Grafana Enterprise

What do you like best about the product?

I love Grafana Labs for its vendor-neutral flexibility, allowing me to query metrics, logs, and traces from diverse sources in one stunning unified dashboard without costly data migration or vendor lock-in. The Explore mode and trace to log correlation with Loki and Tempo are fantastic, letting me jump instantly from an alert spike directly into root-cause traces and logs, which saves critical triage time. I also like how easy it was to connect basic dashboards and pre-built integrations, getting them set up in minutes.

What do you dislike about the product?

I find the alerting setup and notification policies in Grafana Labs to be overly complex. Debugging routing labels and configuring non-intuitive contact points create unnecessary friction during incident triage. Additionally, the alerting configuration can lead to silent failures with complex contracts and PromQL issues. It would be much more user-friendly if there were an intuitive visual alert builder with interactive policy dry runs and real-time debugging capabilities. A visual routing flowchart and built-in dry simulators for alert paths, along with simplified rule builder templates, would also enhance the user experience significantly.

What problems is the product solving and how is that benefiting you?

Grafana Labs solves fragmented observability by providing a unified dashboard that allows me to query metrics, logs, and traces without costly migration. It saves critical triage time with features like trace to log correlation, allowing instant jumps from alerts to root-cause analysis.

What do you like best about the product?

What I like most about Grafana Labs is how flexible it is—I can plug in pretty much any data source and have a working dashboard up in no time. The visualization options are great, too, so it’s easy to make sense of the data at a glance. On top of that, the open-source community around it is a huge plus.

What do you dislike about the product?

The main thing I’d point out is the learning curve. It looks simple on the surface, but as soon as you want to do anything beyond basic panels, you end up diving into PromQL and alerting configuration, and the docs kind of assume you already know what you’re doing. Alerting in particular felt a bit clunky and harder to get right at first, even once I understood the basics.

What problems is the product solving and how is that benefiting you?

Before Grafana, we usually found out about issues from users, which is honestly the worst possible way. Now we can spot latency spikes, resource saturation, and error patterns on dashboards before anyone even files a ticket. It’s basically turned our incident response from “let’s figure it out” into “here’s where it broke.”

What do you like best about the product?

I find Grafana Labs particularly useful in the Fulfillment Innovation Technology (FIT) project for monitoring our application and supporting services in one place. Instead of checking different services separately to find errors or performance issues, I can use dashboards to view important metrics such as API performance, CPU and memory usage, Kafka activity, and other system metrics. This makes it easier to understand the overall health of the application, especially in a production environment. The ability to create dashboards and configure alerts also helps us identify potential issues earlier and makes troubleshooting easier.

What do you dislike about the product?

One area that could be improved is the initial setup and learning curve. Grafana Labs is a powerful tool, but new users may need some time to understand data sources, queries, dashboards, and alerts. In the FIT project, setting up and organizing monitoring for different services requires some configuration and technical knowledge. More guided setup options and beginner-friendly configuration would make it easier for new users to get started.

What problems is the product solving and how is that benefiting you?

In the FIT project, Grafana Labs helps us monitor application performance and identify issues more quickly. Instead of checking different services separately, we can use dashboards to monitor important metrics such as API performance, Kafka consumer activity, and system resources. This gives us better visibility into the production environment and makes it easier to investigate slow services or errors.

What do you like best about the product?

I really appreciate being able to have multiple different data sources like the system, applications, and network all in one place with Grafana Labs. This allows me to centralize all my monitoring data in one place, which is really convenient.

What do you dislike about the product?

The setup process is very complex at first, and there is not really any accessible documentation or support to help. The initial integration is complicated, you have to ensure everything works correctly, then integrate our internal tools one by one.

What problems is the product solving and how is that benefiting you?

I use Grafana Labs to centralize all my monitoring data in one place, bringing together different sources like the system, applications, and network.

What do you like best about the product?

Grafana Labs stands out for how flexible it becomes once you start working with it. What I like most is the dashboard side, because I can bring different monitoring data into one place and build views around what I actually want to see, instead of being stuck with the same fixed dashboard for everything.

The integrations are another big plus. Grafana can work with metrics, logs, traces, and different databases, so it stays useful even when the data is coming from different places. I also like the Explore area for jumping from a dashboard into the underlying data when I want to understand what’s really happening.

One thing I find especially useful, but that people may not notice immediately, is how much you can do with variables, panel queries, and dashboard links. Once these are set up properly, dashboards become more interactive, and you don’t have to keep creating separate dashboards for every small use case.

The new Grafana Assistant is also interesting, because I don’t always have to remember PromQL, LogQL, or other query languages. I can just explain what I’m looking for and get the query I need. Overall, I also like that Grafana doesn’t feel locked into one type of data. There’s definitely a big learning curve, but it’s worth it.

What do you dislike about the product?

The biggest thing I dislike about Grafana is that it can become complicated and expensive to manage as usage grows. At the beginning, it was easy enough to get dashboards running, but once you have more data sources, logs, longer retention, and more dashboards, there are a lot of things to keep track of. I also found the pricing a little difficult to predict, because Grafana Cloud can depend on things like usage, data volume, and retention. That makes it hard to know what the cost will look like when your monitoring requirements increase.

Another issue for me was the learning curve. Grafana is very flexible, but that flexibility also means there are many settings, query languages, and configuration options to understand. For a simple monitoring requirement, sometimes it felt like more setup and maintenance than I wanted.

What problems is the product solving and how is that benefiting you?

The main problem Grafana solves is that monitoring data is usually spread across different places. Instead of checking separate tools for metrics, logs, traces, and infra data, Grafana gives you one place to bring that information together and understand what is happening. For example, if there is a sudden increase in errors, I can start with the metric, look at the related logs, and then follow the trace to see where the problem is coming from. That makes troubleshooting much easier than trying to match everything manually between different tools. Another benefit is the dashboards and alerting. I can have the important system information visible in one dashboard and get alerted when something crosses a threshold instead of someone reporting on production.

Overall, I would say it helps when something is wrong to understand.