Expanded Strategic Collaboration Agreement announced at re:Invent includes tools for monitoring large language models and optimising infrastructure spend
Datadog, the prominent monitoring and security platform, has unveiled a significant expansion of its decade-long partnership with Amazon Web Services (AWS), signing a new Strategic Collaboration Agreement (SCA) that cements its role as a core observability partner for the cloud giant.
Announced at the annual AWS re:Invent conference, the agreement is accompanied by a raft of new product launches designed to help organisations manage the increasing complexity of cloud operations, particularly within the rapidly accelerating fields of Generative AI and cost management.
The strategic push focuses on enabling joint customers to securely migrate to and manage sprawling hybrid and multi-cloud environments, ensuring they can deploy AI applications confidently.
“These launches further extend Datadog’s ability to deliver AI-powered observability and security at scale,” said Yanbing Li, Chief Product Officer at Datadog. “They cover all aspects of a customers’ tech stack, including LLM and agentic applications, so that joint customers can migrate to and manage their AWS environments with confidence.”
The most forward-looking announcements centre on addressing the complexities of Generative AI workflows. Datadog is introducing LLM Observability to monitor, operate, and debug agent workflows for technologies like Amazon Bedrock Agents. This directly addresses a critical pain point: the ‘black box’ nature of AI applications, where debugging performance or security issues can be exceptionally difficult.
Further leveraging AI, Datadog announced Bits AI Serverless Remediation for troubleshooting AWS Lambda applications and Bits AI Kubernetes Active Remediation for Amazon EKS workloads. These tools use AI-guided, evidence-based recommendations to accelerate the resolution of production issues a significant step toward autonomous operations.
Amid pressure on technology budgets, several launches are dedicated to cloud cost optimization. Datadog is introducing granular Storage Management visibility for Amazon S3 buckets, helping teams identify waste and prevent unexpected cloud object storage spend.
Crucially, the platform will offer new automatic Cost Recommendations for AWS Lambda, allowing teams to optimize provisioned concurrency, and for Amazon Relational Database Service (Amazon RDS) instances, sourcing optimisations for resource utilization. These tools directly translate observability data into financial savings, a key priority for chief financial officers.
Other notable capabilities showcased at re:Invent include:
Security: New AI Security for AWS Resources will help detect misconfigurations in Amazon Bedrock deployments, while Cloud SIEM Risk Insights will prioritise investigation of risks across multi-cloud environments.
Infrastructure: Expanded support for container and serverless environments includes gaining full visibility into AWS Lambda Managed Instances and Amazon Elastic Container Service (ECS) Managed Instances and Express Mode.
Data Processing: New Observability Pipelines Packs for AWS will speed up data processing for services like AWS CloudTrail and Amazon VPC, offering ready-to-use configurations.
The SCA is viewed by analysts as a key move by both companies to maintain dominance in the cloud ecosystem. By deepening its technical integration and go-to-market strategies with AWS, Datadog strengthens its position against competitors and ensures its platform remains essential as customers continue to build increasingly complex, AI-driven applications on the AWS infrastructure.
