Technology Category
- Application Infrastructure & Middleware - Data Exchange & Integration
- Application Infrastructure & Middleware - Middleware, SDKs & Libraries
Applicable Industries
- Construction & Infrastructure
- National Security & Defense
Applicable Functions
- Product Research & Development
- Quality Assurance
Use Cases
- Leasing Finance Automation
- Tamper Detection
Services
- System Integration
- Testing & Certification
The Customer
Not disclosed
About The Customer
The customer is a smart security solutions company with a rich legacy of over 150 years. With an annual revenue of $3.17BN, the company is a major player in the security solutions industry. The company is committed to continuous innovation and operational excellence, and aims to sustain years of trust and relationship with its customers. The company offers IoT-based security solutions and is constantly looking for ways to improve its services and user experiences.
The Challenge
The client, a smart security solutions company with over 150 years of legacy and $3.17BN annual revenue, was facing several challenges. The company's infrastructure was running on individual Pods, which increased running costs and created bottlenecks for large scale operations. The lack of automation for UI and test-cases deployment resulted in manual testing, which increased operational time and effort. Additionally, the inability to extend and decentralize access control among individuals was limiting the IoT-based security solutions offered by the company. The non-extendibility of the mobile-app features restrained user experiences and prevented users from sharing their access control.
The Solution
To address these challenges, the company deployed AWS Lambda, replacing the individual Pods. This enabled high-performant automation of UI and test-cases, and allowed the company's applications to connect with relational databases for continuous scaling and security. An automated test-bed was developed to maximize UI performance and deploy various test-cases across environments. Automation tools were deployed to test and analyze the performance of applications, and test scripts were written in Python for disparate test-cases. This allowed the client to design and engineer their products, practice full-fledged innovation with agile capabilities, and thrive in a DevOps culture. Additionally, an API-integration model was carved to allow the clients’ customers to open up with individuals and take complete advantage of Access-as-a-Service offering through subscription-based services.
Operational Impact
Quantitative Benefit
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