Overall, I would rate it an eight out of ten. I would recommend it to other and would recommend that they should go for it because I have experience with it for some time, and they keep evolving and continuously improving. I know they have a lot of new features coming up. I think the team is doing great already.
It is easy for a beginner to learn to use Grafana Loki for the first time. I would recommend the solution to other users. Overall, I rate the solution an eight out of ten.
We are creating multiple dashboards and panels for multiple use cases like CPU, memory, and I/O wait. We are using it for our infrastructure through which clients register to our images. We see in which region how many registrations were done, how much info was denied, and what normal info messages are there. We have over 100 dashboards for each cloud, including Amazon, Azure, and Google. We monitor what's happening on our infra, how many clients have registered, how many have faced issues, what the issues were, and different error logs. We are using Grafana Loki as a monitoring solution. If any of the servers are down, we start our debugging process by looking at the dashboard. We examine what went wrong and how many registrations failed and look at that time frame's logs. We view everything on Grafana. The database on the back end is Grafana Loki, and the metrics are pulled from Prometheus. All three tools go hand in hand. One person is on call every week. We have on-call rotations for any kind of debugging. An engineer checks almost every day or every second day. We actively use the solution every second day to see what's happening on the infrastructure and the production environment and how things are going. I would recommend the solution to other users. Overall, I rate the solution an eight out of ten.
In the tool, I use Promtail and Loki for log utilization. Speaking about the scenarios in which I use Grafana Loki in terms of application debugging or incident response, I would say that I use the tool for Kubernetes cluster. In our company, we use the tool when we have to deal with container logs in a pod. I feel that Grafana Loki is a better tool to use, especially for monitoring your infrastructure and resources. I rate the overall tool a nine out of ten.
For my use cases, Grafana Loki is a good tool. I recommend people use the latest version of the product since the older version may have a few missing features. I rate the overall tool a nine out of ten.
DevOps Engineer at a comms service provider with 501-1,000 employees
Real User
Top 5
2023-11-16T10:31:37Z
Nov 16, 2023
I recently changed jobs and am trying to get my new team to use Grafana Loki. They are currently using Elasticsearch. Considering the market, I would recommend the product to others. The deployment is easy, but the management is hard. However, it is far better than Elasticsearch. Overall, I rate the tool an eight or nine out of ten.
I would suggest going for it. However, my recommendation would also depend on the use cases. There are heavy solutions like full-text search engines, such as Solar and Elasticsearch. These are built mainly for e-commerce purposes, but the downside is the large metadata. This means high storage costs. Maintaining logs also contributes significantly to maintaining metadata. For example, for a terabyte of data, if your metadata is just a few GBs, that's an advantage with Loki. If any node fails because your backend data is in S3 and the metadata is small, it recovers quickly. If you need it only for logging purposes, I'd suggest going for it. Loki offers quick wins over other solutions and is also cost-effective. The operation overhead of maintaining it is very minimal. Overall, I would rate the solution an eight out of ten. The reason is quite simple. These guys have introduced the concept of a unified dashboard, which is commendable. This unified dashboard allows us to monitor logs and metrics side by side. In terms of microservice architecture, if you observe a metric from a certain part and you also see the logs for that same part side by side, it makes diagnosing issues straightforward. For instance, if there was a spike at a particular time, you can directly correlate it with the logs right beside it. Additionally, there's flexibility in log formats. Loki doesn't restrict you to JSON, XML, or CSV. For example, today, if I'm using ContainerD and it's writing in JSON, and tomorrow, if I have another tool writing in plain text format, Loki adapts seamlessly. It parses my logs and allows analytics on top of them. Plus, it now supports SQL-like syntax, which further boosts its versatility. The tool’s single UI supports metrics, logs, and even tracing. You can integrate tracing tools with Loki and access everything from a unified platform. The data complexity is high, but it’s efficiently stored on S3 or any object-based storage, ensuring cost efficiency. Loki also utilizes the same service discovery mechanism as used by Prometheus. So, whatever labeled metadata you see in Prometheus, you have the exact same metadata in the Loki system. Given this level of intricacy and the attempt to address these challenges, I firmly believe that they deserve praise for their work.
