# Skyscanner's journey to effective observability

DevFeed: [Skyscanner's journey to effective observability](<https://devfeed.tech/articles/skyscanner-s-journey-to-effective-observability-32391.md>)

Original publisher: [Read original article](<https://medium.com/@SkyscannerEng/skyscanners-journey-to-effective-observability-655167a49d2f?source=rss-401f3b3c958f------2>)

Author: Skyscanner Engineering

Published: 2025-03-14T10:34:23Z

Content type: opinion

Language: en

Sources: [Stories by Skyscanner Engineering on Medium](<https://devfeed.tech/sources/stories-by-skyscanner-engineering-on-medium.md>)

Topics: [observability](<https://devfeed.tech/topics/observability.md>), [telemetry](<https://devfeed.tech/topics/telemetry.md>), [Instrumentation](<https://devfeed.tech/topics/instrumentation.md>), [OpenTelemetry](<https://devfeed.tech/topics/opentelemetry.md>), [Prometheus](<https://devfeed.tech/topics/prometheus.md>)

Tags: [data](<https://devfeed.tech/tags/data.md>), [engineering](<https://devfeed.tech/tags/engineering.md>), [instrumentation](<https://devfeed.tech/tags/instrumentation.md>), [kubernetes](<https://devfeed.tech/tags/kubernetes.md>), [monitoring](<https://devfeed.tech/tags/monitoring.md>), [observability](<https://devfeed.tech/tags/observability.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [opentelemetry](<https://devfeed.tech/tags/opentelemetry.md>), [prometheus](<https://devfeed.tech/tags/prometheus.md>), [telemetry](<https://devfeed.tech/tags/telemetry.md>), [traces](<https://devfeed.tech/tags/traces.md>), [tracing](<https://devfeed.tech/tags/tracing.md>)

## AI overview

Skyscanner describes its journey to simplify and improve its observability platform. The article explains the limitations of its earlier mix of vendors and internal systems, and outlines goals including reducing engineer cognitive load, correlating telemetry signals, controlling data cost and quality, and adopting open standards such as OpenTelemetry.

## Source excerpt

The year was 2020 and Skyscanner, like the entire travel industry, faced unprecedented challenges due to the global COVID-19 pandemic. Yet, this difficult year also provided an opportunity for introspection, prompting us to enhance our tools and processes to emerge more resilient than ever, to be the world's number one travel ally. This is where our journey to completely revolutionise our approach to observability begins. The image below shows a "simplified" view of what our internal observability platform looked like at the time. As you can see, there was some room for simplification. This platform contained a mix of specialised vendors for RUM, tracing, or synthetics, and a large number of internal systems based on open-source backends like OpenTSDB, Prometheus, or multiple ELK stacks. However, our challenges were not simply related to cost, or the complexity of running this platform with a small team. We understood that our most important problem to solve was improving the confidence of all engineers to understand and operate their services, to reliably connect more than 110 million users to over 1,200 flight, hotel and car hire partners each month. This required an observability platform that would... Reduce cognitive load and context switching for engineers, with one single platform, and one single telemetry language. Correlate traces, metrics, logs, and events, across multiple services and frameworks, from client devices all the way down to Kubernetes containers. Our components don't work in isolation, and neither should the signals we use to observe them. Optimise the cost and quality of the data produced, storing the data we need to operate our systems reliably, and no more. Meaningful, contextual data can be cheaper than low-quality, verbose data. Implement open standards to future-proof our instrumentation and transport layers, to ready our tech stack for changes in the overall industry while reducing maintenance overhead. If you know anything about observab