Operations | Monitoring | ITSM | DevOps | Cloud

Tech is entering another wave of innovation with AI. With accelerated innovation comes increased complexity in already disparate environments. For Defense, those complexities are compounded by the need to maintain and operate mission critical infrastructure with highly sensitive data in air-gapped environments, often running on custom digital systems and applications. Accelerating the speed of innovation with leading technology is key for the military to maintain its competitive edge.

In today’s complex distributed systems, observability has evolved from a nice-to-have feature to a mission-critical engineering discipline. Engineering teams across organizations depend on robust observability to maintain system reliability and quickly diagnose issues when they inevitably arise. However, current observability tooling significantly lags behind user expectations by failing to support a critical capability: querying across different telemetry signals.

Kubernetes is widely used for deploying, scaling, and managing systems and applications and is an industry standard for container orchestration. Google engineers originally developed Kubernetes as an open-source project. Its first release was in September 2014, and since then, it has matured into a graduate project maintained by the Cloud Native Computing Foundation (CNCF). With the complexities of scale and distributed systems, debugging in Kubernetes environments can be difficult.

In modern microservices architectures, container observability is crucial for maintaining reliability and performance. It helps teams detect issues early and optimize distributed systems. This guide will walk you through the essentials of container observability, including advanced techniques and troubleshooting strategies to ensure your containerized applications run smoothly.

For observability adoption to scale, you must eliminate the bottlenecks. A self-service approach is the only sustainable model, enabling all teams–not just a select few–to access, implement, and scale observability easily. But making the shift requires more than access: you have to design for it.

OpenTelemetry has transformed how engineering teams implement observability. This vendor-neutral framework for collecting metrics, traces, and logs has become indispensable for several reasons: Elimination of vendor lock-in Organizations can switch observability providers without changing instrumentation code, enabling greater flexibility and negotiating power with vendors.

Using server-side telemetry to understand what’s going on inside your system is incredibly valuable, but what about the responsiveness the user actually sees? In this post, I’ll cover what synthetic monitoring is and show an example of how you can create a simple monitor using OpenTelemetry, .NET, and an Azure function. If you only want to see how it’s built, skip ahead to building a synthetic monitor.