ScienceLogic and Elastic Observability compete in the monitoring software category. Based on features, ScienceLogic holds an edge due to its infrastructure monitoring and customization capabilities, while Elastic Observability stands out for its strong logging and cost-effectiveness.
Features: ScienceLogic provides robust infrastructure monitoring with dynamic apps and Power Packs, extensive integration capabilities, and multi-tenancy with fine-grained permissions. Elastic Observability integrates well with various solutions via its Kibana dashboard, offering strong logging capabilities, end-to-end monitoring, and flexible data visualization.
Room for Improvement: ScienceLogic could improve reporting functionality, streamline setup for common features, and enhance documentation for troubleshooting backend issues. Elastic Observability needs better application performance metrics, easier configuration tools, and standardized logging.
Ease of Deployment and Customer Service: ScienceLogic supports deployment on-premises and private clouds and is appreciated for its rapid and knowledgeable customer service. Elastic Observability offers deployment across on-premises, hybrid, and public cloud environments, with positive customer service feedback but needing improvement in detailed deployment assistance.
Pricing and ROI: ScienceLogic offers flexible pricing that can become expensive with increased endpoint monitoring, with significant ROI due to reduced incident times. Elastic Observability provides an affordable structure, particularly for large-scale use, with open-source options and positive ROI, but smaller businesses may find pricing tiers less accessible.
Elastic Observability seems to have a good scale-out capability.
What is not scalable for us is not on Elastic's side.
It is very stable, and I would rate it ten out of ten based on my interaction with it.
Elastic Observability is really stable.
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.
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.
Elastic Observability is cost-efficient and provides all features in the enterprise license without asset-based licensing.
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.
All the features that we use, such as monitoring, dashboarding, reporting, the possibility of alerting, and the way we index the data, are important.
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.
ScienceLogic is a comprehensive IT infrastructure monitoring solution that supports networks, servers, cloud environments, and applications, suitable for private cloud and on-premises deployments.
Organizations leverage ScienceLogic for its robust capabilities in monitoring IT infrastructures of all sizes. It offers granular discovery, integration with CMDB, and ticketing systems. Valued for its flexibility, incident automation, remediation, and real-time relationship mapping, it supports hybrid environments with scalable and efficient monitoring functionalities. AI and machine learning enhance its feature set, while ease of deployment and strong support are crucial benefits.
What are ScienceLogic's most important features?ScienceLogic is implemented across multiple industries, including large enterprises, for its capability to handle complex IT ecosystems. Its integration with CMDB and ticketing systems ensures it fits within existing workflows. Organizations use it to monitor diverse infrastructure landscapes, ensuring seamless performance and quick incident resolution.
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