Elastic Observability and Grafana Loki compete in the monitoring and log management category. Grafana Loki appears to have the upper hand due to its superior features and efficient performance, although Elastic is well-regarded for its pricing and support.
Features:Elastic Observability offers comprehensive data integration, scalability, and a range of functionalities tailored for enterprise environments. Grafana Loki is noted for its simplicity, efficient log data management, and user-friendly interface, making it ideal for quick deployments and performance-focused users.
Room for Improvement:Elastic Observability could refine its search functionalities, ease configuration complexity, and streamline user interfaces. Grafana Loki users seek more advanced analytics, stronger integrations with other tools, and enhanced query capabilities.
Ease of Deployment and Customer Service:Elastic Observability has a more intricate deployment process supported by strong customer service, aiding user adoption. Grafana Loki offers straightforward deployment, though customer service experiences vary and indicate areas for improvement.
Pricing and ROI:Elastic Observability provides competitive pricing and a good return on investment, with considerations for initial setup costs. Grafana Loki, though seen as costly upfront by some, delivers efficient performance leading to substantial long-term savings.
We have not had to open any tickets yet, as we solve issues through forums and wikis.
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.
It would be beneficial if Loki could directly access Windows Server logs or events directly from the servers.
Elastic Observability seems to have a good scale-out capability.
What is not scalable for us is not on Elastic's side.
Loki offers great scalability, allowing us to manage and compress logs extensively.
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 cloud version is competitively priced compared to other market solutions.
It is very stable, and I would rate it ten out of ten based on my interaction with it.
Elastic Observability is really stable.
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.
The most valuable part of Loki is the ability to filter logs by keywords and devices.
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.
Grafana Loki is a powerful log aggregation and analysis tool designed for cloud-native environments. Its primary use case is to collect, store, and search logs efficiently, enabling organizations to gain valuable insights from their log data.
The most valuable functionality of Loki is its ability to scale horizontally, making it suitable for high-volume log data. It achieves this by utilizing a unique indexing approach called "Promtail," which efficiently indexes logs and allows for fast searching and filtering. Loki also supports log streaming in real-time, ensuring that organizations can monitor and analyze logs as they are generated.
By centralizing logs in a single location, Loki simplifies log management and troubleshooting processes. It provides a unified view of logs from various sources, making it easier to identify and resolve issues quickly. With its powerful query language, organizations can extract meaningful information from logs, enabling them to gain insights into system performance, identify anomalies, and detect potential security threats.
Loki's integration with Grafana, a popular open-source visualization tool, allows users to create rich dashboards and visualizations based on log data. This combination enhances the observability of systems and applications, enabling organizations to make data-driven decisions and improve overall operational efficiency.
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