Microservices and Serverless Architectures on SAP BTP: A Guide to Building Modern and Scalable Applications

I. Introduction

Software development is a dynamic and evolving field, constantly adapting to the changing needs and expectations of customers, businesses, and society. In the digital era, software applications are expected to be fast, reliable, scalable, and agile, delivering value and innovation to users across various domains and platforms. However, traditional architectures, such as monolithic or hybrid architectures, often face challenges and limitations in meeting these demands, as they tend to be complex, rigid, and inefficient, resulting in high maintenance costs, low performance, and slow delivery.

To overcome these challenges and limitations, microservices and serverless architectures have emerged as revolutionary paradigms, offering a plethora of benefits for building and managing modern applications. Microservices architecture, characterized by a collection of small, independent services, each focusing on a specific functionality and promoting loose coupling, high cohesion, statelessness, and domain-driven design, enables developers to create scalable, agile, and resilient applications, while reducing complexity and improving productivity. Serverless computing, a cloud-based paradigm that eliminates the need for server provisioning and management, shifting the responsibility to the cloud provider, allows developers to focus on writing code and handling business logic, while the infrastructure is managed and scaled automatically, enabling developers to create cost-effective, efficient, and flexible applications.

The main purpose and objectives of this essay are to explore the intricacies of microservices and serverless architectures, and to provide a comprehensive guide to their development and deployment on SAP Business Technology Platform (SAP BTP), a platform that combines data and analytics, artificial intelligence, application development, automation, and integration in one unified environment. SAP BTP provides a robust platform for developing and deploying microservices and serverless applications, empowering developers to create innovative solutions that meet the demands of the digital era.

This essay will discuss the following main points in the body:

• The concepts and characteristics of microservices and serverless architectures, such as their definitions, features, types, and models.
• The advantages and disadvantages of microservices and serverless architectures, such as their benefits and drawbacks, strengths and weaknesses, and trade-offs and challenges.
• The design principles and best practices of microservices and serverless architectures, such as their guidelines, patterns, techniques, and tools for effective implementation and management.
• The tools and frameworks for developing and deploying microservices and serverless applications on SAP BTP, such as its runtimes, IDEs, SDKs, APIs, and services that enable and support these architectures.
• The features and benefits of SAP BTP for microservices and serverless architectures, such as its unique capabilities and offerings, its integration and support for other SAP and non-SAP applications and services, and its comparison and contrast with other cloud platforms that provide similar functionalities.

II. Microservices: A Decentralized Architecture for Scalability and Agility

Microservices architecture is a software development approach that breaks down monolithic applications into smaller, independent units, each focusing on a specific functionality and promoting loose coupling, high cohesion, statelessness, and domain-driven design. Each microservice has its own codebase, data store, development team, deployment cycle, and communication protocol, enabling developers to create scalable, agile, and resilient applications, while reducing complexity and improving productivity.

Microservices architecture offers several advantages for building and managing modern applications, such as:

• Increased scalability: Microservices can be scaled independently, catering to varying demands and traffic spikes, without affecting the performance or availability of other services.
• Improved agility: Development teams can work on microservices in parallel, enhancing overall project velocity, and delivering features and updates faster and more frequently.
• Decreased complexity: Microservices simplify maintenance and troubleshooting, making applications more manageable and modular, and allowing developers to use different languages, frameworks, and tools for each service.
• Increased reliability: Microservices can handle failures gracefully, without causing system-wide outages, and can be easily replaced or repaired, ensuring high availability and fault tolerance.

However, microservices architecture also has some disadvantages and challenges, such as:

• Increased communication overhead: Microservices require robust communication protocols to exchange data and coordinate actions, which can introduce latency, bandwidth consumption, and network dependency issues.
• Increased potential for errors: More moving parts in the architecture can lead to increased error propagation, inconsistency, and unpredictability, requiring rigorous testing and monitoring strategies.
• Increased operational complexity: Managing a large number of interconnected microservices can be challenging, requiring sophisticated orchestration, configuration, and governance mechanisms.

