

Splunk Observability Cloud and Observer GigaStor engage in the network and application monitoring arena. Splunk Observability Cloud holds an advantage in pricing and support as it offers better cost-effectiveness and customer service. Observer GigaStor, meanwhile, shines in feature richness, especially for network forensics.
Features: Splunk Observability Cloud provides real-time analytics, customizable dashboards, and seamless integration with cloud services, offering expansive monitoring capabilities. It supports creating tailored views for various environments, thereby simplifying data insights. Observer GigaStor delivers detailed packet capture, extensive forensic analysis, and can capture data for long-term analysis, offering comprehensive solutions for troubleshooting network issues. Its technology enables precise monitoring of application performance and user response times, facilitating in-depth analysis.
Room for Improvement: Splunk Observability Cloud could enhance its packet capture capabilities to compete more directly with Observer GigaStor in forensic depth. Its forensic analysis options also need improvement for handling complex network analyses. Observer GigaStor could benefit from easier deployment options to reduce its setup complexities. Enhancing cloud integration would also improve its competitive stance, as well as offering more user-friendly interfaces for non-technical users.
Ease of Deployment and Customer Service: Splunk Observability Cloud features a straightforward deployment process with efficient cloud integration, supporting rapid implementation for businesses. Its customer service is robust, handling various scale operations and offering resolution assistance efficiently. Conversely, Observer GigaStor's on-premise setup is complex and time-consuming but provides specialized troubleshooting services, fostering efficiency in detailed technical support.
Pricing and ROI: Splunk Observability Cloud provides competitive pricing options, offering significant ROI through effective and scalable monitoring solutions. It appeals to businesses seeking cost-effective options with strong service and support. Observer GigaStor's upfront costs are higher, but its advanced feature set can justify the investment, delivering value through detailed analysis, performance optimization, and enhanced network security. The robust features it provides can offset the initial financial outlay, ensuring long-term benefits for in-depth technical monitoring needs.
| Product | Market Share (%) |
|---|---|
| Splunk Observability Cloud | 1.3% |
| Observer GigaStor | 0.4% |
| Other | 98.3% |


| Company Size | Count |
|---|---|
| Small Business | 5 |
| Large Enterprise | 3 |
| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 10 |
| Large Enterprise | 48 |
Observer GigaStor is a network analysis tool that comes in a variety of form factors, including rack mount, portable, and virtual. Capable of storing up to a petabyte of traffic for later analysis, GigaStor helps ensure optimal network and application performance.
Splunk Observability Cloud offers sophisticated log searching, data integration, and customizable dashboards. With rapid deployment and ease of use, this cloud service enhances monitoring capabilities across IT infrastructures for comprehensive end-to-end visibility.
Focused on enhancing performance management and security, Splunk Observability Cloud supports environments through its data visualization and analysis tools. Users appreciate its robust application performance monitoring and troubleshooting insights. However, improvements in integrations, interface customization, scalability, and automation are needed. Users find value in its capabilities for infrastructure and network monitoring, as well as log analytics, albeit cost considerations and better documentation are desired. Enhancements in real-time monitoring and network protection are also noted as areas for development.
What are the key features?In industries, Splunk Observability Cloud is implemented for security management by analyzing logs from detection systems, offering real-time alerts and troubleshooting for cloud-native applications. It is leveraged for machine data analysis, improving infrastructure visibility and supporting network and application performance management efforts.
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