MLOps Engineer at a tech services company with 501-1,000 employees
MSP
Top 10
2023-10-18T09:47:00Z
Oct 18, 2023
When contemplating dashboarding tools, Grafana Loki stands out due to its beginner-friendly features. While novices might start with simpler tools, Grafana could be a preferred choice depending on integration needs. Given its ability to aggregate logs from diverse services and its integration with Kubernetes, Grafana sometimes emerges as the sole viable option. For those venturing into Grafana, I'd advocate fully harnessing its features. Monitor metrics, such as API and memory usage, and delve into the specifics of Kubernetes products. Establish dashboards, configure alerts, and sync them with platforms like Slack for effective communication. Leveraging the support of open-source communities can be invaluable—be it through initiating new GitHub discussions or scrutinizing existing ones. It's also imperative to stay updated with Grafana. Outdated versions can pose challenges, from UI glitches to query and alert configurations. Regularly checking the change log helps in staying abreast of resolved issues. While we deploy across multiple clusters, the differences are often minimal. We predominantly rely on a single deployment, with others remaining largely underutilized. To encapsulate my experience, I'd assign Grafana Loki a score of seven out of ten.
Director of Cyber Security & Resilience at Novibet
Real User
Top 5
2023-09-06T06:49:53Z
Sep 6, 2023
I recommend the solution to those who plan to use it since it is a flexible open-source monitoring tool. I rate the overall solution a seven out of ten.
I am using the latest version of Grafana Loki. I'm using both the cloud and the on-premises Grafana Loki solution. Grafana Loki is simple to set up. Non-technical people can use it because it's so simple that you don't need to spend many hours checking or studying it. I suggest Grafana Loki as the first simple and cheap solution for somebody who wants some monitoring of their system. Overall, I rate Grafana Loki an eight out of ten.
Grafana Loki is a powerful log aggregation and analysis tool designed for cloud-native environments. Its primary use case is to collect, store, and search logs efficiently, enabling organizations to gain valuable insights from their log data.
The most valuable functionality of Loki is its ability to scale horizontally, making it suitable for high-volume log data. It achieves this by utilizing a unique indexing approach called "Promtail," which efficiently indexes logs and allows for fast...
Overall, I would rate it an eight out of ten. I would recommend it to other and would recommend that they should go for it because I have experience with it for some time, and they keep evolving and continuously improving. I know they have a lot of new features coming up. I think the team is doing great already.
It is easy for a beginner to learn to use Grafana Loki for the first time. I would recommend the solution to other users. Overall, I rate the solution an eight out of ten.
We are creating multiple dashboards and panels for multiple use cases like CPU, memory, and I/O wait. We are using it for our infrastructure through which clients register to our images. We see in which region how many registrations were done, how much info was denied, and what normal info messages are there. We have over 100 dashboards for each cloud, including Amazon, Azure, and Google. We monitor what's happening on our infra, how many clients have registered, how many have faced issues, what the issues were, and different error logs. We are using Grafana Loki as a monitoring solution. If any of the servers are down, we start our debugging process by looking at the dashboard. We examine what went wrong and how many registrations failed and look at that time frame's logs. We view everything on Grafana. The database on the back end is Grafana Loki, and the metrics are pulled from Prometheus. All three tools go hand in hand. One person is on call every week. We have on-call rotations for any kind of debugging. An engineer checks almost every day or every second day. We actively use the solution every second day to see what's happening on the infrastructure and the production environment and how things are going. I would recommend the solution to other users. Overall, I rate the solution an eight out of ten.
In the tool, I use Promtail and Loki for log utilization. Speaking about the scenarios in which I use Grafana Loki in terms of application debugging or incident response, I would say that I use the tool for Kubernetes cluster. In our company, we use the tool when we have to deal with container logs in a pod. I feel that Grafana Loki is a better tool to use, especially for monitoring your infrastructure and resources. I rate the overall tool a nine out of ten.