To address these challenges and trade-offs, microservices architecture relies on various techniques and tools, such as:

• Service discovery: A process that enables microservices to locate and communicate with each other, using a central registry or a distributed system, such as Consul, Eureka, or ZooKeeper.
• Circuit breakers: A pattern that prevents cascading failures, by detecting and isolating faulty services, and providing fallback responses, using frameworks such as Hystrix, Resilience4j, or Istio.
• API gateways: A component that acts as an intermediary, routing requests to appropriate microservices, and providing consistent performance, security, and authentication, using tools such as Kong, Zuul, or Tyk.
• Service mesh: A framework that provides a centralized layer for managing and monitoring microservices interactions, improving overall application performance and resilience, using tools such as Linkerd, Envoy, or Istio.

Microservices architecture can be implemented using different languages, frameworks, and tools, depending on the requirements and preferences of the developers and the customers. For example, some of the popular choices for developing microservices are:

• Java: A widely used, object-oriented, and platform-independent language, that offers high performance, reliability, and compatibility, and supports various frameworks and tools for microservices development, such as Spring Boot, Micronaut, Quarkus, etc.
• Node.js: A fast, lightweight, and event-driven runtime environment, that uses JavaScript, a popular and versatile scripting language, and supports various frameworks and tools for microservices development, such as Express, Nest, LoopBack, etc.
• Python: A powerful, high-level, and interpreted language, that offers simplicity, readability, and productivity, and supports various frameworks and tools for microservices development, such as Flask, Django, Nameko, etc.

Microservices architecture can also be applied to various domains and platforms, and can solve real-world problems and deliver value to customers. For example, some of the well-known companies that use microservices architecture are:

• Netflix: A leading streaming service, that uses microservices to handle millions of requests per day, and to provide personalized recommendations, content delivery, and user interface, using Java, Python, Node.js, etc.
• Amazon: A giant e-commerce platform, that uses microservices to manage its complex and diverse operations, such as inventory, payment, shipping, and customer service, using Java, Python, Ruby, etc.
• Uber: A global transportation network, that uses microservices to power its core functionalities, such as location tracking, ride matching, pricing, and driver rating, using Node.js, Python, Go, etc.

These are just some of the examples of how microservices architecture can be used to create modern and scalable applications that can handle complex and diverse business needs and customer expectations. However, microservices architecture is not a one-size-fits-all solution, and it may not be suitable for every scenario or requirement. Therefore, developers need to carefully evaluate the pros and cons of microservices architecture, and consider the design principles and best practices that can help them implement and manage microservices effectively and efficiently.

III. Serverless: A Cost-Effective and Efficient Approach

Serverless computing is a cloud-based paradigm that eliminates the need for server provisioning and management, shifting the responsibility to the cloud provider, and allowing developers to focus on writing code and handling business logic, while the infrastructure is managed and scaled automatically. Serverless computing is not a new concept, but it has gained popularity in recent years due to the emergence of various platforms and services that enable it.

Types and Models of Serverless Computing

There are different types and models of serverless computing, each with its own characteristics and applications. The most common ones are:

• Function-as-a-Service (FaaS): This is the core of serverless computing, where developers write and deploy small, stateless, and ephemeral functions that are triggered by events, such as HTTP requests, database changes, message queues, etc. The functions are executed on demand, and the cloud provider handles the scaling, load balancing, security, and billing of the resources. Some examples of FaaS platforms are AWS Lambda, Azure Functions, Google Cloud Functions, etc.
• Backend-as-a-Service (BaaS): This is a complementary service to FaaS, where developers use pre-built and managed backend components, such as authentication, database, storage, notification, etc., without having to worry about the underlying infrastructure. The cloud provider handles the scalability, availability, and maintenance of the components, and the developers only pay for the usage. Some examples of BaaS platforms are Firebase, Parse, AWS Amplify, etc.
• Platform-as-a-Service (PaaS): This is a broader category of cloud computing, where developers deploy and run their applications on a fully managed platform, without having to deal with the servers, operating systems, middleware, etc. The cloud provider handles the provisioning, scaling, updating, and monitoring of the platform, and the developers only pay for the resources they consume. Some examples of PaaS platforms are Heroku, Google App Engine, AWS Elastic Beanstalk, etc.

