

Splunk Observability Cloud and Evanios compete in the IT monitoring space. Splunk offers superior data collection and analytics, while Evanios excels in integration and automation, making them equally compelling choices based on user needs.
Features: Splunk Observability Cloud offers real-time data ingestion, robust anomaly detection, and advanced analytics tools which are essential for dynamic IT environments. Evanios focuses on centralized event management, advanced automation features, and seamless integration capabilities, which streamline IT operations.
Room for Improvement: Splunk could enhance its user interface for easier navigation in complex environments, improve integration with certain third-party tools, and reduce its steep learning curve. Evanios could benefit from simplifying its initial setup process, expanding its documentation for broader configuration scenarios, and enhancing scalability for larger data sets.
Ease of Deployment and Customer Service: Splunk Observability Cloud offers straightforward deployment backed by extensive documentation and strong customer support, ensuring a smooth user experience. Evanios, while integrated seamlessly, might require more on-site support due to complex configurations. Personalized assistance is available for intricate setups to ensure successful deployments.
Pricing and ROI: Splunk Observability Cloud might have higher upfront costs but justifies it with fast analytics-driven ROI. Its comprehensive analytics capabilities lead to quicker insights and operational efficiencies. Evanios offers substantial ROI through its competitive pricing and advanced automation features, lowering operational costs over time, making it attractive for long-term value.
Using Splunk has saved my organization about 30% of our budget compared to using multiple different monitoring products.
Anyone working in front-end management should recognize the market price to see the true value of end-user monitoring.
I have definitely seen a return on investment with Splunk Observability Cloud, particularly through how fast it has grown and how comfortable other teams are in relying on its outputs for monitoring and observability.
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.
They often require multiple questions, with five or six emails to get a response.
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.
I would rate its scalability a nine out of ten.
I would rate its stability a nine out of ten.
We rarely have problems accessing the dashboard or the page.
Unlike NetScout or regular agents for APM, RUM has many problems during the POC phase because customer environments vary widely.
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 is room for improvement in the alerting system, which is complicated and has less documentation available.
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.
It appears to be expensive compared to competitors.
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 | Market Share (%) |
|---|---|
| Splunk Observability Cloud | 2.0% |
| Evanios | 0.4% |
| Other | 97.6% |

| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 10 |
| Large Enterprise | 47 |
A key component of the Event Management process is consolidation of events from across the enterprise. By consolidating disparate events into a single solution, they can be de-duplicated and correlated. For example, network failure events can be correlated with system failures, and then prioritized based on service impact.
Reduce the noise
Evanios Integrations allows filtering and processing close to the event source, keeping the weight off of the ServiceNow system for increased performance. Filters are easily configured. EVA, the Evanios consolidation point also has built in event flood control features, to protect against unexpected event storms which can quickly overload traditional integrations.
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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