Serverless architecture is a type of computing that allows developers to build and run applications and services without worrying about the underlying infrastructure. For example, in healthcare, serverless architecture can develop and deploy applications that handle sensitive patient data, manage electronic health records (EHRs), and platform other healthcare-related tasks.
In addition, serverless architecture can help improve security in the healthcare industry by allowing developers to build and deploy isolated applications, which can help minimize the risk of data breaches and other security incidents.
In this article, we will learn the advantages and limitations, trends, use cases, and other aspects of serverless architecture in healthcare.
Serverless architecture has several advantages that make it appealing for developers, such as scalability, flexibility, and quicker time to release. Additionally, serverless architectures often come at a reduced cost also developers do not need to worry about purchasing or provisioning the backend servers.
However, it’s important to note that serverless computing is not a perfect solution for all web application development needs.
With serverless architecture, you can focus on your core product without worrying about scaling, runtimes, or infrastructure security. This way, developers can easily reduce operational overheads and achieve efficiency. However, businesses can also have benefits like agility, reduced time to market, and minimized infrastructure costs. This widening focus on primary business service enables companies to serve their customers better and achieve their goals.
Serverless architecture continues to play a major role in developing applications. The latest trends in serverless application development are constantly evolving, with new patterns, technology offerings, and innovations being developed.
We have listed some of these emerging serverless architecture trends, which are becoming a boon for businesses.
This trend in serverless computing is the evolution towards building an abstraction layer on top of offerings by public cloud service providers. This will give businesses more flexibility in choosing the provider of a serverless platform as per service-specific requirements.
Providing serverless architecture as another abstraction layer helps the development process with a neutral interface. This is helpful when building a function-as-a-service (FaaS) application.
Containers have become increasingly popular in serverless architectures as a way to package and deploy applications consistently. By using containers, developers can ensure that their applications will run the same regardless of the environment in which they are deployed. This makes developing and testing applications easier before deploying them to production.
Open-source technology is becoming popular for building serverless platforms. The open-source technologies help differentiate their capabilities as vendor-neutral, open, and transparent.
Additionally, if your services are on a hybrid cloud, it helps establish a consistent approach for on-premises serverless platforms using the same open-source technology.
Many organizations are utilizing serverless platforms such as AWS Lambda and Azure functions to build, test and deploy their applications. Serverless computing allows you to run your code without having to provision or manage any servers, making it a more cost-effective and scalable solution for many businesses.
Serverless computing can be a powerful tool for enabling end-to-end application development, particularly in environments where scalability, flexibility, and ease of development are important. This can help streamline the development process and make it easier for developers to build and deploy their applications quickly.
Your applications can be easily scaled up and down which can help businesses to make the app available at minimum costs.
Serverless architecture can be useful for data engineering and analytics applications. It allows you to focus on processing and analyzing data rather than worrying about the underlying infrastructure.
You can use the serverless function to help you build and deploy data pipelines that can process a large amount of data in a scalable manner. Businesses that process data regularly can easily process large data sets with real-time analytics for batch processing.
While building and deploying healthcare applications, it’s important to ensure that you comply with relevant regulations and standards, such as HIPAA. Serverless computing ensures secure and compliant data storage and processing environments. They implement appropriate security measures to protect against unauthorized access to healthcare data.
Such relevant regulations and standards protect the privacy and security of healthcare data in the application.
Serverless architectures run applications that rely on external FaaS and BaaS providers that run the application code in specific temporary containers. Therefore, serverless architecture consists of three core components;
An API gateway is a middleware that takes all API requests from clients and then routes them to the correct microservice. This process might involve requesting routing, composition, and protocol translation.
A typical API gateway has to handle requests by invoking numerous microservices and then collecting the results to determine the best path. However, several serverless providers (such as AWS) allow clients to use their API gateways.
FaaS is a pre-packaged service with a ready-to-implement framework that can easily be tailored to the needs of the business. It allows you to run the code in response to events or triggers without the need to provision or manage infrastructure.
You can write code and deploy it as a function, which will be automatically executed when an event triggers. As a result, developers use this technology to spend fewer resources developing apps rapidly.
Cloud-based computing is a type of internet-based computing that removes operational database overheads and simplifies the process. It enables ubiquitous, convenient, on-demand authenticated access to a shared pool of computing resources, such as networks, servers, storage, applications, and services.
