Snappy Symbolication Server: Difference between revisions

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The Snappy Symbolication Server is a Web server for symbolicating Firefox stacks. It matches PC addresses to modules in memory and looks up the corresponding function names in server-side symbol files (.SYM files).
The Snappy Symbolication Server is a Web server for symbolicating Firefox stacks. It matches PC addresses to modules in memory and looks up the corresponding function names in server-side symbol files (.SYM files).


== Running ==
The documentation for Snappy no longer lives here. It can be found in the [https://github.com/mozilla/Snappy-Symbolication-Server/blob/master/README.md Readme on Snappy's GitHub]
 
The source code for Snappy lives in the [https://github.com/mozilla/Snappy-Symbolication-Server Mozilla Github repository]. Snappy runs at [http://www.python.org Python] 2.7 and depends on [http://www.tornadoweb.org Tornado] and
[https://pypi.python.org/pypi/futures concurrent.futures] packages. The best way to install them is through [https://pip.pypa.io pip]:
 
:<code>pip install tornado futures</code>
 
To run snappy on your machine, just type:
 
:<code>python symbolicationWebService.py <configuration-file></code>
 
The snappy repository contains two sample configuration files for Linux and Windows. Here is a summary for the config fields:
 
{| class="wikitable"
! Section !! colspan=2 | Fields
|-
! !! Field !! Description
|-
| rowspan=6 | General || hostname || Server address or name
|-
| portNumber || Server port number
|-
| remoteSymbolServer || The address of a secondary remote server to forward requests to
|-
| maxCacheEntries || Number of entries for RAM symbol cache
|-
| mruSymbolStateFile || Json file with RAM cache info
|-
| maxMRUSymbolPersist || Maximum number of symbols for cache
|-
| rowspan=2 | DiskCache || cachePath || Path to cached symbol files
|-
| maxCacheFiles || Maximum number of files in the cache dir
|-
| rowspan=4 | Log || MaxFiles || Maximum number of log files
|-
| maxFileSize || Maximum size for a log file
|-
| logPath || Path to log files
|-
| logLevel || NOTSET, DEBUG, INFO, WARNING, ERROR, CRITICAL
|-
| SymbolPaths || || Each entry represents a path to search for symbols in the local disk
|-
| SymbolURLs ||  || Each entry represents a remote path to search for symbols
|}
 
== Contributing ==
 
It is a [https://github.com Github ] project, just fork it and send a PR. If you want to ask something, you can find people involved with Snappy Server in the #perf channel at irc.mozilla.org.
 
== Project ideas ==
* Snappy parses symbol files in another process (which we informally call "Symbolication Process") due to the well known [https://www.youtube.com/watch?v=Obt-vMVdM8s GIL problems]. We could have a Symbolication Process per CPU core, but we have a tricky problem here. The Symbolication Process maintains a in memory symbols cache, with the most recently used symbols. The problem is how we handle this, we could have a single shared cache among all Symbolication Processes, which would bring contention, hurting the code parallelism. Other approach is that each Symbolication Process could have its own memory cache, but we potentially could waste memory due to duplicated symbols among all processes, and we could duplicate work because all subprocesses would parse the same symbol file in case of several similar symbolication requests. One good solution is to maintain the memory cache in the parent process.
 
* The Symbolication Process requests symbol files from S3. This is a I/O bound task, so this should happen in the main process, and then Snappy would use asynchronous I/O for that. The problem is that we have to send the symbol file to the Symbolication Process through IPC. The IPC overhead could kill the performance gain with asynchronous requests. We need performance numbers here to make a decision on what's the best approach.
 
* Too bad we don't have unit tests.
 
=== Symbol file cache proposal ===
 
Snappy searches for symbol files on S3 when it doesn't find them locally. The proposal is to cache these files locally, with a LRU eviction policy. Instead of storing them in the original sym file, we store in the parsed format using [https://docs.python.org/2/library/pickle.html Pickle] module.
 
The cache size is counted by the number of files stored, and must be accounted to keep some extra free space, since the eviction code runs in a timely fashion. Here is some pseudo Python code for file cache:
 
<code>
def Initialize():
:for each file in the cache directory:
::accessTime = AccessTime(filePath)
::ListofFiles.append(FilePath)
:LRU = ListOfFiles reverse sorted by access time
</code>
 
<code>
def StoreCache(SymbolData, path):
:writeFile(SymbolData, path)
:LRU.append(path)
</code>
 
<code>
def FetchCache(path):
:SymbolData = readFile(path)
:LRU.remove(path)
:LRU.append(path)
</code>
 
<code>
def Evict():
:lruSize = len(LRU)
:idealSize = maxSize * 0.6
:while lruSize >= idealSize:
::path = LRU.popleft()
::removeFile(path)
</code>
 
== Regressions tests ==
 
Some regressions tests to perform before sending a PR:
 
* Perform a get request to the server
* Check if the IP in X-Forward-For is logged
* Test requests with /gecko-profiler/ path
* Test for /debug and /nodebug special paths
* Test with compressed symbols files
* Exiting with Control-C should kill the server smoothly
* Check if the host handles ill-formed requests
* Check if symbol server can forward requests
* Parse a symbol file, exit and start the server again. The server should fetch the sym file from cache
* Check if the server writes logs to files

Latest revision as of 00:54, 9 December 2016

The Snappy Symbolication Server is a Web server for symbolicating Firefox stacks. It matches PC addresses to modules in memory and looks up the corresponding function names in server-side symbol files (.SYM files).

The documentation for Snappy no longer lives here. It can be found in the Readme on Snappy's GitHub

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