FlameScope is a visualization tool for exploring different time ranges as Flame Graphs.

Overview

FlameScope

FlameScope

Gitter TravisCI NetflixOSS Lifecycle License

FlameScope is a visualization tool for exploring different time ranges as Flame Graphs, allowing quick analysis of performance issues such as perturbations, variance, single-threaded execution, and more.

FlameScope begins by displaying the input data as an interactive subsecond-offset heat map. This shows patterns in the data. You can then select a time range to highlight on different patterns, and a flame graph will be generated just for that time range.

Disclaimer

FlameScope is in early stages of development and under constant change, so bugs and issues are expected. We count on your support to find and report them!

Installation / Instructions

The quickest way to get started is to run the pre-built client bundle:

$ git clone https://github.com/Netflix/flamescope
$ cd flamescope
$ pip install -r requirements.txt
$ python run.py

(Note python3 is assumed, python2 may work)

Then browse to http://127.0.0.1:5000/, and you can begin exploring profiles from the examples directory. You can add new profiles to that directory, collected using Linux perf. Here are instructions for a generic CPU profile at 49 Hertz for 120 seconds:

$ sudo perf record -F 49 -a -g -- sleep 120
$ sudo perf script --header > stacks.myproductionapp.2018-03-30_01
$ gzip stacks.myproductionapp.2018-03-30_01	# optional

If you are profiling C++ code, you may want to pipe stacks through c++filt to get readable frames.

There are extra steps to fetch stacks correctly for some runtimes, depending on the runtime. For example, we've previously published Java steps in Java in Flames: java needs to be running with the -XX:+PreserveFramePointer option, and perf-map-agent must be run immediately after the perf record to dump a JIT symbol table in /tmp.

FlameScope can visualize any Linux perf script output that includes stack traces, including page faults, context switches, and other events. See the References section below for documentation.

FlameScope is composed of two main components, the Python backend, and a React client interface. A pre-built client bundle is distributed with the backend, so the quickest way to get started is to install the Python requirements and start the application, as described earlier.

Although not necessary, we strongly suggest using virtualenv to isolate your Python environment.

By default, FlameScope will load a list of files from the examples directory, which includes a two profile examples.

Configuration Options

FlameScope configuration file can be found in app/config.py.

DEBUG = True # run the web server in debug mode
PROFILE_DIR = 'examples' # path where flamescope will look for profiles
HOST = '127.0.0.1' # web server host
PORT = 5000 # web server port
JSONIFY_PRETTYPRINT_REGULAR = False # pretty print api json responses

Building Client from Source

In order to build the client application from source, the following command line tools must be installed:

Once those tools are available, you will be able to install the project dependencies and generate a build.

$ npm install
$ npm run webpack

The npm run webpack command will generate a new build under app/public. This directory is exposed by the Python web server.

Webpack can also watch and recompile files whenever they change. To build and start the watch task, run the following command:

$ npm run webpack-watch

Building a Docker Image

FlameScope provides a Dockerfile to build a Docker image:

$ cd flamescope
$ docker build -t flamescope .

The container expects the profiles to be bind-mounted into /profiles and listens on port 5000. To view profiles from /tmp/profiles, start the container with the following command:

$ docker run --rm -it -v /tmp/profiles:/profiles:ro -p 5000:5000 flamescope

Then access FlameScope on http://127.0.0.1:5000

References

Issues
  • feat:

    feat: "save as SVG" button

    This is in response to #2, and adds the minimal amount of code to do so. Unfortunately the way SVGs work I could only style the output image correctly by going through the individual elements and adding the styles that came from the css from the 3-flame-graph/dist/d3-flamegraph.css file.

    The flame graph is converted to a downloadable SVG with styling included, makes that the href of a hidden a tag, makes the a tag a download link, and finally clicks the link. The output file is called FlameGraph.svg, and the whole process happens instantly on my laptop.

    Let me know if anything seems incorrect, it's my first time contributing to a React app.

    opened by doug-skinner 10
  • Ability to view Golang graphs

    Ability to view Golang graphs

    This tool looks really awesome and I'd like to try it out on some profiles taken from our production services, but the tool seems to be having trouble with profiles generated using the go tool pprof command.

    Has anyone tried or gotten this to work with Golang profiles yet?

