Datadog vs. Spot by NetApp

Datadog may be better suited for teams that have a more out-of-the-box infrastructure, on the primary platforms Datadog supports. You may also have better results if you have a bigger team dedicated to devops and/or a bigger budget. We found that trying to adapt it to our use case (small team, .NET on AWS Fargate) wasn't feasible. We continually ran into roadblocks that required us to dig through documentation (and at times, having to figure out some documentation was wrong), go back and forth with support, and in my opinion, waste money on excessive and unintended usages due to opaque pricing models and inaccurate usage reports, as well as broken/non-functional rate sampling controls.

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CloudCheckr is fantastic for those that are purely in the Cloud as it provides everything you need under one roof for a comprehensive configuration and usage monitoring tool. It has SysLog capabilities though so you can farm out the alerts into a SIEM or other log management system, so hybrid environments could also benefit from its use.

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• The thing which Datadog does really well, one of them are its broad range of services integrations and features which makes it one step observability solution for all. We can monitor all types of our application, infrastructure, hosts, databases etc with Datadog.
• Its custom dashboard feature which helps us to visualize the data in a better way . It supports different types of charts through those charts we can create our dashboard more attractive.
• Its AI powered alerting capability though that we can easily identify the root cause and also it has a low noise alerting capability which means it correlated the similar type of issues.

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• Detailed Best Practices. It's important to align your cloud to industry best practices for security and cost—it just performs better if it's used the way it's meant to be used. AWS is very flexible, and that's great when you have special requirements, but you've got to at least know when you're using something in a non-standard way so you can think through the implications.
• Cost Reduction. Some recommendations are almost impossible to make at least for our setup, but many, many others are easy. We only have to log into CloudCheckr every few months and make a few changes for it to more than pay for itself.
• Right-Sizing. This is related to the other points, but for some reason is separate from their cost module. The metrics it's able to pull only tell half the story, so it's good to verify it's sizing recommendations before making changes. But it does show you what instances to focus on first, and even if you choose a slightly different size to move it to, it does clearly indicate it's current size isn't appropriate. And this works both ways, if the size is too big, you can save some cash by making it smaller, but if it's too small, you want to be sure to scale up before you run into performance problems.

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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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• CloudCheckr features have a tendency to break without warning. Functionality in place for months could suddenly stop working.
• CloudCheckr support often delays work on support tickets for fixing broken application functionality.
• The CloudCheckr platform and documentation website often crash or experience performance degradation.
• CloudCheckr cost reporting is often impacted by faulty code or broken report functionality. This can contribute to a low level of confidence in CloudCheckr's ability to deliver accurate cost reporting.

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Definitely will not revisit after our issues and, in my opinion, poor support.

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There are so many features that it can be hard to figure out where you need to go for your own use case. For example, RUM monitoring us buried in a "Digital Experience" sidebar setting when this is one of our key use cases that I sometimes struggle to find in the application. It appears that ECS + Fargate monitoring was recently released which is great because we had to build a lambda reporting solution for ephemeral task monitoring. But this new feature was never on my radar until I starting clicking around the application.

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Overall, CloudCheckr covers all our AWS monitoring needs and great integration through SysLog into our SIEM to capture alerts for investigation. The reports are great and allow for an easy daily review. Small improvements could be made to the interface and better filtering in places would be good. Great product and the price is fair.

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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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Fantastic Support team who are responsive and address question and concerns promptly with a thorough explanation and fast resolution.

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Documentation was difficult to work through, rollout was catastrophic (completely outage)

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Our logs are very important, and Datadog manages them exceptionally well. We frequently use Datadog services for our investigations. Use case: Monitor your apps, infrastructure, APIs, and user experience.


Key features:


Logs, metrics, and APM (Application Performance Monitoring)


Real-time alerting and dashboards


Supports Kubernetes, AWS, GCP, and other integrations


RUM (Real User Monitoring) and Synthetics





✅ Best for backend, server, and distributed systems monitoring.

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There are a few products out there that'll do an aspect or two of what CloudCheckr does, but I honestly couldn't find anything nearly as comprehensive as CloudCheckr.

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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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• CloudCheckr has allowed us to increase resell margins as an MSP.
• CloudCheckr has made us aware of cost savings opportunities that exceed the price of the platform itself.
• CloudCheckr has given us additional visibility that has allowed us to manage and understand cloud computing costs.

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info