Evaluating how a video service performs across devices, networks, and platforms.
Also referred to as video service testing or automated video QA, this process ensures playback success under real-world conditions.
Example: automated testing ensures flawless playback before every release.

Repeated or continuous observation of live or on-demand streams to detect quality issues in real time.
Example: Witbe monitoring robots alert you instantly when playback fails.

Testing the video's full journey from signal to screen, across real devices, networks, and geographies.
Learn more → Absolute end-to-end monitoring

Running tests on the same devices and connections actual consumers use rather than emulators.
Example: only real-world testing reveals what viewers truly experience.

A measure of how enjoyable, reliable, and responsive a service feels to the viewer.

Network or system-level performance metrics such as bandwidth, latency, and packet loss that may influence QoE.

Running predefined or goal-based test scenarios on real devices to validate expected behavior.

A defined scenario with an expected outcome used to validate app or playback availability, performance and/or quality.

QA thresholds (e.g., “startup time < 3s”) determining whether a test succeeds.

Running automated tests at every code commit to prevent regressions before release.

Running a collection of test scenarios after an update to confirm that existing functionality still works correctly.

Validating consistent behavior and quality across devices, OS versions, and applications.

Functional tests check that actions (play, pause, login) work, as opposed to other type of tests, which evaluate performance, stability, and quality.

A new generation of AI that plans, executes, and adapts tests autonomously toward a goal.

Testing that leverages machine learning and reasoning to autonomously validate playback quality and performance.
Also referred to as AI-powered video monitoring or predictive QA analytics.

Instead of scripting steps, define the goal, like "play a live sports channel," and AI figures out how to achieve it at runtime.

Automation that adapts to UI changes or pop-ups without breaking test execution.

AI improves test accuracy and speed through feedback from past executions.

Human experts remain involved to validate anomalies and refine automation behavior.

Groups of specialized AI agents collaborating on complex QA workflows.

AI creates new test cases dynamically based on observed behavior and goals.

An open standard that allows AI agents, LLMs, and systems to communicate securely and contextually.

Coordinating multiple automated tests to run in sequence or parallel, optimizing coverage and efficiency.

Automation that requires no manual scripting, relying instead on AI recognition and high-level goals.

Controlled setup for reproducible test execution.

Automated output of results, logs, and video proof for QA validation.

Witbe's real-time algorithm that quantifies perceived video quality through image and playback analysis.

Algorithm that detects incidents in real time such as black frames, rebuffering, frozen images, or sound availability.

Industry metric developed by YouTube research to benchmark short-form video quality.
Learn more → Adding industry standards to video quality measurements

Streaming method that adjusts resolution and bitrate according to available network bandwidth.

Delay between broadcast origin and viewer playback. Low latency is essential for live events.

Interruptions in playback caused by buffering; a key KPI for QoE.

Automated identification of missing frames or total signal loss.

Number of frames displayed per second; impacts smoothness and perceived quality.

Amount of data per second allowed to encode a video stream; higher bitrates often yield better quality.

Video technology that enhances contrast and color depth for more realistic images.

Comparing performance or quality metrics against competitors or industry standards.

Quantitative metric used to evaluate video service health, such as availability rate or playback time.

Sequential data collected over time to monitor trends in QoE and QoS.

Witbe's hardware robot that performs real-world testing on consumer devices.

The observability platform that collects, correlates, and visualizes monitoring KPIs.

Web app dashboard providing full visibility into monitored devices located anywhere globally.

Witbe's web interface for remotely viewing and controlling devices through multi-device mosaics.

An open-source, cross-platform protocol created by Amazon, Google (YouTube), and Netflix to standardize remote device control.

Feature that lets engineers control multiple devices across locations simultaneously.

Interactive workspace where teams visualize playback KPIs and service health in real time.

Customizable limits that trigger alerts when a KPI exceeds expected parameters.

A global network of servers that cache and deliver video closer to viewers to reduce latency.

Technology to deliver video content via the internet, bypassing traditional broadcast methods.

Content library allowing users to select and play videos at any time.

Real-time content delivery such as sports, news, or events.

Playlist (like .m3u8) that describes how segments/chunks of a video stream are delivered in ABR.

A small chunk of video, typically a few seconds long, that is downloaded sequentially during playback. Segments are listed in the manifest file and allow adaptive bitrate streaming to switch between quality levels dynamically based on network conditions.

Systems that compress and convert video signals into formats suitable for streaming.

Encryption and licensing mechanisms protecting premium content from piracy.

When the displayed content differs from expected programming due to scheduling or delivery errors.

Errors that can be seen by the user (on screen) or invisible (404 error on a chunk where the player can switch before buffering) or even make the player crash without reporting any technical error.

Protocol enabling dynamic switching between quality levels during playback.

Instant notifications sent when a performance issue or anomaly is detected.

Centralized visual interface showing live KPIs, device status, and playback performance.

Identifying the underlying technical reason for service degradation.

Average duration between incident detection and resolution.

Average time required to identify a failure once it occurs.

Commitment defining minimum service quality and uptime guarantees.

Using analytics to perform actions which anticipate and aim at preventing potential failures.

Process of tracking, prioritizing, and resolving service-related issues.

Statistical visualization of service performance over time to identify patterns or anomalies.

A quick-start setup deploying goal-oriented testing directly on your own devices.

Flexible model where tokens represent available automation capacity for testing sessions.

Ability to increase testing coverage easily (e.g. without adding new hardware).

Quantifiable benefits of monitoring, such as reduced MTTR and improved service uptime.

Percentage of times a service is operational and accessible to users.

Proof that KPIs meet regulatory or contractual thresholds.

Optimization of testing and monitoring processes to reduce costs and manual effort.

Automate test execution on real devices to validate playback, navigation, and app behavior before release of new versions.

Monitor live and on-demand streams in real time to detect playback errors, freezes, or quality drops.

Continuously verify live channels' availability, latency, and lineup accuracy, including special events.

Automatically ensure your entire VoD catalog is available, playable, and compliant across all platforms.

Measure the true performance of dynamically inserted ads, detect errors, and verify ad delivery with video proof.

Validate short-form and vertical video performance across mobile apps and social platforms.

Automate end-to-end QA on smart TV platforms like Samsung Tizen, LG webOS, Android TV, and Roku, no SDK or modification needed.

Run automated video playback and navigation tests on iOS and Android smartphones, no SDK or modification needed.

Access and control real devices from anywhere to reproduce issues, troubleshoot, and collaborate across teams.

Verify that scheduled channels are playing correct content and that channel changes are fast, accurate, and correctly sequenced across all broadcast or OTT feeds.

Compare QoE against bandwidth consumption to optimize streaming profiles and CDN costs.

Ensure flawless streaming during high-traffic events like sports finals or award shows, with real-time alerts.

Compare your service performance against competitors to identify optimization opportunities and SLA strengths.

Instantly investigate and fix playback issues on any device through the virtual NOC's remote control interface.

Track uptime, availability, and accessibility across devices and regions to maintain SLA compliance.

Monitoring how AI agents make decisions during QA automation to ensure reliability.

Continuous analysis of incoming test data to generate instant insights.

Combining multiple KPIs (latency, MOS, rebuffering) to pinpoint service issues.

Running QA directly at the network edge for faster results and reduced latency.

Automation that adjusts its own execution based on past outcomes.

Deploying monitoring infrastructure in the cloud for global scalability.