    Here's the stacktrace I'm getting:

    Traceback (most recent call last):
      File "/usr/local/lib/python2.7/site-packages/flask/app.py", line 1997, in __call__
        return self.wsgi_app(environ, start_response)
      File "/usr/local/lib/python2.7/site-packages/flask/app.py", line 1985, in wsgi_app
        response = self.handle_exception(e)
      File "/usr/local/lib/python2.7/site-packages/flask/app.py", line 1540, in handle_exception
        reraise(exc_type, exc_value, tb)
      File "/usr/local/lib/python2.7/site-packages/flask/app.py", line 1982, in wsgi_app
        response = self.full_dispatch_request()
      File "/usr/local/lib/python2.7/site-packages/flask/app.py", line 1614, in full_dispatch_request
        rv = self.handle_user_exception(e)
      File "/usr/local/lib/python2.7/site-packages/flask/app.py", line 1517, in handle_user_exception
        reraise(exc_type, exc_value, tb)
      File "/usr/local/lib/python2.7/site-packages/flask/app.py", line 1612, in full_dispatch_request
        rv = self.dispatch_request()
      File "/usr/local/lib/python2.7/site-packages/flask/app.py", line 1598, in dispatch_request
        return self.view_functions[rule.endpoint](**req.view_args)
      File "/Users/richardartoul/Documents/flamescope/app/views/heatmap.py", line 34, in get_heatmap
        return jsonify(generate_heatmap(filename, rows))
      File "/Users/richardartoul/Documents/flamescope/app/util/heatmap.py", line 120, in generate_heatmap
        cols = int(ceil(end) - floor(start))
    OverflowError: cannot convert float infinity to integer
    

    EDIT: Ah ok it looks like this tool is designed to handle the linux perf output whereas golang generates pprof-formatted files.

    opened by richardartoul 10
  • OverflowError: cannot convert float infinity to integer

    OverflowError: cannot convert float infinity to integer

    Ended up being caused by an empty file: -rw-rw-r-- 1 dan dan 0 Apr 4 20:30 stacks.mysql-64-oltp_read_only_1.2018-04-04 20:30:08-05:00

    Traceback (most recent call last):
      File "/home/dan/pyenv/lib/python2.7/site-packages/flask/app.py", line 1997, in __call__
        return self.wsgi_app(environ, start_response)
      File "/home/dan/pyenv/lib/python2.7/site-packages/flask/app.py", line 1985, in wsgi_app
        response = self.handle_exception(e)
      File "/home/dan/pyenv/lib/python2.7/site-packages/flask/app.py", line 1540, in handle_exception
        reraise(exc_type, exc_value, tb)
      File "/home/dan/pyenv/lib/python2.7/site-packages/flask/app.py", line 1982, in wsgi_app
        response = self.full_dispatch_request()
      File "/home/dan/pyenv/lib/python2.7/site-packages/flask/app.py", line 1614, in full_dispatch_request
        rv = self.handle_user_exception(e)
      File "/home/dan/pyenv/lib/python2.7/site-packages/flask/app.py", line 1517, in handle_user_exception
        reraise(exc_type, exc_value, tb)
      File "/home/dan/pyenv/lib/python2.7/site-packages/flask/app.py", line 1612, in full_dispatch_request
        rv = self.dispatch_request()
      File "/home/dan/pyenv/lib/python2.7/site-packages/flask/app.py", line 1598, in dispatch_request
        return self.view_functions[rule.endpoint](**req.view_args)
      File "/home/dan/flamescope/app/views/heatmap.py", line 34, in get_heatmap
        return jsonify(generate_heatmap(filename, rows))
      File "/home/dan/flamescope/app/util/heatmap.py", line 120, in generate_heatmap
        cols = int(ceil(end) - floor(start))
    OverflowError: cannot convert float infinity to integer
    
    		                                  
    		                                    bug invalid 
    	                                    
    opened by grooverdan 9
  • Remove invalid chars from the stack file in medium.com blog (was - README example).

    Remove invalid chars from the stack file in medium.com blog (was - README example).

