automatron | Infrastructure monitoring framework turning DevOps runbooks | DevOps library
kandi X-RAY | automatron Summary
kandi X-RAY | automatron Summary
Automatron is a framework for creating self-healing infrastructure. Simply put, it detects system events & takes action to correct them. The goal of Automatron is to allow users to automate the execution of common tasks performed during system events. These tasks can be as simple as sending an email to as complicated as restarting services across multiple hosts.
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Top functions reviewed by kandi - BETA
- Start listening for notifications
- Schedule a run
- Subscribe to a channel
- Initialize connection
- Connect to the datastore
- Return the datastore connection
- Start the discovery process
- Get a logger
- Remove handlers from a logger
- Return the config object
- Load config file
- Get command line options
- Add new targets to the queue
- Remove a target
- Get a target by host name or IP
- Execute the fabric
- Set environment variables
- Apply runbooks to the target config
- Render a runbook
- Shutdown the server
- Return a datastore
- Get a logger instance
- Load and cache all runbooks
- Kill processes
- Grab an IP address from the discovery queue
automatron Key Features
automatron Examples and Code Snippets
Community Discussions
Trending Discussions on automatron
QUESTION
In my code for devtool.js I am listening to one-time messages like this:
...ANSWER
Answered 2017-Feb-01 at 15:25In documentation is not directly noted, that it is not possible to receive one-time messages in a devtools panel, however there is only long-lived connection mentioned so I suppose that one-time messaging is not supported for devtools.
It seems that sending one-time messages is possible, as shown in the script above, but not receiving.
We can only use long-lived connection:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install automatron
You can use automatron like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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