What is our primary use case?
I have my own recipe for an infrastructure code where I integrate Fluent Bit with Kubernetes. It scrapes the logs off of all the member nodes of Kubernetes and then it chips that to an input on Graylog. That way, when developers want to troubleshoot an application but don't want to use anything Kubernetes CLI-related, they can jump straight to Graylog. They can type the name and the type of deployment that they're looking for and get all of the logs pulled into one place. Essentially I use this solution to give developers a way to look at all the logs in an aggregated form. It's very helpful.
I also use the solution to extract and quantify data and metrics from the logs. For example, let's say you're running the wallet application and you want to make sure that you are getting the minimum 404's when somebody is trying to make a payment. You can essentially extract the code on Graylog and it will give you a really nice view of how often your wallet times out, or overall performance. If you're looking specifically from a security standpoint, if the application is seeing something that should not be seen, you have a way to log that.
I also use it for building charts and live logging. Also, the pipelines allow you to take a raw log, create something out of it, and transform it into something else, so I use that for streams, presentations, metrics, and health checks from an app runtime standpoint.
What is most valuable?
Everything stands out as valuable, including the fact that I can quantify and qualify the logs, create pipelines and process the logs in any way I like, and create charts or data maps. One time, I created a geo map based on IP addresses accessing a website. The web server generates logs based on who's accessing the application, and we were able to extract the IPs from the logs and even create a chart on Graylog to map out exactly what countries the requests were coming from. Graylog is amazing. It's a beast.
What needs improvement?
Graylog needs to improve their authentication. Their AD integration is really bad. When it comes to ACL's, access control lists, where you want to have different group memberships and control who gets access to what, it really could use major improvements. It seems like a beta authentication version that they came up with in a hurry and said, "Hey guys, we've got something going for you. Use it until we think of something later on." I believe their enterprise version has improved some of these features, but I use the open source version.
The second thing would be the way they handle live logging. The fact that Graylog displays logs from the top down is just ridiculous. I've never seen anything that logs this way except for Graylog. I believe this is an issue because they have the selector going in that direction, so it would make sense that they have to implement it that way, but it's definitely not cool. When you're looking at Graylog's live logging, whether it's doing a one-second or five-second pull, you'll notice that new log lines are placed at the top of the screen, not the bottom of the screen. I find this ridiculous because normally when you're looking at logs anywhere, on Linux, even in Windows, you're going to see that the logs are generated at the bottom. That's one thing that Graylog definitely needs to improve.
Graylog also needs to invest some time to improve the performance and how they handle the maintenance of Elasticsearch.
An added feature I would like to see is the capacity to delegate most of the backend maintenance to the frontend UI. When you have somebody from the service desk working on the solution or somebody who's not a technical person, they could run some of the maintenance stuff directly from the UI.
Another thing is something that I saw in LogDNA, where you could have a color based on log regex. For example, it would color the timestamps next to the log lines orange, make the source of the log purple, and then make the actual log content black. That would be very nice to see in Graylog.
For how long have I used the solution?
I have been using this solution for about four to five years.
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What do I think about the stability of the solution?
I would give this solution a six out of ten for stability. It has quite a few hiccups. I usually try to avoid them the best I can, but sometimes they just happen and you have to deal with it.
What do I think about the scalability of the solution?
Graylog can scale, but technically, Graylog's scalability mainly depends on Elasticsearch because it uses Elasticsearch as the backend. I would say the question should probably be about how well Elasticsearch can scale. The answer to that would be that it is pretty scalable, but it's not simple. It's not like Kubernetes, where you just add a few extra replicas and you get performance right of the box. It's a bit complex to scale it, but it is scalable.
How are customer service and support?
I would rate the technical support as a four out of five. From an experience standpoint, they're pretty good.
How would you rate customer service and support?
How was the initial setup?
It really depends. If you're going to slap Graylog into a very small environment and do a standalone instance, it's super easy and straightforward. You have to install Mongo, Elasticsearch, and Graylog and connect them to each other, which is super simple. There are tons of easy tutorials online available to help you do that.
However, if you want to set up a highly scalable cluster, things will get a little bit complex. It's still very manageable, but it's definitely complex.
What about the implementation team?
It took me about 30 minutes to deploy Graylog.
What's my experience with pricing, setup cost, and licensing?
There is an open source version and an enterprise version. The authentication is bad in the open source version, but I believe they have improved that in the enterprise version.
I wouldn't recommend the enterprise version, but as an open source solution, it is solid and works really well.
What other advice do I have?
My advice to people considering this solution is to first determine where they can use it. The server sizing depends on the amount of logs generated and where you get the logs from. For example, it it a Kubernetes cluster with a lot of things on it, or just a bunch of VMs, or just a couple of VMs? What's the size of that? Based off of this, you would then decide the server sizing and how big your Elasticsearch needs to be and how scalable it needs to be. Graylog is like ELK Stack. It's very, very resource hungry.
I would rate this solution as a seven out of ten.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Disclosure: My company does not have a business relationship with this vendor other than being a customer.