Grafana and Prometheus-AI Platform are both leaders in the monitoring and visualization category. Grafana appears to have the upper hand in visualization capabilities, while Prometheus is stronger in data collection and real-time metrics.
Features: Grafana is known for its extensive visualization features, with customizable dashboards and seamless integration with tools like Zabbix and Nagios. It is an open-source solution, providing significant cost savings. Grafana's flexibility allows for the creation of varied graphs and visual representations. Prometheus is distinguished by its data reliability and quick storage capabilities. It supports a wide range of metric functions and offers open-source adaptability, providing a flexible solution for various monitoring needs.
Room for Improvement: Users point out that Grafana needs to enhance security measures, error messaging, and cross-source data aggregation. Improvements in setup integration and simplification of complex query writing are also necessary. Prometheus needs to improve its basic visualization tools and address occasional instability. Enhancements in UI and additional exporter options are desirable. Both tools can benefit from better documentation and training resources.
Ease of Deployment and Customer Service: Both Grafana and Prometheus offer on-premises and cloud solutions. Grafana is often deployed on-premises and backed by a robust community that assists in issue resolution. Prometheus, primarily used in hybrid and public cloud environments, also relies on community support with adequate documentation, though new users find the learning curve steep.
Pricing and ROI: Grafana and Prometheus are largely open-source, providing affordable solutions. Grafana's visual capabilities are recognized for potentially enriching data analytics ROI. Prometheus's open-source nature offers cost-effectiveness and flexibility in handling expenses. For large-scale deployments, both platforms provide paid versions or managed services to balance costs and features.
Using open-source Prometheus saves me money compared to AWS native services.
My advice for people who are new to Grafana or considering it is to reach out to the community mainly, as that's the primary benefit of Grafana.
I very rarely get in touch with technical support as we don't have that option.
I do not use Grafana's support for technical issues because I have found solutions on Stack Overflow and ChatGPT helps me as well.
Prometheus does not offer traditional technical support.
In assessing Grafana's scalability, we started noticing logs missing or metrics not syncing in time.
In terms of our company, the infrastructure is using two availability zones in AWS.
Prometheus is scalable, with a rating of ten out of ten.
When something in their dashboard does not work, because it is open source, I am able to find all the relative combinations that people are having, making it much easier for me to fix.
Once you get to a higher load, you need to re-evaluate your architecture and put that into account.
The product has been stable.
Deploying it on multiple instances or using Kubernetes for automatic management has enhanced its stability.
I would give it a ten if it were much simpler for users who just want to get a simple objective in Grafana and are not experienced with technical configuration.
Regarding the clarity of the official documentation for installation, I think the official documentation, which has something called Alloy, the Alloy integration, is not that clear.
It would be better if they made the technology easy to use without needing to read extensive documentation.
In an enterprise setting, pricing is reasonable, as many customers use it.
The costs associated with using Grafana are somewhere in the ten thousands because we are able to control the logs in a more efficient way to reduce it.
Prometheus is cost-effective for me as it is free.
Users can monitor metrics with greater ease, and the tool aids in quickly identifying issues by providing a visual representation of data.
We can find information with Grafana much more quickly compared to DataDog because it was open source and there was extensive documentation about it, enabling us to fetch data or information much more quickly using AI tools.
The feature that sets Grafana apart from its competitors is how easy it is to set up data sources.
It allows me to save money by avoiding costs associated with AWS native services like CloudWatch or Amazon Prometheus.
Company Size | Count |
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Small Business | 13 |
Midsize Enterprise | 8 |
Large Enterprise | 24 |
Company Size | Count |
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Small Business | 14 |
Midsize Enterprise | 8 |
Large Enterprise | 12 |
Grafana is an open-source visualization and analytics platform that stands out in the field of monitoring solutions. Grafana is widely recognized for its powerful, easy-to-set-up dashboards and visualizations. Grafana supports integration with a wide array of data sources and tools, including Prometheus, InfluxDB, MySQL, Splunk, and Elasticsearch, enhancing its versatility. Grafana has open-source and cloud options; the open-source version is a good choice for organizations with the resources to manage their infrastructure and want more control over their deployment. The cloud service is a good choice if you want a fully managed solution that is easy to start with and scale.
A key strength of Grafana lies in its ability to explore, visualize, query, and alert on the collected data through operational dashboards. These dashboards are highly customizable and visually appealing, making them a valuable asset for data analysis, performance tracking, trend spotting, and detecting irregularities.
Grafana provides both an open-source solution with an active community and Grafana Cloud, a fully managed and composable observability offering that packages together metrics, logs, and traces with Grafana. The open-source version is licensed under the Affero General Public License version 3.0 (AGPLv3), being free and unlimited. Grafana Cloud and Grafana Enterprise are available for more advanced needs, catering to a wider range of organizational requirements. Grafana offers options for self-managed backend systems or fully managed services via Grafana Cloud. Grafana Cloud extends observability with a wide range of solutions for infrastructure monitoring, IRM, load testing, Kubernetes monitoring, continuous profiling, frontend observability, and more.
The Grafana users we interviewed generally appreciate Grafana's ability to connect with various data sources, its straightforward usability, and its integration capabilities, especially in developer-oriented environments. The platform is noted for its practical alert configurations, ticketing backend integration, and as a powerful tool for developing dashboards. However, some users find a learning curve in the initial setup and mention the need for time investment to customize and leverage Grafana effectively. There are also calls for clearer documentation and simplification of notification alert templates.
In summary, Grafana is a comprehensive solution for data visualization and monitoring, widely used across industries for its versatility, ease of use, and extensive integration options. It suits organizations seeking a customizable and scalable platform for visualizing time-series data from diverse sources. However, users should be prepared for some complexity in setup and customization and may need to invest time in learning and tailoring the system to their specific needs.
Prometheus-AI Platform offers flexible solutions for collecting, visualizing, and comparing metrics, appreciated for its scalability, rich integrations, and open-source adaptability.
Prometheus-AI Platform provides a reliable framework for monitoring and analyzing metrics across diverse environments. With extensive API support, it supports data collection, querying, and visualization, integrating seamlessly with tools like Grafana. High availability, scalability, and lightweight configuration make it suitable for traditional and microservice environments, while community support enhances its utility. Though its query language and interface require improvements for better ease of use, and with calls for stronger integration options, the platform remains a leading choice for comprehensive metric analysis.
What are Prometheus-AI Platform's main features?Companies leverage Prometheus-AI Platform across various industries, utilizing it to monitor and analyze metrics from applications and infrastructure. It is extensively used in financial services and IT sectors for collecting, scraping logs, and monitoring Kubernetes deployments. Deployed both on-premise and in cloud environments like Azure and Amazon, it supports system and application metrics analysis, ensuring a comprehensive view for developers.
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