mongo-x-ray 1.2.2

MongoDB diagnostics toolkit with health checks and log analysis

x-ray

This project aims to create tools for MongoDB analysis and diagnosis. So far 3 modules are being built:

• Health check module.
• Log analysis module.
• getMongoData visualization module (Under construction).

1 Compatibility Matrix

Health Check

Replica Set	Sharded Cluster	Standalone
>=4.2 ✓	>=4.2 ✓	✗

Older versions are not tested.

Log Analysis

Log analysis requires JSON format logs, which is supported since 4.4.

Replica Set	Sharded Cluster	Standalone
>=4.4 ✓	>=4.4 ✓	>=4.4 ✓

2 How to Install

2.1 PyPi

2.1.1 Install with Pip

The easiest and recommended way to install x-ray is to use pip:

pip install mongo-x-ray

2.1.2 Build from Source

git clone https://github.com/zhangyaoxing/x-ray
cd x-ray
pip install .

2.2 PyInstaller

2.2.1 Prebuilt Binaries

Currently the prebuilt binaries are available on 3 platforms:

• Ubuntu 22.04 (AMD64)
• MacOS 14 (ARM64)
• Windows 2022 (AMD64)

Download them from Releases.

2.2.2 Build from Source

x-ray is tested on Python 3.9.22. On MacOS or Linux distributions, you can use the make command to build the binary:

git clone https://github.com/zhangyaoxing/x-ray
cd x-ray
make deps # if it's the first time you build the project
make # equal to `make build` and `make build-lite`

There are other make targets. Use make help to find out.

You can also build the tool with AI modules for log analysis. For more details refer to: Build with AI Support.

For Windows users, if make command is not available. You can use Python commands to build the binary:

python.exe -m venv .venv
.venv\Scripts\python.exe -m pip install --upgrade pip
.venv\Scripts\python.exe -m pip install -e ".[dev]"
.venv\Scripts\python.exe -m PyInstaller --onefile `
  --name x-ray `
  --add-data="templates;templates" `
  --add-data="libs;libs" `
  --icon="misc/x-ray.ico" `
  --hidden-import=openai `
  x-ray

2.3 For Developers

For developers, use make deps to prepare venv and dependencies

make deps

Or

python3 -m venv .venv
python3 -m pip install --upgrade pip
python3 -m pip install -e ".[dev]"

3 Using the Tool

x-ray [-h] [-q] [-c CONFIG] {healthcheck,hc,log}

Argument	Description	Default
-q, --quiet	Quiet mode.	false
-h, --help	Show the help message and exit.	n/a
-c, --config	Path to configuration file.	Built-in libs/config.json
command	Command to run. Include: - healthcheck or hc: Health check. - log: Log analysis. - version: Show version info.	None

Besides, you can use environment variables to control some behaviors:

• ENV=development For developing. It will change the following behaviors:
  • Formatted the output JSON for for easier reading.
  • The output will not create a new folder for each run but overwrite the same files.
• LOG_LEVEL: Can be DEBUG, ERROR or INFO (default).

3.1 Health Check Component

3.1.1 Examples

./x-ray healthcheck localhost:27017 # Scan the cluster with default settings.
./x-ray hc localhost:27017 --output ./output/ # Specify output folder.
./x-ray hc localhost:27017 --config ./config.json # Use your own configuration.

3.1.2 Full Arguments

x-ray healthcheck [-h] [-s CHECKSET] [-o OUTPUT] [-f {markdown,html}] [uri]

Argument	Description	Default
-s, --checkset	Checkset to run.	default
-o, --output	Output folder path.	output/
-f, --format	Output format. Can be markdown or html.	html
uri	MongoDB database URI.	None

For security reasons you may not want to include credentials in the command. There are 2 options:

• If the URI is not provided, user will be asked to input one.
• If URI is provided but not username/password, user will also be asked to input them.

3.1.3 More Info

Refer to the wiki for more details.

• Customize the thresholds
• Database permissions
• Output
• Customize the output

3.2 Log Analysis Component

3.2.1 Examples

# Full analysis
./x-ray log mongodb.log
# For large logs, analyze a random 10% logs
./x-ray log -r 0.1 mongodb.log

3.2.2 Full Arguments

x-ray log [-h] [-s CHECKSET] [-o OUTPUT] [-f {markdown,html}] [log_file]

Argument	Description	Default
-s, --checkset	Checkset to run.	default
-o, --output	Output folder path.	output/
-f, --format	Output format. Can be markdown or html.	html
-r, --rate	Sample rate. Only analyze a subset of logs.	1
--top	When analyzing the slow queries, only list top N.	10