NetSkrt
Shining a Light, on Internet Dark Spots
Internet Streaming, Content Delivery, Broadband Bandwidth
- Industry : Information Technology
Service Offered
TechOps
App Optimization
DevOps
Overview
Netskrt’s edge Content Delivery Network (eCDN) uses edge caching to make streaming video possible anywhere. As consumers increasingly get their news and entertainment from internet streaming services, they expect to access these services from anywhere – on the train, on airplanes, in remote areas, and rural communities. Airlines, railways, and internet service providers are all struggling to meet this demand due to constrained or unreliable network connections. Netskrt’s eCDN is the solution – intelligently caching content, improving the performance of streaming video and other Wi-Fi applications, and at the same time, reducing demand on the backhaul network.
Dissecting Problem
Business Requirement
- End-to-end testing of the Netskrt solution
- A skilled and experienced team of QA engineers
- Structured and well-defined Software Testing/Quality Assurance process.
Challenges
- Remotely onboarding and gaining a solid understanding of a complex product
- Effective communication and alignment between teams working in different time zones
- Efficient knowledge gathering on the product during client sync-ups
- Establishing a Celestial test lab and troubleshooting set up issues
- Mitigating downtime of edge server in our lab; coordinating across time zones with Netskrt
- Identifying environmental/networking/VPN issues vs software issues
- Differentiating between product related issues vs CDN or player issues
- Verifying whether issues are device category-specific or across multiple device categories and browsers
- Reporting issues with sufficient information for development to reproduce and address
Celestial’s Solution
We implemented a manual testing solution that covers multiple kinds of Functional Testing – Smoke, Sanity, Regression, Compatibility, Integration, System, Exploratory, Playability Testing, etc. In automation, we also automated basic Smoke Testing and about 30% of the manual test case.
Test Case Writing
We divided the test cases based on core functional areas of the product and started working on creating a base set. Over time, we built on this to cover all major functionalities.
Analysis
We started by understanding the product and having multiple calls with Netskrt to understand the product and the requirement.
Identify tool for writing Test Cases
Since Netskrt team was already using Atlassian, we chose Zephyr Scale which integrates well with their product.
Set up Query Sheets
Query sheets were shared with client. Since the teams were in different time zones, this worked as a collaboration platform – to record our queries and their answers.
Automation
Once we had enough test cases and had gained enough understanding of the product, automation was brought into place. For Automation, we have a Page Object Model (POM) based pytest automation framework that covers all kinds of test cases – UI, DB, and CLI.
<span data-metadata=""><span data-buffer="">Project Execution
- Followed Agile methodology for execution, each sprint was of two weeks.
- Weekly client calls were scheduled to provide updates on ongoing issues/defects
- Weekly work completion reported over the calls
- Regular daily activity: Ticket verification, Regression Testing, Play Testing, Bug/Defect filing, and Test Case writing
Technology Used :
Outcomes
- Established an efficient QA process for Netskrt
- Identified defects and worked with Netskrt to pinpoint the root cause and resolve
- Collaborated with development to optimize product performance
- Automated QA process to improve overall release time and quality
