Datadog vs. Splunk Observability Cloud

Datadog works really well with complex microservices architecture like any E-commerce platform which will be having multiple services but they all are interdependent to others so in this scenario Datadog will be best to monitor these as it will show the transactions also between those microservices. If you are using multiple services in your architecture whether it will be cloud services or on prem services Datadog will be the best choice to monitor all those service with in Datadog so that you can see everything in a single place. But if you are having small architecture and few services in that then in that scenario you can use Datadog but it will be little costly as compared to other but obviously the features are very well.

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Its great if you need real-time visibility across complex or regulated environments. Also strong for hybrid or multi-cloud setups where uptime, observability and fast IR are required. It’s probably overkill for smaller teams or environments that don’t have constant changes or compliance reporting needs. It's expensive and has a steep learning curve. Also, in my opinion, do not get yourself into a consumption based model. Costs can certainly get out of control quickly.

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• Create Dashboards as per application, environments, and Custom metrics in one panel.
• Log aggregation, one-stop Application monitoring tools for the whole infrastructure.
• Playbooks, SLA definition, success and error quotas, request visualizations.
• DB monitoring, Serverless stack monitoring.
• Alerting of Production incidents so we can quickly resolve the issues on time.

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• 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.

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• Alert windows cause lag in notifications (e.g. if the alert window is X errors in 1 hour, we won't get alerted until the end of the 1 hour range)
• I would appreciate more supportive examples for how to filter and view metrics in the explorer
• I would like a more clear interface for metrics that are missing in a time frame, rather than only showing tags/etc. for metrics that were collected within the currently viewed time frame

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• You can use table-like functionality to generate dashboards, but these queries are heavy on the system.
• It could be easier to give insight into what type of line parsing is used for specific documents in a company-managed environment and/or show ways to gain the insights needed.
• I would like to see ways to anonymize specific data for shared reports without pre-formatting this in a dashboard on which reports could be based.

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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

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There is some room for improvement, but the Datadog team sends out updates frequently, and the UI is user-friendly for engineers, with no significant loading issues or region-specific problems. That was one of the key reasons we preferred Datadog; our company has employees worldwide, and it wasn't difficult to transition to the tool.

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When there is an issue, it’s a win if one can easily identify the root cause. To do the same, it should allow the user to dig deep with multiple data points and compare the data and identify the anomaly. In this use case, it’s good to drive from Splunk 011y.

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The support team usually gets it right. We did have a rather complicate issue setting up monitoring on a domain controller. However, they are usually responsive and helpful over chat. The downside would be I don’t think they have any phone support. If that is important to you this might not be a good fit.

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Splunk support is very quick and efficient. Pre-sale specialists are very skilled and available.

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Follow a training before starting.

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We are still trying other products, but people still like Datadog. After setting up a dashboard, it's great for monitoring instances on Datadog. Also, the DevOps team had a good time setting up Datadog. It means Datadog was way easier to set up compared to those others.

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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 of servers and agents residing together within a single data centre, but modern apps are no longer like this.

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• Saved us (time & money) from developing our own monitoring utilities that would pale in comparison
• Alerts allow us to remedy issues before our customers even know about them
• Tracking resource usage over time allows us to better plan for future needs, before it becomes a pain-point.

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• Significantly reduced the MTTR (Mean Time To Recovery), which in turn has improved the end-user experience tremendously.
• Meets compliance requirements of security policies, audit, regulation, and forensics.
• Helps us to track/manage the resource usage on our cloud instances which has a direct implication on the recurring cost.

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