Attention API professionals and businesses,Are you tired of struggling with managing and modernizing your API lifecycle and architecture? Do you wish there was a comprehensive and reliable guide to help you navigate this complex process? Look no further, because we have the solution for you!
Introducing our API Lifecycle Management and Architecture Modernization Knowledge Base, the essential tool for any professional looking to achieve efficient and successful API management and modernization.
Our knowledge base contains over 1500 prioritized requirements, solutions, benefits, results, and real-world case studies specifically focused on API lifecycle and architecture.
What sets our knowledge base apart from competitors and alternatives is its unparalleled depth and accuracy.
We have painstakingly curated the most important questions and strategies to consider based on urgency and scope, ensuring that you get the best results for your specific needs.
Instead of spending hours researching and sifting through unreliable information, our knowledge base provides all the necessary information you need in one place.
Not only is our product user-friendly and affordable, but it also caters to both professionals and businesses alike.
Whether you are an API developer, architect, or project manager, our knowledge base has everything you need to succeed.
With its detailed product specifications and overview, you can easily understand how to use it to optimize your API lifecycle and architecture.
But don′t just take our word for it – the benefits speak for themselves.
By utilizing our knowledge base, you can expect increased efficiency, cost savings, and improved overall performance of your APIs.
Our research on API lifecycle and architecture has been proven to produce tangible results, making it a valuable investment for any business looking to stay competitive in this fast-paced digital world.
Worried about the cost? Don′t be.
Our knowledge base is a DIY and affordable alternative to expensive consultancy services.
Take control of your API lifecycle and architecture without breaking the bank.
In comparison to semi-related products, our knowledge base stands out for its laser focus on API lifecycle and architecture.
We understand the unique challenges that professionals and businesses face in this field, and our knowledge base is specifically tailored to address them.
So why wait? Upgrade your API lifecycle and architecture with our Knowledge Base today.
With its detailed insights, easy-to-use format, and proven results, it′s the ultimate tool for achieving success in this constantly evolving industry.
Say goodbye to tedious research and hello to streamlined and effective API management and modernization.
Try it out now and experience the difference for yourself.
How does moving to microservices or distributed architecture impact the API lifecycle? What is the impact of distributed architecture to API lifecycle? Which API lifecycle model is the best for API removal management?
API Lifecycle Management
Moving to microservices or distributed architecture increases the number of APIs, complexifying their lifecycle management. Standardization, automation, and monitoring become crucial.
1. Improved Scalability: Allows for individual microservices to scale independently based on demand.
2. Faster Development: Enables development teams to work in parallel, reducing overall time to market.
3. Enhanced Flexibility: Supports the integration of new technologies and services.
4. Granular Monitoring: Allows for monitoring and management of individual microservices.
5. Streamlined Maintenance: Reduces the impact of changes, as modifications to one service do not affect the entire system.
6. Better Security: Enables the implementation of fine-grained security policies for each microservice.
API Security: How can organizations ensure API security when transitioning to modern architecture styles?
1. Implement Authentication: Use API keys, OAuth, or JWTs for authentication.
2. Rate Limiting: Limit the number of requests to prevent abuse and ensure fairness.
3. Input Validation: Validate all input data to prevent injections and other attacks.
4. Encryption: Utilize HTTPS for data in transit and encryption for data at rest.
5. Security Gateway: Employ a security gateway to enforce security policies and detect threats.
6. Regular Audits: Perform regular security audits and penetration testing.
API Documentation: What are the best practices for API documentation in modern architecture styles?
1. Clear and Concise Descriptions: Use clear and concise language to describe the API′s functionality.
2. Example Requests and Responses: Provide example requests and responses for each endpoint.
3. API Schema: Include an OpenAPI or RAML schema to define the API.
4. Versioning: Implement a versioning system for the API.
5. Testing: Provide a testing environment for API clients.
6. Code Samples: Include code samples in multiple programming languages.
CONTROL QUESTION: How does moving to microservices or distributed architecture impact the API lifecycle?
Big Hairy Audacious Goal (BHAG) for 10 years from now: A Big Hairy Audacious Goal (BHAG) for API lifecycle management in the context of microservices or distributed architecture could be:
To enable seamless, secure, and scalable API lifecycle management across a diverse and dynamic ecosystem of microservices, driving a 10-fold increase in API reusability and a 50% reduction in API development and maintenance costs within the next 10 years.
Moving to microservices or distributed architecture requires a significant shift in how APIs are designed, developed, deployed, and managed. Instead of a monolithic architecture with a single, centralized API, there could be hundreds or even thousands of fine-grained APIs spread across multiple services.
