

Splunk Observability Cloud and Red Hat OpenShift both compete in the field of monitoring and infrastructure management. While Splunk Observability Cloud excels in monitoring and alerting, OpenShift gains an advantage with its robust container orchestration and seamless CI/CD integration.
Features: Splunk Observability Cloud offers adaptable data gathering, efficient log analysis, and custom dashboard creation, making it suitable for security and application performance analysis. It also provides comprehensive monitoring and alerting features. Red Hat OpenShift is notable for its container orchestration, scalability, and strong security features. It integrates well with developer tools and supports CI/CD pipelines and multi-cloud environments.
Room for Improvement: Users of Splunk Observability Cloud point out cost issues and desire better integration with various tools and platforms. Enhancements in user experience would be beneficial. Red Hat OpenShift users highlight improvements needed in documentation, ease of setup, and more comprehensive integration with cloud services and legacy systems. Both solutions face pricing challenges, with potential for cost reduction.
Ease of Deployment and Customer Service: Splunk Observability Cloud supports on-premises, cloud, and hybrid environments. Customer service receives mixed reviews, with good response times but areas needing technical support improvement. Red Hat OpenShift supports diverse deployment needs with emphasis on integration with on-premises and private cloud solutions. Users commend Red Hat's strong support, though some deployment complexities exist.
Pricing and ROI: Both products are perceived as expensive. Splunk is often seen as pricier in data indexing and enterprise capabilities but provides ROI through improved efficiencies and monitoring. Red Hat OpenShift's cost is justified by value in security, integration, and enterprise support. Despite high costs, both solutions offer returns through enhanced operational performance and resource management.
With OpenShift combined with IBM Cloud App integration, I can spin an integration server in a second as compared to traditional methods, which could take days or weeks.
Moving to OpenShift resulted in increased system stability and reduced downtime, which contributed to operational efficiency.
It is always advisable to get the bare minimum that you need, and then add more when necessary.
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.
Red Hat's technical support is responsive and effective.
Customer support is really good because so far in our case, we have always received a prompt response, and they have been really helpful to us.
I have been pretty happy in the past with getting support from Red Hat.
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.
The on-demand provisioning of pods and auto-scaling, whether horizontal or vertical, is the best part.
OpenShift's horizontal pod scaling is more effective and efficient than that used in Kubernetes, making it a superior choice for scalability.
Red Hat OpenShift scales excellently, with a rating of ten out of ten.
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.
It provides better performance yet requires more resources compared to vanilla Kubernetes.
I've had my cluster running for over four years.
It performs well under load, providing the desired output.
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.
Learning OpenShift requires complex infrastructure, needing vCenter integration, more advanced answers, active directory, and more expensive hardware.
Red Hat OpenShift's biggest disadvantage is they do not provide any private cloud setup where we can host on our site using their services.
We should aim to include VMware-like capabilities to be competitive, especially considering cost factors.
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.
Initially, licensing was per CPU, with a memory cap, but the price has doubled, making it difficult to justify for clients with smaller compute needs.
The pricing for Red Hat OpenShift is considered quite high.
Red Hat can improve on the pricing part by making it more flexible and possibly on the lower side.
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.
Because it was centrally managed in our company, many metrics that we had to write code for were available out of the box, including utilization, CPU utilization, memory, and similar metrics.
The concept of containers and scaling on demand is a feature I appreciate the most about Red Hat OpenShift.
A valuable feature of Red Hat OpenShift is its ability to handle increased loads by automatically adding nodes.
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 | 0.7% |
| Red Hat OpenShift | 3.5% |
| Other | 95.8% |


| Company Size | Count |
|---|---|
| Small Business | 17 |
| Midsize Enterprise | 4 |
| Large Enterprise | 43 |
| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 10 |
| Large Enterprise | 47 |
Red Hat OpenShift offers a robust, scalable platform with strong security and automation, suitable for container orchestration, application deployment, and microservices architecture.
Designed to modernize applications by transitioning from legacy systems to cloud-native environments, Red Hat OpenShift provides powerful CI/CD integration and Kubernetes compatibility. Its security features, multi-cloud support, and source-to-image functionality enhance deployment flexibility. While the GUI offers user-friendly navigation, users benefit from its cloud-agnostic nature and efficient lifecycle management. However, improvements are needed in documentation, configuration complexity, and integration with third-party platforms. Pricing and high resource demands can also be challenging for wider adoption.
What are the key features of Red Hat OpenShift?Red Hat OpenShift is strategically implemented for diverse industries focusing on container orchestration and application modernization. Organizations leverage it for migrating applications to cloud-native environments and managing CI/CD pipelines. Its functionality facilitates efficient resource management and microservices architecture adoption, supporting enterprise-level DevOps practices. Users employ it across cloud and on-premises platforms to drive performance improvements.
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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