Prometheus-AI Platform Reviews

We use the solution to understand different metrics: RAM usage, CPU usage, application utilization, application performance, container metrics, port metrics, and network metrics.

Prometheus is an open-source product that helps mold and improve it per our requirements. It is a lightweight solution that gives you many different metrics you can use in your application. The product offers complete granularity of your infrastructure. 

It integrates seamlessly with other tools like Grafana, which offers dashboard visibility. Prometheus is an extensively used product. I haven't seen any organization that is not using it. 

Prometheus can be initially difficult for users since it has its query language, PromQL. The minimalistic interface is complicated to understand. They need to improve their interface so that users who don't know PromQL can also use it. You can only leverage the tool when you know PromQL. 

I have been using the product for a year. 

Prometheus is very stable. 

The solution is lightweight, and you can scale it however you want. It is used mainly by our DevOps team, which consists of 10-20 people. 

We haven't contacted the tech support team yet. The tool has rich documentation and a good Slack community. It is a mature tool, and there are a lot of people who have used it. You can get answers to any query or confusion from them. 

Prometheus' deployment is easy and can be completed in seconds. 

Prometheus has both licensed and open-source versions. Most people use the open-source version. The licensing costs are not expensive. 

I rate the product a nine out of ten. 

Our company uses the solution to scrape values from environments in central or sister premises to ensure safety. 

Kavana serves as our general user interface. The solution is used by developers, not general users by default. Developers access the solution when they want to see more details. 

The solution has very much improved our functionality and productivity. 

The solution offers an easy way to install and scratch values. 

The rest API is really valuable.  

The alert functionality is kind of lackluster. 

I have been using the solution for seven years. 

The solution is stable so far, but it might be interesting to view reports. 

For example, we were advised to check memory because Linux has an OOM killer that needs to be watched or monitored. 

The scalability is okay for the default parameters. It would be beneficial to have some kind of context included with the default parameters. We are pursuing this type of information or reporting right now for our Kefana project. 

Depending on the outcome of our RFP, we may be scaling in the near future. 

I have not contacted technical support. 

I did not use a different solution. 

The setup is pretty easy. 

We partnered with Grafana for implementation. 

One day a week if needed, a team member works with Grafana for any ongoing maintenance or support. There really isn't much to do so sometimes maintenance occurs less often. 

The solution is open source so is free. A paid version is also available. 

I rate the solution a seven out of ten. 

My company uses Prometheus because Zabbix is only useful for server machines.

In Prometheus, users can see the logs and containers while also getting to do HTTP monitoring under a single platform.

The most valuable feature of the solution stems from the fact that the HTTP monitoring capabilities offered by the solution help our company monitor SSL certificates while also helping us know if a site can be reached or not. The aforementioned details can be easily acquired with the help of the tool. On the normal desktop, you can create a dashboard from Grafana by using Loki's console.

The services offered by the product are good. Zabbix's site needs improvement.

In Prometheus, everything is query-based. Users can write up queries based on the metrics. In Prometheus, everything is fully for query-based applications. If you want to collect details of metrics, you should be able to write a query for it directly. I want the product to offer better queries for the metrics.

I have three years of experience with Prometheus. I am a user of the tool.

Right now, I don't see any bug-related issues in the product. In the performance part, everything seems to be good.

My company has opted for a centralized setup of the tool, so we have one dashboard set up for multiple applications. Our company's main goal of using the tool is to monitor our applications.

The product's initial setup phase is very easy.

The solution is deployed on an on-premises model.

It is an open-source tool.

Whether I would suggest the product to others or not is something that depends on the applications they use. If you use applications in the government sector or any other sector, then you need to know that the tool fully monitors the applications, and if there are any issues, the details of such problems can be directly acquired through the solution.

The tool is easy to learn and use.

I rate the tool a ten out of ten.

We use Prometheus to monitor the health of more than 300 to 400 servers, including their uptime, CPU memory usage, and iowait.

The most valuable feature of Prometheus is the ease of pulling the metrics.

