Datadog & AWS deepen AI observability & security in the cloud
Datadog has agreed a new collaboration arrangement with Amazon Web Services (AWS) aimed at enhancing monitoring, observability and security tools for organisations operating in cloud and multi-cloud environments. The agreement is intended to broaden product integrations and services, with a particular focus on supporting artificial intelligence workloads and complex infrastructure.
AI and observability
The expanded cooperation brings new Datadog capabilities to customers using AWS, including observability support for large language models and agent-based AI workflows. Teams can now monitor and debug both Amazon Bedrock Agents and Strands Agents Framework, giving greater insight into performance across different components.
Further features now provide detailed visibility into Amazon S3 storage, enabling users to manage costs and address inefficiencies in data usage. New integrations also allow AWS DevOps Agent to query Datadog data directly during incident investigations, with support for live debugging and contextual information within development environments such as Kiro.
Cloud environments
The partnership covers more than 1,000 integrations across the full cloud and IT stack, including 100 that are unique to AWS. These span areas such as serverless and containerised workloads, with support being extended to AWS Lambda and Amazon ECS managed and express mode instances. New cost management tools provide automatic recommendations for AWS Lambda and Amazon RDS instances based on usage patterns and optimisation opportunities.
Additional services announced include AI-augmented troubleshooting for serverless applications and Kubernetes workloads, with evidence-based recommendations to accelerate issue resolution. Observability Pipelines Packs have also been introduced to streamline processing of data from core AWS services such as Amazon VPC, AWS CloudTrail and Amazon CloudFront.
Security priorities
Security features form part of the agreement, with mechanisms to detect AI misconfigurations in Amazon Bedrock and to provide risk insights via cloud SIEM tools. These services intend to help organisations identify, prioritise and address vulnerabilities across AWS and multiple cloud platforms.
"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," said Yanbing Li, Chief Product Officer, Datadog.
Customer experience
Datadog customers can leverage these capabilities for a single, unified view of their AWS environments. With enhanced correlation tools and integrations, IT teams are able to more rapidly diagnose and resolve problems, supporting digital transformation and reducing operational risk.
"When issues arise, the real value isn't just in identifying what's broken, but in understanding the entire stack-otherwise it's easy to miss the forest for the trees amid the cascade of events triggered by a single problem," said Sean Fernandez, CIO, ROLLER. "Datadog gives us a unified view of our AWS environment through a single pane of glass, correlating everything in seconds rather than the hours we once spent sifting through multiple systems. This has helped de-risk our cloud transformation efforts by giving us the observability needed to modernise confidently and reduce costs while we continue to focus on bringing value to our customers in the form of reliable, secure and compliant technology services."
Market reach
The agreement is part of a shared aim between Datadog and AWS to support customers operating in a range of sectors. The arrangement covers all global regions and is designed to make Datadog solutions more widely available through the AWS Marketplace and go-to-market programmes.
"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, Datadog.
"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, 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."
