Prometheus Reviews

We use Prometheus for observability and analyzing data for business metrics and system metrics. It helps us with messaging services observability. It also helps a lot with the architecture and scalability of the services. The solution provides system observability regarding Kubernetes information, CPU usage, memory, and whether the system is scaling or not.

The resilience of the solution's metric collection is very nice. Although it's very strict about the number of unique metrics for each service, the metrics collection is very powerful.

There is a tool called Prometheus Exporter that doesn't work well. I don't know if Prometheus maintains it or if it's an open-source service. When we have Cron jobs from our services, Prometheus needs a live endpoint to collect the metrics.

Since Cron jobs have a time limit, I rely on Prometheus Exporter to collect metrics. When I send metrics for Prometheus Exporter, it doesn't work very well.

I have been using Prometheus for four to five years.

I’ve never had any stability issues with the solution.

I rate the solution’s stability ten out of ten.

Prometheus is a scalable solution.

I would recommend the solution to other users.

Overall, I rate the solution an eight out of ten.

The most valuable features of Prometheus are its ability to collect metrics and its integration with Grafana.

The primary area where Prometheus could be improved is in terms of pricing, particularly when used with managed services like AWS. Many clients have found the pricing for managed services steep, prompting them to switch to the open-source version. This switch has led to the adoption of Prometheus with Amazon EKS. Still, it has also resulted in high data transfer costs due to the multitude of microservices and the associated cluster logs. As a result, clients are facing higher bills, primarily driven by increased data transfer rates and bandwidth usage.

We have been using Prometheus for two and a half years.

It is a stable product.

It is a scalable platform.

The initial setup is easy if you have good knowledge of Helm. It requires setting two to three commands. Without using Helm, you have to create custom file deployments. Overall, it is a simple process.

The alerting functionality provided by Prometheus has significantly improved our incident response time. It enables us to gather data from various instances or ports within our environment, such as ETS.

I advise others to gain essential knowledge of query optimization and Grafana. It is an expensive product if utilized with managed services. It would be beneficial to use the open-source version.

I rate it a nine out of ten.

We use the product for financial transaction monitoring.

Prometheus provides a flexible and adjustable querying and describing time, allowing for more responsive monitoring. The integration with long-term storage solutions like VictoriaMetrics is a valuable feature.

There is a need for a more comprehensive overview of exporters, especially when dealing with many of them. We currently deal with 20 exporters; sometimes, the labels don't match. Clarity and detailed information on relabeling would benefit users, including explanations on enabling different behaviors and understanding labeling methods.

There could be more granular UI and integration with Grafana. The metric inventory and dictionary could be simpler to understand with a flexible UI. Additionally, they should provide support drill-down selection for Grafana, similar to Azure Monitor.

We have been using Prometheus for more than three years.

It is a stable platform. However, sometimes we encounter stability issues with Kubernetes environment configuration.

The product is suitable for enterprise businesses.

I found a lot of good support articles and case studies. I have a positive opinion about the technical support services.

My previous company used InfluxDB. In comparison, Prometheus has a much better and more scalable monitoring system.

The complexity of the initial setup depends on the particular task. The deployment time varies from a few minutes to a few days per project requirement, including development, staging, and production. The time for data pipeline creation also varies as per different parameters. We have a team of more than 20 executives to monitor the process. Further, it is easy to maintain.

We evaluated Dynatrace or other APM solutions.

We managed services in Azure and AWS. Prometheus is a better product than other native monitoring systems. It provides an efficient bridge between multi-cloud infrastructure. I rate it a nine out of ten.

Prometheus is an open-source monitoring system, but Amazon offers a managed service that takes care of all the setup and maintenance for us. 

We also use Grafana on top of Prometheus to create dashboards that visualize the metrics collected by Prometheus. This is a common setup that many companies use for monitoring their containerized workloads.

We go and see the metrics for any issues with our code. You get to know CPU consumption, memory consumption, all that. That's how we use it for monitoring purposes.

The good thing is it integrates well with the Grafana dashboard. It comes with a UI where you see everything as a graph. And that's similar to what New Relic also gave. So, it's in tandem with Grafana to experience the UI. We have a graph and a software dashboard. We see all the metrics.

There is always room for improvement. 

In future releases, I would like to see more automation. For example, Prometheus automatically picks up some of the metrics from the infrastructure or from the application using its own plugins that it deploys. 

I have been using this tool for around three years.

It is a stable solution.

From a scalability point of view, it's pretty scalable because we are using it for multiple applications and for multiple applications. 

