Cribl Reviews

Our use case for Cribl is actually a data pipeline where we collect logs from the source and we stream it through Cribl and then to a destination. The destination is mainly the SIEM tools such as CrowdStrike or SecOps. We collect the logs from various sources, and even the Windows logs are streamed through Cribl worker nodes and data lakes. For example, if it is AWS, from the S3 bucket we stream to Cribl and then send it to Google SecOps, which is the primary SIEM we are using.

The best feature in Cribl, when getting logs from some custom application, is the ability to break up logs that pile up together and come as one event. 

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. This is critical as this generally happens in CrowdStrike. This feature helps us significantly.

When the ingestion is high from unwanted logs, logs not related to security purposes can be dropped by writing the parser function. By dropping events that are not required for security purpose monitoring, we can reduce the ingestion, which drastically reduces the cost as well. Cribl gives another option where I can store some logs, and when needed, I can pick them up from there.

The interface is very handy and not very complicated, yet there are many functions you can perform. You can play around with numerous functions, parse there, and add UDMs to SecOps, which makes it really easy.

To simplify the pipeline, when we go to the pipelines, there are vast options. We can make it specific requirements based on the customers. I would prefer a customized or simplified version. Cribl is a very good platform to work with, with lots of features that other platforms don't provide.

Cribl is a stable product, however, there are areas for improvement. Their documentation should be updated.

I have been using Cribl for a year and a half.

Cribl is a stable product, but there are areas for improvement. Since Cribl is on-premises, server maintenance is required, and we have an IT team specifically to look into that. We are not worried about that.

There is a similar platform by Google called BindPlane, which is not capable of handling high volumes of data as the data gets stuck in the pipeline, causing ingestion delays. 

However, Cribl does not present that problem. Since I have worked with both data pipeline tools, I can compare and say that Cribl is more mature than others.

I have not reached out to Cribl support. That said, my colleagues have.

I'm using another product called BindPlane, which does almost the same things; however, Cribl is a very mature product with many functions. You can use the Eval function, Unroll function, break events, add any particular field you want, or parse in Cribl before sending to a destination.

The initial setup involves dropping some events that are not required for security purpose monitoring. This is based on suggestions from our SOC team or customers.

The deployment itself is a bit compicated and the documentation is not very clear.

We are a partner with Cribl. We have CrowdStrike, and CrowdStrike has partnered with Cribl; they even changed the name to CrowdStream.

It has saved my cost and our customers' cost drastically since I cannot drop the logs directly in SIEM. In Cribl, I can drop the logs, and when I'm not ingesting them, their licensing cost is drastically reduced.

Cribl Search is quite handy; you can use regex where there's a function that contains, and you can search for a specific keyword, which shows everything that matches that keyword. After playing around a couple of times, it becomes easy. At first, it is complicated; you need to go to worker groups, select the data lake, select the worker node. Once you get used to it, it's quite handy. I would definitely recommend Cribl to other users. 

Based on my experience, I would rate Cribl eight out of ten.

Our main use case for Cribl was SIEM migration, where we merged multiple SIEM solutions to a single SIEM solution. SIEM migration was the most major use case we were looking for. The second use case was a manageable logging solution which could have a nice interface and would be easy to manage. Data cutoff or Log Filtering was the third biggest use case we were looking for, where we were seeking data reduction to define what we need and don't need. Additionally, we performed data masking for PII i.e. payments and medical data. These were the main use cases that were all provided by Cribl.

My previous company did a significant amount of business using Cribl, particularly in servicing customers who had a perfect fit for the solution. From a consultant's perspective, I can say that we resold licenses for Cribl, delivered services related to Cribl, and also provided maintenance services. This brought a decent amount of business to our company.

Regarding the reduction in firewall logs due to Cribl, it did influence our overall data processing and workflow. For example, the AWS VPC flow logs were greatly reduced in size, which had a substantial impact on the licensing costs for destination platforms. It did help us and the customer quite a bit. Cribl's role in its reduction of firewall logs, either cloud or on-prem, was vital.

The data cost is an important aspect. Cribl is specifically designed to reduce the data costs associated with the destination platform. This is one of its core offerings.

Regarding platform usability, the Cribl interface is quite intuitive and easy to use. The navigation and seperate sections are easily accessible, making it very user-friendly. The color scheme and palette are excellent, and there’s nothing messy or unmanaged about the user interface. Overall, I personally find the user interface to be very comforting.

