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In Practise Interviews

Datadog, Open Telemetry, & A History of Observability

Nov 6, 2022
Exploring the evolution of observability products, application telemetry collection, and microservices design patterns. Discussing the challenges and growth of observability tools, including the role of distributed tracing and market dynamics between hyperscalers and ISVs. Delving into the shift towards empowering developers, adoption of open telemetry, and the complexities in choosing between Data Dog and OpenTelemetry. Highlighting the benefits of open telemetry in enhancing observability and the impact on software developers.
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Episode guests

Podcast summary created with Snipd AI

Quick takeaways

  • Observability involves real-time system interaction via telemetry signals like tracing and logging for better understanding.
  • Legacy players like Splunk and DataDog have evolved to provide observability solutions through instrumenting applications with telemetry data.

Deep dives

Defining Observability

Observability is the capability of a team to interact with its systems in real time and gain an understanding of those systems through telemetry signals like tracing, logging, metrics, and profiling. It entails the ability to ask unforeseen questions and obtain relevant answers. Achieving observability involves a combination of telemetry signals, a storage engine for querying them, and human interaction. It goes beyond just collecting signals and emphasizes the importance of effectively utilizing them.

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