Splunk Observability Cloud and Google Kubernetes Engine compete in the cloud management and observability space. Splunk Observability Cloud has the upper hand in comprehensive data insights and customization, while Google Kubernetes Engine excels in container management and integration with diverse cloud platforms.
Features: Splunk Observability Cloud offers robust data gathering, efficient log analysis, and customizable dashboards, allowing for detailed reports and extensive integrations. It supports multiple environments, making it suitable for diverse monitoring needs. Google Kubernetes Engine focuses on container deployment ease, automatic scaling, and seamless integration with the Google ecosystem, providing strong capabilities in managing microservices and multi-cloud environments. GKE is noted for its auto-scaling abilities and integration with native Google services like BigQuery and Vertex AI.
Room for Improvement: Users of Splunk Observability Cloud seek improvement in integration with other solutions, pricing, and support for innovative features like AI. They also suggest enhancements in interface navigation and customization. Google Kubernetes Engine users point to documentation and cost management as areas needing attention, along with an enhanced monitoring console and security features. GKE's backup system and user interface could benefit from improvements.
Ease of Deployment and Customer Service: Splunk Observability Cloud supports public, private, and hybrid cloud deployments, offering flexibility but requiring more expertise. Users find its technical support responsive, though not always consistent. Google Kubernetes Engine offers ease of use in cluster deployment and is primarily based in public and hybrid cloud environments. While its customer service is streamlined, users experience challenges similar to those of Splunk when dealing with complex issues.
Pricing and ROI: Splunk Observability Cloud is often considered expensive due to data volume-based pricing, which can increase costs for larger deployments. Despite cost concerns, users report seeing a return on investment through efficiencies and reduced downtime. Google Kubernetes Engine's pricing, based on cloud resource usage, is considered flexible, appealing to cost-sensitive deployments. Users appreciate its balance of cost and functionality, noting significant ROI through streamlined and cost-effective operations.
By migrating from AWS to Google Cloud Platform, we have saved a lot of time and money.
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 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.
The autoscaling capabilities of Google Kubernetes Engine have significantly impacted our operations.
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.
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.
When looking at the web interface, it feels kind of slow due to the many features involved.
Log observability could be made easier so someone from high school can use it without having technological expertise.
It would be helpful if I could easily find log information in a particular namespace without needing to write certain labels.
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.
Google is considered cheaper compared to AWS, making it suitable for smaller to medium companies concerning cost.
The on-demand nodes are 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.
The most valuable aspect of Google Kubernetes Engine (GKE) is its managed nature, which significantly reduces the burden on our platform team.
GKE is easier to understand and use than Elastic Kubernetes Service.
What I find most valuable is the ability to focus solely on my product without worrying about the Kubernetes infrastructure itself.
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.
Kubernetes Engine is a managed, production-ready environment for deploying containerized applications. It brings our latest innovations in developer productivity, resource efficiency, automated operations, and open source flexibility to accelerate your time to market.
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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