Performance Analysis Tool (PAT) is a flexible performance profiling framework designed for Linux operating system. It gathers system level performance metrics including CPU, Disk and Network as well as detailed software hot methods. It generates a pdf and a Microsoft Excel file at the end to provide an instant visual representation of the data. PAT can be configured for a single machine, a subset of a cluster or an entire cluster of machines. User also can customize the metrics being collected. PAT can be used for workload characterization, performance study and software optimization.

Figure 1: CPU chart

Figure 2: Disk chart

Figure 3: Network chart

Figure 4: Perf module

• Python version 3.8 or higher
• Ansible version 2.11.0 or higher
• Ansible Galaxy role and collections

ansible-galaxy install zyluo.pat
ansible-galaxy collection install ansible.posix
ansible-galaxy collection install community.general

• Create playbook directory

mkdir PAT
cd PAT

• Configure PAT variables in site.yml playbook

---
- name: Monitor system performance and usage activity for all hosts
  hosts: all
  vars_files:
    - ~/.ansible/roles/zyluo.pat/vars/config.yml

  roles:
    - role: zyluo.pat
      vars:
        SAMPLE_RATE: 3
        INSTRUMENTS: "cpustat memstat"
        CMD_PATH: sleep 30

• List worker nodes in a inventory file. Find other parameters to customize your ssh connection in the official document

hostname01
hostname02
hostname03

[all:vars]
ansible_ssh_user=username
ansible_ssh_private_key_file=/path/to/private_key

• Run playbook

ansible-playbook -i inventory site.yml

• Once the job is done, all the data is collected and copied to the results directory, under the [JOB_ID] folder.

BSD 3-clause License

For questions regardng tool contact

• Olasoji Denloy at [email protected]
• Yingqi (Lucy) Lu at [email protected]
• Eric Kaczmarek at [email protected]
• Sammy Nah at [email protected]

• Collecting data phase is run completely on the server.
• In postprocess phase modular approach is being used to increase scalability.
• Each node in the cluster is mapped to a node object.
• The node object holds separate objects for each of the metrics (such as DISK, NETWORK, CPU, PERF) that were measured using PAT. These objects contain actual raw data in an internal data structure [Figure 5].
• Modules for DISK, NETWORK, CPU and PERF have been implemented.

Figure 5: PAT Post-Processing architecture

/usr/lib64/python2.7/site-packages/matplotlib/init.py:1005: UserWarning: This call to matplotlib.use() has no effect because the the backend has already been chosen; matplotlib.use() must be called before pylab, matplotlib.pyplot, or matplotlib.backends is imported for the first time.

pip install --upgrade numpy scipy matplotlib will upgrade Python libraries and solve the error

config.xml is the file where you make all postprocess configuration changes. Below instructions are dedicated to that file.

• Before you modify anything in configuration file, make sure your data are stored in directories (each data node in separate directory). Most likely your data are in a format of <hostname>:<port>
• Make changes in config.xml file that suit your needs. Between the tag <source></source> specify the path to the directory that contains PAT data. By default it is a directory where your <hostname>:<port> data are located (for most cases this will be an instruments directory in your PAT-RESULT folder. In this case the path will be of the form /foo/bar/instruments/).
• You may eliminate node(s) if you do not want to do any calculations on that node(s). To do that between the tag <exclude-node></exclude-node> specify the name of the node(s) that you want to discard. The exclude-node entry should match the value under 'hostname' in files within the node-name directory. This node will be excluded while computing averages across all nodes. Otherwise further actions are not required. If you wish to do calculations on all nodes then leave everything in default settings.
• You are also able to turn on or off detailed graphs and averaged graphs by modifying the config.xml file. By default only averaged graphs will be printed and excel file will contain all 4 metric outputs.
• During runtime a different config.xml file can be given as a command line argument to the pat-post-process script. It will override the default config.xml file.

• Postprocess data will be located at the same path that was entered in the tag <source></source>. Copy the entire results directory to a Windows machine, navigate to the instruments directory and then open the provided spreadsheet. In Excel 2010 and above press Ctrl+q to launch the macros that will import all the data, draw tables and plot graphs.
• Output can be customized by editing the config.xml file. The pdf and excel contains only the data specified in the config.xml file.
• The output consists of 2 files – a pdf file that gives a visual representation of data, and an excel file that contains RAW data along with macros to draw the relevant charts.