The features of Cribl I have found most valuable include its SIEM migration capability. It facilitates migration quite nicely. The data reduction and preprocessing capabilities make Cribl really unique. Data masking is an important one. And as Cribl Stream can be deployed on-prem, on cloud or as a hybrid model, its support for every sort of enterprise estate is highly appreciated.  

The UI interface is very good. It's user-friendly, intuitive, not complicated, and sufficient. It's not more than what it needs to be, and it's simple without being overly complicated.

They've already done many good things with the product, but perhaps they could implement a temporary SIEM solution where we could store logs and display them as a SIEM, though I think that's not the space that Cribl is actually looking into. Based on my experience, this product is brilliant and there isn't much or anything important lacking in the product.

We encountered some occasional issues with the syslog data stream, particularly when handling large data volume, and getting it to parse and field extracted correctly, but no major alarms that would halt the days operation. There were few source vendor specific challenges, but overall, I didn't notice anything major beyond that. Most of the process went smoothly. However, we did need to carry some troubleshooting to resolve the issues we faced while connecting with other platforms and few data stream miss-behaving, which wasn't a straightforward task for us. 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. In summary, aside from the usual difficulties or issues that someone could face with any project, everything else went well.

I have been working with Cribl for more than four years now.

Cribl is quite stable and doesn't crash; there's no unusual behavior. If it's stable, then it's reliable. I could see the data that goes in and how it is being processed at each stage. There are no concerns when Cribl is working in production environment.

Cribl is quite scalable, as we could add worker nodes as our data grows, so it's sufficiently scalable and able to facilitate as much data as there can be.

Their technical support has been really great, and solution architects we worked with were really knowledgeable. They had extensive expertise with the product and were able to facilitate with everything we needed. The experience with Cribl technical staff has been one of the best.

Positive

For similar use cases, different companies were using different tactical solutions i.e. custom scripting. None of the solutions were strategic and well thought through. Some were using scripting, some were not utilizing anything. Some were ingesting into the SIEM and then doing all the tasks which should be done pre-ingestion. There was a lot of disorganization, and Cribl had really found the gap where they could offer their services.

I performed the entire setup of the Cribl infrastructure.

With the Cribl Stream setup, I first had to initiate the tenant. Once the tenant was provisioned, I configured IAM setup i.e SSO, RBAC etc. I onboarded the data sources and deployed the worker nodes to the appropriate locations. These locations could be various subnets, cloud virtual machines, on-premises virtual machines, or any ready-to-use Cribl cloud workers  we needed. The process depended on the company's IT infrastructure. After the worker nodes were set up, it was simply a matter of onboarding the data stream into the platform and then directing it to the destination platforms.

As for Cribl's deployment, it operates in a hybrid environment, utilizing both cloud and on-premises solutions, tailored to meet the needs of different customers.

I delivered Cribl services as a Certified Cribl Consultant to various customers. Cribl technical support was arranged whenever there was a need for it.

We have managed to save significant money and resources for multiple customers, reducing operational complexity and the cost of destination platforms but unfortunately I cannot quote specific numbers due to NDA. 

Cribl is very inexpensive, with enterprise pricing around 30 cents per GB, which is really decent. Organizations looking to ingest terabytes or petabytes of data each day find it quite an inexpensive solution. The pricing model for Cribl Stream is one of the best values that customers would be getting, and I don't think any other solution offers this much value at this price point.

Confluent was considered, but Cribl emerged as the best solution.

I would rate Cribl an eight out of ten.

We use Cribl for log management.

Cribl has the ability to send data to different destinations, making it a vendor-agnostic tool. For log management, we can parse values or enhance fields at Cribl level and then send it to different destinations such as S3, Splunk, Elastic, or other destinations. This feature is the one I love most because it acts as an intermediate heavy forwarder which can route data to different destinations.

Cribl is intuitive and user-friendly in navigating the UI.

Some of the integrations such as SNMP need improvement, and I feel Cribl should improve on SNMP integration and also on the database monitoring space. These two areas need improvement.

I have been using it for one and a half to two years.

Cribl handles volume of logs effectively. In case of any issues, Cribl support does their job in resolving the issues. Overall, it handles the volume of logs very effectively.

I rate the technical support for Cribl as nine out of ten.

Positive

Cribl is solving these issues and bridging the gap. There is Splunk which is equivalent to Cribl, but Cribl is currently leading in this space. There may be other alternatives, but they are still in evolving phase. Cribl is a mature product.

