Splunk Observability Cloud and AWS Auto Scaling cater to different infrastructure and application management needs. Splunk Observability Cloud often holds the advantage in terms of feature richness and customization options, while AWS Auto Scaling excels in cost-efficiency and seamless integration with AWS services.
Features: Splunk Observability Cloud delivers extensive data aggregation, log analysis, and application performance monitoring with customizable dashboards that offer detailed insights across platforms. It provides comprehensive features for security monitoring and data visualization. Alternatively, AWS Auto Scaling focuses on automatic resource allocation adjustment, efficient workload management within the AWS ecosystem, and offers robust integration with AWS services, enabling automatic self-healing and scale operations.
Room for Improvement: Splunk Observability Cloud requires enhanced third-party integration and a more intuitive user interface, and addressing cost-effectiveness with improved automation. AWS Auto Scaling could benefit from expanded security features, additional automation options, and a more refined pricing model. Both demand simpler initial setup and improved technical support to align with customer expectations more effectively.
Ease of Deployment and Customer Service: Splunk Observability Cloud supports diverse deployment environments, including on-premises, hybrid, public, and private clouds, allowing flexibility at times with added complexity. Customer support receives mixed reviews, with responsiveness needing more consistency. AWS Auto Scaling offers streamlined public cloud deployment benefiting AWS users specifically, while its customer support is generally reliable, although improvements in documentation clarity and response time are desirable.
Pricing and ROI: Splunk Observability Cloud presents a costly option with its data volume-based pricing model supporting scalability yet elevating expenses. Users acknowledge the value it offers in analytics and insights, contributing to ROI despite initial costs. Conversely, AWS Auto Scaling offers flexible and cost-effective pricing through a pay-as-you-go model aligning with cloud resource management needs, often resulting in positive ROI for users extensively utilizing AWS services.
| Product | Market Share (%) |
|---|---|
| Splunk Observability Cloud | 2.0% |
| AWS Auto Scaling | 0.3% |
| Other | 97.7% |
| Company Size | Count |
|---|---|
| Small Business | 11 |
| Midsize Enterprise | 2 |
| Large Enterprise | 11 |
| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 10 |
| Large Enterprise | 43 |
AWS Auto Scaling monitors your applications and automatically adjusts capacity to maintain steady, predictable performance at the lowest possible cost. Using AWS Auto Scaling, it’s easy to setup application scaling for multiple resources across multiple services in minutes. The service provides a simple, powerful user interface that lets you build scaling plans for resources including Amazon EC2 instances and Spot Fleets, Amazon ECS tasks, Amazon DynamoDB tables and indexes, and Amazon Aurora Replicas. AWS Auto Scaling makes scaling simple with recommendations that allow you to optimize performance, costs, or balance between them. If you’re already using Amazon EC2 Auto Scaling to dynamically scale your Amazon EC2 instances, you can now combine it with AWS Auto Scaling to scale additional resources for other AWS services. With AWS Auto Scaling, your applications always have the right resources at the right time.
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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