The solution's error handling part could be improved. The errors that are sometimes shown are not accurate enough to debug. The code base can be improved so that the debugging part is easy if Prometheus is not working. The error should be so that the user can easily understand where the issue could be, and it would become easy to debug.

I have been using Prometheus for one year.

We had issues with the solution's stability regarding SSL certificates around a year back, but now it's stable.

I rate the solution an eight out of ten for stability.

Whenever a new region comes up on any of the clouds, like Azure, Google, or AWS, we need to add Prometheus servers over there, and the metrics need to be pulled from those new servers. Every month, we increase the number of servers where Prometheus is used. We did not find any challenges, and we are able to view the metrics.

I rate the solution a nine out of ten for scalability.

I joined my current company around one and a half years ago. Since that time, we have been using Prometheus. In my previous organization, we used a separate stack for monitoring solutions, including an open-source solution called Telegraf.

The initial setup of the solution is easy because it has pretty good documentation.

We were able to deploy Prometheus, Grafana, and Loki, and we were able to pull the metrics from more than 300 servers in one week.

Prometheus is an open-source solution.

I would recommend Prometheus to other users. If you have to monitor the health of multiple servers, just write an Ansible playbook or a Salt state, and the ease of deployment of Prometheus to any number of services is really easy. We are also using SSL certificates with the solution. With Prometheus, you will not face any security issues. It's a great monitoring solution for pulling the metrics.

Overall, I rate the solution a nine out of ten.

The solution is used for monitoring the metrics of applications. The applications have multiple functions, and each function should be monitored. I contact the developer teams to add the solution to the applications. I also use Alertmanager. If, for a specific test, a required metric is below the expected rate, the alert manager will fire a notification to the users.

The solution is useful to collect huge metrics. We have multiple applications. Collecting metrics from all the environments in my data center using the solution is very simple. The dashboards are very useful.

The product must allow users to run multiple instances to get metrics. Thanos is a bit complicated to deploy. It would be better if the solution provided a tool similar to Thanos natively.

I have been using the solution for two to three years.

The product is stable, but sometimes, when we run heavy queries like line data for the previous 24 hours, the CPU and memory utilization are very high. So, we use the product for shorter queries, like line data for the previous 30 minutes or an hour.

The scalability must be improved. More than 20 people use the tool indirectly.

My colleagues use Grafana. Grafana is integrated into Prometheus in our organization.

The initial setup is very easy. It took us an hour to deploy the tool.

It is not difficult to maintain the solution because I run it on Kubernetes.

The tool is open-sourced.

Prometheus is a famous solution. It is a useful product for monitoring application metrics. It needs a developer team to monitor the application functions completely. There are different dashboards like SLO and SLI dashboards. It also has an alert manager tool. The tool is important for modern applications because modern applications employ microservices. The product helps monitor all the functions, but it lacks scalability. Overall, I rate the solution an eight out of ten.

We use Prometheus for monitoring all aspects of our infrastructure end-to-end. That includes servers, virtual machines, databases, caching servers, ELK stack, and our Kubernetes servers. We are users of Prometheus.

The scraping mechanism is a wonderful feature. I've used many other monitoring systems that were mostly client-server-based models including Nagios, Zabbix, and New Relic, among others. With all of them, the server used to get overloaded when the client sent too much matrix, even in the case of a pull or push mechanism of client-server architecture. In my previous organization, we had to host several Nagios individual servers in case one went down. Prometheus gives us high availability automatically and a stand-alone process; if it doesn't run on one server, it runs on another. It's wonderful that the exports run on different servers. They scrape the matrix and then open it to a particular URL for Prometheus to read those metrics and then store them. 

I very much like the remote write feature. Prometheus bridges the gap for everyone whether they've come from an old monitoring setup or are into microservices. I also like the concept of dynamic conflict which is brilliant. 

We chose Prometheus because it's open source with a lot of documentation and community support which is lacking in other products.  

