Elastic Observability and Prometheus compete in software operations monitoring and observability. Prometheus seems to have the upper hand due to its efficient metrics collection, alerting features, and scalability in large-scale environments.
Features: Elastic Observability users highlight its data indexing, search capabilities, and Kibana integration for visualizing large datasets. Prometheus is praised for its lightweight nature, efficient metrics collection, and powerful query language for handling time-series data.
Room for Improvement: Elastic Observability could enhance real-time data monitoring, streamline its setup process, and improve long-term data storage options. Prometheus could reduce the complexity of its configuration files, enhance its configuration ease, and improve long-term data storage options.
Ease of Deployment and Customer Service: Elastic Observability benefits from comprehensive documentation and strong customer support, simplifying the onboarding process. Prometheus has a manual setup complexity but benefits from an active, supportive community and extensive plugins.
Pricing and ROI: Elastic Observability's pricing reflects its broad-feature set, with users generally reporting a favorable ROI. Prometheus, being open-source, offers a cost-effective solution with lower ongoing costs, making it appealing for budget-conscious users.
Using open-source Prometheus saves me money compared to AWS native services.
Prometheus does not offer traditional technical support.
Elastic Observability seems to have a good scale-out capability.
What is not scalable for us is not on Elastic's side.
Prometheus is scalable, with a rating of ten out of ten.
It is very stable, and I would rate it ten out of ten based on my interaction with it.
Elastic Observability is really stable.
Deploying it on multiple instances or using Kubernetes for automatic management has enhanced its stability.
It lacked some capabilities when handling on-prem devices, like network observability, package flow analysis, and device performance data on the infrastructure side.
One example is the inability to monitor very old databases with the newest version.
Elastic Observability could improve asset discovery as the current requirement to push the agent is not ideal.
Elastic Observability is cost-efficient and provides all features in the enterprise license without asset-based licensing.
The license is reasonably priced, however, the VMs where we host the solution are extremely expensive, making the overall cost in the public cloud high.
Prometheus is cost-effective for me as it is free.
The most valuable feature is the integrated platform that allows customers to start from observability and expand into other areas like security, EDR solutions, etc.
the most valued feature of Elastic is its log analytics capabilities.
All the features that we use, such as monitoring, dashboarding, reporting, the possibility of alerting, and the way we index the data, are important.
It allows me to save money by avoiding costs associated with AWS native services like CloudWatch or Amazon Prometheus.
Elastic Observability is primarily used for monitoring login events, application performance, and infrastructure, supporting significant data volumes through features like log aggregation, centralized logging, and system metric analysis.
Elastic Observability employs Elastic APM for performance and latency analysis, significantly aiding business KPIs and technical stability. It is popular among users for system and server monitoring, capacity planning, cyber security, and managing data pipelines. With the integration of Kibana, it offers robust visualization, reporting, and incident response capabilities through rapid log searches while supporting machine learning and hybrid cloud environments.
What are Elastic Observability's key features?Companies in technology, finance, healthcare, and other industries implement Elastic Observability for tailored monitoring solutions. They find its integration with existing systems useful for maintaining operation efficiency and security, particularly valuing the visualization capabilities through Kibana to monitor KPIs and improve incident response times.
Prometheus specializes in gathering, monitoring, and analyzing logs and metrics. Utilized for data visualization in Grafana, cloud deployments, Kubernetes monitoring, and financial transactions, it provides a comprehensive view of application performance.
Prometheus is widely adopted for its robust metrics collection and scraping capabilities. It integrates seamlessly with Grafana for detailed visualizations and supports installations in cloud environments like Azure and Amazon. Prometheus is especially valued for monitoring Kubernetes deployments and ensuring efficient operation of servers, databases, and microservices. Its open-source nature provides reliability, flexibility, and scalability. Users appreciate its extensive integrations, APIs, and libraries, supporting multiple languages. Prometheus also offers remote writing, dynamic conflict resolution, high availability, and lightweight configuration with detailed documentation.
What are the key features of Prometheus?Prometheus is extensively used in industries requiring robust monitoring and alerting systems. Financial services leverage it for tracking transactions, while tech companies deploy it for Kubernetes and microservices monitoring. Its scalable and flexible nature makes it a preferred choice for cloud environments, supporting the efficient operation of infrastructure and applications.
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