Examples and Case Studies of Serverless Functions

Serverless functions can be implemented effectively using different languages, frameworks, and tools, depending on the requirements and preferences of the developers. Some of the benefits of using serverless functions are:

• Faster development and deployment: Developers can write and deploy functions in minutes, without having to set up and configure servers, containers, or clusters. They can also use existing libraries, frameworks, and tools to speed up the development process.
• Lower cost and higher efficiency: Developers only pay for the resources they use, and not for the idle time or the reserved capacity. They can also leverage the cloud provider's economies of scale and optimization techniques to reduce the cost and improve the efficiency of the functions.
• Higher scalability and availability: Developers do not have to worry about the scalability and availability of the functions, as the cloud provider handles the load balancing, autoscaling, fault tolerance, and redundancy of the resources. The functions can handle any amount of traffic and requests, without compromising the performance or reliability.

Some examples and case studies of how serverless functions can solve real-world problems and deliver value to customers are:

• Airbnb: The online marketplace for lodging and tourism uses AWS Lambda to power its image moderation service, which automatically detects and flags inappropriate or fraudulent images uploaded by the users. The service runs on a serverless architecture, which allows Airbnb to scale the function according to the demand, and pay only for the resources it consumes. The service also improves the user experience and trust, as well as the operational efficiency and security of the platform.
• Coca-Cola: The beverage company uses Google Cloud Functions to power its vending machine analytics service, which collects and processes data from thousands of vending machines across the world. The service runs on a serverless architecture, which allows Coca-Cola to handle the massive amount of data and events, and pay only for the resources it uses. The service also enables Coca-Cola to gain insights and optimize the performance, inventory, and maintenance of the vending machines.
• Slack: The collaboration platform uses Azure Functions to power its slash commands service, which allows users to interact with external applications and services using simple commands in the chat interface. The service runs on a serverless architecture, which allows Slack to execute the commands quickly and efficiently, and pay only for the resources it needs. The service also enhances the user experience and productivity, as well as the integration and extensibility of the platform.

Advantages and Disadvantages of Serverless Architecture

Serverless architecture has many advantages, but it also has some disadvantages and trade-offs that need to be considered. Some of the advantages are:

• Pay-per-use model: Serverless architecture follows a pay-per-use model, where developers only pay for the resources they consume, and not for the idle time or the reserved capacity. This can result in significant cost savings and better utilization of the resources.
• Reduced operational overhead: Serverless architecture reduces the operational overhead, as developers do not have to deal with the server provisioning, management, scaling, updating, monitoring, etc. The cloud provider handles all these aspects, and the developers can focus on the code and the business logic.
• Autoscaling: Serverless architecture enables autoscaling, where the cloud provider automatically scales the resources up or down, depending on the demand and the load. This can improve the performance and reliability of the functions, as well as the user satisfaction and experience.

Some of the disadvantages are:

• Limited control over infrastructure: Serverless architecture limits the control over the infrastructure, as developers do not have access to the servers, operating systems, middleware, etc. They have to rely on the cloud provider's choices, configurations, and policies, which may not suit their needs or preferences. They also have to deal with the potential issues and limitations of the cloud provider, such as outages, downtime, latency, etc.
• Potential for cold starts: Serverless architecture introduces the possibility of cold starts, where the functions take longer to execute when they are invoked for the first time, or after a period of inactivity. This is because the cloud provider has to allocate and initialize the resources for the functions, which can add to the response time and affect the user experience and satisfaction.
• Limited customizability: Serverless architecture limits the customizability of the functions, as developers have to adhere to the cloud provider's specifications, restrictions, and constraints, such as the supported languages, frameworks, tools, libraries, etc. They also have to comply with the cloud provider's policies, regulations, and terms of service, which may not align with their goals or values.
• Vendor lock-in: Serverless architecture increases the risk of vendor lock-in, where developers become dependent on the cloud provider's platform, services, and features, and have difficulty migrating or switching to another provider. This can reduce the flexibility and portability of the functions, as well as the bargaining power and leverage of the developers.
• State management difficulty: Serverless architecture poses a challenge for state management, as the functions are stateless, ephemeral, and isolated. They do not store or share any state or context between the invocations, and they have to rely on external services or databases to persist and retrieve the state. This can add to the complexity and cost of the functions, as well as the potential for errors and inconsistencies.

