What is Nyagos and what are its top alternatives?
Top Alternatives to Nyagos
Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License. ...
A command-line shell and scripting language built on .NET. Helps system administrators and power-users rapidly automate tasks that manage operating systems (Linux, macOS, and Windows) and processes. ...
The Bourne Again SHell is an sh-compatible shell that incorporates useful features from the Korn shell (ksh) and C shell (csh). It is intended to conform to the IEEE POSIX P1003.2/ISO 9945.2 Shell and Tools standard. ...
Zsh (Z shell)
An interactive login shell, command interpreter and scripting language.
It provides a rich architecture for interactive computing with a powerful interactive shell, a kernel for Jupyter. It has a support for interactive data visualization and use of GUI toolkits. Flexible, embeddable interpreters to load into your own projects. Easy to use, high performance tools for parallel computing. ...
It is a useful utility filled shell which makes command line operations quicker with customized functions, easy to append path variable command, command history and more right out of the box. ...
It is a simple bash-like Unix shell written in Rust.
It comes with a set of built-in commands. If a command is unknown, the command will shell-out and execute it (using cmd on Windows or bash on Linux and MacOS), correctly passing through stdin, stdout and stderr, so things like your daily git workflows and even vim will work just fine. ...
Nyagos alternatives & related posts
related Nagios posts
Why we spent several years building an open source, large-scale metrics alerting system, M3, built for Prometheus:
By late 2014, all services, infrastructure, and servers at Uber emitted metrics to a Graphite stack that stored them using the Whisper file format in a sharded Carbon cluster. We used Grafana for dashboarding and Nagios for alerting, issuing Graphite threshold checks via source-controlled scripts. While this worked for a while, expanding the Carbon cluster required a manual resharding process and, due to lack of replication, any single node’s disk failure caused permanent loss of its associated metrics. In short, this solution was not able to meet our needs as the company continued to grow.
To ensure the scalability of Uber’s metrics backend, we decided to build out a system that provided fault tolerant metrics ingestion, storage, and querying as a managed platform...
(GitHub : https://github.com/m3db/m3)
related PowerShell posts
I currently work helpdesk and have been for about 6 years. I am looking to become more valuable, and I can't decide what route to take? Python is of interest, and so is PowerShell. What are some recommendations? Maybe something that would benefit a helpdesk position or even get into a network administrator.
Objective: I am trying to build a custom service that will create VMs in Azure, based on inputs taken from a web interface. I want the backend code that interacts with Azure to be PowerShell.
Ask: Hoping to find help with deciding the simplest architecture of tools to achieve this.
What I have so far with my Limited Knowledge: I am new to Azure and Jenkins. I arrived at Jenkins coz it can run PowerShell and has API that can be called to trigger a job. Although integrating with it over the web seems problematic since its on-prem network. I hear it is possible using the VPN. For the Web, I hope to use Azure Web App with Python/Node.js that I can manage to make API calls to Jenkins.
Is there a better way? I just need help getting the right directions; I will walk the way.
related GNU Bash posts
Recently I've switched from GNU Bash to Oh My ZSH and I'm happy with the way I can customize the environment, picking between options by tab and seeing git status or hardware status while typing commands and a beautiful UI that's easy on eyes. Also ability to turn-off case-sensitivity comes in handy. I don't think if I will go back!
related Zsh (Z shell) posts
related IPython posts
Jupyter Anaconda Pandas IPython
A great way to prototype your data analytic modules. The use of the package is simple and user-friendly and the migration from ipython to python is fairly simple: a lot of cleaning, but no more.
The negative aspect comes when you want to streamline your productive system or does CI with your anaconda environment: - most tools don't accept conda environments (as smoothly as pip requirements) - the conda environments (even with miniconda) have quite an overhead