Nagios vs Vulcan: What are the differences?
Developers describe Nagios as "Complete monitoring and alerting for servers, switches, applications, and services". Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License. On the other hand, Vulcan is detailed as "DigitalOcean's API-compatible alternative to Prometheus". Vulcan is an API-compatible alternative to Prometheus. It aims to provide a better story for long-term storage, data durability, high cardinality metrics, high availability, and scalability. Vulcan is much more complex to operate, but should integrate with ease to an existing Prometheus environment.
Nagios and Vulcan can be primarily classified as "Monitoring" tools.
Nagios and Vulcan are both open source tools. Vulcan with 542 GitHub stars and 32 forks on GitHub appears to be more popular than Nagios with 60 GitHub stars and 36 GitHub forks.
What is Nagios?
What is Vulcan?
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Why do developers choose Vulcan?
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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)
We use Nagios to monitor our stack and alert us when problems arise. Nagios allows us to monitor every aspect of each of our servers such as running processes, CPU usage, disk usage, and more. This means that as soon as problems arise, we can detect them and call out an engineer to resolve the issues as soon as possible.
We use Nagios to monitor customer instances of Bridge and proactively alert us about issues like queue sizes, downed services, errors in logs, etc.
We use nagios based OpsView to monitor our server farm and keep everything running smoothly.