Techniques and Tools to Address the Challenges and Trade-offs of Serverless Architecture

Serverless architecture has some challenges and trade-offs, but they can be addressed using various techniques and tools, depending on the situation and the requirements. Some of the techniques and tools are:

• Caching: Caching is a technique to store and reuse the data or the results of the functions, to reduce the latency, the cost, and the dependency on the external services or databases. Caching can be implemented using different methods and levels, such as in-memory, local, distributed, etc. Some examples of caching tools are Redis, Memcached, AWS ElastiCache, etc.
• Warm-up: Warm-up is a technique to prevent or reduce the cold starts, by keeping the functions warm and ready to execute, instead of letting them go cold and idle. Warm-up can be implemented using different methods and strategies, such as scheduled invocations, ping requests, pre-warming, etc. Some examples of warm-up tools are AWS Lambda Warmer, Serverless WarmUp Plugin, etc.
• Orchestration: Orchestration is a technique to coordinate and manage the execution and the interaction of multiple functions, to create complex and dynamic workflows, such as data pipelines, business processes, etc. Orchestration can be implemented using different methods and patterns, such as choreography, orchestration, saga, etc. Some examples of orchestration tools are AWS Step Functions, Azure Logic Apps, Google Cloud Workflows, etc.

IV. Developing and Deploying Microservices and Serverless Applications on SAP BTP

SAP BTP, formerly known as SAP Cloud Platform, is a platform that combines data and analytics, artificial intelligence, application development, automation, and integration in one unified environment. SAP BTP supports both microservices and serverless architectures, and integrates with other SAP and non-SAP applications and services, enabling developers to build modern and scalable applications that run on any cloud or on-premise.

Features and Benefits of SAP BTP

SAP BTP offers a variety of features and benefits that enable developers to create innovative and scalable solutions using microservices and serverless architectures on SAP BTP. Some of the features and benefits are:

• Cloud Foundry and Kyma runtimes: SAP BTP provides two runtimes for developing and deploying applications: Cloud Foundry and Kyma. Cloud Foundry is an open-source, industry-standard platform-as-a-service (PaaS) that supports multiple languages, frameworks, and services, and allows developers to deploy applications on any cloud infrastructure. Kyma is an open-source, Kubernetes-based platform that extends Cloud Foundry with serverless functions, event-driven architecture, and service mesh, and allows developers to deploy applications on any Kubernetes cluster. Both runtimes are fully integrated and interoperable, and provide a consistent and flexible development experience.
• Business Application Studio and SDKs: SAP BTP provides a web-based integrated development environment (IDE) called Business Application Studio, and software development kits (SDKs) for various languages and frameworks, such as Java, Node.js, Python, SAPUI5, etc. Business Application Studio and SDKs simplify and accelerate the development and testing of applications, and provide tools and templates for creating microservices and serverless functions, as well as integrating with SAP and non-SAP applications and services.
• APIs and services: SAP BTP provides a rich set of APIs and services that enable developers to access and leverage the data and capabilities of SAP and non-SAP applications and services, such as SAP S/4HANA, SAP SuccessFactors, SAP Concur, etc. SAP BTP also provides services for data and analytics, artificial intelligence, automation, and integration, such as SAP HANA Cloud, SAP Data Intelligence, SAP AI Business Services, SAP Workflow Management, SAP API Management, etc. These APIs and services enhance the functionality and value of the applications, and enable developers to create intelligent and connected solutions.

Comparison of SAP BTP with Other Cloud Platforms

SAP BTP is not the only cloud platform that offers capabilities for developing and deploying microservices and serverless applications. There are other cloud platforms that provide similar or comparable features and benefits, such as AWS, Azure, Google Cloud, etc. However, each platform has its own strengths and weaknesses, as well as its suitability for different scenarios and requirements. Some of the comparison criteria are:

• Compatibility and integration: SAP BTP is designed to be compatible and integrated with SAP and non-SAP applications and services, and provides APIs and services that enable developers to access and leverage the data and capabilities of SAP and non-SAP applications and services. Other cloud platforms may not have the same level of compatibility and integration with SAP and non-SAP applications and services, and may require additional effort and cost to achieve the same level of functionality and value.
• Flexibility and portability: SAP BTP provides two runtimes, Cloud Foundry and Kyma, that support multiple languages, frameworks, and services, and allow developers to deploy applications on any cloud infrastructure or Kubernetes cluster. Other cloud platforms may not have the same level of flexibility and portability, and may limit the choice of languages, frameworks, and services, or the choice of cloud infrastructure or Kubernetes cluster.
• Functionality and value: SAP BTP provides a rich set of APIs and services that enable developers to create intelligent and connected solutions, and leverage the data and analytics, artificial intelligence, application development, automation, and integration capabilities of SAP BTP. Other cloud platforms may not have the same level of functionality and value, and may require additional tools and services to achieve the same level of intelligence and connectivity.

