dagu

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A just another Cron alternative with a Web UI, but with much more capabilities
It runs DAGs (Directed acyclic graph) defined in a simple YAML format.

Highlights

• Install by placing just a single binary file
• Schedule executions of DAGs with Cron expressions
• Define dependencies between related jobs and represent them as a single DAG (unit of execution)

Contents

• Highlights
• Contents
• Getting started
• Motivation
• Why not existing workflow schedulers, such as Airflow?
• How does it work?
• Install dagu
  • via Homebrew
  • via Bash script
  • via GitHub Release Page
• ️Quick start
  • 1. Launch the Web UI
  • 2. Create a new DAG
  • 3. Edit the DAG
  • 4. Execute the DAG
• Command Line User Interface
• Web User Interface
• YAML format
  • Minimal Definition
  • Code Snippet
  • Environment Variables
  • Parameters
  • Command Substitution
  • Conditional Logic
  • Output
  • Redirection
  • Lifecycle Hooks
  • Repeating Task
  • Calling Sub DAGs
  • All Available Fields
• Admin Configuration
• Environment Variable
• Base Configuration for all DAGs
• Scheduler
  • Execution Schedule
  • Run Scheduler as a daemon
  • Scheduler Configuration
• REST API Interface
• FAQ
  • How to contribute?
  • Where is the history data stored?
  • Where are the log files stored?
  • How long will the history data be stored?
  • How to use specific host and port for dagu server?
  • How to specify the DAGs directory for dagu server and dagu scheduler?
  • How can I retry a DAG from a specific task?
  • How does it track running processes without DBMS?
• License
• Contributors

Getting started

See Install dagu and ️Quick start.

Motivation

In the projects I worked on, our ETL pipeline had many problems. There were hundreds of cron jobs on the server's crontab, and it is impossible to keep track of those dependencies between them. If one job failed, we were not sure which to rerun. We also have to SSH into the server to see the logs and run each shell script one by one. So we needed a tool that could explicitly visualize and manage the dependencies of the pipeline. How nice it would be to be able to visually see the job dependencies, execution status, and logs of each job in a Web UI and to be able to rerun or stop a series of jobs with just a mouse click!

Why not existing workflow schedulers, such as Airflow?

There are existing tools such as Airflow, Prefect, Temporal, etc, but in most cases they require writing code in a programming language such as Python to define DAGs. In systems that have been in operation for a long time, there are already complex jobs written in hundreds of thousands of lines of code in other languages such as Perl or Shell Scripts, and there is concern that adding another layer of Python code will further decrease maintainability. So we developed Dagu, which requires no coding, and is easy-to-use and self-contained, making it ideal for smaller projects with fewer people.

How does it work?

Dagu is a single command and it uses the local file system to store data. Therefore, no DBMS or cloud service is required. Dagu executes DAGs defined in declarative YAML format. Existing programs can be used without any modification.

Install dagu

You can quickly install dagu command and try it out.

via Homebrew

brew install yohamta/tap/dagu

Upgrade to the latest version:

brew upgrade yohamta/tap/dagu

via Bash script

curl -L https://raw.githubusercontent.com/yohamta/dagu/main/scripts/downloader.sh | bash

via GitHub Release Page

Download the latest binary from the Releases page and place it in your $PATH (e.g. /usr/local/bin).

️Quick start

1. Launch the Web UI

Start the server with dagu server and browse to http://127.0.0.1:8080 to explore the Web UI.

2. Create a new DAG

Create a DAG by clicking the New DAG button on the top page of the web UI. Input example in the dialog.

Note: DAG (YAML) files will be placed in ~/.dagu/dags by default. See Admin Configuration for more details.

3. Edit the DAG

Go to the SPEC Tab and hit the Edit button. Copy & Paste this example YAML and click the Save button.