Cribl is easy to deploy. Spinning it up does not take much time, just about a week's time. However, getting the data in and configuring those destination sources will take time.

For scalability, I would rate it as nine out of ten.

I am not aware of the data cost. However, Cribl solves the complexity of having different agents installed. If we shift from Splunk to Elastic, we would have to get a new agent installed and point our applications to Elastic. With Cribl, it solves the complexity of having multiple agents in between and forwarding data. We can forward it to Cribl and then Cribl can send it to wherever we like. This kind of complexity is something it solves.

Big businesses use Cribl.

I assess the stability of Cribl as eight out of ten. I recommend Cribl for others looking to implement this product. I would rate Cribl overall as eight out of ten.

My main use case for Cribl is to send and process logs from our AWS network and multiple other cloud networks to an S3 bucket to store the logs as well as to stream the logs to other service providers like Logz.io where we will set up a logging and alerting platform.

A quick specific example of how I'm using Cribl in this process is that we have been using different types of logs such as Python from ECS and EKS Kubernetes-based logs, and all those logs are in different formats. We add all the logs from different streams to Cribl and then from there we add specific formats and add certain tags to those logs so that it is easy to format and set alerts at the logging level.

Cribl is very useful because we have multiple clouds and it has been processing our logs from multiple different platforms into a single one, and it is processing to multiple other platforms as well. It is used as a bridge to stream and process the logs.

One of the best features Cribl offers is that it runs on Kubernetes clusters, which is easy to manage and comes with easier upgrades. It is very compatible with container-based environments and supports multiple different types of logs. It has many connectors and can send to many endpoints. The workflow features are also strong.

The compatibility with container-based environments has made my day-to-day work easier because it supports Kubernetes. In day-to-day work it is mostly useful for container-based logs because we mostly run on Kubernetes and ECS. We are a completely container-based organization, so most of our logs are container-based logs and application-based logs. All those logs are easily processed from Cribl.

Cribl has positively impacted my organization in terms of efficiency. We used to run on Lambda functions in AWS, which is an older process, and we used to drop many of our logs, which was problematic because those are necessary for future use cases. Now everything is working well.

This has impacted troubleshooting and compliance in my team because we are able to keep the logs indefinitely. There is no drop in the logs and no loss of the logs. This has impacted my team meaningfully because we have all the logs, we have very strict monitoring, and compatibility with all of our standards.

I think Cribl can be improved because I do not believe it is a mature product. It has gone down many times and when we are doing upgrades, many things break and we face a lot of issues, especially with scaling. If the logs are high volume, most of the time it is down or some connectors are down and it is not performing as well as we thought.

Moving from version 3 to version 4 became very difficult during the upgrade. The scalability issue is very problematic. We are running on Kubernetes and there are a lot of issues with respect to scaling. When we have more logs coming in, the connectors are failing.

I would like to see other improvements with Cribl beyond scaling and upgrades. The product should be more mature and the documentation can be improved.

I have been using Cribl for four years.

Cribl is not really stable, although it may become stable. It is close.

Cribl's scalability is not great.

The customer support is also not great. They are connecting with us, but they are not able to figure out solutions very quickly. They may need more knowledge.

I previously used a different solution, which was Lambda functions. It was highly costly and it used to drop many of our metrics and logs, which was problematic.

I assess Cribl's ability to handle high volumes of diverse data types such as logs and metrics. I think it is feature-rich, but the scalability and reliability are major issues.

I am using the new search in place technology feature of Cribl Search, and the search is good. However, we need to go into the particular workflow and then from there we need to do the search. It is not a global search, which is not a good sign.

I have seen a return on investment. With respect to money, the savings are not significant. With respect to time, there is a little bit of saving, but because things broke during the upgrade, we needed to go back to the older methods of using Lambda. In terms of employees, we did decrease the employee count, but I do not know if Cribl is really the reason for that.

My experience with pricing, setup cost, and licensing shows that I am not completely involved in the pricing part, but I did participate in the setup part. Cribl provided an image and we used that image. It is also publicly available and it is not difficult to set up in a Kubernetes cluster. I think it is easy.

Before choosing Cribl, I was not part of the team which explored Cribl. I was already part of the team implementing Cribl. We used to use Lambda functions and then we moved to Cribl. I am not sure which other options were explored.