We are on a Kubernetes cluster. We are on a multiple-names basis. So it's pretty scalable. It depends on how you use it. I did a POC long back, so for Amazon, that's pretty much scalable. That's why people use managed services because Amazon or any cloud vendor is responsible for scaling up and scaling down as we are using it. So the management is scalable, for sure.

We have around 200 end-users using this solution in my team.

Prometheus installation is pretty easy. We are using the managed one from Amazon. So that's easy. You don't have to install anything. It comes as a service, like a software service from AWS. But even then, installing that, I've done it long back. It's not complex; it's pretty easy.

The deployment doesn't take more than half an hour. However, for any unmanaged solution, you have to maintain it. For example, there will be updates to the solution on your end. But if you're using the managed ones from Amazon, you don't have to worry about those updates. Maintenance: that mechanism will take care of it. You just have to use it and consume it. 

Prometheus is open source, so you can install it on your own or use a managed service like Amazon Managed Prometheus. We chose to use a managed service because it's easier to manage and scale.

We have the open-source version, so we don't pay for it.

Overall, I would rate the solution an eight out of ten.

I use Prometheus to monitor my application, system, and database.

The best thing about Prometheus is its integration. It's completely flexible and customizable, which is great. You have a lot of flexibility with Prometheus.

Prometheus can definitely improve its visualization. For example, the matrices represented in Prometheus do not have a very good visualization on their dashboard. The graphs displayed in Prometheus are not well-animated, so that is the area Prometheus can work on to make it more precise and better.

In the future release, logs are the thing I would add here. Currently, Prometheus does not have anything to log in to an application. So, I would definitely like to add that feature. Additionally, Prometheus has a lot of exporters, but they do not have any exporters for a database except MySQL. So, I would like to add more exporters for other data sources like databases.

I have been using this solution for three months now. I am using the latest version of Prometheus. The previous version I used was 2.43.0.

It is a stable product.

Prometheus is a scalable product.

Prometheus is an open source tech. You can go over to the online community for support, and your queries will be answered. 

It's an easy setup. I would rate it a three on a scale of one to ten, where one is very easy, and ten is very complex. The whole setup took around a week.

I would say that you can use Prometheus as it's definitely good to work with, and if you need any support from me, you can definitely contact me.

Overall, I would rate the solution an eight out of ten.

We use it for monitoring our infrastructure metrics.

It is highly valuable as it serves as the foundation for our infrastructure monitoring tools.

The installation process proved to be exceptionally straightforward.

The interface is not particularly user-friendly and that could be improved.

We have been using it for two years.

I would rate its stability abilities eight out of ten.

I would rate its scalability capabilities eight out of ten.

The initial setup was straightforward, thanks to our utilization of the Kubernetes operator.

In terms of ROI, you can potentially save a few weeks, or perhaps two to three days, depending on the use case.

We evaluated Elastic and Kibana.

I recommend it because it's an incredibly useful tool, and its installation and usage are very straightforward. Overall, I would rate it eight out of ten.

We use the solution as a centralized system to monitor multiple servers.

The solution's most valuable feature is exporters. It helps us extract data from multiple sources and store it in a single place. It is a user-friendly data voucher that gets insights and essential information about our servers. It works well for the end production environment.

The solution's documentation needs improvement. Presently, we need help to get metrics. Whenever CPU utilization is high, we should receive alerts on emails. But, we encounter difficulties here as the documentation is unclear.

I have been using the solution for the last two months.

It is a stable solution. We have deployed it for around 20+ servers and multiple dashboards.

It is a scalable solution. We have around 50 solution users in our organization.

We used CloudWatch before. Later, we switched to Prometheus for centralized dashboards and extensive data capacity.

The solution's initial setup process was relatively easy. We followed the documentation to understand the essential steps required for deployment.

We use the solution's open-source version.

I recommend Prometheus as it has multiple exposures. I rate the overall solution a seven out of ten.

We use all of the metrics of Prometheus as an indicator if something goes wrong with our own applications as part of our on-call service. We represent the data on Grafana because Grafana is tightly integrated with Prometheus.

It has lots of APIs and libraries to integrate with any kind of language, including Python, Perl, PHP, Java, and Kotlin. You can easily plug and play integrating Prometheus with many operators. The official operators can be run on top of Kubernetes. It is a widely known and good solution for monitoring. 

The simplicity of the query language could be improved. The current query language is not easy to work with.

I have been using Prometheus for the past year.

Prometheus is definitely stable.

I do not handle scalability because it is managed by other teams.

I would recommend that you use it with simple applications, by running a Docker inside the Docker. It is a good and robust solution, and it is widely known by many companies across the software domain. I would rate Prometheus a nine out of ten.