weave-into-mesos | Integrating Weave with Mesos | Job Orchestrator library

by TrentBrown Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | weave-into-mesos Summary

weave-into-mesos is a Python library typically used in Data Processing, Job Orchestrator applications. weave-into-mesos has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

This project defines a configurable command-line tool that installs [Weave] into an existing [Mesos] cluster as systemd services running on each slave node. When it grows up, it would like to be flexible enough to work with a variety of Mesos installations, but has been tested only against a [DCOS] Mesos cluster, so far. (Volunteers?).

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Support

weave-into-mesos has a low active ecosystem.

It has 4 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of weave-into-mesos is current.

Quality

weave-into-mesos has no bugs reported.

Security

weave-into-mesos has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

weave-into-mesos is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

weave-into-mesos releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed weave-into-mesos and discovered the below as its top functions. This is intended to give you an instant insight into weave-into-mesos implemented functionality, and help decide if they suit your requirements.

Install weave into Mesos slave
Adds the weave arguments to the parser .
Add Mesos arguments to the parser .
Parse a delimited string .
Substitute substitutions in a file .
Check if string is truthy

Get all kandi verified functions for this library.

weave-into-mesos Key Features

No Key Features are available at this moment for weave-into-mesos.

weave-into-mesos Examples and Code Snippets

No Code Snippets are available at this moment for weave-into-mesos.

Community Discussions

Trending Discussions on Job Orchestrator

Azure OPC Publisher says "no job received" when trying to write OPC UA data to cloud

QUESTION

Azure OPC Publisher says "no job received" when trying to write OPC UA data to cloud

Asked 2020-May-24 at 13:58

im trying to follow those tutorials:

https://sandervandevelde.wordpress.com/2018/11/06/getting-started-with-opc-ua-on-azure-iot-edge/ and https://docs.microsoft.com/en-us/azure/iot-accelerators/howto-opc-publisher-run

to bring data from an opc-ua server to the azure cloud.

I have already successfully played through the https://docs.microsoft.com/en-us/azure/iot-edge/quickstart tutorial.

I think maybe the OPCPublisher does not find the configuration file?!

I set up the configuration file under C:\iiotedge\pn.json (with changed ip):

...

ANSWER

Answered 2020-May-24 at 13:58

Was facing the same issue. It looks like the container is not running in appdata but in app. I've changed the createOptions to:

Source https://stackoverflow.com/questions/61938039

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install weave-into-mesos

You can download it from GitHub.
You can use weave-into-mesos 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.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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