My advice to others looking into using Cribl is that if you are not a billion dollar company or if you are a startup that does not want to go into reinventing the wheel by writing all the code, Cribl is a great solution for streaming logs. I would rate this review a 6 out of 10.

A few use cases for Cribl include mainly reducing the amount of data that goes into our CM solution by reducing the data that flows through and only sending the important data into our CM solution.

With Cribl, I have seen a decrease in firewall logs as we send a lot of firewall logs into Cribl, aggregating and reducing the log size by aggregation or removing unwanted data, which works smoothly. Anything with logs—firewall, network logs, DNS logs—works fine.

Cribl does a great job at containing data costs, which is our major use case to reduce data costs for the CM solution, and we do that quite efficiently with Cribl by aggregating the data, masking unnecessary parts, and changing the structure into key-value pairs, thus reducing the cost significantly.

What I like about Cribl is that it is quite easy to use because everything is via UI, so there is no coding involved, making it more like a drag and drop functionality to add your items. It is an easy tool, easy to learn, and handy, allowing a lot more to be done without requiring extensive coding.

Cribl UI feels quite intuitive based on my experience after using Cribl for four years with my team and other vendors. It is easy to use, allowing many people to work at the same time, and versioning is already integrated. The same packs can be used with different machines and different workflows, which is also a good part. Cribl provides free education, unlike other tools, allowing us to learn the necessary skills and implement them in the actual production environment.

Cribl brings significant benefits like cost-effectiveness, reducing CM costs, and making our data vendor-agnostic since data flows through Cribl. If I decide to change my CM solution later, it will be an easy switch. Complex data can be simplified into easier formats like key-value pairs, making our current use cases streamlined.

I would like to see improvements in the metrics and traces, as Cribl is currently more geared towards logs, making it hard to get very long traces to view in the UI when they are quite big. I have not used metrics much because I am aware of the issues Cribl has with handling proper metrics, particularly with multi-metrics when there are multiple dimensions into a single metric. We use Cribl nearly 99.9% for logs only, not for metrics and traces, but I hope to see improvements in the future.

On the other hand, I would like to see improvements in pack management, which is currently a mess with no way to manage packs differently across worker groups. I also wish Cribl would introduce more functions, as sometimes we have to create more JavaScript functions ourselves. Aside from that, everything is going well, especially with recent AI integrations.

I have been working with Cribl for four years.

Cribl is pretty stable, with me experiencing only minor hiccups and no major alarms. Previous data loss issues have been resolved over the past two and a half years, making it a stable option.

I consider Cribl scalable as we are using the Kubernetes version, and I have seen that scaling is manageable. We have also checked on-prem and found similar results, confirming it to be a scalable solution.

Cribl technical support is generally good, albeit sometimes inconsistent. The U.S. team is excellent once a ticket is escalated, while the support in Germany or Europe could be improved. I would rate the technical support at a seven on a scale of one to ten.

Positive

Prior to Cribl, I had not used any different product of the same kind, which is an advantage for Cribl. While there are a few products emerging now, the last time I checked, they were not equivalent to Cribl.

Cribl initial setup was not complex because Cribl is very similar to another product we used for multiple years, allowing us to extend scripts easily. I would say installation is pretty straightforward, and the documentation and education provided by Cribl greatly aids the process.

Our deployment was primarily in-house, with initial assistance from Cribl engineers. We have managed it internally for the last three and a half years.

Regarding ROI, Cribl reduces our CM cost by about twenty to twenty-five percent due to the data that is flowing in and reducing the overall amount.

I did not evaluate any other options before choosing Cribl since there was hardly anything on the market like it at that time, although I see a couple of viable options now.

My advice for organizations considering Cribl is that it is a nice tool, very effective with limited competition, but you should plan thoroughly regarding your use case to avoid wasting licenses. It is essential to implement something significant, considering the infrastructure as well. I rate Cribl at an eight overall.

Our use case for Cribl is that we want to make sure that we parse everything correctly, and it is easier for us to transfer our data in our system in a more compact way; it runs smoothly.

We're in the beginning stage of using Cribl, but the reduction in firewall logs will help significantly with processing speed. We just worked on handling high volumes of diverse data including logs, metrics, and files last week, and it ran very smoothly with quick processing.

The best feature about Cribl is how easy it is to move; the UI is very simple, everything is very neat, and everything is organized. We have been dealing with Cribl extensively recently.

