Datadog announces raft of new products for AWS

At AWS re:Invent, Datadog has announced a new strategic collaboration with the cloud giant and a raft of new products. The company already has over 100 integrations specific to AWS. These sixteen new solutions deepen that relationship. The products span the breadth of AWS services from AI to observability and security. It is the biggest set of new announcements for AWS that Datadog has announced.

Yanbing Li, Chief Product Officer at Datadog, said, “These launches further extend Datadog’s ability to deliver AI-powered observability and security at scale.

“They cover all aspects of a customers’ tech stack, including LLM and agentic applications, cloud object storage, and containerized and serverless infrastructure, so that joint customers can migrate to and manage their AWS, hybrid and multi-cloud environments with confidence.”

Datadog wants to be your observability platform

Observability is key to knowing what is going on inside any IT infrastructure. Understanding where data is, who is accessing it, how it is being used, and how it is performing are just some of the observability challenges organisations have. Unfortunately, many are struggling to get the levels of insight that they need. As they continue to move to multi-platform environments, that problem gets worse.

For many IT departments, the solution is a mix of different applications that don’t integrate or share data well. It creates issues with training, data consistency and leaves blind spots.

In this announcement, there is a lot of focus on the observability of AI. The solutions range from the ability to see what is happening in Amazon Bedrock to multiple MCP integrations. Datadog has also added new Bits AI capabilities. This allows its AI agent to provide the ability to better remediate Kubernetes and Serverless issues.

There are also new capabilities to monitor your workloads across AWS Lambda, Amazon RDS and ECS. Security teams will welcome the ability to identify misconfigurations across AWS and multi-cloud environments. This should help reduce the number of data breaches caused by poor resource allocation management.

However, customers should note that half of these are preview only. That means they could take months to appear as full products.

16 new solutions

Here is the full list of new Datadog product capabilities for joint AWS customers:

• LLM Observability: Monitor, operate and debug agent workflows for both Amazon Bedrock Agents and Strands Agents Framework.
• Storage Management: Get granular visibility into Amazon S3 buckets and prefixes, enabling teams to eliminate waste and prevent unexpected cloud object storage spend.
• Datadog MCP Server Integration with AWS DevOps Agent (in Preview): Automate incident resolution by enabling AWS DevOps Agent to query Datadog logs, metrics, and traces during investigations.
• Support for Datadog MCP Server in Kiro (in Preview): Fix bugs more effectively within your IDE by giving Kiro full Datadog context including errors, recent deployments, linked tickets, and more.
• New Kiro power from Datadog (in preview): Specialize your Kiro agents for observability use cases by one-click download of MCP server and steering files for use in Kiro to enable debugging of production issues and develop better code.
• Support for AWS Lambda Managed Instances (in Preview): Gain full visibility into AWS Lambda Functions running on EC2.
• Support for Amazon Elastic Container Service (ECS) Managed Instances (in Preview): Monitor and troubleshoot workloads running on Amazon ECS Managed Instances.
• Support for Amazon ECS Express Mode: Gain visibility into containers running on ECS Express Mode.
• Bits AI Serverless Remediation (in Preview): Troubleshoot issues running serverless applications on AWS with AI-augmented remediation.
• Bits AI Kubernetes Active Remediation: Accelerate issue resolution for Amazon EKS workloads with AI-guided, evidence-based recommendations.
• AWS Lambda Cost Recommendations: Automatically identify saving opportunities for AWS Lambda, such as optimizing provisioned concurrency or deleting redundant Amazon CloudWatch logs in AWS Lambda.
• Amazon Relational Database Service (Amazon RDS) Instance Recommendations: Automatically source optimizations for Amazon RDS instances, such as when an instance has low disk space, high disk queue depth or read-only traffic.
• Observability Pipelines Packs for AWS (in Preview): Speed up data processing with predefined, ready-to-use Packs for Amazon Virtual Private Cloud (Amazon VPC), AWS CloudTrail and Amazon CloudFront.
• Observability Pipelines S3 Log Rehydration (in Preview): Quickly access and reprocess historical logs from Amazon S3 to any destination.
• AI Security for AWS Resources: Detect AI misconfigurations to bolster the security of Amazon Bedrock.
• Cloud SIEM Risk Insights: Identify risks and AI misconfigurations across AWS and multi-cloud environments to prioritize investigations.

A new Strategic Collaboration Arrangement

Datadog and AWS have also signed a new strategic collaboration agreement (SCA). There is little detail available about what it contains, apart from the statement in the announcement. That says:

“Through deeper collaboration with AWS on solution development, AWS marketplace availability, and go-to-market programs, Datadog will help customers de-risk cloud migrations, accelerate modernization, secure AWS and multi-cloud environments, and confidently deploy GenAI capabilities on AWS.

“Datadog’s collaboration spans all regions and industries, including public sector, enterprise and ISVs, and strengthens Datadog’s position as a strategic partner of AWS.”

It’s a highly comprehensive agreement, based on that statement. It also positions Datadog as the go-to platform for IT support teams using AWS. It now has over 116 solutions, integrations and capabilities, including those just announced.

Enterprise Times: What does this mean?

This is the second announcement from Datadog this week. It follows on from the general availability of Bits AI SRE. 2025 has seen the company significantly step up its product delivery cadence, sign new deals with major vendors and blast through the 1,000 integration mark.

This particular announcement, especially with the SCA, continues the company’s push to be the key integration and observability platform. Although half of the new 16 products announced are just in preview, customers can sign up for early access. That will allow them to test and understand what they offer before they go GA.

What will be interesting now is whether Datadog can get similar SCAs, with the same scope, on Microsoft Azure and Google Cloud. If it does, then it will become the dominant player in this space.

For IT operations teams at enterprises and MSPs, this is good news. They struggle with multi-platform observability, which creates risk and adds cost as they buy multiple tools. Can Datadog emerge as the platform of choice, especially for MSPs? It’s certainly heading in that direction.

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