

Competing in application performance monitoring, Splunk AppDynamics is ideal for application monitoring across various environments, whereas Cribl stands out in data processing and routing. Splunk AppDynamics has the advantage in application insights, while Cribl leads in flexible data management.
Features: Splunk AppDynamics monitors and diagnoses application performance, offering JVM monitoring, transaction snapshots, and business transaction tracking. Cribl processes and routes large volumes of diverse data types, provides LogStream and Edge functionalities, and ensures flexible data transformation.
Room for Improvement: Splunk AppDynamics can enhance data granularity and user navigation, and improve network performance monitoring. Cribl could improve documentation, offer more feature packs, and better integrate with legacy systems while handling high-volume logs efficiently.
Ease of Deployment and Customer Service: Splunk AppDynamics is deployed across hybrid and on-premises environments, receiving good customer service ratings but could improve geographical support. Cribl deploys in on-premises, hybrid, and public cloud environments with responsive support, although documentation and onboarding could be better.
Pricing and ROI: Splunk AppDynamics offers a premium ROI for large enterprises but can be expensive for smaller organizations due to its licensing model. Cribl is cost-effective, providing significant savings compared to other solutions, though long-term cost rise is a concern. Both deliver good ROI.
What we've seen is really an overall reduction of just shy of 40% in our ingest into our SIM platform versus prior to having Cribl.
The second thing is that data aggregation, sampling, and reduction that we're able to do of the data, lowering our overall data volume, both traversing the network as well as what's being stored inside of our final solutions.
In terms of reduction, we were able to save almost ~40% of our total cost.
Overall, as a production gatekeeper, we achieve at least 50% efficiency immediately, with potential savings ranging from 60 to 70% as well, reinforcing why it is a popular tool in the banking industry.
According to errors, exceptions, and code-level details related to their application performance on a daily basis, the application development team tries to help with Splunk AppDynamics to reduce errors and exceptions, which helps the end users get application availability and feel more confident.
To understand the magnitude of it, when the company asked to replace Splunk AppDynamics with another tool, I indicated that for the proposed tool, we would need five people to do the analysis that Splunk AppDynamics enables me to do.
They had extensive expertise with the product and were able to facilitate everything we needed.
Usually, within an hour, we get a response, and we are able to work with them back and forth until we resolve the issues.
Sometimes by hearing the problem itself, they will know what the solution is, and they will let us know how to resolve it, and we do it immediately.
AppDynamics is much more helpful.
We got a contact, an account manager, to work directly with for technical support.
They help us resolve any issues raised by our team relating to operations, application instrumentation, or any other issues.
The infrastructure behind Cribl Search is also scalable as it uses a CPU and just spawns horizontally more instances as it demands and requires.
Compared to other SIEM tools I use, any slight change on the operating system end impacts a lot on our SIEM tools and other things, but Cribl performs well in that regard.
It's an enterprise version, and we have a good amount of users using this solution.
We have reached maximum capacity in our tier, and extending capacity has not been cost-effective from Splunk's perspective.
I would rate the scalability of Splunk AppDynamics as a nine out of ten.
I assess how Splunk AppDynamics scales with the growing needs of my organization as good, since we are growing and adding more servers.
Migrating from those SC4S servers to Cribl worker nodes has truly been a game-changer.
Regarding scalability, we started with zero servers and have around 285 servers now.
I would rate the stability as ten out of ten.
It is necessary to conduct appropriate testing before deploying them in production to prevent potential outages.
There are no issues or bugs with the 20.4 version; it is very stable with no functionality or operational issues.
Splunk AppDynamics is superior to any alternative, including Dynatrace.
A more stringent role-based access control feature would enhance security and allow granular control over what users can see and access.
If we can have more internal logs and more debug logs to validate the error, that would be beneficial because instead of reaching out to Cribl support, we can troubleshoot and find the root cause ourselves.
In terms of large datasets—whether they originated from network inputs, virtual machines, or cloud instances—ingesting the data into the destination was relatively easy.
