Granular origin to edge visibility

Explore metrics from responses delivered from your origin servers

Integrating a content delivery network (CDN) into your delivery network is paramount for boosting performance and speed. However, it shouldn't come at the expense of compromising visibility into your origin's performance. Say goodbye to complicated origin data pipelines or lack of visibility with Origin Inspector.

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Fastly Origin Inspector

Discover real-time and historical origin visibility

Access real-time and historical metrics from the responses delivered between your origin servers and the Fastly edge cloud network with no need to send log data to a third-party data collector.

Metrics are presented in datasets and visualizations that allow you to effortlessly monitor every aspect of your origin performance - from responses and bytes to status codes and beyond.

Granular origin metrics as performance indicators

The granular metrics available via Origin Inspector quantify origin infrastructure and egress cost savings. For instance, a higher cache hit ratio (CHR) indicates that the cache is effectively serving a significant portion of requests from its stored content, leading to improved performance and reduced load on the origin server.

Data driven action

Up to the second real-time and historical metrics allow you to troubleshoot errors by narrowing down performance issues from the top down, starting with your origin server. This vantage point also lets you discover areas for improvement and gather valuable insights for data driven CI/CD.

Reduce complexity and effort by simplifying data collection

Origin traffic metrics and other performance benchmarks available directly within the Fastly app assure consistent data reference between teams and streamlines issue resolution. Easily monitor egress traffic (between your origin and Fastly edge server) within the Fastly app without spending time and cost on separate data storage and analysis tools.

Features

Break open black box data

Performance indicators like cache hit ratio, origin offload, origin health and more are exposed and easily interpreted within the app alongside domain and service level detail.

Other solutions require 3rd party data vendors to uncover your origin data. Origin Inspector surfaces origin traffic trends and granular data points that would be otherwise difficult to view and correlate with other metrics and stats.

System and custom visualizations

Insightful metrics can be shared via preset system dashboards or customized for different use cases. Your teams are able to reference the precise data needed, knowing that other teams are utilizing the same dataset.

Origin Inspector for serverless compute

All the origin traffic metrics available from Fastly Network Services are also available for serverless programs built and run with Compute.

We looked up at our big Fastly Dashboard in the office and noticed that the pattern of errors had radically altered

Ecommerce

“We often look at our Fastly logs before we look at our origin’s logs. Once, we did a release, and it turned out that there was an edge case throwing tons of service errors. We looked up at our big Fastly Dashboard in the office and noticed that the pattern of errors had radically altered. By visualizing Fastly’s logs, we are able to identify and quickly fix bugs.”

Ross Paul

CTO

A complete picture of what’s happening

Media & Entertainment

“We use Fastly’s analytics to check hit rates and errors in real time, and we also use the API to grab stats and pump them into our Graphite setup here — along with doing automated deploys, which are amazing. This way, we have data on both ends and gain a complete picture of what’s happening.”

Darrell Mozingo

Former Team Lead of Content Development

Easy for us to figure out what was going on in the stack and fix any issues

Financial services

“The Fastly Dashboard gives us real-time visibility into what is actually going on. At one point during the event, it was immediately clear from our monitoring systems and Fastly that a particular subsystem of ours started to have problems. This made it easy for us to figure out what was going on in the stack and fix any issues as they were happening.”

Andrew Metcalf

Engineering Manager