This repo contains code to compute and present critical path summary from Jaeger microservice traces.
To use first collect the microservice traces of a specific endpoint in a directory (say traces).
Let the traces be for OP operation and SVC service (these are Jaeger termonologies).
python3 process.py --operationName OP --serviceName SVC -t <path to trace> -o . --parallelism 8 will produce the critical path summary using 8 concurrent processes.
The summary will be output in the current directory as an HTML file with a heatmap, flamegraph, and summary text in criticalPaths.html.
It will also produce three flamegraphs flame-graph-*.svg for three different percentile values.
The script accepts the following options:
python3 process.py --help
usage: process.py [-h] -a OPERATIONNAME -s SERVICENAME [-t TRACEDIR] [--file FILE] -o OUTPUTDIR
[--parallelism PARALLELISM] [--topN TOPN] [--numTrace NUMTRACE] [--numOperation NUMOPERATION]
optional arguments:
-h, --help show this help message and exit
-a OPERATIONNAME, --operationName OPERATIONNAME
operation name
-s SERVICENAME, --serviceName SERVICENAME
name of the service
-t TRACEDIR, --traceDir TRACEDIR
path of the trace directory (mutually exclusive with --file)
--file FILE input path of the trace file (mutually exclusivbe with --traceDir)
-o OUTPUTDIR, --outputDir OUTPUTDIR
directory where output will be produced
--parallelism PARALLELISM
number of concurrent python processes.
--topN TOPN number of services to show in the summary
--numTrace NUMTRACE number of traces to show in the heatmap
--numOperation NUMOPERATION
number of operations to show in the heatmap
- We released the artifact of the original CRISP paper at https://zenodo.org/records/13956078.
- We released 1.5 Million production traces along with our paper The Tale of Errors in Microservices at https://zenodo.org/records/13947828.
Please cite our paper if you use the dataset in your research.