Examples and Case Studies of Microservices and Serverless Applications on SAP BTP

Microservices and serverless applications can be developed and deployed on SAP BTP, using its tools and frameworks, and can solve real-world problems and deliver value to customers. Some examples and case studies are:

• SAP S/4HANA: SAP S/4HANA is SAP's flagship enterprise resource planning (ERP) system that runs on SAP HANA, a powerful in-memory database. SAP S/4HANA is composed of microservices and serverless functions that run on SAP BTP, and provide various functionalities and features, such as finance, sales, procurement, manufacturing, etc. SAP S/4HANA leverages the APIs and services of SAP BTP to access and integrate with other SAP and non-SAP applications and services, such as SAP Ariba, SAP Fieldglass, SAP SuccessFactors, etc. SAP S/4HANA also leverages the data and analytics, artificial intelligence, automation, and integration capabilities of SAP BTP to enhance its performance, intelligence, and connectivity.

• SAP SuccessFactors: SAP SuccessFactors is SAP's cloud-based human capital management (HCM) system that helps organizations manage their workforce and talent. SAP SuccessFactors is composed of microservices and serverless functions that run on SAP BTP, and provide various functionalities and features, such as recruiting, learning, performance, compensation, etc. SAP SuccessFactors leverages the APIs and services of SAP BTP to access and integrate with other SAP and non-SAP applications and services, such as SAP S/4HANA, SAP Concur, SAP Jam, etc. SAP SuccessFactors also leverages the data and analytics, artificial intelligence, automation, and integration capabilities of SAP BTP to enhance its functionality, intelligence, and connectivity.
• SAP Concur: SAP Concur is SAP's cloud-based travel and expense management system that helps organizations manage their travel and expense policies and processes. SAP Concur is composed of microservices and serverless functions that run on SAP BTP, and provide various functionalities and features, such as booking, reporting, auditing, etc. SAP Concur leverages the APIs and services of SAP BTP to access and integrate with other SAP and non-SAP applications and services, such as SAP S/4HANA, SAP SuccessFactors, SAP Ariba, etc. SAP Concur also leverages the data and analytics, artificial intelligence, automation, and integration capabilities of SAP BTP to enhance its functionality, intelligence, and connectivity.

V. Conclusion

In this essay, I have explored the intricacies of microservices and serverless architectures, and provided a comprehensive guide to their development and deployment on SAP Business Technology Platform (SAP BTP), a platform that combines data and analytics, artificial intelligence, application development, automation, and integration in one unified environment. I have argued that microservices and serverless architectures are the best paradigms for developing and deploying modern applications, and that SAP BTP is the best platform for implementing and managing these architectures, as it provides a robust, flexible, and integrated environment that enables developers to create innovative solutions that meet the demands of the digital era.

I have discussed the following main points in the body of the essay:

• The concepts and characteristics of microservices and serverless architectures, such as their definitions, features, types, and models.
• The advantages and disadvantages of microservices and serverless architectures, such as their benefits and drawbacks, strengths and weaknesses, and trade-offs and challenges.
• The design principles and best practices of microservices and serverless architectures, such as their guidelines, patterns, techniques, and tools for effective implementation and management.
• The tools and frameworks for developing and deploying microservices and serverless applications on SAP BTP, such as its runtimes, IDEs, SDKs, APIs, and services that enable and support these architectures.
• The features and benefits of SAP BTP for microservices and serverless architectures, such as its unique capabilities and offerings, its integration and support for other SAP and non-SAP applications and services, and its comparison and contrast with other cloud platforms that provide similar functionalities.

