dcos-autoscaler | Autoscaler for DC/OS hosted in a cloud provider | Job Orchestrator library

by julienstroheker Python Version: master-v0.40 License: No License

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

kandi X-RAY | dcos-autoscaler Summary

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

Autoscaler for DC/OS hosted in a cloud provider

Support

Quality

Security

License

Reuse

Support

dcos-autoscaler has a low active ecosystem.

It has 12 star(s) with 3 fork(s). There are 5 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 1 have been closed. On average issues are closed in 1 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of dcos-autoscaler is master-v0.40

Quality

dcos-autoscaler has no bugs reported.

Security

dcos-autoscaler has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

dcos-autoscaler does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

dcos-autoscaler releases are available to install and integrate.

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

Calculate the health of the given metrics
Filter out the health of a health object
Get health cluster
Determines whether to scale to scale
Scale the cluster down
Wait for new status of the cluster
Scale cluster up
Scale up the VM
Creates a new virtual machine scale set
Returns the VMSS information
Scales the VS

Get all kandi verified functions for this library.

dcos-autoscaler Key Features

No Key Features are available at this moment for dcos-autoscaler.

dcos-autoscaler Examples and Code Snippets

No Code Snippets are available at this moment for dcos-autoscaler.

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 dcos-autoscaler

You can download it from GitHub.
You can use dcos-autoscaler 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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