This shift has several implications for API lifecycle management:
1. **Design:** APIs need to be designed to be stateless, idempotent, and loosely coupled. This requires a shift away from RPC-style APIs to resource-oriented APIs.
2. **Development:** API development needs to be automated and standardized, using tools like OpenAPI, RAML, or gRPC. This enables collaboration and reusability of APIs across teams and services.
3. **Testing:** API testing needs to be automated and integrated into the CI/CD pipeline. This ensures that changes to one microservice do not break the APIs of other services.
4. **Deployment:** API deployment needs to be automated, using containerization, orchestration, and service discovery technologies like Docker, Kubernetes, and Istio. This enables seamless deployment of APIs and ensures high availability and load balancing.
5. **Security:** API security needs to be strengthened, using authentication, authorization, encryption, and API gateways. This ensures that APIs are secure and only accessible to authorized users and services.
6. **Monitoring:** API monitoring needs to be real-time, using tools like Prometheus, Grafana, or ELK stack. This enables proactive identification and resolution of issues, ensuring high availability and performance of APIs.
7. **Governance:** API governance needs to be centralized, using tools like Apigee, Tyk, or Kong. This enables policy management, versioning, and lifecycle management of APIs across services and teams.
By addressing these challenges, organizations can unlock the full potential of microservices and distributed architecture, enabling faster innovation, greater agility, and lower costs in API development and maintenance.
"The prioritized recommendations in this dataset have added tremendous value to my work. The accuracy and depth of insights have exceeded my expectations. A fantastic resource for decision-makers in any industry."
Synopsis:
A mid-sized e-commerce company, E-Com, was struggling to keep up with the demands of a growing customer base and increasingly complex application landscape. With a monolithic architecture, E-Com was finding it difficult to quickly develop, test, and deploy new features and services. In order to address these challenges, E-Com decided to migrate to a microservices architecture and implement API lifecycle management to ensure the smooth operation of the new system.
Consulting Methodology:
In order to help E-Com with this transition, a team of consultants from XYZ Consulting followed a four-phase approach:
1. Assessment: The consultants conducted a thorough assessment of E-Com′s current architecture, identifying the key pain points and areas for improvement. They also evaluated the company′s readiness for a move to microservices, taking into account factors such as organizational structure, development processes, and infrastructure.
2. Design: Based on the assessment findings, the consultants worked with E-Com to design a microservices architecture that addressed the company′s specific needs. This included identifying the appropriate granularity of services, defining the boundaries between them, and selecting the right technologies and tools for implementation.
3. Implementation: The consultants helped E-Com implement the new architecture, providing guidance on best practices for service development, testing, and deployment. They also assisted with the integration of existing systems and data sources into the new architecture.
4. Management: To ensure the long-term success of the new architecture, the consultants worked with E-Com to establish an API lifecycle management process. This included defining the stages of the API lifecycle, establishing governance and security policies, and setting up monitoring and reporting mechanisms.
Deliverables:
The main deliverables of the engagement were:
1. A detailed architecture design, including a decomposition of the monolithic application into microservices and a definition of the communication patterns between them.
2. A set of best practices and guidelines for service development, testing, and deployment.
3. An API lifecycle management process, including definitions of the stages of the lifecycle, governance and security policies, and monitoring and reporting mechanisms.
4. Training and mentoring for E-Com′s development teams on the new architecture and tools.
Implementation Challenges:
The implementation of the new architecture and API lifecycle management process was not without challenges. Some of the key challenges included:
1. Cultural shift: The move to microservices required a significant shift in the way that E-Com′s development teams worked. This included a greater emphasis on collaboration, a shift from monolithic thinking to a service-oriented mindset, and the adoption of new tools and processes.
2. Skills gap: The new architecture and tools required a different set of skills than those that the development teams already possessed. This required significant investment in training and mentoring.
3. Infrastructure: The new architecture required a more robust infrastructure than the existing one. This included investments in containerization, orchestration, and service discovery tools.
4. Data management: The new architecture introduced new challenges around data management, including data consistency, transaction management, and eventual consistency.
KPIs:
In order to measure the success of the engagement, the following KPIs were established:
1. Reduction in deployment time: The time it takes to deploy a new feature or service should be reduced by at least 50%.
2. Increase in development productivity: The number of features or services developed per developer per month should increase by at least 20%.
3. Improvement in system reliability: The number of system outages and incidents should be reduced by at least 30%.
4. Reduction in mean time to recovery: The time it takes to recover from a system outage or incident should be reduced by at least 50%.
Other Management Considerations:
In addition to the KPIs, there were several other management considerations that needed to be taken into account, including:
1. Governance: A clear governance structure needed to be established to ensure that the new architecture was being used effectively and efficiently. This included defining roles and responsibilities, establishing policies and procedures, and setting up monitoring and reporting mechanisms.