4. Execute the DAG

You can execute the example by pressing the Start button

Command Line User Interface

• dagu start [--params=<params>] <file> - Runs the DAG
• dagu status <file> - Displays the current status of the DAG
• dagu retry --req=<request-id> <file> - Re-runs the specified DAG run
• dagu stop <file> - Stops the DAG execution by sending TERM signals
• dagu dry [--params=<params>] <file> - Dry-runs the DAG
• dagu server [--host=<host>] [--port=<port>] [--dags=<path/to/the DAGs directory>] - Starts the web server for web UI
• dagu scheduler [--dags=<path/to/the DAGs directory>] - Starts the scheduler process
• dagu version - Shows the current binary version

The --config=<config> option is available to all commands. It allows to specify different Dagu configuration for the commands. Which enables you to manage multiple Dagu process in a single instance. See Admin Configuration for more details.

For example:

dagu server --config=~/.dagu/dev.yaml
dagu scheduler --config=~/.dagu/dev.yaml

Web User Interface

• DAGs: It shows all DAGs and the real-time status.

  

• DAG Details: It shows the real-time status, logs, and DAG configurations. You can edit DAG configurations on a browser.

  

  You can switch to the vertical graph with the button on the top right corner.

  

• Execution History: It shows past execution results and logs.

  

• DAG Execution Log: It shows the detail log and standard output of each execution and step.

  

YAML format

Minimal Definition

The minimal DAG definition is as simple as follows:

steps:
  - name: step 1
    command: echo hello
  - name: step 2
    command: echo world
    depends:
      - step 1

Code Snippet

script field provides a way to run arbitrary snippets of code in any language.

steps:
  - name: step 1
    command: "bash"
    script: |
      cd /tmp
      echo "hello world" > hello
      cat hello
    output: RESULT
  - name: step 2
    command: echo ${RESULT} # hello world
    depends:
      - step 1

Environment Variables

You can define environment variables and refer to using env field.

env:
  - SOME_DIR: ${HOME}/batch
  - SOME_FILE: ${SOME_DIR}/some_file 
steps:
  - name: some task in some dir
    dir: ${SOME_DIR}
    command: python main.py ${SOME_FILE}

Parameters

You can define parameters using params field and refer to each parameter as $1, $2, etc. Parameters can also be command substitutions or environment variables. It can be overridden by --params= parameter of start command.

params: param1 param2
steps:
  - name: some task with parameters
    command: python main.py $1 $2

Named parameters are also available as follows:

params: ONE=1 TWO=`echo 2`
steps:
  - name: some task with parameters
    command: python main.py $ONE $TWO

Command Substitution

You can use command substitution in field values. I.e., a string enclosed in backquotes (`) is evaluated as a command and replaced with the result of standard output.

env:
  TODAY: "`date '+%Y%m%d'`"
steps:
  - name: hello
    command: "echo hello, today is ${TODAY}"

Conditional Logic

Sometimes you have parts of a DAG that you only want to run under certain conditions. You can use the precondition field to add conditional branches to your DAG.

For example, the below task only runs on the first date of each month.

steps:
  - name: A monthly task
    command: monthly.sh
    preconditions:
      - condition: "`date '+%d'`"
        expected: "01"

If you want the DAG to continue to the next step regardless of the step's conditional check result, you can use the continueOn field:

steps:
  - name: A monthly task
    command: monthly.sh
    preconditions:
      - condition: "`date '+%d'`"
        expected: "01"
    continueOn:
      skipped: true

Output

output field can be used to set a environment variable with standard output. Leading and trailing space will be trimmed automatically. The environment variables can be used in subsequent steps.

steps:
  - name: step 1
    command: "echo foo"
    output: FOO # will contain "foo"

Redirection

stdout field can be used to write standard output to a file.

steps:
  - name: create a file
    command: "echo hello"
    stdout: "/tmp/hello" # the content will be "hello\n"

Lifecycle Hooks

It is often desirable to take action when a specific event happens, for example, when a DAG fails. To achieve this, you can use handlerOn fields.

handlerOn:
  failure:
    command: notify_error.sh
  exit:
    command: cleanup.sh
steps:
  - name: A task
    command: main.sh

