For our last episode of 2025, we’re focusing on Datadog releases announced at AWS re:Invent. Join Jeremy to see how you can manage logs at petabyte scale in your infrastructure, eliminate unneeded costs in Amazon S3 buckets, build agentic workflows, and detect credential leaks.
Later in the episode, Scott spotlights how you can connect your AI agents to Datadog tools and context with our MCP Server. After that, Kai shows how Bits AI SRE can help you investigate alerts, coordinate incidents, and more. We also take a look at how parts of the cloud landscape are changing with Datadog’s 2025 State of Cloud Security report and State of Containers and Serverless report.
When you’re done watching the episode, visit our re:Invent microsite for a full list of our announcements.
Having the right context is an essential part of real-time data analysis by AI agents. Datadog MCP Server enables you to connect AI agents, such as Amazon Kiro, to Datadog tools and context. Once connected, you can ask questions about your production systems and get insights backed by Datadog data.
Identify root causes and remediate issues faster with Bits AI SRE. Our new product helps you spend less time investigating alerts and coordinating incidents, so you can stay focused on building and shipping great software. Bits AI SRE is now generally available.
Teams need a way to balance complete visibility against retention needs and residency requirements. Datadog CloudPrem is a hybrid log management solution that runs in your infrastructure and stays fully integrated with our platform. Filter your CloudPrem logs with Log Explorer, preprocess data before indexing with Observability Pipelines, and more with our new product, which is now available in Preview.
Bucket-level metrics can show how much you spend on storage but not what drives those costs. Datadog Storage Management breaks down cost drivers to the prefix level so you can attribute spend to specific sources, such as teams, services, and workloads. Combined with object count and age metrics, this visibility also helps you spot opportunities to move cold data to lower-cost tiers.
To help workflows adapt to real-world complexity, teams often try to hardcode logic branches for every possible outcome. Datadog Agent Builder lets you create AI agents that analyze data, reason through complex decisions, and adapt to changing inputs. With this new feature, you can define an agent’s goals using natural language, add prompts, and control which data sources and tools it can access.
Continuously monitor your source code, repositories, and CI/CD pipelines for credential leaks with Datadog Secret Scanning. When a potential leak is found, Datadog automatically verifies it with the corresponding third-party provider, such as AWS, to determine if the credential is active. This new feature also integrates with CI/CD workflows and enforces pre-commit and pre-merge checks that stop keys from entering repositories.
More new features and updates released this month:
This Month in Datadog is a monthly roundup of our latest features, product announcements, and more. Subscribe to our YouTube channel to get notified when future episodes are live.
In the meantime, check out our release notes for a full list of new features and updates. Or see them in action by logging in to the Datadog platform or signing up for a 14-day free trial. See you next month!
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