Sentry and Prometheus-AI Platform are competing products in monitoring and error tracking. Prometheus-AI Platform appears superior due to its robust feature set, which justifies the investment.
Features: Sentry offers real-time error tracking, alerting capabilities, and seamless integration with popular apps. The Prometheus-AI Platform provides a comprehensive analytics suite with AI-driven insights, predictive analytics, and advanced data processing capabilities.
Room for Improvement: Sentry could enhance AI capabilities, predictive analytics, and customer support. Prometheus-AI Platform could improve deployment simplicity, reduce initial costs, and refine its integration with more platforms.
Ease of Deployment and Customer Service: Prometheus-AI Platform's deployment is straightforward with comprehensive steps and strong customer service support. Sentry offers an effortless setup with minimal configuration but lacks advanced customer support.
Pricing and ROI: Sentry offers competitive setup costs with significant ROI due to its straightforward pricing model. Prometheus-AI Platform has a higher initial cost but provides substantial long-term ROI with its extensive functionality and AI-focused features.
Using open-source Prometheus saves me money compared to AWS native services.
Prometheus does not offer traditional technical support.
We have not contacted their technical support because everything is easy to set up under Sentry.
Prometheus is scalable, with a rating of ten out of ten.
We have not encountered any scalability issues with Sentry.
Deploying it on multiple instances or using Kubernetes for automatic management has enhanced its stability.
Integrations or single sign-on capability with Microsoft would be beneficial for securing all assets.
Prometheus is cost-effective for me as it is free.
Compared to New Relic, it provides the necessary features at a cheaper cost, especially since we moved infrastructure monitoring to Azure.
It allows me to save money by avoiding costs associated with AWS native services like CloudWatch or Amazon Prometheus.
Real-time error tracking helps our Quality Assurance team easily identify the root causes of problems or bugs and promptly inform the developers about specific issues.
Sentry provides real-time error tracking which is invaluable for identifying and resolving issues quickly.
At this time, I focus on finding and fixing bugs.
| Product | Market Share (%) |
|---|---|
| Prometheus-AI Platform | 0.8% |
| IBM Maximo | 18.3% |
| IFS Cloud Platform | 8.4% |
| Other | 72.5% |
| Product | Market Share (%) |
|---|---|
| Sentry | 4.5% |
| Dynatrace | 7.4% |
| Datadog | 6.0% |
| Other | 82.1% |
| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 8 |
| Large Enterprise | 13 |
| Company Size | Count |
|---|---|
| Small Business | 7 |
| Midsize Enterprise | 3 |
| Large Enterprise | 3 |
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.
Sentry is a robust error management system known for real-time error tracking and integration with tools like Slack, GitLab, and Jira, benefiting those seeking comprehensive application performance insights.
Sentry offers a seamless platform to monitor errors in both front-end and back-end applications, providing real-time alerts and comprehensive event log context. With its integration capabilities, teams effectively track application metrics and access performance data without direct production access, ensuring enhanced reliability. Sentry's features such as event grouping and code trace logs linked to Git repositories highlight its utility in maintaining application efficiency. Enhanced security and regular updates make it a preferred choice over competitors. Despite some requests for improvements in automation and UI enhancements, Sentry remains invaluable for error management and application performance monitoring.
What are the key features of Sentry?In industries like technology, Sentry is crucial for monitoring errors in web applications, offering real-time alerts and performance tracking. It is frequently used in ETL processes to detect failures without direct developer access, benefiting teams who manage large-scale applications and databases efficiently.
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