NetApp Cloud Insights is an infrastructure monitoring tool that gives
users visibility into their complete infrastructure. With Cloud Insights, users can monitor, troubleshoot and optimize all resources including
public clouds and private data centers.
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Splunk Observability Cloud
Score 8.5 out of 10
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Splunk Observability Cloud aims to enable operational agility and better customer experience through real-time AI-driven streaming analytics allowing accurate alerts in seconds. It is designed to shorten MTTD and MTTR by providing real-time visibility into cloud infrastructure and services.
For a while, we were using Zabbix to monitor our Kubernetes applications and microservices on our infrastructure in more than one public cloud platform. Cloud Insights has much better visualized dashboards. In addition, despite such a large number of quality features, it's …
Cloud Insights is a very compact service compared to others. This is very compatible with the service selection policy suitable for the purpose. So you really pay for the part of the product you need, which increases your financial efficiency and lowers start-up costs (time to …
I assumed that this was a new product on the market and gave it a try since it had good customer feedback. So far it has done the job and provides some really good features.
Easy to install data collectors; the main focus of the product is multi-vendor cloud technology systems. Easy-to-use dashboards with widely supported features, which can be easily used in a WYSIWYG-manner. The NetApp data collector uses Telegraf as a way to integrate data from …
Cloud Insights allows us to create custom dashboards to monitor and trend any aspect of their infrastructure including CPU, memory, storage network utilization, IOPS, capacity utilization and more. Cloud Insights also provides visibility into the inter-connectivity of the …
Azure Bot Service isn't as responsive as Cloud Insights. Neither tool will pinpoint the problem exactly for you. If one did, that would be the clear choice. Work is still necessary to actually solve the problem, and Cloud Insights is more responsive to give the team more time …
it could stack up against this version of Splunk because in this instance of having the cloud option as an available use case it furthermore has more use cases and the options for the data to always be readily available will furthermore allows for analysts to review the data in …
Datadog pushes intom proprietary ecosystem and pricing structure.Compared to self hosted prometheus and grafarna but it gave headache og managing our own monitoring infrastructure at scale.Prometheus is excellent for scraping cluster metrics but it doesnt handle distributed …
I guess scale is the main factor against grafana and ease of use against amazon elasticsearch service and also i have used signoz and ELK Stack also, but stability Splunk Observability Cloud gives is too good and also it comes with high avability and you have to maintain …
We initially chose Splunk Observability Cloud because it promised full-stack visibility and tighter integration. The other tools didn't offer this as part of the core package. Their analytics and real-time dashboards looked strong during the demo but it turned out to a lot …
I selected Splunk Observability Cloud because it focused so much on OTEL standards which will help us in future as OTEL is covering most of the observability standards. And also it has the best Kubernetes observability as I already explained it has several predefined dashboards …
Splunk Observability Cloud stood out for its real-time data ingestion, native OpenTelemetry support, and seamless correlation between metrics, traces, and logs, which gave us faster root cause analysis and better end-to-end visibility compared to Grafana setups that required …
To be honest, Datadog is very similar to Splunk and LogScale to a lesser degree, but it is just as good if you don't need too complex observability. Grafana is still growing and might reach the same level soon.
It's able to quickly detect and resolve issues across the entire spectrum of deployments including on-premises, public cloud, private cloud, hybrid cloud and multicloud
The above applications have their own use cases. Thousand Eyes or Sitescope is used for URL monitoring and Splunk is used for application monitoring. Appdynamics is also used for application monitoring and can monitor the server very well but it lacks when searching in logs …
Splunk is superior in many ways to these solutions when I'm comes to ingesting, storing, manipulating, and using data, but dynatraces automatic agents do make it much easier to use out of the box. Nagios seems much cheaper but does not provide as much functionality as Splunk. …
SQL is a great tool for smaller quick checks. When trying to monitor several different environments, applications, APIs, several thousand devices, connections, and technology, it just doesn't stand up to what you need. Splunk Infrastructure Monitoring has really stood out …
We are having other monitoring tools like AppDynamics, Dynatrace, Datadog and already using their end-user monitoring capability. Most of our customers are looking for agent-free monitoring where they don't want to instrument any agent on their client-side (as it might …
Splunk Infrastructure Monitoring provides far superior options for anybody using a complex hybrid multi-cloud environment and allows both your SOC and NOC to work together on the same data while driving their own insights.
We found other products are still in the old world view …
For example, we had an application slowdown. It looked like the slowdown was storage. However, it was a malformed SQL query that no one realized was pulling data from the storage location that also housed the application. Cloud Insights saved us hours of downtime and frustration. Cloud Insights pinpointed which system was hogging resources. What makes Cloud Insights special is the way it looks at the data collected from the data sources. The insights it provides into the flow of data; sheds new light on how things work in your environment.
Good for below cases 1. There is a front end and need to correlate data with front end data 2. multiple microservices and need to check the health of each system 3. correlate data from various sources 4. Application performance is a key to be captured 5. application performance is a key metric.
The first one is its Kubernetes container monitoring.
I really like this features because as we know how much K8s is vast and to manually monitor each part of the Kubernetes it takes so much time but Splunk Observability Cloud makes it easier. And even once we integrate K8s with Splunk Observability Cloud it gives us some prebuilt dashboards which gives holistic view of our Cluster and its nodes, pods, etc.
The dashbaord feature of Splunk Observability Cloud, it gives us full flexibility to customize our dashboard with a wide range of predefined chart types.
Now it also supports OTEL, which is a plus point for observability. As now everyone is moving towards Otel and in current market there are only few tools who supports OTEL based integrations, Splunk Observability Cloud is one out of them.
An indicator for errors on the navigations pane so that we don't have to go through each tab.
As we go more and more cloud maybe you guys can implement a pay-as-you-use strategy so that small companies using it not frequently can also afford it.
That's it can't think of any and it wont let me skip to next question. Thanks
Good: Stable system with low error rate Easy to use for simple use cases Bad: UI is not very clear for complex usage Mobile view (when logged in from phone) is bad No library for .net
I have been extremely happy with its usability. You can take thins as they are out of the box and it is useful. You can carry it as far as you want to go and every step you take improves your ROI.
Overall a great tool to have in your toolbox, It is very intuitive and our entire staff uses the tool. It is easy to use and cost is very reasonable. Splunk also has excellent support team and very easy to work with. Every time we had a challenge, support team was able to help us with the end result.
Before using Cloud Insights, we quickly resolved all the issues we had by talking with the support team. The support team is eager to assist and technically well equipped. They quickly understood what we needed and helped us during the setup and the first use period so that we could adapt easily.
Cloud Insights allows us to create custom dashboards to monitor and trend any aspect of their infrastructure including CPU, memory, storage network utilization, IOPS, capacity utilization and more. Cloud Insights also provides visibility into the inter-connectivity of the components in our infrastructure by providing topology views of any component.
To be honest, Datadog is very similar to Splunk and LogScale to a lesser degree, but it is just as good if you don't need too complex observability. Grafana is still growing and might reach the same level soon.