Las Vegas — Datadog (NASDAQ: DDOG), the monitoring and safety platform for cloud functions, at AWS re:Invent introduced a collaboration with Amazon Internet Providers and showcased a number of product launches throughout AI, observability and safety to assist organizations operating on AWS to watch and safe their cloud environments.
“These launches additional prolong Datadog’s potential to ship AI-powered observability and safety at scale. They cowl all features of a clients’ tech stack, together with LLM and agentic functions, cloud object storage, and containerized and serverless infrastructure, in order that joint clients can migrate to and handle their AWS, hybrid and multi-cloud environments with confidence,” mentioned Yanbing Li, Chief Product Officer at Datadog.
Clients use Datadog to watch their AWS environments via greater than 1,000 integrations, together with 100 distinctive to AWS.
“When points come up, the actual worth isn’t simply in figuring out what’s damaged, however in understanding all the stack—in any other case it’s straightforward to overlook the forest for the timber amid the cascade of occasions triggered by a single downside,” mentioned Sean Fernandez, CIO at ROLLER. “Datadog offers us a unified view of our AWS setting via a single pane of glass, correlating all the pieces in seconds moderately than the hours we as soon as spent sifting via a number of programs. This has helped de-risk our cloud transformation efforts by giving us the observability wanted to modernise confidently and scale back prices whereas we proceed to give attention to bringing worth to our clients within the type of dependable, safe and compliant expertise companies.”
The brand new Datadog product capabilities for joint AWS clients 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 eradicate waste and forestall sudden 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, current deployments, linked tickets, and extra.
- New Kiro energy from Datadog (in preview): Specialize your Kiro brokers for observability use circumstances by one-click obtain of MCP server and steering recordsdata to be used in Kiro to allow debugging of manufacturing points and develop higher code.
- Assist for AWS Lambda Managed Cases (in Preview): Achieve full visibility into AWS Lambda Capabilities operating on EC2.
- Assist for Amazon Elastic Container Service (ECS) Managed Cases (in Preview): Monitor and troubleshoot workloads operating on Amazon ECS Managed Cases.
- Assist for Amazon ECS Categorical Mode: Achieve visibility into containers operating on ECS Categorical Mode.
- Bits AI Serverless Remediation (in Preview): Troubleshoot points operating serverless functions on AWS with AI-augmented remediation.
- Bits AI Kubernetes Energetic Remediation: Speed up challenge decision for Amazon EKS workloads with AI-guided, evidence-based suggestions.
- AWS Lambda Price Suggestions: Routinely establish saving alternatives for AWS Lambda, resembling optimizing provisioned concurrency or deleting redundant Amazon CloudWatch logs in AWS Lambda.
- Amazon Relational Database Service (Amazon RDS) Occasion Suggestions: Routinely supply optimizations for Amazon RDS situations, resembling 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 information 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): Rapidly entry and reprocess historic logs from Amazon S3 to any vacation spot.
- AI Safety for AWS Sources: Detect AI misconfigurations to bolster the safety of Amazon Bedrock.
- Cloud SIEM Danger Insights: Establish dangers and AI misconfigurations throughout AWS and multi-cloud environments to prioritize investigations.
A part of an ongoing dedication to ship worth to joint clients, Datadog has additionally signed a brand new Strategic Collaboration Settlement (SCA) with AWS. By means of deeper collaboration with AWS on resolution improvement, AWS market availability, and go-to-market applications, Datadog will assist clients 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 functions and AI workloads speed up, observability and safety throughout AWS environments are prime of thoughts for enterprise clients,” mentioned Jarrod Buckley, Vice President of Channels and Alliances at Datadog. “Increasing our international collaboration with AWS permits continued innovation to assist clients turn out to be extra resilient, scale back danger, and obtain time-to-value sooner.”
“AWS is dedicated to working with companions like Datadog to assist clients innovate and succeed within the AI period,” mentioned Chris Grusz, Managing Director, Know-how Partnerships at AWS. “As organizations more and more depend on AI-powered functions, observability has turn out to be important for guaranteeing efficiency, reliability, and price optimization at scale. By means of this strategic collaboration and new integrations with AWS companies, we’re making it simpler for purchasers to achieve deep insights into their AWS infrastructure and functions, enabling them to construct with confidence and speed up their AI initiatives.”