IoT devices in the healthcare industry generate a lot of data. Serverless architectures can build and deploy data pipelines that help process large volumes of data in real-time, allowing real-time analytics and decision-making.
Related Read: The Impact And Benefits of Internet of Things in Healthcare
Video conferencing and remote healthcare monitoring paired with serverless architecture have a lot of benefits, like reduced operational costs and managed auto-scaling by the cloud provider. In addition, with serverless architecture, you can build and deploy telemedicine apps, allowing for remote consultations between patients and healthcare providers.
Related Read: How to Build a Scalable Video Streaming App Architecture
The serverless architecture enables automation in workflows and repetitive tasks. As a result, it improves productivity for the developers working on healthcare projects. Functions like responding to events, scheduling tasks, and processing alerts can be carried out smoothly by implementing event-based automation for the development process.
👍 Cloud providers like AWS, Azure, and GCP ensure cloud security best practices and HIPAA-compliant managed services. Your data and information will be safe and secure, and you can rest assured that your cloud provider complies with all relevant regulations.
👍 Health organizations can benefit greatly from cost optimizations that come with serverless options.
👍 Healthcare data processing can benefit greatly from a serverless architecture, as it can provide the fast performance required for large amounts of data from various devices and remote monitoring systems.
👍 Healthcare products must quickly go to the market to focus on research activities and clinical trials. Serverless architecture can reduce the time to market.
👍 Healthcare providers need on-demand, flexible, cost-effective serverless computing in certain areas to effectively manage unpredictable, fluctuating workloads.
👎 Because serverless architecture relies on the “pay as you use” model, the physical servers that host your code may not always be running. This can result in – cold start latency when the serverless function is first triggered, which can be frustrating for users and potentially impact the performance of your application.
👎 Allowing a vendor to manage all backend services for an application can make it difficult to switch vendors if necessary, especially since each vendor offers slightly different features and workflows.
👎 It can be difficult to replicate the serverless environment when testing code, as debugging can be more complicated without visibility into the backend process. Application functions may also be broken up into smaller, separate pieces, making it difficult to track issues.
👎 Serverless architecture is not ideal for applications with long-running processes because providers charge for the amount of time the code is running. As a result, running an application in a serverless infrastructure may be more expensive than a traditional one.
HIPAA compliance is important for companies and organizations that handle protected health information (PHI), as non-compliance can result in significant fines and legal consequences.
Serverless computing can be a useful tool for businesses that need to comply with HIPAA, as it allows them to build and run applications and services without worrying about infrastructure management.
When we leverage serverless computing to an application or service, the following can be the boundaries for those areas where Lambda can be deployed for private and proper security groups. It can also be exposed as a functional URL with HTTPS, which provides transport-level security.
Including various functions in serverless platforms is a major win for organizations looking to process PHI using serverless technologies. You can use non-eligible services to orchestrate the storage, transmission, and processing of the metadata around PHI. This opens up numerous opportunities.
This Video Might Help: Understanding all about HIPAA Compliance
These are the building blocks of serverless architecture. In serverless architecture, the service provider is mainly responsible for computing storage and security scaling and leveraging different computations that can bring reduced time to market.
Once it’s got to market, the innovation group can start working on many research capabilities. Therefore, serverless brings product innovation quickly and new things to the market.
▶️ Monolithic architecture is a traditional approach to building software applications in which all application components are bundled into a single codebase and deployed as a single unit.
This can make it difficult to scale and maintain the application, as any changes to the codebase can require the entire application to redeploy.
▶️ Microservice architecture is an alternative approach in which the application is broken down into smaller, independent units of functionality called microservices. Each microservice is a self-contained unit that can be developed and deployed independently of the rest of the application.
This makes it easier to scale and maintain the application, as changes to a single microservice can be developed and deployed without affecting the rest of the application.
▶️ Function as a Service (FaaS) is a cloud computing model in which developers can build and deploy their applications as small, independent units of code called functions.
These functions are executed in response to a trigger, such as an HTTP request or a change in the database. FaaS is often used in conjunction with microservices architecture and can be a way to implement microservices in the cloud.
Moving from a monolithic architecture to microservice architecture or using FaaS can provide many benefits, including improved scalability, flexibility, and maintainability. However, it is important to carefully consider the tradeoffs and ensure that the architecture is appropriate for the application’s specific needs.
Related Read: How to Select the Right Architecture for Your Healthcare Software?
Several key architectural metrics can be used to evaluate the design and performance of the product. These metrics are the different measures that we consider with serverless architecture.
