Graylog

We have various environments, including UAT, SIT, Dev, and Production, with automated deployments. We refer to Graylog Enterprise  to verify if deployments have completed, check their status if they have failed, and determine what version is currently running.

Some team members from the QA team are unable to see the exact version or the newer version. We use Graylog Enterprise  to check if the deployment is done, identify what version has been deployed, and determine on what date the environment was updated.

We provide variables to fit in the relevant section and select the appropriate one, such as the environment and what we need to check. This is the main feature I appreciate about Graylog Enterprise. Whatever we select, such as the database name or environment name, all the information appears, including the date of the last deployment and related details.

Troubleshooting is straightforward with Graylog Enterprise. Whenever we encounter an issue, whether from the QA team or other team members, we use it to troubleshoot the specific problem and implement a fix.

During deployments, we fix issues as quickly as possible using Graylog Enterprise. When team members from the QA team inform us that something is not working or an environment is down, we access Graylog Enterprise to verify if the deployment has been completed and check exactly what version is running.

We receive approximately 15 to 16 daily requests, and we resolve them through Graylog Enterprise.

We have been using Graylog Enterprise for the last two years. Graylog Enterprise is deployed in our organization as a private cloud solution.

There are many other applications in the market that influenced my rating reduction.

We describe our customers' usual use cases for Graylog  as one where we use it for event correlation. We take typical IT events, and we also use it for security event correlation as well. So, both security and general IT.

We use Graylog  internally in our company.

The features and capabilities of Graylog that we have found most valuable are related to its basis on open search, which was ElasticSearch. We appreciate being able to integrate custom feeds and do custom parsers, and to be able to do some of the correlation on it. That all works effectively.

The Graylog features that have proven to be most beneficial for our data analysis in particular are that we tend to use it as a big data store, so we have the correlation rules that, if something matches under certain conditions, it raises an alarm. We use it for investigating problems and problem management. We throw all the information at it, we have it alerting for certain conditions, but generally we use it for deep diving into issues as needed.

The area in Graylog that needs to be improved or enhanced would be the integrations. It would be useful to have more parsers and filters for different types of systems, which is growing, but we still find many systems that there aren't any, and we have to create our own. Having a library of parsers would help. Mainly, it's about integrations: being able to parse different sources and output to different systems easier.

I have been working with Graylog for about 8 years or so. That is quite a while.

I rate the stability of Graylog as very stable, probably a nine out of ten.

On a scale from 1 to 10, where 10 is the highest level of scalability, I would rate Graylog's scalability as an eight. I think Graylog itself is scalable, but where it needs improvement is around the underlying features of open search, particularly concerning data logs and things. More up-to-date documentation on how to do high ingestion and high search scenarios, including recommendations for configuration and deployment, would be useful.

Regarding technical support for Graylog, I can't comment much because I've not had to use it. Even though we have the enterprise products, we've not needed to use technical support because we've been using Graylog for many years and can fix most problems ourselves. There are some sizing documents online, but they were a few years out of date when we looked a few months back.

Before Graylog, we had a customer running IBM QRadar , which is a big security logging platform. We used other products such as RSyslog, Kiwi Syslog, which is Windows-based, and Syslog-ng, among others.

The decision to switch to Graylog was influenced by my appreciation of its user interface. It separates out the ingestion from the backend. For instance, if Graylog is running and you take the backend down, you don't lose events. In contrast, with RSyslog, if you turn it off, you can't do backend-frontend maintenance, which is an advantage Graylog offers. It also handles clustering nicely, making it easy to scale up quickly.

I would rate my experience with the initial setup of Graylog on a scale of 1 to 10 as probably about a five. If someone has never used Linux before, it would be very difficult, but if you're familiar with Linux and the day-to-day things behind the scenes, it's quite straightforward. The guides online are simple, follow the guide, and you've got a system that works. There could possibly be more around improving the performance, and maybe some more up-to-date calculators on sizing because some of the sizing information we've seen previously are a few years out of date.

For maintenance, we usually need just one or two people. We have a team of three engineers who look after it, and they rotate the maintenance responsibilities every three weeks.

