines, there is a high degree of similarity

9. Majority of variations in the genome sequence simply create diversity • Majority of variations in Registry simply reflect diversity in hardware/software installation and user preferences • But some genetic differences are responsible for causing diseases: the gene for Huntington’s disease was found at the tip of the short arm of Chromosome 4 • Some differences in Registry data are responsible for configuration problems. • For example, the gene for the “Short-cuts-do-not- work” problem was found at the following Registry location:HKEY_CLASSES_ROOT\CLSID\{00021401-0000-0000-C000-000000000046}\shellex\MayChangeDefaultMenu

10. Huntington’s Gene & Human Chromosomes http://www.hdsa-wi.org/chromosomes.gif Short-cuts-do-not-work’s Gene

11. Most diseases involve the interaction of several genes • Studies have shown irrefutable evidence of the role environment plays in gene expression • Studies of Registry problems reveal that the “healthy” or “sick” values of many entries are not absolute on their own and very often depend on the environment of individual machines

12. Gene therapy can potentially treat diseases by using normal genes to replace a defective gene • But some failed experiments have shown the risk of unexpected side effects of creating new diseases • The equivalent of gene therapy can be easily performed with a Registry or file editor • But direct modifications to these low-level state information can potentially cause inconsistency and lead to more serious problems

13. What We’ve Learned From The Analogy • Configuration problems are solvable • One order of magnitude easier than the genomics problem • Techniques for complexity reduction • Noise filtering through “junk” labeling • Diff can be very powerful: two orders of magnitude reduction • Attack the Mess with the Mass: statistical analysis across multiple machines • Computer Genomics Database for problem detection and repair • Problems with known root causes: which gene causes which problem and how to fix it • Problems with unknown root causes: which action should be tried to provide safe gene therapy

14. No.1: Configuration Troubleshooting • “It worked yesterday, but not today.” • “It worked for that user, but not this user.” • “It worked on that machine, but not this machine.” • “I restarted the application, rebooted the machine, but still can’t fix the problem!”

15. The program keeps failing Support Articles Config Action UI App Info Doc Tracing State Diff Intersection Support Database Lookup Ownership Mapping PC Genomics Database Noise Filtering State Ranking Filtered & Ranked Candidate Set Strider Process for Configuration Troubleshooting Context Information Gathering phase Complexity Reduction Phase It was working Now it doesn’t work User Tool

16. After diff & trace intersection Average Registry size Two Orders Another Two Orders Of Magnitude After state diff Root cause Order-ranking After noise filtering Cross-Restore-Point Results

17. No.2: Patch Impact Analysis • “If I apply this security patch, which one of the 3,000 applications in my company is going to be affected?”

18. All Program Executions Applications Requiring High-Priority Testing Tracing State Diff Intersection PC Genomics Database Noise Filtering (System Processes) Process-to-Application Mapping State Ranking (Process Criticality) Filtered & Ranked Candidate Set Strider Process for Patch Impact Analysis Context Information Gathering phase Complexity Reduction Phase Before Patching After Patching User Tool

19. No.3: Spyware Management • “I’m getting lots of pop-ups and my browser is crashing a lot. What software got installed on my machine?”

20. Objective Criteria Evaluation, Bundle Information, & Support Articles Reboot Machine & Launch IE Tracing State Diff Intersection PC Genomics Database Known-* Database Lookup Noise Filtering (Known Goods) State Ranking (Behavior Criticality) Filtered & Ranked Candidate Set Strider Process for Spyware Management Context Information Gathering phase Complexity Reduction Phase Before Spyware Infection After Spyware Infection User Tool

21. Towards Self-Management • Flight Data Recorder (FDR) • Always-on tracing, diff’ing, intersection, noise filtering, and state ranking • Automatic genomic lookup for known problems • “Self-healing”, “known-bad”, and “wait for user complaint” • Automatic PeerPressure analysis for anomaly detection • Automatic generation of black-box application dependency database • Automatic trace analysis for new ASEP hooks • ASEP = Auto-Start Extensibility Point

22. Summary • The Strider Process for Handling Persistent-State Complexity • Diff • Trace • Intersection • Noise Filtering • State Ranking • Look-up

23. For More InformationGoogle “MSR Strider” or http://research.microsoft.com/sn/strider/ • Configuration Management • Strider Troubleshooting: DSN’03, LISA’04, DSN’04, LISA’05 • Glean: ICAC’04 • Flight Data Recorder (FDR): LISA’05 • Friends Troubleshooting Network (FTN): IPTPS’04 • PeerPressure: SigMetrics’04 (poster) • Patch Management • ICAC’04 • Spyware Management • LISA’05

24. Thank You! • International Conference on Autonomic Computing (ICAC’05) • Tentative: May 2005 in Seattle