    Hello and thanks for flamescope, In https://medium.com/netflix-techblog/netflix-flamescope-a57ca19d47bb and https://github.com/Netflix/flamescope/blob/master/README.md#installation--instructions the example filename used is stacks.myproductionapp.2018-03-30_01 , (UPDATE - the first dash on the medium site is a non ASCII char), as of https://github.com/Netflix/flamescope/commit/cbd13e187d913cc522c512ed4725a4bd79209078 for https://github.com/Netflix/flamescope/issues/7 this is now invalid and the heatmap generation fails with a 500 from app/util/heatmap.py::read_offsets when fileutil.validpath returns false. I was thinking that in addition to a change to the filename used in the example (UPDATE - on medium.com), that an error could be printed to the terminal, something like:

         if not fileutil.validpath(path):
    +        print("ERROR: File %s path %s is not valid" % (filename, path) )
             return abort(500)
    

    Thanks.

    Reproducer:

    > cp examples/perf.test01 examples/stacks.myproductionapp.2018-03-30_01 (copy-and-paste from blog on medium.com)
    > python run.py
    Click on link for the heatmap.
    

    Error in terminal is:

    [16/Apr/2018 07:38:09] "GET /heatmap/?filename=stacks.myproductionapp.2018%E2%80%9303%E2%80%9330_01&rows=50 HTTP/1.1" 500 -
    

    Error in the web app is a missing heatmap.

    documentation 
    opened by thatsafunnyname 6
  • perf flamegraphs: no tooltips

    perf flamegraphs: no tooltips

    flamescope used to show nice tooltips when hovering a stack frame. However now (commit 8eee5949c138c868895fa4db7982375f28b17cdf) there are no tooltips. Instead there are lots of error messages in the browser console:

    Uncaught TypeError: n.data.extras is undefined
        e http://HHHH.local:5000/main.js:43
        e http://HHHH.local:5000/main.js:43
        show http://HHHH.local:5000/main.js:43
        H http://HHHH.local:5000/main.js:11
        J http://HHHH.local:5000/main.js:11
    main.js:43:1021238
    
    bug javascript 
    opened by asheplyakov 5
  • flame graphs sometimes do not render correctly; uncaught exception

    flame graphs sometimes do not render correctly; uncaught exception

    Sometimes when I select ranges of time the flamegraph comes out broken (no text and not clickable). Looking at my console I see the following exception:

    Uncaught (in promise) TypeError: Cannot read property 'match' of undefined
        at main.js:17
        at F (main.js:17)
        at SVGRectElement.<anonymous> (main.js:17)
        at SVGRectElement.<anonymous> (main.js:1)
        at G.each (main.js:1)
        at G.attr (main.js:1)
        at HTMLDivElement.<anonymous> (main.js:17)
        at G.each (main.js:1)
        at T (main.js:17)
        at O (main.js:17)
    

    It appears to happen when I pick bigger time windows. Attached a stack file that you can drop into examples. Selecting the bottom left to top right pixels leads to a broken flame graph. Smaller selections can also trigger the issue.

    mesos-agent.stacks.1.zip

    Here's an example of what it looks like:

    image

    bug review 
    opened by bmahler 5
  • Enable Settings view for UI controls

    Enable Settings view for UI controls

    With more requests coming through for enhanced controls (#39 , #2 , #30 , ...), we should look at enabling the settings view or some other UI component and push some/all of the UI controls there that modify the view.

    enhancement review 
    opened by nhick 5
  • fix to allow to run the app on windows

    fix to allow to run the app on windows

    due to valid file path check regular expression, examples were not loading on windows. For windows path, it contains \ which is a part of valid path check in fileutils files.

    opened by koushiksaha89 5
  • Could not find a version that satisfies the requirement click==6.7 (from -r requirements.txt (line 1))

    Could not find a version that satisfies the requirement click==6.7 (from -r requirements.txt (line 1))

    When running pip install -r requirements.txt then I get the below error message:

    Could not find a version that satisfies the requirement click==6.7 (from -r requirements.txt (line 1)) (from versions: ) No matching distribution found for click==6.7 (from -r requirements.txt (line 1)) I am using Python 3.6.5. Also, when I then try to run python run.py then I get a error saying: ImportError: No module named flask.

    Thanks

    bug invalid 
    opened by i0na-k 5
  • ERROR: Bad range, 622353.26 -> 622351.26.

