Enabling auto-instrumentation for your Lambda functions provides detailed insights into the performance and security of your serverless applications. Developers often also use custom instrumentation to fine-tune visibility and further tailor telemetry to their business needs. However, different teams within your organization might use a variety of instrumentation libraries, and achieving more granular visibility can come at the expense of data portability and interoperability.

Amazon Bedrock is a fully managed service that offers foundation models (FMs) built by leading AI companies, such as AI21 labs, Meta, and Amazon along with other tools for building generative AI applications. After enabling access to validation and training data stored in Amazon S3, customers can fine-tune their FMs to invoke tasks such as text generation, content creation, and chatbot Q&A—without provisioning or managing any infrastructure.

AWS Step Functions allows you to coordinate activity from hundreds of services—including AWS Lambda, Amazon EKS, and Amazon API Gateway—to build and orchestrate serverless workflows. With Step Functions, you organize work into workflows known as state machines, in which each state defines a task or decision and specifies the next state in the workflow.

Tailscale is a modern remote access solution that allows customers to easily scale, segment, and manage a private network as their business grows. It enables encrypted point-to-point connections using the open source WireGuard protocol, so that devices on your private network can only communicate with each other.

As organizations adopt Kubernetes, they face gaps in security, reliability, and observability such as unencrypted communication, lack of multi-cluster support, and missing reliability features like circuit breaking. Buoyant Cloud is the dashboarding and automated monitoring component of Buoyant Enterprise for Linkerd, which helps organizations secure and monitor communication between Kubernetes workloads.

As customers scale to thousands of hosts and deploy increasingly complex applications, it can be difficult to ensure that every host is configured to give you the visibility you need to monitor your infrastructure and applications. To ensure visibility across a growing number of hosts, you need to know that your observability strategy is implemented uniformly across your entire fleet of Datadog Agents installed on these hosts.

Datadog customers have an abundance of observability data at their fingertips. Using this data effectively requires having the right visualizations and analysis tools. For some teams, the powerful functionality of spreadsheets is critical to their ability to make data-driven forecasting and business decisions. That’s why we are pleased to announce that Actiondesk—a spreadsheet-powered connection to your live data—is joining Datadog.

The Datadog Service Catalog is a centralized hub of information around the performance, reliability, security, efficiency, and ownership of your distributed services. By using the Service Catalog, teams can eliminate knowledge silos and realize seamless DevSecOps workflows.

Incidents put systems and organizations to the test. They pose particular challenges at scale: in complex distributed environments overseen by many different teams, managing incidents requires extensive structure and planning. But incidents, by definition, break structures and foil plans. As a result, they demand carefully orchestrated yet highly flexible forms of response. This post will provide a look into how we manage incidents at Datadog. We’ll cover our entire process.

In this year’s report, we see how organizations are using containers not just to solve their day-to-day infrastructure needs. Rather, customers are exploring the next technology frontier of containers by building next-generation applications, enhancing developer productivity, and optimizing costs.