

Elastic Observability and Cribl operate in the log and metric management category. Elastic Observability holds an advantage with its extensive feature set for cloud environments and customizable dashboards, while Cribl stands out in data routing and cost-effective log data reduction.
Features: Elastic Observability offers exceptional text search, open-source flexibility, and system integration. Its customizable dashboards are highly valued, and it provides a comprehensive feature set for cloud and hybrid environments. Cribl distinguishes itself with user-friendly data manipulation, efficient data routing, and significant log data reduction, enhancing cost-effectiveness across various platforms.
Room for Improvement: Elastic Observability's challenges include pricing, customization, and flexibility with log retrieval and monitoring. It also has a steep learning curve and limited out-of-the-box use cases. Cribl needs improvements in certification, documentation, complexity management with high data volumes, and optimization for older infrastructure and pricing models.
Ease of Deployment and Customer Service: Elastic Observability supports deployments across on-premise, public, and hybrid clouds, with generally positive technical support and well-regarded documentation. Cribl also deploys well across environments, with customer service praised but requiring enhancements in technical support experience.
Pricing and ROI: Elastic Observability is cost-effective for large deployments and offers ROI through data availability and operational efficiency, though its pricing structure can confuse smaller users. Cribl's pricing is competitive with reduced data ingestion costs, delivering good value despite a higher price point, and offering substantial ROI in diverse environments.
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.
Elastic Observability has saved us time as it's much easier to find relevant pieces across the system in one screen compared to our own software, and it has saved resources too since the same resources can use less time.
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.
Elastic support really struggles in complex situations to resolve issues.
Their excellent documentation typically helps me solve any issues I encounter.
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.
Cribl performs effectively across both market segments.
I rate the scalability of Elastic Observability as a ten, as we have never seen issues even with a lot of data coming in from more customers, provided we have the appropriate configuration.
Elastic Observability seems to have a good scale-out capability.
Elastic Observability is easy in deployment in general for small scale, but when you deploy it at a really large scale, the complexity comes with the customizations.
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.
Cribl is designed to deal with certain kinds of loads and is not designed to handle any scenario in the market.
There are some bugs that come with each release, but they are keen always to build major versions and minor versions on time, including the CVE vulnerabilities to fix it.
It is very stable, and I would rate it ten out of ten based on my interaction with it.
I would rate the stability of Elastic Observability as a ten, as we don't experience any issues.
A more stringent role-based access control feature would enhance security and allow granular control over what users can see and access.
When passing query logs or DNS logs, if certain malicious query patterns need to be identified or if fast-flux attacks are happening, Cribl can report that and those would definitely be a plus for them.
I would advise others looking to implement Cribl that if they are evolving Cribl Search, it would be very interesting to see more capability, more flexibility, and more ways to share the data similar to Splunk.
For instance, if you have many error logs and want to create a rule with a custom query, such as triggering an alert for five errors in the last hour, all you need to do is open the AI bot, type this question, and it generates an Elastic query for you to use in your alert rules.
It lacked some capabilities when handling on-prem devices, like network observability, package flow analysis, and device performance data on the infrastructure side.
Some areas such as AI Ops still require data scientists to understand machine learning and AI, and it doesn't have a quick win with no-brainer use cases.
Over time, the licensing cost has increased.
It was cheaper than the Splunk license.
Splunk is more expensive, and Cribl appears to be more affordable.
The license is reasonably priced, however, the VMs where we host the solution are extremely expensive, making the overall cost in the public cloud high.
Elastic Observability is cost-efficient and provides all features in the enterprise license without asset-based licensing.
Observability is actually cheaper compared to logs because you're not indexing huge blobs of text and trying to parse those.
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.
The most valuable feature is the integrated platform that allows customers to start from observability and expand into other areas like security, EDR solutions, etc.
the most valued feature of Elastic is its log analytics capabilities.
All the features that we use, such as monitoring, dashboarding, reporting, the possibility of alerting, and the way we index the data, are important.
| Product | Mindshare (%) |
|---|---|
| Cribl | 1.2% |
| Elastic Observability | 1.9% |
| Other | 96.9% |


| Company Size | Count |
|---|---|
| Small Business | 41 |
| Midsize Enterprise | 7 |
| Large Enterprise | 34 |
| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 4 |
| Large Enterprise | 16 |
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.
Elastic Observability offers a comprehensive suite for log analytics, application performance monitoring, and machine learning. It integrates seamlessly with platforms like Teams and Slack, enhancing data visualization and scalability for real-time insights.
Elastic Observability is designed to support production environments with features like logging, data collection, and infrastructure tracking. Centralized logging and powerful search functionalities make incident response and performance tracking efficient. Elastic APM and Kibana facilitate detailed data visualization, promoting rapid troubleshooting and effective system performance analysis. Integrated services and extensive connectivity options enhance its role in business and technical decision-making by providing actionable data insights.
What are the most important features of Elastic Observability?Elastic Observability is employed across industries for critical operations, such as in finance for transaction monitoring, in healthcare for secure data management, and in technology for optimizing application performance. Its data-driven approach aids efficient event tracing, supporting diverse industry requirements.
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