As infrastructures become increasingly ephemeral and complex, traditional monitoring approaches are hitting their limits. From the emergence of eBPF (Extended Berkeley Packet Filter), which enables deep, agentless visibility at the heart of the Linux kernel, to the adaptation of observability for Serverless, companies are shifting toward an “as-Code” model.
This technological convergence no longer merely monitors service availability; it integrates performance data from the outset of software design (Observability-as-Code), turning invisible infrastructure into a transparent, automated, and highly resilient system.
eBPF: The Kernel’s “Superpower”
This article on eBPF (Extended Berkeley Packet Filter) explains how this technology is reshaping DevOps. Traditionally, to monitor a system, you had to modify application code or load risky kernel modules.
> The concept: eBPF enables running programs directly in the Linux kernel in a secure way, without changing a single line of application code.
> The DevOps advantage: Total visibility into the network, security, and performance with almost no impact on resources. It marks the end of heavy agents that slow down servers.
Read: https://www.silicon.fr/cloud-1370/ebpf-devops-225348
The Serverless Observability Challenge
This article discusses the complexity of Serverless (such as AWS Lambda). Since you no longer manage the server, you lose access to traditional hardware metrics.
> The problem: Functions are ephemeral (they appear and disappear in a few milliseconds). Traditional monitoring tools are often too slow to capture them.
> The solution: Distributed tracing. The emphasis is on tracking the request across all services rather than the health of a single server.
Read: https://www.silicon.fr/cloud-1370/observabilite-serverless-225361
Observability-as-Code (OaC)
This article advocates integrating observability directly into the development lifecycle, on par with Infrastructure-as-Code (Terraform, CloudFormation).
> The idea: Instead of manually configuring alerts and dashboards after deployment, you define them in your YAML or JSON code.
> The objective: Ensure that every new microservice is born with its own measurement tools, avoiding blind spots during rapid production deployments.
Read: https://www.silicon.fr/cloud-1370/observability-as-code-225520
