Splunk Observability Cloud and Red Hat OpenShift Container Platform both serve the cloud solutions category. Splunk seems to have an advantage in comprehensive data monitoring, while OpenShift excels in advanced container orchestration and security.
Features: Splunk Observability Cloud enhances visibility with advanced dashboard features, offers a detailed service map, and provides robust capabilities that improve incident resolution times. OpenShift stands out with its powerful container orchestration capabilities, seamless CI/CD pipeline integration, and granular application deployment control.
Room for Improvement: Splunk users recommend improvements in database connectivity and real-time network device integration. The high-cost data volume licensing and need for better sampling methods are areas to address. OpenShift users desire enhanced documentation for cloud migrations, simplified deployment setups, and improved network security features.
Ease of Deployment and Customer Service: Splunk requires complex initial configuration but benefits from its cloud-based, cross-environment deployment model. Customer support experiences are mixed, impacted by slow response times. OpenShift offers strong deployment capabilities for hybrid and on-premise environments but presents a steep learning curve for newcomers. Its responsive support meets enterprise needs, yet documentation could be more comprehensive.
Pricing and ROI: Splunk's high-cost model, tied to data volume, can deter smaller enterprises but offers ROI through enhanced operational efficiency. OpenShift presents a costly solution with flexible licensing, providing ROI by reducing infrastructure management costs and boosting application scalability. Its premium pricing warrants careful consideration.
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.
They should prioritize skilled engineers for urgent issues.
They often require multiple questions, with five or six emails to get a response.
Support from Splunk is not very helpful because Splunk doesn't have a dedicated APM; they only have one APM engineer in Korea.
They did respond to us, but they did not explicitly inform us about the feature's absence.
I rate the scalability of Red Hat OpenShift Container Platform as a nine, as I haven't encountered any issues with scaling a cluster or applications.
Scalability is rated nine out of ten.
We've used the solution across more than 250 people, including engineers.
I would rate its scalability a nine out of ten.
The issue is mainly about pricing because if they want to monitor more, it costs money.
There haven't been any issues so far; it remains stable with no downtime or crashes, and even the upgrades are handled seamlessly without issues.
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 solution itself doesn't require a high learning curve; it is actually quite good to manage.
I would like to see advanced cluster management added in future releases, such as a single pane of glass to manage multiple clusters.
There is room for improvement in the alerting system, which is complicated and has less documentation available.
Improvements in dashboard configuration, customization, and artificial intelligence functionalities are desired.
Customers sometimes need to create specific dashboards, particularly for applicative metrics such as Java and process terms.
The current licensing cost for this solution is around $23,000 per year, per month.
Regarding whether Red Hat OpenShift Container Platform is expensive or if the price is reasonable for my customers, to me, the services it provides should incur some costs, but based on market feedback, it is quite expensive.
Splunk is a bit expensive since it charges based on the indexing rate of data.
It appears to be expensive compared to competitors.
Splunk is a little expensive, however, it is in line with the current market pricing.
It is important for critical systems.
The cluster scaling features, such as the auto-scaling of cluster nodes and application replicas using horizontal and vertical pod auto-scaling, significantly impact our operations.
In terms of features in Red Hat OpenShift Container Platform, I find the orchestration itself quite useful for my customers because it integrates with lots of tools.
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.
Red Hat® OpenShift® offers a consistent hybrid cloud foundation for building and scaling containerized applications. Benefit from streamlined platform installation and upgrades from one of the enterprise Kubernetes leaders.
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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