In 2020 we released distributed tracing for AWS Lambda functions written in Python, Node.js, and Ruby, providing you with health and performance insights across your serverless applications. Since then, we’ve expanded our support to additional Lambda runtimes such as Java and Go, and are pleased to announce that real-time distributed tracing is now also available for.NET Lambda functions.

Logs are records of system events and activities that provide valuable information used to support a wide range of administrative tasks—from analyzing application performance and debugging system errors to investigating security and compliance issues. Large-scale production environments emit enormous quantities of logs, which can make them more challenging to manage and introduces the risk of losing important data if underlying resources run out of space.

Datadog Notebooks enable your teams to create and manage key reports and documentation as they build out, monitor, and maintain their infrastructure. Notebooks can include both text and graphs of any telemetry data you have collected in Datadog, and they support collaborative editing so that multiple team members can edit and leave comments simultaneously.

MongoDB Atlas is a fully managed cloud database service for modern applications. Earlier this year, the MongoDB team released MongoDB Atlas for Government, a dedicated environment for US federal agencies and state, local, and education (SLED) entities that need to meet stringent security and compliance requirements.

Whether you’re investigating an issue or simply exploring your data, the ability to perform advanced log analytics is key to uncovering patterns and insights. Datadog Log Management makes it easy to centralize your log data, which you can then manipulate and analyze to answer complex questions.

Many organizations leverage AWS to build fully managed, event-driven applications, which break down complex workloads into APIs, event streams, and other decentralized services in order to improve performance and scalability. This type of architecture relies primarily on AWS Lambda functions to process synchronous and asynchronous requests as they move between a workload’s resources, such as Amazon API Gateway and Amazon Kinesis.

Engineers who support production environments are tasked with resolving new issues as quickly and efficiently as possible. But as they look to carry out these responsibilities, their remediation workflows tend to take on the following pattern: For example, someone on your team might discover in a log analysis tool that a user is flooding a key service by making an abnormal number of requests.