Nagios provides monitoring of all mission-critical infrastructure components. Multiple APIs and community-build add-ons enable integration and monitoring with in-house and third-party applications for optimized scaling.
Perfect for projects where Elasticsearch makes sense: if you decide to employ ES in a project, then you will almost inevitably use LogStash, and you should anyways. Such projects would include: 1. Data Science (reading, recording or measure web-based Analytics, Metrics) 2. Web Scraping (which was one of our earlier projects involving LogStash) 3. Syslog-ng Management: While I did point out that it can be a bit of an electric boo-ga-loo in finding an errant configuration item, it is still worth it to implement Syslog-ng management via LogStash: being able to fine-tune your log messages and then pipe them to other sources, depending on the data being read in, is incredibly powerful, and I would say is exemplar of what modern Computer Science looks like: Less Specialization in mathematics, and more specialization in storing and recording data (i.e. Less Engineering, and more Design).
Nagios monitoring is well suited for any mission critical application that requires per/second (or minute) monitoring. This would probably include even a shuttle launch. As Nagios was built around Linux, most (85%) plugins are Linux based, therefore its more suitable for a Linux environment.
As Nagios (and dependent components) requires complex configurations & compilations, an experienced Linux engineer would be needed to install all relevant components.
Any company that has hundreds (or thousands) of servers & services to monitor would require a stable monitoring solution like Nagios. I have seen Nagios used in extremely mediocre ways, but the core power lies when its fully configured with all remaining open-source components (i.e. MySQL, Grafana, NRDP etc). Nagios in the hands of an experienced Linux engineer can transform the organizations monitoring by taking preventative measures before a disaster strikes.
Logstash design is definitely perfect for the use case of ELK. Logstash has "drivers" using which it can inject from virtually any source. This takes the headache from source to implement those "drivers" to store data to ES.
Logstash is fast, very fast. As per my observance, you don't need more than 1 or 2 servers for even big size projects.
Data in different shape, size, and formats? No worries, Logstash can handle it. It lets you write simple rules to programmatically take decisions real-time on data.
You can change your data on the fly! This is the CORE power of Logstash. The concept is similar to Kafka streams, the difference being the source and destination are application and ES respectively.
Nagios could use core improvements in HA, though, Nagios itself recommends monitoring itself with just another Nagios installation, which has worked fine for us. Given its stability, and this work-around, a minor need.
Nagios could also use improvements, feature wise, to the web gui. There is a lot in Nagios XI which I felt were almost excluded intentionally from the core project. Given the core functionality, a minor need. We have moved admin facing alerts to appear as though they originate from a different service to make interacting with alerts more practical.
We're currently looking to combine a bunch of our network montioring solutions into a single platform. Running multiple unique solutions for monitoring, data collection, compliance reporting etc has become a lot to manage.
As I said earlier, for a production-grade OpenStack Telco cloud, Logstash brings high value in flexibility, compliance, and troubleshooting efficiency. However, this brings a higher infra & ops cost on resources, but that is not a problem in big datacenters because there is no resource crunch in terms of servers or CPU/RAM
The Nagios UI is in need of a complete overhaul. Nice graphics and trendy fonts are easy on the eyes, but the menu system is dated, the lack of built in graphing support is confusing, and the learning curve for a new user is too steep.
I haven't had to use support very often, but when I have, it has been effective in helping to accomplish our goals. Since Nagios has been very popular for a long time, there is also a very large user base from which to learn from and help you get your questions answered.
Logstash can be compared to other ETL frameworks or tools, but it is also complementary to several, for example, Kafka. I would not only suggest using Logstash when the rest of the ELK stack is available, but also for a self-hosted event collection pipeline for various searching systems such as Solr or Graylog, or even monitoring solutions built on top of Graphite or OpenTSDB.
Because we get all we required in Nagios [Core] and for npm, we have to do lots of configuration as it is not as easy as Comair to Nagios [Core]. On npm UI, there is lots of data, so we are not able to track exact data for analysis, which is why we use Nagios [Core].
Positive: LogStash is OpenSource. While this should not be directly construed as Free, it's a great start towards Free. OpenSource means that while it's free to download, there are no regular patch schedules, no support from a company, no engineer you can get on the phone / email to solve a problem. You are your own Engineer. You are your own Phone Call. You are your own ticketing system.
Negative: Since Logstash's features are so extensive, you will often find yourself saying "I can just solve this problem better going further down / up the Stack!". This is not a BAD quality, necessarily and it really only depends on what Your Project's Aim is.
Positive: LogStash is a dream to configure and run. A few hours of work, and you are on your way to collecting and shipping logs to their required addresses!
With it being a free tool, there is no cost associated with it, so it's very valuable to an organization to get something that is so great and widely used for free.
You can set up as many alerts as you want without incurring any fees.
