- — Bridging Cloud and Edge —​​​​​​​ -

Cloud Corner (name changed) is a Web application designed to help IT professionals, business of all sizes and hyper scalers to effortlessly manage and use computing, data storage, data analytics, artificial intelligence, machine learning, and more.

In today's digital world, the integration of cloud and edge computing involves a lot of complex challenges for businesses. 

Cloud Corner aims to revolutionize work management on cloud and edge with a Single-pane-of-Glass having maximum security at reasonable costs that can be managed in a seamless and effortless manner.

Our journey began with a user centric approach. We started understanding the real-world issues and pain points faced by organizations and professionals seeking to optimize their cloud and edge infrastructure.

We started our research by understanding and capturing the demographics of our users, which was used to create our User Personas. once we had the personas in place we made some assumptions for us to prepare a questionnaire for the users. 

The objective was clear, to figure out all the problems from the users. We conducted short interviews, surveys and shared some questionnaires to the diverse stakeholders (IT professionals, developers, administrators, and decision-makers) to understand their pain points and aspirations. We also noted insights from other cloud and edge related platforms which helped us uncover some common challenges.

With all the user statements in hand we started with affinity mapping and grouped the user statements, observations and insights based on their similarities under certain categories. 

Based on the different behaviors, pain points, goals and motivations that we categorized in affinity mapping, we recorded the top problem statements in this area that are listed below:

- Resource management: Edge computing involves managing a large number of geographically dispersed resources, such as edge devices, gateways, and servers. These resources have different processing capabilities, storage capacity, and connectivity requirements, which makes managing them very challenging.

- Security: Edge computing environments are susceptible to a wide range of security threats, such as data breaches, hacking, and malware attacks. Security measures must
be in place to protect edge devices and data from these threats.

- Interoperability: Edge computing involves integrating multiple devices, platforms, and protocols, which may not be compatible with each other. Interoperability challenges
may arise due to the lack of standardization and diversity of technologies involved.

- Connectivity: Edge computing environments require reliable and high-bandwidth connectivity to enable real-time processing and data transfer. However, network connectivity in remote and rural areas may be limited, which can impact the performance of edge applications.

- Data management: Edge computing generates vast amounts of data that must be managed effectively. The data generated at the edge must be processed, analyzed,
and stored in real-time, which poses significant challenges in terms of data storage, processing, and management.

- Scalability: Edge computing environments must be scalable to support changing workloads and requirements. Scalability challenges may arise due to the limited
processing power and storage capacity of edge devices, which may not be sufficient to handle peak workloads.

- Application Management: Managing applications in an edge cloud environment can be challenging due to the dynamic nature of edge devices and the need for real-time
processing. Applications need to be optimized for the edge environment and must be able to handle intermittent network connectivity and varying device capabilities.

With all the above pain points what was also needed to be in place was:

With these problem statements we created wireframes of use flows and task flows. These were tested with some real users and a few of our colleagues. we captured the flows, actions and behaviors of our users. This data helped us refine our flows and test again which resulted in making it seamless.

As we moved into implementation, our focus was on seamless integration and user onboarding. We worked closely with early adopters, gathering feedback and refining the product based on real-world usage.

- User Training: Comprehensive training resources and tutorials for easy adoption.

- API Integrations: Open APIs for custom integrations with existing systems.

- Scalability: Designing for scalability to accommodate growing cloud and edge footprints.

- Phase 4: Impact & Success

​​​​​​​- Efficiency Gains: Reduced complexity led to enhanced productivity.

- Improved Performance: Optimal data flow & reduced latency improved system performance.

- Cost Savings: Better cost management resulted in significant savings for organizations.

- User Satisfaction: Positive feedback reflected improved usability & overall experience.

- Conclusion: Enabling Tomorrow's Infrastructure.

In conclusion, our journey from research to implementation exemplifies the power of UX design in addressing complex technological challenges. By prioritizing user needs and refining our solutions iteratively, we bridged the gap between cloud and edge computing, empowering organizations to leverage these technologies effectively.

Through ongoing user engagement and continuous improvement, we remain committed to shaping the future of cloud and edge computing support—a journey fueled by innovation, empathy, and a relentless pursuit of exceptional user experience.