The document discusses the importance of self-monitoring in applications, emphasizing a hierarchical strategy for monitoring CPU, memory, garbage collection, and deadlocks. It highlights the necessity for both large-scale servers and simpler applications to use customized monitoring tools that meet specific business needs. Additionally, it outlines various performance counters and APIs for effective diagnostics and profiling while acknowledging the complexity and overhead involved in implementing such monitoring systems.

1. SELF-AWARE APPLICATIONS
AUTOMATIC PRODUCTION MONITORING
DINA GOLDSHTEIN,

2. Agenda
Motivation
Hierarchy of self-monitoring
CPU profiling
GC monitoring
Heap analysis
Deadlock detection
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3. Agenda
Motivation
Hierarchy of self-monitoring
CPU profiling
GC monitoring
Heap analysis
Deadlock detection
Not today: profiling tools, 3rd party monitoring, dashboards
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4. Motivation
Why monitor?
Obviously a must for servers and/or anything at scale
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5. Motivation
Why monitor?
Obviously a must for servers and/or anything at scale
But also a must for “simple” shrink-wrap software
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6. Motivation
Why monitor?
Obviously a must for servers and/or anything at scale
But also a must for “simple” shrink-wrap software
Why our own?
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7. Motivation
Why monitor?
Obviously a must for servers and/or anything at scale
But also a must for “simple” shrink-wrap software
Why our own?
Customized for specific business needs
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8. Motivation
Why monitor?
Obviously a must for servers and/or anything at scale
But also a must for “simple” shrink-wrap software
Why our own?
Customized for specific business needs
Diagnostics flow from ground up
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9. Motivation
Why monitor?
Obviously a must for servers and/or anything at scale
But also a must for “simple” shrink-wrap software
Why our own?
Customized for specific business needs
Diagnostics flow from ground up
That’s what all the cool kids do :-)
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10. Master Plan
Use a hierarchical monitoring strategy
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11. Master Plan
Use a hierarchical monitoring strategy
Lightweight for continuous and frequent monitoring of all basics
Numerical resource consumption: CPU, memory, disk
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12. Master Plan
Use a hierarchical monitoring strategy
Lightweight for continuous and frequent monitoring of all basics
Numerical resource consumption: CPU, memory, disk
Medium for less frequency events
Rare exceptions, deadlocks
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13. Master Plan
Use a hierarchical monitoring strategy
Lightweight for continuous and frequent monitoring of all basics
Numerical resource consumption: CPU, memory, disk
Medium for less frequency events
Rare exceptions, deadlocks
Invasive for deep-dive and concrete diagnostics
Memory leaks, bulk call-stack data (e.g. CPU profiling)
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14. TOOLS

15. Lightweight Monitoring
Performance counters - provide numeric information about the
system and specific processes (CPU, memory, disk, …)
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16. Lightweight Monitoring
Performance counters - provide numeric information about the
system and specific processes (CPU, memory, disk, …)
Win32 APIs
GetProcessTimes - provides CPU information for a process
GetProcessMemoryInfo - query for memory usage
And others…
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17. Lightweight Monitoring
Performance counters - provide numeric information about the
system and specific processes (CPU, memory, disk, …)
Win32 APIs
GetProcessTimes - provides CPU information for a process
GetProcessMemoryInfo - query for memory usage
And others…
Stopwatch - you know what this is :-)
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18. Halfway Monitoring Tools
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19. Halfway Monitoring Tools
ETW - a structured logging framework incorporated into Windows
which can provide very rich data with relatively low overhead
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20. Halfway Monitoring Tools
ETW - a structured logging framework incorporated into Windows
which can provide very rich data with relatively low overhead
Evaluate your own logs
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21. Halfway Monitoring Tools
ETW - a structured logging framework incorporated into Windows
which can provide very rich data with relatively low overhead
Evaluate your own logs
ClrMD - open source C# library which provides programatic APIs
which until recently were only available using a fully fledged debugger
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22. Invasive Analysis APIs
CLR profiling APIs - a whole bunch of native APIs which provide lots
of data about what’s going on in your managed (attached) application
AppDomain creation, assembly loading, JIT, thread creation, GC
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23. Invasive Analysis APIs
CLR profiling APIs - a whole bunch of native APIs which provide lots
of data about what’s going on in your managed (attached) application
AppDomain creation, assembly loading, JIT, thread creation, GC
CLR debugging APIs - a whole bunch of native APIs which provide
programmatic APIs to debugging actions
Setting breakpoints, exception notifications, state modification
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24. Invasive Analysis APIs
CLR profiling APIs - a whole bunch of native APIs which provide lots
of data about what’s going on in your managed (attached) application
AppDomain creation, assembly loading, JIT, thread creation, GC
CLR debugging APIs - a whole bunch of native APIs which provide
programmatic APIs to debugging actions
Setting breakpoints, exception notifications, state modification
Hooks - to specific APIs of your choosing
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25. LET’S GET TO BUSINESS

