

Find out in this report how the two Application Performance Monitoring (APM) and Observability solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
We are seeing a return on investment from using Gremlin Reliability Management Platform because we are getting less production issues by thirty percent, as I mentioned earlier, making it a great investment.
We do not need to look at all the day's metrics on Grafana dashboards; we run our chaos experiments in a production environment to see how reliable our product or service is.
If we needed ten people to do tests once upon a time, now, using Gremlin Reliability Management Platform, we can do it with a fifty percent reduction in employees.
Honeycomb Enterprise played a vital role in identifying the problems in the initial calls itself. That has actually saved us a lot of incidents.
The biggest return on investment with Honeycomb Enterprise is being able to find, if I am doing production support and something goes wrong, the exact scenario or the exact request and response and the details of that really quickly.
When I have questions or run into issues with Gremlin Reliability Management Platform, their support team is helpful and responsive.
The expert partnership model is a significant strength I can suggest for Gremlin Reliability Management Platform.
The customer support for Gremlin Reliability Management Platform is good overall.
To highlight what is the issue going on in our currently running 100 requests, we just highlight that one request which is very slow or maybe we just move it to the top so that we can alert everybody that this is the problem.
When I was looking at Honeycomb Enterprise support with Go Lambdas, it was a little tricky to find someone who could help me answer the question.
Gremlin Reliability Management Platform scales smoothly for running more chaos experiments, adding more services, or supporting a larger team.
Gremlin Reliability Management Platform's workload management capability is good, effectively managing large workloads seamlessly while providing safety mechanisms and governance around chaos engineering.
More than scalability, I thought about availability because it is a really important thing of the architecture tools.
When you send traces, you will get the complete view of the life of the code and how it has been executed.
Honeycomb Enterprise scales best when all the products in the company use it because it allows tracing outside of individual products to see how they interact.
At times we can be shocked to see that this price is too high for involving too many developers on one peak or having a much bigger data set or more advanced features for our use.
I have not seen any downtime or issues with its behavior or performance.
They could not get proper tracing with Honeycomb Enterprise at that time.
In terms of stability and availability, this is an impressive one.
Mostly it is reliable, but at times, maybe one or two times in two to three months, these issues do happen.
I think it would be useful to have some integration with Splunk or other log collectors, or maybe in the future, the ability to link Dynatrace or any other observability platform.
If we can integrate it with natural language, could we talk to Gremlin Reliability Management Platform and have it configure some of the basic settings so that non-technical persons can also work on Gremlin Reliability Management Platform-like tools?
The user interface is great, the integration is smooth, and Gremlin Reliability Management Platform has a fantastic support team that helps us a lot in many cases.
Rather, it must be treated as a powerful supplementary tool that augments the existing code security solutions (such as Snyk or Checkmarx) in a DevSecOps or Secure DevOps environment.
The main thing is that I think everything should very hard aim for the direction of being AI compatible because every engineer, or most engineers now use AI to code.
That is what performance engineers and SREs need to see for each request, where it spent the entire time; how many other services or databases it interacted with and what took more or less time.
It is not so cheap, but it has very powerful features.
From a pricing standpoint of view regarding Gremlin Reliability Management Platform, I would say it is a bit expensive, but that expense is worth it given the kind of benefits it offers.
My role does not incur costs for us since we have an NFR for Gremlin Reliability Management Platform that we can use in our case.
In terms of pricing, it was a little challenging to get the company to commit to the full pricing of Enterprise, but once we got there it was nice.
There are really two pathways along: fewer incidents because with Gremlin Reliability Management Platform, we can make every part of the infrastructure more solid, and less downtime because we can test more architectures and then things like how to put in high availability clusters.
We fix failures even before they occur, which is basically proactive risk detection and risk mitigation.
Gremlin Reliability Management Platform has positively impacted our organization by making outages less frequent and improving recovery time significantly, resulting in fewer complaints on the customer success side and overall optimization of our DevOps process.
We get alerts into Slack, and they work great. We see a lot of metrics go through into Slack, and they are really useful for keeping our team focused on only seeing one place to see alerts.
The most valuable feature of Honeycomb Enterprise for me is the root cause analysis part because it helps me greatly with the response messages and derived error messages which are very clearly mentioned in Honeycomb Enterprise logs.
Honeycomb Enterprise is designed for modern cloud native systems.
| Product | Mindshare (%) |
|---|---|
| Honeycomb Enterprise | 1.1% |
| Gremlin Reliability Management Platform | 0.2% |
| Other | 98.7% |

| Company Size | Count |
|---|---|
| Small Business | 3 |
| Large Enterprise | 7 |
| Company Size | Count |
|---|---|
| Small Business | 5 |
| Midsize Enterprise | 1 |
| Large Enterprise | 8 |
Gremlin Reliability Management Platform empowers organizations to proactively identify and mitigate potential failures. It enhances system resilience through controlled chaos engineering, aiding tech teams in delivering reliable services.
Designed for tech-savvy users, Gremlin enables teams to implement chaos engineering effectively to ensure system reliability. It offers precise control over variables, allowing teams to simulate real-world scenarios and fortify system operations. Gremlin plays a strategic role in preventing downtime and maintaining optimal service delivery through a suite of advanced tools tailored for IT infrastructure.
What are the most important features of Gremlin?In industries such as e-commerce, finance, and healthcare, Gremlin helps maintain service reliability by identifying vulnerabilities before they affect operations. IT teams can simulate stress tests specific to their industry, ensuring systems are resilient against potential threats, enhancing customer satisfaction, and securing business continuity.
Honeycomb Enterprise is designed to optimize performance visibility, offering a robust platform for distributed system observability. It provides insights for complex data and aids in faster issue resolution, making it a valuable tool for IT professionals.
This tool is tailored for real-time data tracking and improving system performance efficiency. Enterprises benefit from its capacity to handle large-scale data, ensuring seamless operations and continuity. Honeycomb Enterprise helps teams to tackle data challenges head-on by delivering comprehensive analytics that enhance infrastructure reliability and performance metrics.
What Features Make Honeycomb Enterprise Stand Out?In industries like finance, e-commerce, and technology, Honeycomb Enterprise implementations demonstrate its utility in managing complex data flows and optimizing system reliability. Businesses in these sectors leverage its capabilities to maintain high service standards and operational efficiency.
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