Logstash vs. Nagios Core

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Logstash
Score 7.6 out of 10
N/A
N/AN/A
Nagios Core
Score 7.3 out of 10
N/A
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.N/A
Pricing
LogstashNagios Core
Editions & Modules
No answers on this topic
Single License
Free
Single License
Free
Offerings
Pricing Offerings
LogstashNagios Core
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Best Alternatives
LogstashNagios Core
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SolarWinds Papertrail
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Score 8.8 out of 10
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Score 8.9 out of 10
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SolarWinds Papertrail
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Score 8.8 out of 10
IBM Instana
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Splunk Log Observer
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IBM Instana
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Score 9.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
LogstashNagios Core
Likelihood to Recommend
10.0
(3 ratings)
7.7
(42 ratings)
Likelihood to Renew
-
(0 ratings)
9.9
(3 ratings)
Usability
-
(0 ratings)
4.0
(1 ratings)
Support Rating
-
(0 ratings)
7.7
(9 ratings)
User Testimonials
LogstashNagios Core
Likelihood to Recommend
Elastic
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).
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Nagios Enterprises
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.
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Pros
Elastic
  • 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.
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Nagios Enterprises
  • Monitoring of services is one of the biggest benefits for our company. Being able to respond in a timely fashion keeps business smooth.
  • Hardware and device monitoring are easy to set up with proper parameters.
  • Notification to key staff to be able to respond quickly makes issues go away faster.
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Cons
Elastic
  • Since it's a Java product, JVM tuning must be done for handling high-load.
  • The persistent queue feature is nice, but I feel like most companies would want to use Kafka as a general storage location for persistent messages for all consumers to use. Using some pipeline of "Kafka input -> filter plugins -> Kafka output" seems like a good solution for data enrichment without needing to maintain a custom Kafka consumer to accomplish a similar feature.
  • I would like to see more documentation around creating a distributed Logstash cluster because I imagine for high ingestion use cases, that would be necessary.
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Nagios Enterprises
  • 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.
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Likelihood to Renew
Elastic
No answers on this topic
Nagios Enterprises
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.
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Usability
Elastic
No answers on this topic
Nagios Enterprises
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.
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Support Rating
Elastic
No answers on this topic
Nagios Enterprises
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.
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Alternatives Considered
Elastic
MongoDB and Azure SQL Database are just that: Databases, and they allow you to pipe data into a database, which means that alot of the log filtering becomes a simple exercise of querying information from a DBMS. However, LogStash was chosen for it's ease of integration into our choice of using ELK Elasticsearch is an obvious inclusion: Using Logstash with it's native DevOps stack its really rational
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Nagios Enterprises
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].
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Return on Investment
Elastic
  • Positive: Learning curve was relatively easy for our team. We were up and running within a sprint.
  • Positive: Managing Logstash has generally been easy. We configure it, and usually, don't have to worry about misbehavior.
  • Negative: Updating/Rehydrating Logstash servers have been little challenging. We sometimes even loose data while Logstash is down. It requires more in-depth research and experiments to figure the fine-grained details.
  • Negative: This is now one more application/skill/server to manage. Like any other servers, it requires proper grooming or else you will get in trouble. This is also a single point of failure which can have the ability to make other servers useless if it is not running.
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Nagios Enterprises
  • 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.
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