Splunk AppDynamics does not support the complete MELT framework, which includes metrics, events, logging, and tracing for the entire stack.
If AppDynamics could develop a means to monitor without an agent, it could significantly improve application performance and reduce potential problems.
A good integration with Splunk would be very interesting, as Splunk is a good product for logs, and that part is currently missing in Splunk AppDynamics.
Over time, the licensing cost has increased.
Cribl is very inexpensive, with enterprise pricing around 30 cents per GB, which is really decent.
They have a universal license that allows us to consume the portions of Cribl that we want to use or flex into other portions of Cribl.
We completed a three-year deal for Splunk and for AppDynamics, which costs millions of dollars.
Overall, I consider Splunk AppDynamics an expensive product; it's very expensive.
Customers have to pay a premium price, however, they receive considerable value from the product.
The data reduction and preprocessing capabilities make Cribl really unique.
Cribl has a feature called JSON Unroll or Unroll function that allows you to differentiate the events; each event will come ingested as a single log instead of piling it up with multiple events.
The Cribl UI is very simple and easy to use, particularly when working with data from various sources; it makes it very easy to create pipelines, add complex logic to those pipelines, and then gives you a preview of what your data looks like before applying that pipeline and what you get after.
We have multiple tools, but end users prefer to use Splunk AppDynamics because their portal navigation is very simple and clear.
The real user monitoring and digital experience monitoring effectively track actual user experience with the applications, including page loading, interaction time for both desktop and mobile applications.
This is the best feature because, although you can't monitor a whole application at once, Splunk AppDynamics gives you the option that if there is any failure—simple failure regarding anything set up as per our use cases—you will get an alert.
| Product | Market Share (%) |
|---|---|
| Splunk AppDynamics | 3.6% |
| Cribl | 1.2% |
| Other | 95.2% |

| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 5 |
| Large Enterprise | 18 |
| Company Size | Count |
|---|---|
| Small Business | 55 |
| Midsize Enterprise | 36 |
| Large Enterprise | 194 |
Cribl offers advanced data transformation and routing with features such as data reduction, plugin configurations, and log collection within a user-friendly framework supporting various deployments, significantly reducing data volumes and costs.
Cribl is designed to streamline data management, offering real-time data transformation and efficient log management. It supports seamless SIEM migration, enabling organizations to optimize costs associated with platforms like Splunk through data trimming. The capability to handle multiple data destinations and compression eases log control. With flexibility across on-prem, cloud, or hybrid environments, Cribl provides an adaptable interface that facilitates quick data model replication. While it significantly reduces data volumes, enhancing overall efficiency, there are areas for improvement, including compatibility with legacy systems and integration with enterprise products. Organizations can enhance their operational capabilities through certification opportunities and explore added functionalities tailored towards specific industry needs.
What are Cribl's most important features?Cribl sees extensive use in industries prioritizing efficient data management and cost optimization. Organizations leverage its capabilities to connect between different data sources, including cloud environments, improving both data handling and storage efficiency. Its customization options appeal to firms needing specific industry compliance and operational enhancements.
Splunk AppDynamics enhances application performance monitoring with advanced diagnostics and real-time insights, offering seamless end-to-end transaction tracking and infrastructure visibility.
AppDynamics provides critical tools for businesses to analyze application behavior and performance. Through innovative features like transaction snapshot analysis and adaptable dashboards, users can quickly identify and address issues, ensuring high levels of system uptime and efficiency. It is designed to support complex environments including Kubernetes and AWS, enhancing user experience by detecting performance issues early. Despite needing improvements in network monitoring and integration, it remains a robust option for tracking application health.
What are the key features of AppDynamics?In industries like financial services and e-commerce, AppDynamics facilitates performance tracking across distributed systems, optimizing infrastructure to meet consumer demands. It excels in environments needing precise transaction monitoring and is pivotal in delivering high value and satisfaction.
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