For my use cases, Grafana Loki is a good tool. I recommend people use the latest version of the product since the older version may have a few missing features. I rate the overall tool a nine out of ten.
I recently changed jobs and am trying to get my new team to use Grafana Loki. They are currently using Elasticsearch. Considering the market, I would recommend the product to others. The deployment is easy, but the management is hard. However, it is far better than Elasticsearch. Overall, I rate the tool an eight or nine out of ten.
I recommend it because it's highly useful. Overall, I rate it seven out of ten.
I would suggest going for it. However, my recommendation would also depend on the use cases. There are heavy solutions like full-text search engines, such as Solar and Elasticsearch. These are built mainly for e-commerce purposes, but the downside is the large metadata. This means high storage costs. Maintaining logs also contributes significantly to maintaining metadata. For example, for a terabyte of data, if your metadata is just a few GBs, that's an advantage with Loki. If any node fails because your backend data is in S3 and the metadata is small, it recovers quickly. If you need it only for logging purposes, I'd suggest going for it. Loki offers quick wins over other solutions and is also cost-effective. The operation overhead of maintaining it is very minimal. Overall, I would rate the solution an eight out of ten. The reason is quite simple. These guys have introduced the concept of a unified dashboard, which is commendable. This unified dashboard allows us to monitor logs and metrics side by side. In terms of microservice architecture, if you observe a metric from a certain part and you also see the logs for that same part side by side, it makes diagnosing issues straightforward. For instance, if there was a spike at a particular time, you can directly correlate it with the logs right beside it. Additionally, there's flexibility in log formats. Loki doesn't restrict you to JSON, XML, or CSV. For example, today, if I'm using ContainerD and it's writing in JSON, and tomorrow, if I have another tool writing in plain text format, Loki adapts seamlessly. It parses my logs and allows analytics on top of them. Plus, it now supports SQL-like syntax, which further boosts its versatility. The tool’s single UI supports metrics, logs, and even tracing. You can integrate tracing tools with Loki and access everything from a unified platform. The data complexity is high, but it’s efficiently stored on S3 or any object-based storage, ensuring cost efficiency. Loki also utilizes the same service discovery mechanism as used by Prometheus. So, whatever labeled metadata you see in Prometheus, you have the exact same metadata in the Loki system. Given this level of intricacy and the attempt to address these challenges, I firmly believe that they deserve praise for their work.
When contemplating dashboarding tools, Grafana Loki stands out due to its beginner-friendly features. While novices might start with simpler tools, Grafana could be a preferred choice depending on integration needs. Given its ability to aggregate logs from diverse services and its integration with Kubernetes, Grafana sometimes emerges as the sole viable option. For those venturing into Grafana, I'd advocate fully harnessing its features. Monitor metrics, such as API and memory usage, and delve into the specifics of Kubernetes products. Establish dashboards, configure alerts, and sync them with platforms like Slack for effective communication. Leveraging the support of open-source communities can be invaluable—be it through initiating new GitHub discussions or scrutinizing existing ones. It's also imperative to stay updated with Grafana. Outdated versions can pose challenges, from UI glitches to query and alert configurations. Regularly checking the change log helps in staying abreast of resolved issues. While we deploy across multiple clusters, the differences are often minimal. We predominantly rely on a single deployment, with others remaining largely underutilized. To encapsulate my experience, I'd assign Grafana Loki a score of seven out of ten.
I recommend the solution to those who plan to use it since it is a flexible open-source monitoring tool. I rate the overall solution a seven out of ten.
I am using the latest version of Grafana Loki. I'm using both the cloud and the on-premises Grafana Loki solution. Grafana Loki is simple to set up. Non-technical people can use it because it's so simple that you don't need to spend many hours checking or studying it. I suggest Grafana Loki as the first simple and cheap solution for somebody who wants some monitoring of their system. Overall, I rate Grafana Loki an eight out of ten.