Overview
This listing allows you to build an AMI with a pre-configured version of the latest Datadog Agent. By using the AMI with built-in Datadog Agent, you can easily deploy EC2 instances with Datadog's full stack monitoring capabilities, streamlining the setup of observability across your AWS infrastructure.
Highlights
- Collects real-time logs, traces, and metrics for full-stack monitoring.
- Provides deep visibility into infrastructure and application performance.
- Easy to deploy on EC2 instances for streamlined observability setup.
Details
Unlock automation with AI agent solutions

Features and programs
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Pricing
- ...
Dimension | Cost/hour |
---|---|
t2.micro AWS Free Tier | $0.00 |
t3.micro AWS Free Tier | $0.00 |
m6i.16xlarge | $0.00 |
g6.2xlarge | $0.00 |
m5zn.12xlarge | $0.00 |
m7i.48xlarge | $0.00 |
r6a.24xlarge | $0.00 |
r6idn.2xlarge | $0.00 |
i2.8xlarge | $0.00 |
c5a.2xlarge | $0.00 |
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no refunds
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Delivery details
Datadog Agent Component for EC2 Image Builder
- Amazon EC2 Image Builder
EC2 Image Builder Component
EC2 Image Builder is a fully managed AWS service. It automates creation, management, and deployment of custom, secure, and up-to-date server images. After procurement, use the EC2 Image Builder console/API to include this third-party component in golden images for future EC2 instances.
Version release notes
First release of Datadog Agent IB component for Windows
Additional details
Usage instructions
Product usage instructions available at https://docs.datadoghq.com/integrations/amazon_ec2/?tab=ec2imagebuilder#agent-installation-through-ec2-image-builderÂ
Support
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Customer reviews
Alerting and metrics improve monitoring efficiency while pricing presents challenges
What is our primary use case?
The primary purposes for which Datadog is used include infrastructure monitoring and application monitoring.
The main use case for Datadog integration capabilities is to monitor workloads in public cloud, and those public cloud integrations that reached the public cloud metric natively were helpful or critical for us. We are not using Datadog for AI-driven data analysis tasks, but more cloud-native and vendor-native tools at the moment, and at the time when I was still in my last employer, we didn't use Datadog for the AI piece at all.
What is most valuable?
I find alerting and metrics to be the most effective features of Datadog for system monitoring. It was still cheaper to run Datadog than other alternatives, so the running costs were cheaper because it was SaaS and quite easy to use.
Datadog is only available in SaaS.
What needs improvement?
The pricing nowadays is quite complex.
In future updates, I would like to see AI features included in Datadog for monitoring AI spend and usage to make the product more versatile and appealing for the customer.
For how long have I used the solution?
I have been using Datadog since 2014.
What was my experience with deployment of the solution?
There were no problems with the deployment of Datadog.
The deployment of Datadog just took a few hours.
What do I think about the stability of the solution?
The challenges I encountered while using Datadog were in the early days when the product was missing the ability to monitor Kubernetes and similar features, but they have since added those features. At the moment, I don't think there are too many challenges that I am worrying about.
How was the initial setup?
One person is enough to do the installation.
What other advice do I have?
I am not working with any of these solutions currently because I'm on sabbatical, but I used to work with Datadog six months ago, and now at the moment I'm on sabbatical.
We were using the tools that AWS and Azure came with natively to monitor the AI workflows on their platforms.
I used to work as the CTO at Northcloud, but I no longer work there.
On a scale of one to ten, I rate Datadog an eight out of ten.