    ERROR: Bad range, 622353.26 -> 622351.26.

    Wondering if this could be less fatal. I'm assuming out of order or missed perf record elements.

    Got no output in browser with this error log:

    9.192.254.114 - - [04/Apr/2018 20:52:53] "GET /stack?filename=stacks.mysql-prep.2018-04-04%2020:49:33-05:00&start=18.26&end=16.26 HTTP/1.1" 301 -
    ERROR: Bad range, 622353.26 -> 622351.26.
    

    Decent file size:

    31235407 Apr  4 20:49 stacks.mysql-prep.2018-04-04 20:49:33-05:00
    

    Trying to look at data at 622353.26, 622351.26:

     grep  62235[13].26 stacks.mysql-prep.2018-04-04\ 20\:49\:33-05\:00
    mysqld 26608 [176] 622351.261861:  114686965 cycles:ppp:
    mysqld 26652 [116] 622351.262978:  114685776 cycles:ppp:
    mysqld 26060 [092] 622351.265249:  114685758 cycles:ppp:
    mysqld 26502 [176] 622353.262046:  114692803 cycles:ppp:
    mysqld 25987 [116] 622353.263136:  114683275 cycles:ppp:
    mysqld 26751 [092] 622353.265415:  114686145 cycles:ppp:
    swapper     0 [088] 622353.265751:  260814858 cycles:ppp:
    
     sudo perf script --debug-mode -i perf-prep.data --header > "stacks.mysql-prep.`date --rfc-3339=seconds`"
    Misordered timestamps: 0
    
    This generated a header only:
    # ========
    # captured on: Wed Apr  4 20:48:53 2018
    # hostname : bobby
    # os release : 4.13.0-37-generic
    # perf version : 4.15.0
    # arch : ppc64le
    # nrcpus online : 46
    # nrcpus avail : 184
    # cpudesc : POWER9, altivec supported
    # cpuid : 78,4609
    # total memory : 536032448 kB
    # cmdline : /usr/local/bin/perf record -F 20 --proc-map-timeout=50000 -o perf-prep.data -a -g -- sleep 30
    # event : name = cycles:ppp, , size = 112, { sample_period, sample_freq } = 20, sample_type = IP|TID|TIME|CALLCHAIN|CPU|PERIOD, disabled = 1, inherit = 1, mmap = 1, comm = 1, fre
    q = 1, task = 1, precise_ip = 3, sample_id_all = 1, exclude_guest = 1, mmap2 = 1, comm_exec = 1
    # CPU_TOPOLOGY info available, use -I to display
    # pmu mappings: nest_mba1_imc = 9, nest_mba5_imc = 13, nest_phb1_imc = 22, nest_phb5_imc = 26, nest_nvlink0_imc = 18, breakpoint = 5, nest_powerbus0_imc = 27, nest_mba2_imc = 10,
     nest_nx_imc = 20, nest_mba6_imc = 14, nest_phb2_imc = 23, cpu = 4, nest_nvlink1_imc = 19, nest_mcs01_imc = 16, software = 1, thread_imc = 28, nest_mba3_imc = 11, nest_mba7_imc =
     15, nest_phb3_imc = 24, nest_capp0_imc = 6, nest_xlink1_imc = 29, nest_mcs23_imc = 17, nest_mba0_imc = 8, nest_mba4_imc = 12, nest_phb0_imc = 21, tracepoint = 2, nest_phb4_imc =
     25, nest_xlink2_imc = 30, core_imc = 7
    # missing features: TRACING_DATA NUMA_TOPOLOGY BRANCH_STACK GROUP_DESC AUXTRACE STAT CACHE
    # ========
    #
    
    bug 
    opened by grooverdan 5
  •     ImportError: cannot import name 'Feature' from 'setuptools'

    ImportError: cannot import name 'Feature' from 'setuptools'

