End-user streaming services have grown exponentially in the past years. The mechanisms to serve the enormous amounts of content available have seen a lot of improvements in terms of reliability, flexibility, and overall quality. However, significant problems that affect the content quality exist in the last -segment of the delivery infrastructure: home networks. The home networks -are oftern unmanaged and poor configuration and misuse - directly affect the quality of the video streaming experience. Detecting home network issues and appropriately reporting them is key to being able to provide - appropriate remedial solutions when users report problems. We propose a Microservices driven system that will cover these aspects: 1. Client-side services that collects data about the local network and reports issues - 2. Cloud-enabled series of microservices that: a. Collect data from the clients b. Store the data collected from the clients c. Analyze the data and create summarized information d. Send alerts into various systems (to allow preemptive action or on-demand action) The client-side library should be available on a variety of platforms: Windows, OS X, Linux, iOS, Android, WebOS, Tizen, etc. The cloud-side should provide: 1. Support for multi-tenancy 2. Ability to store data securely (on a per-tenant basis, or in a “public pool”) 3. Various levels of analysis on the data: a. Basic (just storage and the ability to access it) b. Structured (storage + organize the collected data to be more easily digested) c. Pre-analyzed (structured + basic analysis on the structured data) i. Provide information about the frequency with which some events happen ii. Basic correlation between various events (ex: event X happens if event Y is present) d. Fully analyzed data (pre-analyzed + predictions) i. Create predictions related to a specific issue (or set of issues) ii. Create predictions on a per-user basis (for the issues that are likely to happen to that specific user)