Based on my analysis and findings, I would like to offer some recommendations and implications for future research and practice, and identify some of the emerging trends and opportunities in the field of microservices and serverless architectures, such as:

• Edge computing: Edge computing is a paradigm that brings computation and data storage closer to the location where it is needed, improving response times and saving bandwidth. Edge computing can enhance the performance and efficiency of microservices and serverless applications, especially for scenarios that require low latency, high availability, and data privacy, such as IoT, AR/VR, gaming, etc. Edge computing can also enable new use cases and innovations, such as smart cities, autonomous vehicles, etc. Future research and practice should explore how to leverage edge computing for microservices and serverless architectures, and how to address the challenges and trade-offs, such as security, synchronization, orchestration, etc.
• Hybrid cloud: Hybrid cloud is a model that combines public and private cloud services, allowing for greater flexibility, scalability, and cost-effectiveness. Hybrid cloud can enhance the portability and interoperability of microservices and serverless applications, especially for scenarios that require a balance between performance, security, and compliance, such as finance, healthcare, government, etc. Hybrid cloud can also enable new possibilities and opportunities, such as multi-cloud, cloud bursting, etc. Future research and practice should explore how to leverage hybrid cloud for microservices and serverless architectures, and how to address the challenges and trade-offs, such as complexity, governance, integration, etc.
• Artificial intelligence: Artificial intelligence is a field that aims to create machines and systems that can perform tasks that normally require human intelligence, such as reasoning, learning, decision making, etc. Artificial intelligence can enhance the functionality and value of microservices and serverless applications, especially for scenarios that require high intelligence, automation, and personalization, such as e-commerce, education, entertainment, etc. Artificial intelligence can also enable new capabilities and innovations, such as natural language processing, computer vision, machine learning, etc. Future research and practice should explore how to leverage artificial intelligence for microservices and serverless architectures, and how to address the challenges and trade-offs, such as ethics, bias, explainability, etc.

In conclusion, microservices and serverless architectures are revolutionary paradigms that offer a plethora of benefits for building and managing modern applications, and SAP BTP is a platform that provides a robust platform for developing and deploying these architectures, empowering developers to create innovative solutions that meet the demands of the digital era. However, these architectures are not without challenges and trade-offs, and require careful evaluation and consideration of the design principles and best practices, as well as the emerging trends and opportunities, that can help them achieve their full potential and value. I hope this essay has provided a useful and insightful overview and analysis of microservices and serverless architectures on SAP BTP, and has inspired further research and practice in this exciting and evolving field.

Text: Microsoft Bing Chat with ChatGPT4

References

Introduction

• Fowler, M. (2014). Microservices: A definition of this new architectural style. Martinfowler.com. https://martinfowler.com/microservices/
• Newman, S. (2021). Building microservices. " O'Reilly Media, Inc."
• Saputra, D., Gaol, F. L., Abdurachman, E., Sensuse, D. I., & Matsuo, T. (2023). A model of service-oriented architecture of e-certification system to support boat registration and site visit inspection to support maritime safety and crew health inspection. Marine Systems & Ocean Technology, 1-19.
• Vural, H., Koyuncu, M., Guney, S. (2017). A Systematic Literature Review on Microservices. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2017. ICCSA 2017. Lecture Notes in Computer Science(), vol 10409. Springer, Cham. https://doi.org/10.1007/978-3-319-62407-5_14

Microservices: A Decentralized Architecture for Scalability and Agility

• Indrasiri, K., & Siriwardena, P. (2018). Microservices for the Enterprise. Apress, Berkeley, 143-148.
• Munaf, R. M., Ahmed, J., Khakwani, F., & Rana, T. (2019, March). Microservices architecture: Challenges and proposed conceptual design. In 2019 International Conference on Communication Technologies (ComTech) (pp. 82-87). IEEE.
• Pacheco, V. F. (2018). Microservice Patterns and Best Practices: Explore patterns like CQRS and event sourcing to create scalable, maintainable, and testable microservices. Packt Publishing Ltd.
• Salah, T., Zemerly, M. J., Yeun, C. Y., Al-Qutayri, M., & Al-Hammadi, Y. (2016, December). The evolution of distributed systems towards microservices architecture. In 2016 11th International Conference for Internet Technology and Secured Transactions (ICITST) (pp. 318-325). IEEE.
• Surianarayanan, C., Ganapathy, G., & Pethuru, R. (2019). Essentials of microservices architecture: Paradigms, applications, and techniques.
• Taibi, D., Lenarduzzi, V., & Pahl, C. (2018). Architectural patterns for microservices: a systematic mapping study. In CLOSER 2018: Proceedings of the 8th International Conference on Cloud Computing and Services Science; Funchal, Madeira, Portugal, 19-21 March 2018. SciTePress.
• Wang, Y., Kadiyala, H., & Rubin, J. (2021). Promises and challenges of microservices: an exploratory study. Empirical Software Engineering, 26(4), 63.

