CI/CD services such as AWS CodePipeline enable developers to automate and accelerate the process of building, testing, and deploying code. But with the speed, scale, and complexity of the modern software development life cycle, even small performance regressions or increases in failure rates in your CI system can quickly snowball, slowing or even halting releases and causing cost overruns.

Containers are powerful tools for scaling and deploying your applications, but with so many components pulled from different sources, there’s a greater potential for issues within them to go undetected. As a result, you need to monitor every layer of your containerized environments for vulnerabilities and performance problems—from your application to your container images.

When you’re responding to an issue with your application in the heat of on-call, you need reliable, well-maintained tooling that’s painless to use. Otherwise, the time you’ll spend combing through monitoring data for context, connecting to hosts and other infrastructure resources, and pivoting between consoles for various managed services can add up quickly and slow your response.

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.

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.

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.

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.