Las Vegas — Datadog (NASDAQ: DDOG), the monitoring and safety platform for cloud purposes, at AWS re:Invent introduced a collaboration with Amazon Net Providers and showcased a number of product launches throughout AI, observability and safety to assist organizations working on AWS to observe and safe their cloud environments.
“These launches additional lengthen Datadog’s potential to ship AI-powered observability and safety at scale. They cowl all elements of a prospects’ tech stack, together with LLM and agentic purposes, cloud object storage, and containerized and serverless infrastructure, in order that joint prospects can migrate to and handle their AWS, hybrid and multi-cloud environments with confidence,” stated Yanbing Li, Chief Product Officer at Datadog.
Clients use Datadog to observe their AWS environments by greater than 1,000 integrations, together with 100 distinctive to AWS.
“When points come up, the true worth isn’t simply in figuring out what’s damaged, however in understanding your entire stack—in any other case it’s simple to overlook the forest for the timber amid the cascade of occasions triggered by a single drawback,” stated Sean Fernandez, CIO at ROLLER. “Datadog provides us a unified view of our AWS setting by a single pane of glass, correlating every little thing in seconds somewhat than the hours we as soon as spent sifting by a number of techniques. This has helped de-risk our cloud transformation efforts by giving us the observability wanted to modernise confidently and cut back prices whereas we proceed to give attention to bringing worth to our prospects within the type of dependable, safe and compliant know-how companies.”
The brand new Datadog product capabilities for joint AWS prospects showcased at re:Invent embody:
- LLM Observability: Monitor, function and debug agent workflows for each Amazon Bedrock Brokers and Strands Brokers Framework.
- Storage Administration: Get granular visibility into Amazon S3 buckets and prefixes, enabling groups to get rid of waste and forestall surprising cloud object storage spend.
- Datadog MCP Server Integration with AWS DevOps Agent (in Preview): Automate incident decision by enabling AWS DevOps Agent to question Datadog logs, metrics, and traces throughout investigations.
- Assist for Datadog MCP Server in Kiro (in Preview): Repair bugs extra successfully inside your IDE by giving Kiro full Datadog context together with errors, latest deployments, linked tickets, and extra.
- New Kiro energy from Datadog (in preview): Specialize your Kiro brokers for observability use instances by one-click obtain of MCP server and steering information to be used in Kiro to allow debugging of manufacturing points and develop higher code.
- Assist for AWS Lambda Managed Cases (in Preview): Acquire full visibility into AWS Lambda Features working on EC2.
- Assist for Amazon Elastic Container Service (ECS) Managed Cases (in Preview): Monitor and troubleshoot workloads working on Amazon ECS Managed Cases.
- Assist for Amazon ECS Categorical Mode: Acquire visibility into containers working on ECS Categorical Mode.
- Bits AI Serverless Remediation (in Preview): Troubleshoot points working serverless purposes on AWS with AI-augmented remediation.
- Bits AI Kubernetes Lively Remediation: Speed up concern decision for Amazon EKS workloads with AI-guided, evidence-based suggestions.
- AWS Lambda Value Suggestions: Mechanically determine saving alternatives for AWS Lambda, equivalent to optimizing provisioned concurrency or deleting redundant Amazon CloudWatch logs in AWS Lambda.
- Amazon Relational Database Service (Amazon RDS) Occasion Suggestions: Mechanically supply optimizations for Amazon RDS situations, equivalent to when an occasion has low disk house, excessive disk queue depth or read-only site visitors.
- Observability Pipelines Packs for AWS (in Preview): Velocity up knowledge processing with predefined, ready-to-use Packs for Amazon Digital Non-public Cloud (Amazon VPC), AWS CloudTrail and Amazon CloudFront.
- Observability Pipelines S3 Log Rehydration (in Preview): Shortly entry and reprocess historic logs from Amazon S3 to any vacation spot.
- AI Safety for AWS Assets: Detect AI misconfigurations to bolster the safety of Amazon Bedrock.
- Cloud SIEM Threat Insights: Determine dangers and AI misconfigurations throughout AWS and multi-cloud environments to prioritize investigations.
A part of an ongoing dedication to ship worth to joint prospects, Datadog has additionally signed a brand new Strategic Collaboration Settlement (SCA) with AWS. By deeper collaboration with AWS on resolution growth, AWS market availability, and go-to-market applications, Datadog will assist prospects de-risk cloud migrations, speed up modernization, safe AWS and multi-cloud environments, and confidently deploy GenAI capabilities on AWS. Datadog’s collaboration spans all areas and industries, together with public sector, enterprise and ISVs, and strengths Datadog’s place as a strategic accomplice of AWS.
“As cloud-native purposes and AI workloads speed up, observability and safety throughout AWS environments are high of thoughts for enterprise prospects,” stated Jarrod Buckley, Vice President of Channels and Alliances at Datadog. “Increasing our world collaboration with AWS permits continued innovation to assist prospects turn out to be extra resilient, cut back threat, and obtain time-to-value sooner.”
“AWS is dedicated to working with companions like Datadog to assist prospects innovate and succeed within the AI period,” stated Chris Grusz, Managing Director, Know-how Partnerships at AWS. “As organizations more and more depend on AI-powered purposes, observability has turn out to be important for guaranteeing efficiency, reliability, and value optimization at scale. By this strategic collaboration and new integrations with AWS companies, we’re making it simpler for purchasers to realize deep insights into their AWS infrastructure and purposes, enabling them to construct with confidence and speed up their AI initiatives.”
