Operations | Monitoring | ITSM | DevOps | Cloud

A synthetic test is only useful if you can trust what it’s telling you. When one fails, the reason may not be obvious. Was the application updated? Did the test change? Or both? As more people contribute and refine the same test, it becomes harder to understand what changed or restore a working version. Without clear visibility into those updates, teams can spend more time tracking down the cause of a failure than resolving it.

Historically, developers have relied on languages like C and C++ for explicit control over memory allocation and deallocation. This approach can yield very low overhead and tight control over performance, but it also increases complexity and risk (e.g., memory leaks, dangling pointers, and double frees). This often results in runtime issues that are difficult to diagnose, which can become a drag on team velocity.

Many organizations rely on OpenTelemetry (OTel) to standardize observability across distributed systems. These organizations are at varying stages of adoption and are implementing OTel in complex environments with diverse configurations. To support this range of use cases, Datadog offers many ways to use OpenTelemetry with Datadog.

Amazon EKS on Fargate is a managed service that reduces the operational overhead of maintaining a Kubernetes cluster by abstracting away the underlying infrastructure. In a serverless Fargate environment, each pod is assigned its own isolated compute resources; there is no direct host-level access.

Engineering teams need to deliver reliable, secure, and high-performing applications, all while keeping costs under control. But engineers often lack visibility into cloud cost data, relying on finance-driven reports that they receive only after the billing cycle closes. Without daily cost insights alongside observability data, they don’t know until it’s too late that an infrastructure change caused a significant cost increase.