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HomeDatabase ManagementIdea to product: PricewaterhouseCoopers launches Check-In within three months on Amazon Keyspaces

Idea to product: PricewaterhouseCoopers launches Check-In within three months on Amazon Keyspaces

The COVID-19 pandemic presented enterprises with various challenges. Enterprises notably need to safeguard employees, partners, and customers when they return to the office. Holistic workforce strategies require a combination of preventative screening tools and detailed contact tracing solutions. PricewaterhouseCoopers LLP (PwC) quickly responded and adapted to develop Check-In, powered by AWS. Check-In provides companies with a way to prepare for and help reduce risk for their employees. Its preventative screening tools and automated contact tracing empowers enterprises to safeguard their people and business.

In this post, we show you how PwC built the Check-In solution from idea to product within 3 months using Amazon Keyspaces (for Apache Cassandra) and additional AWS technologies.

About PwC

With offices in 155 countries and more than 284,000 people, PwC is among the leading professional services networks in the world. PwC is a community of solvers combining human ingenuity, experience, and technology innovation to deliver sustained outcomes and build trust.

The Check-In product

Check-In is a single, technology-driven solution that provides clients the data to plan, prevent, and react precisely to mitigate risk to their people and business. As a privacy-first platform, Check-In delivers exposure-risk insights to support clear communications and inform workforce decision-making. Organizations can help protect their people with a digital health check that may help prevent potentially ill employees from coming to the workplace. Check-In’s contact tracing technology can help assess and limit the impact of a possible infection. Clients are using Check-In as part of their baseline for returning to work, a key part of their strategy to support their workforce and customers.

Given our work environment, we knew that even a single COVID-19 infection could mean a full production shutdown if we didn’t have appropriate precautions in place, and that would be catastrophic for our business.

—VP of Operations, Creative Publishing

Check-In’s automatic contact tracing has provided incremental detail in at least half a dozen cases where interviews did not fully cover the potentially exposed individuals on our team.

—SVP, Industrial Services client who achieved a 95% employee adoption rate in 2 weeks

How AWS powers Check-In’s automatic contact tracing

The following diagram illustrates the process of using Check-In.

For Check-In, speed to market was critical. With Amazon Keyspaces, PwC was given rapid, flexible scalability in response to traffic while keeping costs in line with demand and the ability to pass cost savings on to customers for this important pandemic tool. Check-In uses Amazon CloudWatch integration to build data-driven dashboards and alarms, providing clients oversight on reported cases, potential exposures, and number of affected locations. By collaborating with AWS, Check-In places user trust and security as one of the highest priorities. Check-In data within the AWS Cloud is encrypted at rest and in transit, which enables data protection for all Check-In users.

“PwC’s agility to build and deliver a high performance and scalable solution within three months during COVID-19 is remarkable. The PwC-AWS collaboration yielded incredible results for our customers and a solution that helps safeguard employees, partners, and customers when they return to the office.”

—Anil Lalwani, AWS Databases Worldwide Go-To-Market, and Mihir Desai, AWS Principal Solution Architect

Data proximity in the cloud

The following diagram illustrates the architecture of the Check-In platform.

To create a scalable framework that can ingest large amounts of data, the Check-In platform uses the following AWS components:

Amazon Elastic Kubernetes Service (Amazon EKS) – Allows the solution to deliver near-real-time results from high volume streaming data by hosting the input API. The API handles signal observation, data ingestion, as well as the query layer and output API microservices that power the client dashboards behind Elastic Load Balancers (ELB).
Amazon EMR – Enables scalable flexibility to run the Check-In platform analytics jobs that generate and deliver client metrics on top of the cold storage reporting.
Amazon Keyspaces – Stores the graph data generated by Check-In to help determine proximity between users. This is done through surveying Bluetooth Low Energy (BLE) and Wi-Fi signal detections from enabled user devices. The hot storage microservices reads the data from Amazon MSK and writes to the Keyspaces database in a streaming fashion. The data consists of observer and observation events that are used to create a graph model. Based on the number of devices and observations, the schema is designed with high cardinality to take advantage of the highly distributed database service. The workload has high variance for reads and writes, and requires auto scaling to horizontally scale in and out based on the change in throughput. A distributed query layer microservice uses the MapReduce pattern to read large volume data concurrently and provide users consistent single-digit millisecond performance experience.
Amazon Managed Streaming for Apache Kafka (Amazon MSK) – Provides decoupling to accommodate slowdowns and avoid potential data loss by handling queuing between ingest and the Amazon Keyspaces graph database storage.
Amazon Relational Database Service (Amazon RDS) – Links users to their devices in the platform by maintaining registrations and access controls to the platform data input and query layers.
Amazon Simple Storage Service (Amazon S3) – Provides signal observation data backup and cold storage reporting capabilities for client and user device metrics and analytics.

Building Check-In with AWS technologies was instrumental to the product’s success. We were able to rapidly scale up to meet the market demand while keeping data protection and privacy at the forefront of our strategy.

—David Sapin, Principal, PwC

Conclusion

In this post, we described how PwC was able to build the Check-In application. With the technologies provided by AWS, PwC has helped companies safeguard employees.

The pace at which the technology is employed has a direct impact on its ability to reduce the risk of exposure to others from an infected individual. By working with AWS, PwC increased their speed to market. Within 3 months, PwC built Check-In and was able to rapidly scale up capacity to help meet increasing demand as companies navigated this transition.

Now, over 70 enterprises and educational institutions in the US use Check-In to make more confident decisions around closures and safety measures. The application has been rapidly adopted by users, increasing trust across the workforce and aiding in the seamless transition in returning to the office.

About the Authors:

Rob Mesirow, leader of the PwC Connected Solutions/IoT practice, is a partner in the Technology, Media, and Telecom (TMT) Risk and Regulatory practice. He helps clients plan and execute their mobile and business strategies, and advises them about regulatory and market complexity and operational and financial risks.

 

 

David Sapin brings over 30 years of experience to his role as the Chief Revenue and Risk Officer for PwC’s Digital Products business. Sapin and PwC Digital help PwC’s clients solve their most pressing business problems by leveraging IoT and other digital solutions.

 

 

Anil Lalwani is responsible for AWS Databases Global GTM and brings over 20 years of experience in the enterprise technology space. He is passionate about helping customers solve business problems using modern digital technologies, and building scalable technology products.

 

 

Mihir Desai is a Principal Solution Architect working with Global Systems Integrators. He is passionate about helping customers leverage the power of the AWS Cloud. He works to provide them with architectural guidance for building scalable and resilient architectures in AWS.

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