Serverless: A Cost-Effective and Efficient Approach

• Barcelona-Pons, D., Sánchez-Artigas, M., París, G., Sutra, P., & García-López, P. (2019, December). On the faas track: Building stateful distributed applications with serverless architectures. In Proceedings of the 20th international middleware conference (pp. 41-54).
• Bhatt, I. V. (2022). A Study on the Temporal Predictability of Serverless Functions. North Carolina State University.
• Chapin, J., & Roberts, M. (2020). Programming AWS Lambda: build and deploy serverless applications with Java. O'Reilly Media.
• Gurturk, C. (2017). Building Serverless Architectures. Packt Publishing Ltd.
• Labouardy, M. (2018). Hands-On Serverless Applications with Go: Build real-world, production-ready applications with AWS Lambda. Packt Publishing Ltd.
• Mondal, S. K., Pan, R., Kabir, H. D., Tian, T., & Dai, H. N. (2022). Kubernetes in IT administration and serverless computing: An empirical study and research challenges. The Journal of Supercomputing, 1-51.
• Rohit, J. R. (2018). Building Serverless Applications with Python: Develop fast, scalable, and cost-effective web applications that are always available. Packt Publishing Ltd.
• Sbarski, P., & Kroonenburg, S. (2017). Serverless architectures on AWS: with examples using Aws Lambda. Simon and Schuster.
• Zanon, D. (2017). Building Serverless Web Applications. Packt Publishing Ltd.

Developing and Deploying Microservices and Serverless Applications on SAP BTP

• Bogner, J., Fritzsch, J., Wagner, S., & Zimmermann, A. (2019, March). Microservices in industry: insights into technologies, characteristics, and software quality. In 2019 IEEE international conference on software architecture companion (ICSA-C) (pp. 187-195). IEEE.
• Figueiredo, M. (2022). Developing Applications on SAP HANA Cloud. In SAP HANA Cloud in a Nutshell: Design, Develop, and Deploy Data Models using SAP HANA Cloud (pp. 103-127). Berkeley, CA: Apress.
• Kanikathottu, H. (2019). Serverless Programming Cookbook: Practical solutions to building serverless applications using Java and AWS. Packt Publishing Ltd.
• Leung, J. (2021). Serverless Computing in Enterprise Application Integration: An Organizational Cost Perspective.
• Novokmet, A. (2022). Monolith to serverless microservice application evolution (Doctoral dissertation, University of Rijeka. Faculty of Informatics and Digital Technologies).
• SAP. (2022). SAP Business Technology Platform. https://www.sap.com/products/technology-platform.html
• SAP. (2022). SAP Cloud Foundry. https://help.sap.com/docs/btp/sap-business-technology-platform/cloud-foundry-environment
• SAP. (2022). SAP Kyma. https://discovery-center.cloud.sap/serviceCatalog/kyma-runtime
• SAP. (2022). SAP BTP Business Application Studio. https://www.sap.com/products/technology-platform/business-application-studio.html
• Weber, F. (2023). AI and BA Platforms. In Artificial Intelligence for Business Analytics: Algorithms, Platforms and Application Scenarios (pp. 65-112). Wiesbaden: Springer Fachmedien Wiesbaden.

Conclusion

• Bass, L., Clements, P., & Kazman, R. (2003). Software architecture in practice. Addison-Wesley Professional.
• Dunkel, J., & Holitschke, A. (2013). Softwarearchitektur für die Praxis. Springer-Verlag.
• Jacobson, L., & Booch, J. R. G. (2021). The unified modeling language reference manual.

#Microservices #Serverless #SAPBTP