Datadog vs. Memfault vs. Percepio Tracealyzer

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.

Incentivized

If you're running a fleet of embedded devices that has a tight RAM, CPU, & power footprint, Memfault is a must-have. From managing firmware deployments to monitoring every facet of the device lifecycle and performance, this is a solution that is built with a founding team that are the absolute best in the industry. They know your chipset and OS extraordinarily well and in some cases have been able to work directly with the chip vendors to provide support for their SDKs. With Memfault's help, our chip vendor diagnosed an issue in their BLE SDK and dramatically decreased the number of crash events on our devices.

Incentivized

This is a perfect tool to debug complex bugs in your system, especially in regards to inter-task communication. It is also a great tool for beginners, as the documentation is accessible and the support given by the company is excellent

• 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.

Incentivized

• Great visualization
• Sometimes awkward views (vertical vs horizontal)

• 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

Incentivized

• It's not always easy to include/integrate Tracealyzer in the OS build. It would be nice to have a simple install/plug n play method for our target.
• Sometimes, the .bin files from Tracealyzer don't always work and we don't know why

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

Incentivized

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.

Incentivized

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.

Incentivized

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

Incentivized

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.

Incentivized

While we started using uCOSIII for our simpler microcontroller products, we also use QNX on more complex targets (full microprocessors) and it is a much more complex platform offering event tracing, memory tracing, and performance measures that are extremely good and integrated. More importantly these tools are fully integrated without any code changes. Tracealyzer is not integrated as much into uCOSIII like QNX's tools, debugger, etc. But, going thru the manual work of adding Tracealyzer to the build, it did help us get to a shippable product.

• 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.

Incentivized

• Positive: We were able to find some thread priority issues with Tracealyzer.
• Positive: we were able to see timing of events in the sw/hw that we couldn't otherwise see.