🔸 Percentage of Reduced Operation Cost: Here, we compare the rate of reduced operation cost when using serverless architecture to the expenses before implementing the serverless architecture.
🔸 Percentage of Auto-scaling with Demand: This refers to the system’s ability to handle increased workloads or user demand without a decrease in performance.
🔸 Percentage of Developer Efficiency: Here, we refer to the efficiency with which the system can perform its intended tasks. Factors that can affect the performance include the types of resources, the code’s efficiency and the system’s design.
🔸 Engineering Lead Time Reduction in Hours per Month: It is the time taken to complete the task or project from start to finish. Reducing engineering lead time can have several benefits, including productivity, improved efficiency, and faster time to market.
🔸 Percentage of Availability per Month: While using serverless architecture, you will observe a variation between RTO and high availability values.
🔸 Throughput Values: Measures how much work a system can handle in a given period. It determines how quickly the system can respond to requests and process tasks.
🔸 RTO & RPO Values: In the context of disaster recovery and business continuity, RTO (Recovery Time Objective) & RPO (Recovery Point Objective) are important metrics that can help a system recover from failures or disruptions in a timely and effective manner.
🔸 Latency Measures in Seconds: In serverless architecture, latency can be important, as it determines how quickly the system can respond to requests.
🔸 Percentage of Security Incidents per Month: This refers to the measures to protect the system and its data from unauthorized access or attack. This includes measures such as authentication, encryption and access controls.
Google Cloud Platform(GCP) is a design pattern for building and deploying applications that utilize serverless computing services on GCP. GCP’s serverless computing services will automatically execute that code in response to events or requests.
There are several serverless computing services on GCP that you can use to build serverless architecture, including Google Cloud Functions, Cloud Run, and Cloud Functions for Firebase.
Through Azure’s application integration, you build new integrated solutions that can be connected to the applications and services on-premises and in the cloud. You can create and orchestrate business processes and workflows to connect hundreds of services in the cloud and on-premises.
Services like Azure functions, cognitive services, and Azure machine learning make building an efficient serverless architecture easy. You can manage your APIs and test frameworks to develop and debug your application.
Related Read: AWS vs Azure vs GCP: Finding the Right Cloud Computing Service for you
A multi-cloud with serverless architecture refers to a design pattern for building and deploying applications that take advantage of services across multiple cloud platforms. It provides benefits such as increased flexibility, improved resiliency, and the ability to take advantage of the unique features and capabilities of different cloud platforms.
The multi-cloud services bring requests from external systems to the various cloud providers. It is a multi-region-based architecture with high availability where we can have a router that distributes the traffic between multi-clouds.
Here we have three clouds AWS, Azure and GCP. So 33% of traffic can go to AWS, Azure and GCP. This uniform distribution is only possible in an ideal situation. But in practical situations, this uniform distribution cannot be seen.
For example, the left-hand side also includes the API management and front door, which triggers Azure functions. Here we are taking the serverless framework for the e-commerce-based application where we have orders and products. These orders are deployed across Lambdas in AWS Azure and cloud functions. We have a persistent store that is serverless cosmos DB in Azure event for messaging systems.
Similarly, we have Amazon SQL for querying or messaging system Azure serverless for datastore. In GCP, we have a big query and PubSubs for messaging systems. With this kind of architecture, we can develop in multi-cloud with high availability.
Serverless computing is a computing execution model in which the cloud provider dynamically allocates resources to run an application’s code in response to events or requests.
PaaS is a cloud computing model in which the cloud provider offers a platform for building, deploying, and managing applications. PaaS providers typically provide a range of tools and services, such as development environments, databases, and messaging systems, that developers can use to build and deploy their applications.
Both cloud providers in PaaS and serverless take care of the runtime. But it is designed for only some requests to bring inferences up and down. Once you provision the PaaS service, it will interface, and the charge will be there even for the ideal time. But serverless only will be charged for the processing time and not the perfect time. It brings the infrastructure up and down, resulting in low latency, cold starts, and bootstrapping.
Containers are a way to package and deploy applications in a lightweight and portable manner. Containerization allows developers to package their applications and dependencies into a single container, which can be easily deployed and run on any compatible infrastructure.
However, the different components between containers and serverless, mainly containers of our request. Here scaling doesn’t have the same level of control as serverless except for Kubernetes. We have a horizontal part rising that scales based on the road system, but serverless scaling is completely transparent and completely manages the big cloud. In the coming trends, we can see that serverless and containers are going to be combined.
