When a playback error occurs, a Law & Order-esque drama unfolds for video product managers seeking to understand the root cause of the issue. First, they review the analytics which indicated the error. These often include metrics like high buffer ratios, user drop-offs, and Exits Before Video Starts (EBVS). But when it comes time to dig down through the delivery chain to identify the failing links, siloed data fails them. Then the real mystery begins, what caused the problem?
Today, we have no shortage of alerts, indicators, metrics, and reports which define playback errors. However, aside from institutional knowledge (really a glorified ‘best guess’), there are few resources available to identify the culprit, or culprits, causing the problem. The resulting confusion affects user QoE and ultimately, revenues.
Fortunately, there’s a way to avoid these mysteries in order to perform efficient and effective root-cause analysis. This methodology centers around an identifier traveling through the delivery chain: the Datazoom Session_ID.
What is the Datazoom Session_ID
The Datazoom Session_ID is like an anchor, a unique 1-to-1 identifier which allows you to correlate events generated during playback against other events generated “upstream.” These events could include ISP drop-offs, CDN abnormalities, a problem with the encoder, et cetera.
As a common variable spanning the entire delivery chain from CDN to end-point, the Session_ID a key nexus with which logs and events from each link can be correlated. This means information like CDN logs can be queried and correlated with client-side player events in an analytics system. Today, we’ll focus on this CDN use case and provide a starting point for testing it.
Implementation of the Datazoom Session_ID is possible for Self-Service and Enterprise customers of Datazoom. For step by step guides, click the links below:
1. Setting Up Custom Header Requests: This article lays out the steps necessary for configuring the Datazoom Session_ID on a webpage hosting a supported Datazoom Collector.
2. Configuring CDN logs to Accept the Datazoom Session_ID: This article lays out the steps for configuring a CDN to accept the Datazoom Session_ID to facilitate the joining of client-side player events with CDN logs. Fastly enables customers to set this themselves, while other CDNs like Akamai, Edgecast, Cloudfront, and Limelight can support this functionality via a request made to your account representative.
Visualizing CDN Data with Playback Data
Once the Datazoom Session_ID is implemented across players and the CDNs, you can begin constructing metrics and visualizations for this data. Our team has prepared a sample dashboard (as an XML file) for Splunk users which can be easily imported into their account.
Alongside conventional QoE metrics built using Datazoom’s Data Dictionary (KPIs like Minutes Viewed, Requests, Starts, Average Time to First Frame, Exits Before Video Start, Average Bitrate, and Buffer Ratio), this dashboard includes CDN focused metrics for Cache Status, Fastly State (for this example), Edge v. Shield, as well as Cache and Cluster Hit Ratios. This dashboard is a great starting point for conducting root cause analysis and obtaining a grasp on how different links in the video delivery chain affect the performance of your service.
Interested in implementing the Datazoom Session_ID across your video delivery stack? Click here to signup for your 15-day, 5GB free trial of Datazoom. Reach out to us if you want more information on how to get started.