Icinga vs. Logstash

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Icinga
Score 9.0 out of 10
N/A
Icinga is an open source network monitoring platform. It includes automation, modularized integration packages, and prebuilt alerts and reporting capabilities.N/A
Logstash
Score 8.0 out of 10
N/A
N/AN/A
Pricing
IcingaLogstash
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
IcingaLogstash
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Best Alternatives
IcingaLogstash
Small Businesses
Auvik
Auvik
Score 7.9 out of 10
SolarWinds Papertrail
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Medium-sized Companies
Zabbix
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Score 8.9 out of 10
PRTG
PRTG
Score 8.9 out of 10
Enterprises
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Score 8.9 out of 10
PRTG
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Score 8.9 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IcingaLogstash
Likelihood to Recommend
9.1
(8 ratings)
10.0
(3 ratings)
Likelihood to Renew
9.0
(1 ratings)
-
(0 ratings)
Usability
9.0
(1 ratings)
-
(0 ratings)
User Testimonials
IcingaLogstash
Likelihood to Recommend
Icinga GmbH
Icinga is a world-class monitoring system. It can be used for most general monitoring situations. It is not a silver bullet, however, and there are instances where domain-specific monitoring systems are necessary. However, the output from those monitoring systems can be funneled into Icinga as a central monitoring and alerting system.
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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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Pros
Icinga GmbH
  • Advanced infrastructure analytics.
  • Live dashboards for real-time monitoring.
  • Instant notifications when an incident is detected.
  • Workflow automations for monitoring tasks.
  • Flexibility that makes it easy to scale and customize.
  • Efficient security tools for safe infrastructure monitoring.
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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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Cons
Icinga GmbH
  • Difficult, arcane configuration.
  • Very difficult to integrate into modern configuration management systems.
  • Hard to fit concepts like auto-scaling groups of ephemeral servers into Icinga's aging conception of servers as static entities.
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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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Likelihood to Renew
Icinga GmbH
Icinga is a solid solution which does everything it promises. It is backwards compatible with most Nagios instances, making the transition very easy. Once you get the hang of installing new plugins and editing configuration files expanding its monitoring capabilities are easy.
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Elastic
No answers on this topic
Usability
Icinga GmbH
There was a bit of learning curve but after understanding the concepts, it become so easy for us to use Icinga. The interface itself is intuitive allowing us to navigate through it with ease. There are available workflow automations for the recurring monitoring tasks that make our work even much simpler.
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Elastic
No answers on this topic
Alternatives Considered
Icinga GmbH
Icinga is better than Nagios because of its nicer user interface. New Relic can monitor CPU/memory and disk usage, but it's more of a performance and application troubleshooting tool rather than monitoring
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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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Return on Investment
Icinga GmbH
  • With one check you know which applications are faulty e.g. after an upgrade. Which is big time saver
  • You easily detect outages ion the applications so that your customer ideally does not even realize there was an outage.
  • Detect if the environment does deliver the same result as in the same time as before to detect shortages.
  • Additional information when debugging. Saved us several hours where we could simply point to a database which was slow.
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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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