Elastic Observability and Prometheus Group compete in the monitoring and data collection category. Elastic Observability appears to have the upper hand due to its extensive features and ease of deployment, although Prometheus stands out for its metrics collection and cost-effectiveness.
Features: Elastic Observability offers integrated features, scalability, and real-time data analysis via Kibana. It includes exceptional search capabilities, ease of deployment, and comprehensive plugins. Prometheus is known for powerful metrics collection, flexibility, and integration with Grafana, all key aspects for efficient monitoring.
Room for Improvement: Elastic Observability could enhance automation, visualization, and user management controls. It also has potential to grow in predictive analytics and overall ease of use. Prometheus should improve dashboard visualization, query language accessibility, and cluster management while expanding exporter support and documentation.
Ease of Deployment and Customer Service: Elastic Observability is preferred for its simple deployment in hybrid and cloud environments, with strong support and resources for premium users. Prometheus, while flexible across deployments, may require technical expertise for setup and lacks direct vendor support, though it benefits from a strong community.
Pricing and ROI: Elastic Observability, although premium, offers solid ROI by reducing incidents and providing complete visibility, making it competitive for large organizations though costly for small enterprises. Prometheus, being open-source, provides cost-effectiveness without licensing fees, though managed services might incur additional costs.
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.
For instance, if you have many error logs and want to create a rule with a custom query, such as triggering an alert for five errors in the last hour, all you need to do is open the AI bot, type this question, and it generates an Elastic query for you to use in your alert rules.
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 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.
Observability is actually cheaper compared to logs because you're not indexing huge blobs of text and trying to parse those.
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.
Every integration, whether for Windows or Linux or even Palo Alto or Fortinet, installs the out-of-the-box dashboards along with it, making it easy to parse incoming data meaningfully and immediately start viewing dashboards to see what's happening in the platform.
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 Group specializes in robust monitoring and observability, offering comprehensive data collection, analysis, and visualization across cloud and on-premise environments. Its integration with tools like Python, Java, and Kubernetes enables users to track metrics efficiently.
Prometheus Group provides an open-source, customizable platform focused on flexibility and reliability. Its integration with Grafana enhances data visualization while supporting complex infrastructures for improved productivity. Users rely on its scalable architecture for effective monitoring and observability, aiding performance analytics and alerting. Despite its strengths, challenges with its query language and interface usability persist, along with a need for simpler setup. Enhancing documentation and reporting capabilities remains essential for broader adoption, especially among less technical users.
What are the standout features of Prometheus Group?Prometheus Group is widely implemented across industries like cloud services and IT infrastructure. Organizations monitor infrastructure, applications, and databases, utilizing its capabilities for system scalability and health checks within Azure and Amazon ecosystems. Its integration with Kubernetes supports performance monitoring and ensures reliable data analytics, fostering comprehensive metric tracking.
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