26. (Self) CPU-Profiling
Monitor CPU using performance counters
Are we above a certain threshold for a certain amount of time?
Turn on ETW and collect stacks (live using LiveStacks)
Find hot paths, produce flame graphs
Suggest recommendations
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27. What Can Be Done?
AuthenticationController takes 95% CPU, maybe we're being
DDoS'ed
Image processing component takes 100% CPU, need to auto-scale
the app
Encoding this 30 second video takes 3 minutes at 100% CPU, tell the
user she can send us a bug report
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28. DEMO
MONITOR FOR CPU SPIKES
http://jeremiahblatz.com/personal/pics/Australia_Travel_Pictures_2009/day2/22_Kangaroo_Island_Kangaroo_Portrait_Kangaroo_Island.html (CC BY-NC-SA 1.0)

29. (Self) GC-Monitoring
Monitor GC performance using performance counters
Register on ETW’s GC events such as GCAllocationTick
Types of objects allocated and their stacks(!)
Number of GCs of each kind and size of reclaimed memory
Duration of GC pauses
Attach ClrMD to get heap breakdown
Generations, segments, reserved/committed, number of objects
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30. DEMO
MONITOR FOR ALLOCATION SPIKES
https://www.flickr.com/photos/thegirlsny/2803794829/

31. (Self) Heap Analysis
Monitor memory usage using performance counters
Has memory increased above a certain threshold for a certain time?
Attach ClrMD to get heap statistics
Compare snapshots
Report which objects are not freed
Combine with ETW GCAllocationTick to get rate of allocation
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32. DEMO
FIND A LEAK
https://www.flickr.com/photos/53368913@N05/6038464060 (CC BY-NC-SA 2.0)

33. (Self) Deadlock Detection
Monitor for potential deadlock
Low CPU
Request timeouts
Increased thread count
Attach ClrMD to create wait chains and detect deadlocks
Report, try to break, pray for a miracle…
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34. DEMO
DETECT A DEADLOCK
https://www.flickr.com/photos/34547542@N08/3205125391/ (CC BY 2.0)

35. Food for Thought
Many more scenarios are possible
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36. Food for Thought
Many more scenarios are possible
Monitor heap fragmentation and compact large objects if needed
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37. Food for Thought
Many more scenarios are possible
Monitor heap fragmentation and compact large objects if needed
Native memory leak analysis using ETW
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38. Food for Thought
Many more scenarios are possible
Monitor heap fragmentation and compact large objects if needed
Native memory leak analysis using ETW
Side notes:
ClrMD is also very suitable for automating crash dump analysis
You can automate opening tickets in bug tracker, consolidate same
issue from different users, versions, etc.
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39. Not Everything is Perfect
The pros are obvious (visibility, easy scaling…)
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40. Not Everything is Perfect
The pros are obvious (visibility, easy scaling…)
But there are some cons as well…
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41. Not Everything is Perfect
The pros are obvious (visibility, easy scaling…)
But there are some cons as well…
Adds complexity (reduce risk by using separate process)
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42. Not Everything is Perfect
The pros are obvious (visibility, easy scaling…)
But there are some cons as well…
Adds complexity (reduce risk by using separate process)
Adds overhead
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43. Not Everything is Perfect
The pros are obvious
But there are some cons as well…
Adds complexity (reduce risk by using separate process)
Adds overhead
Requires additional development
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44. Summary
Self-monitoring is important for all kinds of software
Best to create a hierarchy of monitoring (and overhead and
complexity)
Lots of scenarios: CPU, GC, memory, deadlocks
Demos: https://github.com/dinazil/self-aware-applications
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45. THANK YOU
DINA GOLDSHTEIN,
@DINAGOZIL