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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Nagios Core

    Score7.7 out of 10
    N/ANagios 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

    Optimizely Feature Experimentation

    Score8.4 out of 10
    N/AOptimizely Feature Experimentation unites feature flagging, A/B testing, and built-in collaboration—so marketers can release, experiment, and optimize with confidence in one platform.N/A
    Pricing
    Nagios CoreOptimizely Feature Experimentation
    Editions & Modules
    Single License
    Free
    No answers on this topic
    Offerings
    Pricing Offerings
    Nagios CoreOptimizely Feature Experimentation
    Free Trial
    YesNo
    Free/Freemium Version
    YesYes
    Premium Consulting/Integration Services
    YesYes
    Entry-level Setup FeeNo setup feeRequired
    Additional Details——
    More Pricing Information
    Community Pulse
    Nagios CoreOptimizely Feature Experimentation
    Considered Both Products
    Nagios Enterprises
    No answer on this topic
    Optimizely
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    13 Answers
    89%
    Would buy again
    41 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    13 Answers
    97%
    Delivers good value for the price
    33 Answers
    Happy with the feature set
    100%
    Happy with the feature set
    13 Answers
    91%
    Happy with the feature set
    42 Answers
    Lived up to sales and marketing promises
    91%
    Lived up to sales and marketing promises
    10 Answers
    88%
    Lived up to sales and marketing promises
    21 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    12 Answers
    80%
    Implementation went as expected
    28 Answers
    Best Alternatives
    Nagios CoreOptimizely Feature Experimentation
    Small Businesses
    No answers on this topic
    No answers on this topic
    Medium-sized Companies
    Icinga
    Score9 out of 10
    No answers on this topic
    Enterprises
    HPE OneView
    Score6 out of 10
    No answers on this topic
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Nagios CoreOptimizely Feature Experimentation
    Likelihood to Recommend
    8.5
    (44 ratings)
    8.2
    (47 ratings)
    Likelihood to Renew
    9.9
    (3 ratings)
    4.5
    (2 ratings)
    Usability
    4.0
    (1 ratings)
    7.6
    (26 ratings)
    Support Rating
    7.7
    (9 ratings)
    3.6
    (1 ratings)
    Implementation Rating
    -
    (0 ratings)
    10.0
    (1 ratings)
    Product Scalability
    -
    (0 ratings)
    5.0
    (1 ratings)
    User Testimonials
    Nagios CoreOptimizely Feature Experimentation
    Likelihood to Recommend
    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.
    Incentivized
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    Optimizely
    Based on my experience with Optimizely Feature Experimentation, I can highlight several scenarios where it excels and a few where it may be less suitable. Well-suited scenarios: - Multi-Channel product launches - Complex A/B testing and feature flag management - Gradual rollout and risk mitigation Less suited scenarios: - Simple A/B tests (their Web Experimentation product is probably better for that) - Non-technical team usage -
    Incentivized
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    Pros
    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.
    Incentivized
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    Optimizely
    • It is easy to use any of our product owners, marketers, developers can set up experiments and roll them out with some developer support. So the key thing there is this front end UI easy to use and maybe this will come later, but the new features such as Opal and the analytics or database centric engine is something we're interested in as well.
    Incentivized
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    Cons
    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.
    Incentivized
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    Optimizely
    • Would be nice to able to switch variants between say an MVT to a 50:50 if one of the variants is not performing very well quickly and effectively so can still use the standardised report
    • Interface can feel very bare bones/not very many graphs or visuals, which other providers have to make it a bit more engaging
    • Doesn't show easily what each variant that is live looks like, so can be hard to remember what is actually being shown in each test
    Incentivized
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    Likelihood to Renew
    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.
    Incentivized
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    Optimizely
    Competitive landscape
    Incentivized
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    Usability
    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.
    Incentivized
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    Optimizely
    Easy to navigate the UI. Once you know how to use it, it is very easy to run experiments. And when the experiment is setup, the SDK code variables are generated and available for developers to use immediately so they can quickly build the experiment code
    Incentivized
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    Support Rating
    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.
    Incentivized
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    Optimizely
    Support was there but it was pretty slow at most times. Only after escalation was support really given to our teams
    Incentivized
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    Implementation Rating
    Nagios Enterprises
    No answers on this topic
    Optimizely
    It’s straightforward. Docs are well written and I believe there must be a support. But we haven’t used it
    Incentivized
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    Alternatives Considered
    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].
    Read full review
    Optimizely
    When Google Optimize goes off we searched for a tool where you can be sure to get a good GA4 implementation and easy to use for IT team and product team. Optimizely Feature Experimentation seems to have a good balance between pricing and capabilities. If you are searching for an experimentation tool and personalization all in one... then maybe these comparison change and Optimizely turns to expensive. In the same way... if you want a server side solution. For us, it will be a challenge in the following years
    Incentivized
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    Scalability
    Nagios Enterprises
    No answers on this topic
    Optimizely
    had troubles with performance for SSR and the React SDK
    Incentivized
    Read full review
    Return on Investment
    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.
    Incentivized
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    Optimizely
    • We have improved various metrics throughout the course of our experimentation program with Optimizely and therefore sharing numbers is tricky. Essentially we only implement versions of the product that perform the best in terms of CVR, revenue/visitor, ATV, average order value, average basket size and so forth dependent on the north star we are trying to move with each release.
    Incentivized
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    ScreenShots

    Optimizely Feature Experimentation Screenshots

    Screenshot of Feature Flag Setup. Here users can run A/B and multi-armed bandit tests, as well as:

- Set up a single feature flag to test multiple variations and experiment types
- Enable targeted deliveries and rollouts for more precise experimentation
- Roll back changes quickly when needed to ensure experiment accuracy and reduce risks
- Increase testing flexibility with control over experiment types and delivery methodsScreenshot of Audience Setup. This is used to target specific user segments for personalized experiments, and:

- Create and customize audiences based on user attributes
- Refine audience segments to ensure the right users are included in tests
- Enhance experiment relevance by setting specific conditions for user groupsScreenshot of Experiment Results, supporting the analysis and optimization of experimentation outcomes. Viewers can also:

- examine detailed experiment results, including key metrics like conversion rates and statistical significance
- Compare variations side-by-side to identify winning treatments
- Use advanced filters to segment and drill down into specific audience or test dataScreenshot of A Program Overview. These offer insights into any experimentation program’s performance. It also offers:

- A comprehensive view of the entire experimentation program’s status and progress
- Monitoring for key performance metrics like test velocity, success rates, and overall impact
- Evaluation of the impact of experiments with easy-to-read visualizations and reporting tools
- Performance tracking of experiments over time to guide decision-making and optimize strategiesScreenshot of AI Variable Suggestions. These enhance experimentation with AI-driven insights, and can also help with:

- Generating multiple content variations with AI to speed up experiment design
- Improving test quality with content suggestions
- Increasing experimentation velocity and achieving better outcomes with AI-powered optimizationScreenshot of Schedule Changes, to streamline experimentation. Users can also:

- Set specific times to toggle flags or rules on/off, ensuring precise control
- Schedule traffic allocation percentages for smooth experiment rollouts
- Increase test velocity and confidence by automating progressive changes