Repeating Task

If you want a task to repeat execution at regular intervals, you can use the repeatPolicy field. If you want to stop the repeating task, you can use the stop command to gracefully stop the task.

steps:
  - name: A task
    command: main.sh
    repeatPolicy:
      repeat: true
      intervalSec: 60

Calling Sub DAGs

You can call other DAGs in the same directory by using dagu start command (you can omit .yaml).

steps:
  - name: Sub DAG
    command: dagu start other_dag

If you want to call DAGs in other directory you can specify the DAG by absolute path.

steps:
  - name: Sub DAG
    command: dagu start /path/to/dag.yaml

All Available Fields

Combining these settings gives you granular control over how the DAG runs.

name: all configuration              # Name (optional, default is filename)
description: run a DAG               # Description
schedule: "0 * * * *"                # Execution schedule (cron expression)
group: DailyJobs                     # Group name to organize DAGs (optional)
tags: example                        # Free tags (separated by comma)
env:                                 # Environment variables
  - LOG_DIR: ${HOME}/logs
  - PATH: /usr/local/bin:${PATH}
logDir: ${LOG_DIR}                   # Log directory to write standard output, default: ${DAG_HOME}/logs/dags
histRetentionDays: 3                 # Execution history retention days (not for log files)
delaySec: 1                          # Interval seconds between steps
maxActiveRuns: 1                     # Max parallel number of running step
params: param1 param2                # Default parameters that can be referred to by $1, $2, ...
preconditions:                       # Precondisions for whether the it is allowed to run
  - condition: "`echo $2`"           # Command or variables to evaluate
    expected: "param2"               # Expected value for the condition
mailOn:
  failure: true                      # Send a mail when the it failed
  success: true                      # Send a mail when the it finished
MaxCleanUpTimeSec: 300               # The maximum amount of time to wait after sending a TERM signal to running steps before killing them
handlerOn:                           # Handlers on Success, Failure, Cancel, and Exit
  success:
    command: "echo succeed"          # Command to execute when the execution succeed
  failure:
    command: "echo failed"           # Command to execute when the execution failed
  cancel:
    command: "echo canceled"         # Command to execute when the execution canceled
  exit:
    command: "echo finished"         # Command to execute when the execution finished
steps:
  - name: some task                  # Step name
    description: some task           # Step description
    dir: ${HOME}/logs                # Working directory (default: the same directory of the DAG file)
    command: bash                    # Command and parameters
    stdout: /tmp/outfile
    ouptut: RESULT_VARIABLE
    script: |
      echo "any script"
    signalOnStop: "SIGINT"           # Specify signal name (e.g. SIGINT) to be sent when process is stopped
    mailOn:
      failure: true                  # Send a mail when the step failed
      success: true                  # Send a mail when the step finished
    continueOn:
      failure: true                   # Continue to the next regardless of the step failed or not
      skipped: true                  # Continue to the next regardless the preconditions are met or not
    retryPolicy:                     # Retry policy for the step
      limit: 2                       # Retry up to 2 times when the step failed
      intervalSec: 5                 # Interval time before retry
    repeatPolicy:                    # Repeat policy for the step
      repeat: true                   # Boolean whether to repeat this step
      intervalSec: 60                # Interval time to repeat the step in seconds
    preconditions:                   # Precondisions for whether the step is allowed to run
      - condition: "`echo $1`"       # Command or variables to evaluate
        expected: "param1"           # Expected Value for the condition

The global configuration file ~/.dagu/config.yaml is useful to gather common settings, such as logDir or env.

Admin Configuration

To configure Dagu, please create the config file (default path: ~/.dagu/admin.yaml). All fields are optional.