Cribl is awesome. The university offers a lot of great resources, but there could be more detailed information about Cribl itself. It would be helpful to have a step-by-step guide that covers everything from the basics. Since Cribl is such a large platform with numerous features, having a clear, structured approach would make it easier for me and others to understand and utilize its capabilities.

I believe it would be beneficial to have a step-by-step guide for users on our endpoint. This would make it easier for them to understand how to use it. When I explored the endpoint, I found myself wishing for clearer instructions presented in a sequential manner. This is just a small critique based on my experience using it so far.

We started using Cribl around three months ago.

I would rate stability as a nine; nothing is perfect, but it's great. 

I would definitely give scalability a nine as in terms of what we're seeing and thinking about, it's solid.

We have around eight or nine users. Everyone is touching base with it. For now, it will stay at eight unless we expand. We are going through an expansion, so it’s possible we might increase the number of users; but for now, we’re steady at our current count. We are a medium-sized business.

Their customer support is fantastic.

Positive

We were using a manual solution previously; this transition to Cribl is our first time implementing an automated solution.

We are typically on-premises. I believe Cribl is currently focused more on the OT side because the primary customer base is more enterprise-oriented. OT relies heavily on this. However, if I'm not mistaken, we operate in an on-premises or hybrid environment; we are definitely not using the cloud.

We are still in the process of deployment, and so far, the deployment has been going fairly well and has been relatively quick for us.

We are in the transitioning stage; we're implementing everything from square one with our team, participating in daily calls to make that happen. We are experiencing some issues with data transfer and parsing errors, which is extending our SIEM transfer time.

Based on what our managers say, we have saved a significant amount of time and resources moving from a manual approach to something that's more automated.

As I visited different booths at the conference, I realized that I still prefer Cribl. Even though I haven't worked with any other platforms, I was impressed by how everything is laid out and how simple it feels to work with your system. I genuinely appreciate the user interface. I find it straightforward and well-organized, making it easy to navigate.

I also noticed that they have implemented something like a password manager, which sounded familiar. Overall, everything I saw reaffirmed my preference for Cribl. So, despite checking out various booths, I'm still committed to Cribl at the end of the day.

I would definitely recommend it. The user interface is great, and the customer support has been fantastic as well. Our experience with Cribl has been very smooth; everything runs seamlessly. There are no delays or sluggishness, which I really appreciate. I have to give it props for that; everything operates very smoothly.

I would rate Cribl a nine out of ten.

I use Cribl to move data and help with moving data, connecting different data sources to different destinations, which is what I mainly use it for.

I also use it to help parse the data as well.

Something that I really appreciate about Cribl is the preview feature. Whether it would be on the JavaScript I'm working on, it shows me the output in real time, which really helps with development.

I also appreciate the preview feature when it comes to data pipelines, as it shows me in real time how my pipeline would be working with the data. Additionally, I really appreciate the live capture feature as well to get an idea of how the data looks at different stages in Cribl environment.

I think Cribl is an excellent tool for helping to manage data cost and keep it down as well as manage complexity.

Cribl has come a long way. I've been using it for three years, but there are still a lot of other features that I would appreciate regarding new data sources. One example would be open WebSockets.

There's currently not a native feature for that, so that requires a lot of time in development. I would also appreciate better support for JWT tokens for a REST API collection. While sometimes it does work, it seems very janky and seems like a stitched-together solution. It would be nice if there was a more supported version to help with JWT.

I've been working with Cribl for a long time, at least three years, maybe more.

Cribl is very robust. It's not perfect, but very good stability.

Cribl is very scalable. The product itself lends itself well to being scaled. Any issues I've had with scaling have mainly just been human issues of people not wanting to scale, but the product itself is very capable of scaling.

The speed was fast. The quality, however, there wasn't a solution just because I think it was a bug and it was never fixed as far as I know. The speed was nice, but there was never a solution provided.

Negative

I use Splunk.

From what I understand, I'm mainly on the engineering side, not the sales side, but the pricing is very competitive. Although the pricing can be a little bit high, I know that Cribl as a product helps save a lot of money by reducing data storage. The pricing is offset by the money I save by using Cribl.

Cribl does require maintenance, especially if I'm deploying it on-premises. If I'm deploying on-premises on my machines, I've just got to make sure that they're being provisioned well, that they're being updated successfully, and that they're constantly balancing the worker processing across them.

