

Splunk Observability Cloud and Eggplant Test are contenders in the enterprise IT solutions sector, focusing on observability and automated testing, respectively. Splunk Observability Cloud has an edge in scalability and data handling, making it preferable for complex environments, while Eggplant Test shines in broad automated testing capabilities.
Features: Splunk Observability Cloud excels in handling high data volumes with features such as APM monitoring, real-time metrics dashboards, and fast incident alerting. Its wide integration capabilities and user adaptability make it ideal for complex environments. Eggplant Test stands out with advanced scripting languages, robust automation capabilities, and OCR technology, catering well to GUI automation across various platforms.
Room for Improvement: Splunk Observability Cloud could aim for better cost transparency, enhanced log management, and smoother new user onboarding. Users seek more refined alert systems and improved integration options. Eggplant Test can improve its installation processes, further enhance the IDE, and provide better documentation. Users also express the need for more intuitive pre-programmed actions and stability in recognition features.
Ease of Deployment and Customer Service: Splunk Observability Cloud offers flexible deployment options across hybrid and cloud environments, backed by highly-rated customer support known for quick response times and valuable guidance. Eggplant Test, primarily on-premises, supports businesses with strict security needs, though some users indicate room for improvement in documentation and support scope.
Pricing and ROI: Splunk Observability Cloud is perceived as expensive, with pricing based on data volume but offers significant operational efficiency and ROI through enhanced visibility and performance management. Eggplant Test's high cost is justified for large enterprises due to its comprehensive capabilities but may be less attractive to smaller firms when compared to other market tools.
We have saved considerable amounts of money, reducing our expenditures from around three to four crores to approximately one to one point two crores.
We have been able to save a great deal of money, and our profits have increased by twenty percent.
Using Splunk has saved my organization about 30% of our budget compared to using multiple different monitoring products.
Eggplant Test offers 24x7 support.
I'm not impressed because it depends on the resolution of the screen, so I wouldn't highly recommend this tool.
On a scale of 1 to 10, the customer service and technical support deserve a 10.
They have consistently helped us resolve any issues we've encountered.
The customer support system is the foundational pillar of any successful business.
We've used the solution across more than 250 people, including engineers.
As we are a growing company transitioning all our applications to the cloud, and with the increasing number of cloud-native applications, Splunk Observability Cloud will help us achieve digital resiliency and reduce our mean time to resolution.
We have never seen any kind of downtime or crashes, as it has been absolutely very easy to scale.
When downtime occurs, it raises concerns about how we measure and receive alerts, as everything needs to be in place.
Splunk Observability Cloud is very stable.
It is highly scalable because it can handle approximately up to one hundred applications at a time without any lapse or lag.
For big problems and complex automation tasks, I would prefer UFT because it has more flexibility and is more effective.
The two-system architecture that we currently follow could be better replaced with a one-system architecture.
The out-of-the-box customizable dashboards in Splunk Observability Cloud are very effective in showcasing IT performance to business leaders.
The next release of Splunk Observability Cloud should include a feature that makes it so that when looking at charts and dashboards, and also looking at one environment regardless of the product feature that you're in, APM, infrastructure, RUM, the environment that is chosen in the first location when you sign into Splunk Observability Cloud needs to stay persistent all the way through.
There should be a solution to update OTeL agents from Splunk Observability Cloud itself.
Splunk is a bit expensive since it charges based on the indexing rate of data.
It is expensive, especially when there are other vendors that offer something similar for much cheaper.
I can confidently say our availability improved by forty percent, and downtime was reduced by approximately seventy to eighty percent.
It can auto-heal the test cases and suggest new paths for testing, enhancing our ability to automate end-to-end journeys across various applications.
It can integrate with GitHub, allowing you to work with DevOps pipelines, so whenever you make changes in GitHub, it runs and checks the smoke testing on the server.
Splunk provides advanced notifications of roadblocks in the application, which helps us to improve and avoid impacts during high-volume days.
For troubleshooting, we can detect problems in seconds, which is particularly helpful for digital teams.
It offers unified visibility for logs, metrics, and traces.
| Product | Mindshare (%) |
|---|---|
| Splunk Observability Cloud | 6.4% |
| Eggplant Test | 1.5% |
| Other | 92.1% |

| Company Size | Count |
|---|---|
| Small Business | 4 |
| Midsize Enterprise | 3 |
| Large Enterprise | 14 |
| Company Size | Count |
|---|---|
| Small Business | 33 |
| Midsize Enterprise | 9 |
| Large Enterprise | 56 |
Eggplant Test stands out with its AI-driven and image recognition features, facilitating quick bug detection across multiple systems. Its ease of use, coupled with robust integration capabilities, makes it a top choice for efficient and comprehensive testing solutions.
Offering OCR, image recognition, and extensive AI capabilities, Eggplant Test enhances automation and reduces testing time. Known for its versatility, it operates independently from system constraints and supports scriptless testing. With a user-centric design, the tool integrates with platforms like GitHub and operates on diverse operating systems. Despite advancements, considerations include its affordability, installation complexities, and need for better text recognition and stability. Its success is bolstered by seamless scripting, robust reporting features, and the option for digital twin utilization, making it ideal for real-world user action simulations.
What are the most important features of Eggplant Test?Industries utilize Eggplant Test primarily for regression and GUI automation testing, especially in desktop applications. Its capacity for post-development validation and vulnerability scanning supports businesses with testers having minimal coding experience. Deployed on virtual machines, it effectively tests web pages, Windows apps, and streaming devices, simulating real-world user actions efficiently. Eggplant Test's role in simplifying robotic process automation and functional testing is significant, offering a spectrum of operational support across varied sectors.
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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