Security is an important consideration in any architecture, including serverless architectures. In a serverless architecture, the service provider is responsible for the security of the underlying infrastructure and platform. At the same time, the developer is responsible for the security of the application code and data. This can be a great relief for healthcare providers who often have to consider securing a server, which can be time-consuming and costly.
Related Read: Healthcare Data Security Checklist
In serverless architecture, data requested by the users are stored on their devices. This means that when they load more tweets, the page is refreshed on their device. This data is cached on the device, focusing on permissions and security. This helps to protect applications from coding and library vulnerabilities.
It refers to monitoring the performance and availability of serverless applications and services. Serverless architectures rely on cloud providers, so monitoring these systems requires a different approach than traditional server-based architectures.
Several tools and services are available to monitor serverless architectures, including AWS CloudWatch, Lumigo, and X-Ray. These tools provide features such as metric monitoring, log analysis, and alerts to help you manage and troubleshoot your serverless systems.
But it comes with a few challenges, such as
🔹 Due to hidden costs like network, storage, and API requests, serverless architecture can make it difficult to estimate infrastructure costs.
🔹 Monitoring serverless architecture can be challenging because there is only one way to access servers once the function is called.
🔹 Serverless architecture is vulnerable to cold hits because there are no standby operations.
In the case of healthcare, there are a lot of complex needs at every stage of products. It can be at the code level or the infrastructure level. At the network level, we need to ensure that things are followed for compliance so different tools are available in the market. These are some of the top tools that we use in Mindbowser.
| Tool | Description |
| Rancher | Opensource Container Management platform for Kubernetes distributions manages multi clusters in a multi-cloud environment that have integrations and high compatibilities with CI/CD, Monitoring, Container Securities, Backup and restores, Service Mesh(Istio) |
| Jenkins | Opensource automation tool for Continuous Integration and deployment tool |
| Prowler | Opensource tool for Infrascan. Assessment of AWS Security Best Practices, Auditing, Hardening and Forensics Readiness Tool. It follows guidelines of the CIS Amazon Web Services Foundations Benchmark and DOZENS of additional checks including GDPR and HIPAA (+100) |
| Software Composite Analysis(SCA) tools | Detect and evaluate open-source software’s security, code quality, license compliance and any vulnerabilities within the code and project dependencies.
|
| Static Application Security testing (SAST) tools | Scans the application before the compilation of code. Developers can utilize this before code build phase. Analyzes source code to find security vulnerabilities that makes applications susceptible to attack. Codegrip: Mindbowser Inbuilt tool for static code analysis |
| Dynamic Application Security Testing(DAST) tools | Scans security vulnerabilities by simulating external attacks on application while application is running. It is a kind of penetration testing from external OWASP ZAP: Opensource web application security scanner that detects vulnerabilities at API request-response level |
| Interactive Application Security testing tools | Analyzes code for security vulnerabilities when an automated testing Tools run the application: Contrast Community Edition(CE), limited to Java and .NET applications only |
| NeuVector | Security platform for complete container security |
| Terragrunt | Thin wrapper for Terraform for managing multiple Terraform modules |
Serverless architecture can be a useful approach for building and running applications and services in the healthcare industry. It offers additional security benefits, as data is typically stored in a secure cloud environment and only accessed when needed.
However, it’s important to note while serverless architecture can offer some help to the healthcare industry, it’s also important to carefully consider the potential challenges and limitations of the approach.
Besides security, serverless architecture is highly scalable and can be monitored easily. There are different use cases of serverless architecture in healthcare, such as data analytics, IoT devices and telemedicine applications.
We recently hosted a webinar discussing the various aspects of serverless architecture within the healthcare sector. To view the full webinar, please click here.
Serverless architecture is a cloud-based approach where developers build and run applications without managing servers directly. Applications are broken down into functions triggered by events (e.g., patient data updates, and medication alerts). Healthcare benefits include Scalability, Agility, Cost-efficiency, and Security.
Yes, serverless architecture can be HIPAA compliant when used with HIPAA-compliant cloud providers and implemented with proper security controls. Cloud providers offer secure data storage, encryption, and access controls.
Healthcare organizations venturing into serverless architecture should conduct a feasibility study, choosing HIPAA-compliant cloud providers for serverless solutions. Start with small projects, invest in IT training, and seek guidance from serverless experts for a seamless implementation process.
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