    ERROR: Command errored out with exit status 1:
     command: /Users/fwy/env/ksdb/bin/python -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/private/var/folders/p3/88pf4865713bvhx1g0qq07980000gn/T/pip-install-n_c6hrko/markupsafe_f7a88688051645a9b3bb18103afea1ba/setup.py'"'"'; __file__='"'"'/private/var/folders/p3/88pf4865713bvhx1g0qq07980000gn/T/pip-install-n_c6hrko/markupsafe_f7a88688051645a9b3bb18103afea1ba/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' egg_info --egg-base /private/var/folders/p3/88pf4865713bvhx1g0qq07980000gn/T/pip-pip-egg-info-mabo4a6b
         cwd: /private/var/folders/p3/88pf4865713bvhx1g0qq07980000gn/T/pip-install-n_c6hrko/markupsafe_f7a88688051645a9b3bb18103afea1ba/
    Complete output (5 lines):
    Traceback (most recent call last):
      File "<string>", line 1, in <module>
      File "/private/var/folders/p3/88pf4865713bvhx1g0qq07980000gn/T/pip-install-n_c6hrko/markupsafe_f7a88688051645a9b3bb18103afea1ba/setup.py", line 6, in <module>
        from setuptools import setup, Extension, Feature
    ImportError: cannot import name 'Feature' from 'setuptools' (/Users/fwy/env/ksdb/lib/python3.8/site-packages/setuptools/__init__.py)
    ----------------------------------------
    

    ERROR: Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.

    review python 
    opened by fengweiyuan 4
  • Add y-axis label markers to help people understand the visualisation

    Add y-axis label markers to help people understand the visualisation

    I'm trying to popularise these visualisations for mobile development, but common feedback I get is that people aren't sure what they're looking at.

    I think adding axis labels would help.

    Just something like +100ms, +200ms, along the left side of the vis, would help I think to make it clear that the cells represent subsecond slices.

    image (9)

    What do you think? We could possibly work on this. Wondering if you think this would be a reasonable addition.

    opened by mhansen 2
  • No pre-built client bundle in the master branch

    No pre-built client bundle in the master branch

    In the README.md it is stated that "A pre-built client bundle is distributed with the backend" but there is none: https://github.com/Netflix/flamescope/tree/master/app/public folder contains only favicon. I see that in the artifacts that are available for tag v0.2.0 (https://github.com/Netflix/flamescope/releases/tag/v0.2.0) the same folder contains an actual client but that version is quite old. It would be nice to see the client in the master branch so that I don't have to install Node.js and build the client from source.

    review 
    opened by wndrws 4
  • more caching in parsed events

    more caching in parsed events

    Large files require reprocessing once served, adding a way to cache the heatmap module is a big time saver, e.g. trace_event/heatmap can store the genreated namedtuple into a JSON so when called again the existing JSON is just loaded; tried this with a 10GB file, response went down from 2 minutes to 10 seconds. This plus a larger response.cache_control.max_age when responding can reduce greatly the loading time of previously parsed events not to say lowers the resource utilization in the service

    # draft on how this can be implemented
    def cpuprofile_read_offsets(file_path):
    ...
        offsets = []
        start_time = None
        end_time = None
        try:
            with open(f"{file_path}.json", "r") as f:
                offsets_collection = collections.namedtuple('offsets', ['start', 'end', 'offsets'])
                res = offsets_collection(**json.load(f))
                return res
        except Exception:
            pass
        ...
        # store the res into a JSON somewehere before returning res
        try:
            with open(f"{file_path}.json", "w+") as f:
                json.dump(res._asdict(), f)
        except Exception:
            pass
        return res
    
    enhancement review 
    opened by ramonf-garcia 0
  • support node.stack in nflxprofile format

    support node.stack in nflxprofile format

    This patch adds support for node.stack in nflxprofile.

    The nflxprofile format supports attaching a list of stack frames to a node. As far as I can tell, this is currently ignored by flamescope, which expects one node per stack frame.

    This patch will use the node.stack if present, and otherwise fall back to the node-level value.

    A sample profile is attached (needs to be gunzipped to work).

    test.nflxprofile.gz

    opened by igorwwwwwwwwwwwwwwwwwwww 1
  • add an upload endpoint

    add an upload endpoint

    Thanks for this great project. It would come handy having an upload endpoint, I forked the project and added one based on the base flask example but my react skills are close to none so I don't find it worth of a pull request, so, what about including one? I'm thinking on the scenario when we profile a remote host and want to upload the results directly to our application running in our workstation.

    enhancement 
    opened by ramonf-garcia 2
Owner
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Netflix Open Source Platform
Netflix, Inc.
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