# Web Server Host and Port
host: <hostname for web UI address>                          # default: 127.0.0.1
port: <port number for web UI address>                       # default: 8000

# path to the DAGs directory
dags: <the location of DAG configuration files>              # default: ${DAG_HOME}/dags

# Web UI Color & Title
navbarColor: <admin-web header color>                        # header color for web UI (e.g. "#ff0000")
navbarTitle: <admin-web title text>                          # header title for web UI (e.g. "PROD")

# Basic Auth
isBasicAuth: <true|false>                                    # enables basic auth
basicAuthUsername: <username for basic auth of web UI>       # basic auth user
basicAuthPassword: <password for basic auth of web UI>       # basic auth password

# Base Config
baseConfig: <base DAG config path> .                         # default: ${DAG_HOME}/config.yaml

# Others
logDir: <internal logdirectory>                              # default: ${DAG_HOME}/logs/admin
command: <Absolute path to the dagu binary>                  # default: dagu

Environment Variable

You can configure the Dagu's internal work directory by defining DAGU_HOME environment variables. Default path is ~/.dagu/.

Base Configuration for all DAGs

Creating a base configuration (default path: ~/.dagu/config.yaml) is a convenient way to organize shared settings among all DAGs. The path to the base configuration file can be configured. See Admin Configuration for more details.

logDir: <path-to-write-log>         # log directory to write standard output
histRetentionDays: 3                # history retention days
smtp:                               # [optional] mail server configuration to send notifications
  host: <smtp server host>
  port: <stmp server port>
errorMail:                          # [optional] mail configuration for error-level
  from: <from address>
  to: <to address>
  prefix: <prefix of mail subject>
infoMail:
  from: <from address>              # [optional] mail configuration for info-level
  to: <to address>
  prefix: <prefix of mail subject>

Scheduler

To run DAGs automatically, you need to run dagu scheduler process on your system.

Execution Schedule

You can specify the schedule with cron expression in the schedule field in the config file as follows:

schedule: "5 4 * * *" # Run at 04:05.
steps:
  - name: scheduled job
    command: job.sh

Or you can set multiple schedules:

schedule:
  - "30 7 * * *" # Run at 7:30
  - "0 20 * * *" # Also run at 20:00
steps:
  - name: scheduled job
    command: job.sh

Run Scheduler as a daemon

The easiest way to make sure the process is always running on your system is to create the script below and execute it every minute using cron (you don't need root account in this way):

#!/bin/bash
process="dagu scheduler"
command="/usr/bin/dagu scheduler"

if ps ax | grep -v grep | grep "$process" > /dev/null
then
    exit
else
    $command &
fi

exit

Scheduler Configuration

Set the dags field to specify the directory of the DAGs.

dags: <the location of DAG configuration files> # default: (~/.dagu/dags)

REST API Interface

Please refer to REST API Docs

FAQ

How to contribute?

Feel free to contribute in any way you want. Share ideas, questions, submit issues, and create pull requests. Thanks!

Where is the history data stored?

It will store execution history data in the DAGU__DATA environment variable path. The default location is $HOME/.dagu/data.

Where are the log files stored?

It will store log files in the DAGU__LOGS environment variable path. The default location is $HOME/.dagu/logs. You can override the setting by the logDir field in a YAML file.

How long will the history data be stored?

The default retention period for execution history is 30 days. However, you can override the setting by the histRetentionDays field in a YAML file.

How to use specific host and port for dagu server?

dagu server's host and port can be configured in the admin configuration file as below. See Admin Configuration for more details.

host: <hostname for web UI address>                          # default: 127.0.0.1
port: <port number for web UI address>                       # default: 8000

How to specify the DAGs directory for dagu server and dagu scheduler?

You can customize DAGs directory that will be used by dagu server and dagu scheduler. See Admin Configuration for more details.

dags: <the location of DAG configuration files>              # default: ${DAG_HOME}/dags

How can I retry a DAG from a specific task?

You can change the status of any task to a failed state. Then, when you retry the DAG, it will execute the failed one and any subsequent.

How does it track running processes without DBMS?

Dagu uses Unix sockets to communicate with running processes.

License

This project is licensed under the GNU GPLv3 - see the LICENSE.md file for details

Contributors

Made with contrib.rocks.