Modernizing healthcare with robust cloud-native app testing strategies
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Pandharinath Jadhav
Sr. Manager, Quality & Validation Services,
CitiusTech
Ankur Pandya
Manager, Quality & Validation Services,
CitiusTech
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Harshal Kulkarni
Tech Specialist, Quality & Validation Services,
CitiusTech
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Tapan Sahoo
Tech Specialist, Quality & Validation Services,
CitiusTech
Sep - 24
Article
Insights
- Cloud-native applications are scalable, resilient, and capable of enhancing patient experiences and outcomes.
- End-to-end testing is essential for comprehensive validation across all layers and components to ensure exceptional cloud-native healthcare applications.
- Cloud-native testing streamlines the development process and enables faster deployment pipelines.
Healthcare companies are increasingly enticed by the agile and flexible software development approaches enabled by cloud-native applications. Transitioning from traditional monolithic enterprise applications to cloud-native ones offer numerous advantages. This shift is driven by the cloud computing delivery model, which emphasizes how applications are created rather than where they exist.
Developers can efficiently build, deploy, and manage applications in interoperable cloud environments by leveraging technologies such as Kubernetes, containers, microservices, service mesh, APIs, and immutable infrastructure. For the healthcare industry, cloud-based applications provide even greater benefits: they are more scalable, resilient, and capable of enhancing patient experiences and outcomes. This modernization streamlines operations and fosters innovation, ensuring that healthcare providers can meet the growing needs of patients and the healthcare industry.
Cloud-native applications in the limelight
Despite the promising benefits of cloud computing, the healthcare industry has been slow to embrace cloud transformation for several reasons — strict regulations, risks associated with protected health information (PHI), and a lack of expertise in data migration, among others. However, to stay ahead of the curve and enhance patient care, healthcare facilities are now more open to adopting cloud migration to provide their customers with comprehensive services.
The global healthcare cloud computing market is currently worth USD 53.8 billion and is expected to witness sharp growth by 2029, reaching USD 120.6 billion at a CAGR of 17.5%.[1] The main drivers of this exponential growth are the widespread acceptance of e-prescribing, wearable devices, and electronic health records (EHR), among others. Cloud-native applications are reshaping software development from secured shared data access to analytics, remote monitoring, flexible payment models, and integration and interoperability.
Successful integration with the cloud denotes minimal downtime, quick care services, and the highest security measures, which are critical in the healthcare industry. However, delayed or faulty services can come at a high cost. To prevent this, healthcare organizations must undergo robust testing before development for exceptional care.
The significance of cloud-native app testing
Many companies fail to unlock their full potential on their journey to the cloud due to their simple 'lift and shift' strategy instead of pursuing holistic digital transformation. True cloud migration involves standardizing and automating the IT environment through APIs, integrating the latest security models, and automating operations.
Furthermore, adopting a full-proof test strategy helps create and execute unit and component tests, detect bugs early, boost code quality, simulate realistic load conditions, and resolve issues quickly. Below are essential test strategies that assist in producing exceptional cloud-native applications.
- Contract and integration test
Each unit or component in a cloud-native application has a contract that dictates its interactions with other services, treating them as black boxes. The interactions between different microservices are evaluated to verify adherence to these contract requirements using the test double technique (mocked or stubbed data). This practice helps prevent service disruptions, ensures code ownership, reduces infrastructure costs, accelerates development, and guarantees continuous consumer service.
On the other hand, the integration tests verify the communication paths between microservices and individual components of a system. This method leverages real data to validate interaction and integration as a whole in a real-world scenario. - Service virtualization
Creating virtual simulations that mimic the behavior, performance, and response of inaccessible dependent components or systems in a controlled and scalable environment helps testers eliminate bottlenecks, minimize the risk of failure, and lower costs associated with maintaining dependencies. Developers often create virtual services by recording traffic using service virtualization platforms instead of building the interaction pattern from ground zero based on interface or API documentation. - User interface testing
Developers should perform user interface (UI) testing to support accurate data rendering on application pages, views, and smooth navigation. This testing focuses on an interface's visual elements, layout, design, and menus to enable a consistent experience, swift responsiveness, and convenient accessibility.
In a microservices architecture, Backend for Frontend (BFF) services are utilized to streamline the integration of the UI with multiple backend business or adapter services, streamlining the information at the front end to align with users' requirements. - Functional and end-to-end testing
Each functionality of the software application is assessed by comparing the actual and expected output to meet the requirements. System-level testing covers the entire flow from the consumer (UI) to the exact system of record or data source.
In end-to-end testing, developers test the entire application, going beyond enterprise boundaries for comprehensive validation across all layers and components. This allows all services to work together and function as a cohesive whole.
