Telemetry standards & trends in 2023

A non-exhaustive list for telemetry concepts

Photo by Annie Spratt on Unsplash

Preface

The trigger for the following blogpost was pulled while looking for a new role in summer 2023. I realised companies were very interested in the topic, mainly because of the increased complexity in developed software and its underlying infrastructure on the cloud or on premises. Development teams needed more information about how the systems behave on a daily basis in very granular level i.e. cloud environments, Kubernetes clusters, containers, software applications.

Introduction

In today’s fast-paced digital landscape, businesses are increasingly relying on data to drive their decision-making processes and gain a competitive edge. Telemetry has emerged as a crucial component in this data-driven ecosystem, providing organizations with real-time visibility and actionable insights into the performance and behavior of their systems. From tracking application metrics to monitoring infrastructure health, telemetry acts as a critical foundation for understanding complex systems. However, among the vast array of data and metrics available, there is one fundamental requirement that stands above all — the ability to transform raw data into meaningful and actionable information.

In this blog post, we explore some industry standards and trends related to telemetry and software pipelines:

Telemetry Standards and Protocols

• OpenTelemetry: An open-source observability framework that provides standardized APIs and instrumentation libraries for collecting telemetry data. It supports multiple programming languages and offers flexibility in choosing backends for storing and analyzing telemetry data.
• Prometheus: A popular open-source monitoring and alerting system that follows the pull-based model for metrics collection. It uses a simple text-based exposition format for metrics and provides powerful querying capabilities.

Observability as Code

• The rise of “Observability as Code” focuses on defining and managing observability configurations and settings as code. This enables version control, reproducibility, and automation of observability setups alongside…