The Prometheus community says it's not meant to be clusterized so people shift to solutions like Thanos and VictoriaMetrics. Prometheus could have done that too, it's not complicated. Rather than us having to use a different database, Prometheus could develop its own database a little more so that it becomes a one-stop solution. That would be wonderful. 

One of the issues is that dynamic conflict uses regular expressions and it can be confusing for people not familiar with them and the unique specific symbols and line-cut characters. 

I've been using this solution for six years. 

The product is stable. In my previous company, we used Prometheus with Docker Compose and kept high data retention. We didn't have a third database to store the matrix so the container used to go down very often. The issue was not with Prometheus but that there were insufficient resources for the monitoring system. 

40% of those in our company need Prometheus for their daily work, including developers. Indirectly, that number goes to 80% when you include those reliant on the reporting. We do everything through Prometheus. We also use Nagios for monitoring bare metals and in a way Nagios monitors Prometheus and Prometheus monitors Nagios. In that way, we're able to monitor two different monitoring systems.

The solution is not meant to scale.

There is good documentation and the open source community offers good support, so I haven't needed to contact customer support. 

Prometheus is very easy to set up and is user friendly. It just runs and gets you a very simple UI running on export. Where it becomes complicated is people not understanding the configuration because its support of many exporters means a lot of jobs need to be written in order to use it well.

Deployment time depends on the use case. Our present use case is quite complex so implementation took about a week. We wanted to monitor 10 to 15 clusters so we had to deploy Prometheus on a different environment and ensure that our data was placed at a stable central location. We initially carried out a POC which took less than a day.

The solution is open source. 

If a company uses bare metal systems and their product doesn't need significant extensive monitoring, I wouldn't recommend Prometheus. That's not because it's difficult to use but because it doesn't qualify for that use case. If you have a use case where you already have microservices deployed and you want information, then that's a suitable use case. Otherwise, Nagios or any other simple operating system is easier to use. It depends on what kind of product needs monitoring.

In spite of the scaling issue, Prometheus provides almost everything I need. Despite needing to integrate it with other tools, it's seamless and simple to use. I rate this solution 10 out of 10.

Our primary use case for Prometheus is collecting metrics.

The feature I found most valuable is the number of integrations. It is the industry standard for metrics.

If you are not quite technical, it can be pretty hard to understand the way it works and how to query data in Prometheus.

In the next release, I'd like to see a more user-friendly interface where you can have more options on the graphical interface and more integrations that can help with the scalability.

I have been using Prometheus for about five years.

I would rate the stability of Prometheus a nine, on a scale from one to 10, with one being the worst and 10 being the best.

I would rate the scalability of this solution a five, on a scale from one to 10, with one being the worst and 10 being the best.

In case you want to make it more scalable, you can add other open-source projects like Thanos that can integrate with Prometheus.

I have not contacted technical support because there is none. The community is the technical support.

The initial setup of Prometheus was easy.

The deployment time mostly depends on the desired use case for Prometheus.
For example, monitoring a couple of servers would take about one hour to deploy. On the other hand, if you are planning to deploy several clusters or Kubernetes and other managed services, that adds complexity, and then deployment takes days or even weeks.

The reason we didn't go with, for example, AWS X-ray, Azure Monitor, or AppDynamics is that we didn't want to be tied to a specific provider.

I would advise others that before buying this solution they make a good design and think about their use case because the metrics can scale rapidly as can the amount of data you ingest. Without a good design, that might not be possible.

Overall, I would rate the Prometheus solution a nine, on a scale from one to 10, with one being the worst and 10 being the best. The reason for this is because it's open source, so there are no fees. There are no licenses to pay for and it has a great community. 

Prometheus became the standard of the industry for metrics as you can find a lot of documentation, forums, and many answers to any questions online. Also, Prometheus has constant updates to improve applications and to fix either the box or the issues. The ability to integrate with a wide range of other applications makes this solution even better.

We have Prometheus deployed in both the public cloud and on-premises.

There are about 100 users of Prometheus in our company.

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.