Telemetry standards & trends in 2023
A non-exhaustive list for telemetry concepts
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 infrastructure and application code.
Cloud-Native Observability
- With the adoption of cloud-native architectures and technologies like containers and microservices, observability practices have evolved to cater to these environments. Cloud-native observability leverages tools and techniques that are specifically designed for distributed, dynamic, and scalable systems.
Distributed Tracing
- Distributed tracing has gained significant traction as a way to gain visibility into complex, distributed systems. Standards like the OpenTracing and OpenTelemetry projects provide consistent approaches to trace requests across services and gain insights into latency, bottlenecks, and dependencies.
Shift-Left Observability
- There is a growing emphasis on incorporating observability practices early in the software development lifecycle, shifting observability activities to the left. This includes instrumenting code, designing for observability, and integrating observability checks into the CI/CD pipeline.
Continuous Delivery and Deployment Pipelines
- DevOps practices and CI/CD pipelines have become industry standards for rapid and automated software delivery. Integration of observability into these pipelines allows for automated testing, quality checks, and monitoring of applications throughout the delivery process.
Site Reliability Engineering (SRE) Practices
- SRE practices, popularized by Google, emphasize the importance of observability in achieving reliable and highly available systems. SREs utilize telemetry data for error budget calculations, incident management, and proactive monitoring.
AI and Machine Learning for Observability
- AI and machine learning techniques are being applied to observability data to gain deeper insights, detect anomalies, and automate troubleshooting. These technologies can help identify patterns, predict issues, and provide intelligent recommendations.
We have explored how telemetry, observability and software pipelines relate to each other. In summary, observability practices are applied throughout the software development lifecycle to ensure the development and operations teams have a good understanding of the implemented software.
About me
As a DevOps engineer and technical writer, I am committed to providing high-quality services to my clients. With my expertise and experience, I can help you streamline your development processes and improve your overall software development lifecycle. Additionally, my technical writing skills enable me to communicate complex ideas and concepts in a clear and concise manner. Whether you need help with DevOps implementation, technical writing, or both, I can provide you with customized solutions that meet your specific needs. If you’re interested in learning more about myself and my services, please visit my website at www.smos.gr or contact me on LinkedIn.
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