Datadog announced a new strategic collaboration agreement (SCA) with Amazon Web Services (AWS) and showcased multiple product launches across AI, observability and security to help organizations running on AWS monitor, optimize and secure their cloud environments.

“These launches further extend Datadog’s ability to deliver AI-powered observability and security at scale. They cover all aspects of a customer’s 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,” said Yanbing Li, Chief Product Officer at Datadog.

The new Datadog product capabilities for joint AWS customers showcased at re:Invent include:

• 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 savings 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.

As part of an ongoing commitment to deliver value to joint customers, Datadog has also signed a new Strategic Collaboration Agreement (SCA) with AWS. 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.

“As cloud-native applications and AI workloads accelerate, observability and security across AWS environments are top of mind for enterprise customers,” said Jarrod Buckley, Vice President of Channels and Alliances at Datadog. “Expanding our global collaboration with AWS enables continued innovation to help customers become more resilient, reduce risk, and achieve time-to-value faster.”

“AWS is committed to working with partners like Datadog to help customers innovate and succeed in the AI era,” said Chris Grusz, Managing Director, Technology Partnerships at AWS. “As organizations increasingly rely on AI-powered applications, observability has become essential for ensuring performance, reliability and cost optimization at scale. Through this strategic collaboration and new integrations with AWS services, we’re making it easier for customers to gain deep insights into their AWS infrastructure and applications, enabling them to build with confidence and accelerate their AI initiatives."