Tackling the challenges
Transitioning to the cloud often presents several challenges, including a lack of coordination across teams, the vast scale of testing required, and the irregular behavior of applications when changes occur to the underlying infrastructure. These factors can significantly hinder migration speed and quality. Additional challenges include:
- Shorter testing span
With native applications undergoing shorter release cycles and frequent updates, these condensed timelines significantly impact testing efforts. Testers must ensure that testing is completed within tight deadlines without compromising on quality. - Platform independence
Consistent behavior across different platforms can be tricky due to vendor lock-in, limiting cross-platform compatibility. Moreover, when customers use multiple third-party APIs or other cloud services, testing is even more challenging as providers use different database schemas and architectures. - Dealing with serverless functions and stateless programs
Serverless functions exhibit varied cold start periods and have local environments that differ from the cloud. This could pose challenges for testers in estimating and assessing response times. Additionally, when customers rely on stateless programs that lack information from previous interactions, managing each request becomes laborious as each is treated independently of others. - Data security and privacy
Native applications handle sensitive user data and operate in multi-tenant environments, upholding robust security measures becomes paramount. Testers must prioritize authentication and authorization, secure communication protocols and encryption algorithms, and prevent data leakage while complying with privacy laws.
To counter these problems, testers should initiate their evaluation process early to identify and address issues in the development phase. Automated testing helps keep up with rapid deployments, and implementing monitoring and observability procedures offers valuable insights into application performance and behavior. In addition, chaos engineering assesses potential system weaknesses and rectifies them before failure, boosting system resilience.
Diving into the promising benefits
Overcoming these challenges by leveraging the cloud streamlines the development process and enables faster deployment pipelines. From agility to cost-effectiveness, cloud-native applications offer numerous benefits.
- Quick and precise release schedules
As organizations work in a cloud computing environment, it enables faster and more targeted release schedules. - Fault-tolerant systems
Cloud-based applications help minimize service disruption during system failure through continuous availability. - Reduced vendor dependence
Using open-source technologies reduces dependence on specific vendors, providing flexibility in choosing and switching between them. - Improved infrastructure management
Cloud-native testing empowers organizations to simplify storage allocation, provision cloud resources, or establish network configurations, enhancing overall infrastructure management. - Saved costs with containerization
Containerization promotes consistency and portability across different environments, lowering development costs and complexities.
Inside healthcare use cases of cloud-native applications
Cloud applications are becoming the mainstay of healthcare transformation, connecting providers, patients, and data for enhanced care. Here are a few ways how the cloud is elevating user experience:
- Remote patient monitoring and virtual consultations
The Internet of Medical Things (IoMT) hosted on cloud is integrated into wearables, collecting patient data on smartphone applications. This data is analyzed to help doctors supervise patient health and consult with them remotely, an added benefit for those who cannot frequently travel to healthcare facilities. - Optimized emergency care with smart ambulances
Cloud-enabled smart ambulances reduce casualties enroute to the hospital by enabling emergency medical technicians (EMTs) to communicate with emergency room (ER) doctors through VR. By providing detailed patient conditions and data, cloud-powered ambulances enable timely treatment on the road. - Interoperability among healthcare systems
Cloud-native applications facilitate a seamless flow of data across devices and systems, wherein information is no longer fragmented. This provides healthcare professionals with real-time updates on patient status, bed availability, medications, and other crucial details, enabling them to work with the most current information.
The road ahead: Rethinking cloud-native with AI
As the healthcare revolution gains momentum, the integration of artificial intelligence (AI) into cloud-native applications is set to accelerate significantly. Cloud-based AI solutions expedite development and deployment and promote global collaboration by being accessible from anywhere. By 2030, the cloud AI market will reach USD 397.81 billion, growing at a staggering CAGR of 30.9% between 2023 and 2030.[2]
The primary drivers for increased cloud AI adoption in healthcare include enhanced security measures, advanced analytics, intelligent automation, error flagging in medicine dosage, medical imaging analysis, and reduced administrative overhead through minimal human intervention. These advancements are not just beneficial; they are essential. Embracing AI in cloud-native applications is indispensable for those in charge of modernizing healthcare. This integration promises to transform patient care, streamline operations, and drive unprecedented innovation in the industry.
References
- 1. Healthcare cloud computing market size, share & trends 2029 [marketsandmarkets.com]
- 2. Cloud AI market size, share & growth 2030 [fortunebusinessinsights.com]
- 3. Cloud as the ultimate digital enabler [mckinsey.com]
- 4. In search of cloud value: Can generative AI transform cloud ROI? [mckinsey.com]