The return on investment or cost savings we have seen since the deployment of Graylog is primarily in time savings, allowing our security team and IT engineers quick access to information, as it all goes to one place. It makes it quite quick to find things, enabling us to retrieve the information needed to respond swiftly.

Evaluating other options before choosing Graylog was somewhat straightforward because we've been using it for some time and are confident with it. Originally, we recommended Graylog to a customer, but they chose QRadar, which is very expensive and didn't scale as effectively. Eventually, we put Graylog next to QRadar because QRadar couldn't keep up.

My impression of the overall visibility of Graylog is good. In the past few years, as it's transitioning from just an open-source product into more of an enterprise solution, they're trying to grow into that area and do more in the API space. I think it will get better, particularly for orchestration pieces. That's probably its weaker area compared to some of the other products such as Microsoft Sentinel  or Log Analytics, where they have more hooks into different products. I appreciate that Graylog is moving towards that, and it's quite simple to get it stood up quickly. We have used it during security incidents with customers, and we have spun up a separate Graylog instance to help them with ransomware type issues.

Graylog has supported our compliance and security monitoring activities because, for one of our customers who falls under the NIST 2 regulation due to critical infrastructure, we heavily use it for that side. However, for the rest, we don't tend to use it for compliance really. A lot of that's handled separately, so it's not really an area we do much with Graylog at the moment, but it could be something that we could do more with in the future.

Graylog is not assisting us with our AI-driven data analysis or any operations with AI at the moment, but it could be something that we could do in the future.

Currently, about 10 people are using Graylog in our company.

We have plans to use Graylog more in the future as we deploy more. We run a private cloud for different platforms, and our intention is to have all of those systems folding their events into Graylog.

Overall, I would rate Graylog at about a seven or eight. The only downside is some of the integrations; if it had more integrations, it would be easier to work with other tools. Contextually, they're transitioning from an open-source background to a more enterprise-oriented space, which understandably takes time.

In my opinion, the best use case for Graylog  is for backend services due to its excellent real-time updates. It is especially effective with strong type languages, like Java or C++. The streaming of messages happens with the GELF protocol over UDP, making it quite fast. Deploying Graylog  into a Docker  image where microservices are placed allows for easy log retrieval. Logs from different Docker  machines can be combined into one Graylog instance, providing a complete view of backend behavior for both developers and customer support teams.

Graylog is valuable because it bridges technical knowledge to non-technical teams, presenting complex backend processes in a simple timeline. It boosts the knowledge of sales and customer support teams by allowing them to see the backend operations without needing to read the code. Its API is flexible for visualization, and its powerful search engine efficiently handles large volumes of log data. Moreover, its stability, fast search capabilities, and compatibility with languages like ANSI SQL enhance its utility in IT infrastructure.

An improvement I would suggest is in Graylog's user interface, such as allowing for font size adjustments. A potential enhancement could be the integration with Ollama to run large language models locally, maintaining high privacy standards.

I have been using Graylog for three years.

Deploying Graylog required about one week of preparation to evaluate the best setup, especially regarding Docker integration and the computing power requirements for scalability.

Graylog is very stable and capable of handling millions of messages without sudden shutdowns or service interruptions.

Deploying on the cloud for Graylog is advisable due to its need for scalability under varying message loads. Graylog offers the capability to withstand large volumes of data, adapting to fluctuating inflows.

I never personally reached out to Graylog technical support. I mostly relied on documentation to address my needs, which was adequate for my purposes.

I used my own logging service, Elasticsearch, and OpenSearch  before transitioning to Graylog. OpenSearch  was not as intuitive and had a steeper learning curve compared to Graylog.

The initial setup of Graylog was straightforward, provided the codebase was prepared for logging. The documentation, although not visually appealing, was informative and helpful.

I am not familiar with the pricing details of Graylog, as I was not responsible for that aspect. It was determined that we didn't need an enterprise plan, which is more suited for clients with less programming capabilities.

I evaluated Datadog  among other solutions, but its pricing model deterred me since I preferred a solution like Graylog, which allowed testing without initial payment.

I would recommend Graylog for its stability, API capabilities, and fast search engine. However, it's not ideal for developers lacking in setting up comprehensive logging in their codebase. I rate Graylog an eight out of ten.