Amazon CloudWatch vs. Datadog vs. LogicMonitor

For out business we find that AWS Cloudwatch is good at providing real-time metrics for monitoring and analysing the performance and usage of our platform by customers. It is possible to create custom metrics from log events, such people adding items to a basket, checking out or abandoning their orders.

Incentivized

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

The example I will give will explain my rating for it. One employee left our company due to a personal issue, and at that time, our team was working on a highly secure project. He wanted to take revenge on our company, so he began hacking our systems from the outside. Since it appears that someone without authorization is attempting to access our systems, LogicMonitor simultaneously alerted our team to the problem. We stopped that threat with LogicMonitor.

Incentivized

• It provides lot many out of the box dashboard to observe the health and usage of your cloud deployments. Few examples are CPU usage, Disk read/write, Network in/out etc.
• It is possible to stream CloudWatch log data to Amazon Elasticsearch to process them almost real time.
• If you have setup your code pipeline and wants to see the status, CloudWatch really helps. It can trigger lambda function when certain cloudWatch event happens and lambda can store the data to S3 or Athena which Quicksight can represent.

Incentivized

• 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

• It shows us system issues right away so we can fix them fast.
• It finds new devices on its own, so we do not miss anything.
• It alerts us only when something really unusual happens.
• Its dashboards make it easy for everyone to see system health.
• It helps us see trends so we are ready for busy times.

Incentivized

• Memory metrics on EC2 are not available on CloudWatch. Depending on workloads if we need visibility on memory metrics we use Solarwinds Orion with the agent installed. For scalable workloads, this involves customization of images being used.
• Visualization out of the box. But this can easily be addressed with other solutions such as Grafana.
• By design, this is only used for AWS workloads so depending on your environment cannot be used as an all in one solution for your monitoring.

Incentivized

• 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

• Segmentation at an instance level not just the resource when clients are sharing the same device but shouldn't see each other's relevant data
• ARM CPU support for collectors to allow for a lighter weight appliance deployment
• WMI collection with a Linux collector so a windows collector would not be needed or a virtual appliance template that can be used to deploy collectors

Incentivized

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

Incentivized

This product has met virtually all of our needs. It was easy to implement and has been simple to support. Customization has been intuitive with many options available. They keep adding features and expanding available options. The future of LogicMonitor looks even better than it is today which is very promising. The management and support teams at LogicMonitor are always helpful

Incentivized

It's excellent at collecting logs. It's easy to set up. The viewing & querying part could be much better, though. The query syntax takes some time to get used to, & the examples are not helpful. Also, while being great, Log Insights requires manual picking of log streams to query across every time.

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

Set up is super easy. Just stand up a small Linux or Windows server to act as a collector. There are no agents to install on monitored devices and all you need is SNMP or WMI access. When creating dashboards, all you have to do is find the widget on the device you want to show up and choose the menu option to add it.

Incentivized

Support is effective, and we were able to get any problems that we couldn't get solved through community discussion forums solved for us by the AWS support team. For example, we were assisted in one instance where we were not sure about the best metrics to use in order to optimize an auto-scaling group on EC2. The support team was able to look at our metrics and give a useful recommendation on which metrics to use.

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

The sales team support we received was top notch. They worked hand in hand to make sure the product met all expectations. So far we have not really had to work with support that much; we have worked with setup team after purchase to deploy product fully. No issues so far and we are four weeks in.

Incentivized

Add good training

Incentivized

The training is good but room to improve

Incentivized

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

Incentivized

I did not truly dedicate myself to implementing LogicMonitor. However, I overheard the IT team members explain that "LogicMonitor is perfect for us as it has made most of the work automated, and implementation and training sessions were perfect for us." Thus, I can state that everything went smoothly with our implementation.

Incentivized

Grafana is definitely a lot better and flexible in comparison with Amazon CloudWatch for visualisation, as it offers much more options and is versatile. VictoriaMetrics and Prometheus are time-series databases which can do almost everything cloudwatch can do in a better and cheaper way. Integrating Grafana with them will make it more capable Elasticsearch for log retention and querying will surpass cloudwatch log monitoring in both performance and speed

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

Basically, we did not have any idea about it and how to choose, but we asked one of our former bosses, as they were very experienced with it, so they helped us by clarifying a few things between New Relic and LogicMonitor, as they told us that if you are looking for an automated option, then there is no better option than LogicMonitor.

Incentivized

Pricing seems to be getting more and more aggressive, I worry that it's going to turn into ServiceNow or SAP and everything minor feature will be an extreme cost that prices out us and our customers

Incentivized

Haven't really used it but our initial onboarding PS was disappointing. Felt like we were being told what we needed to cover as opposed to what we wanted to cover. In addition, we were pushed into using the PS in tight time frames and we were not ready to do so.

Incentivized

• Positive for alarms and alert notifications once configured/customized.
• Has upfront learning curve, and cost can increase as does the alarm activity and monitoring details you may require.
• Cost-effective for any size organization keeping with AWS and utilizing its native tools is a savings in long-term ROI.

Incentivized

• 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

• We Eliminated an on-prem monitoring tool which was in excess of 25 servers
• A decrease in time to response from our Network Operations Center resulted in a more consistent client experience
• Dynamic alert thresholds helped reduce alerting by about 10 to 15% as soon as we turned it on for volatile metrics like CPU and memory

Incentivized