Logstash vs Nagios: What are the differences?
What is Logstash? Collect, Parse, & Enrich Data. Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.
What is Nagios? 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.
Logstash belongs to "Log Management" category of the tech stack, while Nagios can be primarily classified under "Monitoring Tools".
Some of the features offered by Logstash are:
- Centralize data processing of all types
- Normalize varying schema and formats
- Quickly extend to custom log formats
On the other hand, Nagios provides the following key features:
- Monitor your entire IT infrastructure
- Spot problems before they occur
- Know immediately when problems arise
"Free" is the primary reason why developers consider Logstash over the competitors, whereas "It just works" was stated as the key factor in picking Nagios.
Logstash and Nagios are both open source tools. It seems that Logstash with 10.3K GitHub stars and 2.76K forks on GitHub has more adoption than Nagios with 60 GitHub stars and 36 GitHub forks.
reddit, Docplanner, and Harvest are some of the popular companies that use Logstash, whereas Nagios is used by Twitch, Vine Labs, and PedidosYa. Logstash has a broader approval, being mentioned in 551 company stacks & 270 developers stacks; compared to Nagios, which is listed in 176 company stacks and 39 developer stacks.
What is Logstash?
What is Nagios?
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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.