I definitely prefer Cribl more, mainly for the UI and the preview feature that I mentioned about being able to see in real time my in and out for development. I think that speeds things up a lot.

However, I do like Splunk a lot too.

I think Splunk is better tailored for visualizations and presenting to clients, especially around metrics. I think I can do some visualizations and presentations of metrics in Cribl, but it's not as robust as Splunk.

Definitely for large corporations, they would see the most benefit, but I think small and medium businesses could also benefit as well.

Our main use case for Cribl was primarily data reduction, as we were spending a lot of money on data ingest, and we brought Cribl on board to reduce the amount of money we were spending on that ingest. 

Reduction in firewall logs was our primary use case for Cribl, as 80% of our data is Palo Alto firewall logs, and a lot of it we don't necessarily need in the SIEM tool, so we use Cribl to reduce that, keep only the stuff we want, drop the rest, and keep it out of the SIEM tool. The reduction in firewall logs keeps the unwanted data out so that when the security engineers are inside the SIEM tool, they only see the stuff they need to see.

The features of Cribl that I appreciate the most are the vendor agnosticism and the ability to send data almost anywhere you want, regardless of the data type, the format, or the destination; it's very flexible, and we've been able to integrate it with the tools that we have used in the past and are planning to use in the future.

The UI is very clean and super intuitive, making it very easy to bring data on via the sources, route the data to any number of destinations that you want, and create pipelines to transform and morph that data however you want. 

Cribl is great in the sense that it can handle a large amount of volume and scales with the amount of data that you want to bring on board; if you need to bring on board more data, you just increase the amount of workers that you have.

We use Cribl to reduce data cost and complexity by both dropping fields that we don't want or parts of events that we don't want while keeping the things we do want, while also keeping all of the data, the event in its full form. We're a government agency, so we ned to keep everything. With Cribl, we can have our cake and eat it too, in a sense.

I'm an engineer, so I think about logging. Improvement could be made in the logging area, as sometimes we encounter issues in a pipeline or something, and it's not immediately obvious when you look at the logs that the pipeline is failing.

I've been using Cribl for around four years.

I would give Cribl a great rating on stability and reliability, especially if you use the built-in alerting engine that they have, as you can get alerts directly if there are any problems with the worker itself or worker processes, and the built-in monitoring page makes it super easy to monitor the health of all your worker processes.

Cribl scales great with our company as we're actually bringing on a lot more data with all the AI tools rolling out, which generate a lot of logs, and Cribl scales horizontally by just adding more workers and worker processes, allowing us to tackle that data smoothly, quickly, and efficiently.

We've had a great experience with Cribl customer service, as we have dedicated PS resources that have been super helpful when we were rolling out Cribl initially, migrating sources of data from syslog over to Cribl, routing, and parsing, with the support being A+ on both the PS side and the technical support side.

Positive

Cribl is really the only tool out there that does what it does, especially when looking at Splunk, as when Cribl first came out, Splunk wasn't able to intuitively do a lot of the things that Cribl did just out of the box with a GUI, making it super easy. 

We were dabbling in data reduction, transformation using Splunk's Universal Forwarder and even the Heavy Forwarder in some instances, but it was just not as intuitive, with a lot of command line interaction and no GUI on the front end, making it harder to do, while Cribl makes it super easy.

When we deployed Cribl, we were on-prem. All of our workers are on-prem. Our leaders are on-prem. Nothing's in the cloud. The major challenges that we faced really were related to the load balancer that needs to sit in front of the workers. I would like to maybe see that rolled up into Cribl in the future. That posed a lot of challenges for us just coordinating with our infrastructure team, getting the F5 engineers involved, using F5 load balancer. That was a challenge for us. We ultimately tackled it, however.

From my point of view, the biggest return on investment is just the downstream licensing costs we save on the SIEM side; we've reduced our data by a certain amount, and it has almost paid for Cribl itself and also allowed us to chop some licensing off of the SIEM side. We've reduced our amount of ingest by about 40% overall.

I'm not really involved in the pricing and payment aspect of Cribl. I'm just the guy who implements it all once it's bought and paid for.

We're not using Cribl Search at the moment; we're only using Stream and Edge.

If you're a company out there considering Cribl, I would highly recommend at least giving it due diligence; get linked up with the sales rep, as they're going to explain everything to you, and the sales engineers are great and very knowledgeable, making it worth your time and money, so you're going to be glad you did. 

I rate Cribl nine out of ten.