2. Security: With the increased number of services and APIs, security became a critical concern. This required the implementation of measures such as authentication, authorization, and encryption.
3. Scalability: The new architecture needed to be scalable to support the growth of the company. This required the implementation of measures such as load balancing, auto-scaling, and caching.
4. Monitoring: With the increased complexity of the system, monitoring became even more critical. This required the implementation of measures such as log aggregation, tracing, and alerting.
Conclusion:
The move to a microservices architecture and the implementation of API lifecycle management significantly improved E-Com′s ability to quickly develop, test, and deploy new features and services. By following a structured approach and addressing the implementation challenges, E-Com was able to achieve significant improvements in deployment time, development productivity, system reliability, and mean time to recovery.
Sources:
* Newman, S. (2015). Building Microservices. O′Reilly Media.
* Richardson, C. (2018). Microservices Patterns. Manning.
* Smith, M. (2015). Monolithic versus Microservices Architecture. O′Reilly Media.
* Masse, J. (2018). APIs: A Strategy Guide. O′Reilly Media.
* Microservices Best Practices. (n.d.). Retrieved from u003chttps://auth0.com/resources/ebooks/microservices-best-practicesu003e
* Microservices vs Monolithic Architecture: Pros and Cons. (2021). Retrieved from u003chttps://dzone.com/articles/microservices-vs-monolithic-architecture-pros-and-cu003e
* Microservices Architecture - A Definition from TechTarget. (n.d.). Retrieved from u003chttps://internetofthingsagenda.techtarget.com/definition/microservices-architectureu003e
* Microservices Security Best Practices. (2020). Retrieved from u003chttps://www.nginx.com/blog/microservices-security-best-practices/u003e
* Microservices vs Monolithic Architecture: Pros and Cons. (2021). Retrieved from u003chttps://dzone.com/articles/microservices-vs-monolithic-architecture-pros-and-cu003e
* Microservices: Breaking Down the Monolith. (2017). Retrieved from u003chttps://www.redhat.com/en/resources/microservices-breaking-down-monolith-whitepaperu003e
Introducing our API Lifecycle Management and Architecture Modernization Knowledge Base, the essential tool for any professional looking to achieve efficient and successful API management and modernization.
Our knowledge base contains over 1500 prioritized requirements, solutions, benefits, results, and real-world case studies specifically focused on API lifecycle and architecture.
What sets our knowledge base apart from competitors and alternatives is its unparalleled depth and accuracy.
We have painstakingly curated the most important questions and strategies to consider based on urgency and scope, ensuring that you get the best results for your specific needs.
Instead of spending hours researching and sifting through unreliable information, our knowledge base provides all the necessary information you need in one place.
Not only is our product user-friendly and affordable, but it also caters to both professionals and businesses alike.
Whether you are an API developer, architect, or project manager, our knowledge base has everything you need to succeed.
With its detailed product specifications and overview, you can easily understand how to use it to optimize your API lifecycle and architecture.
But don′t just take our word for it – the benefits speak for themselves.
By utilizing our knowledge base, you can expect increased efficiency, cost savings, and improved overall performance of your APIs.
Our research on API lifecycle and architecture has been proven to produce tangible results, making it a valuable investment for any business looking to stay competitive in this fast-paced digital world.
Worried about the cost? Don′t be.
Our knowledge base is a DIY and affordable alternative to expensive consultancy services.
Take control of your API lifecycle and architecture without breaking the bank.
In comparison to semi-related products, our knowledge base stands out for its laser focus on API lifecycle and architecture.
We understand the unique challenges that professionals and businesses face in this field, and our knowledge base is specifically tailored to address them.
So why wait? Upgrade your API lifecycle and architecture with our Knowledge Base today.
With its detailed insights, easy-to-use format, and proven results, it′s the ultimate tool for achieving success in this constantly evolving industry.
Say goodbye to tedious research and hello to streamlined and effective API management and modernization.
Try it out now and experience the difference for yourself.
Discover Insights, Make Informed Decisions, and Stay Ahead of the Curve:
Key Features:
Comprehensive set of 1541 prioritized API Lifecycle Management requirements. - Extensive coverage of 136 API Lifecycle Management topic scopes.
- In-depth analysis of 136 API Lifecycle Management step-by-step solutions, benefits, BHAGs.
- Detailed examination of 136 API Lifecycle Management case studies and use cases.
- Digital download upon purchase.
- Enjoy lifetime document updates included with your purchase.
- Benefit from a fully editable and customizable Excel format.
- Trusted and utilized by over 10,000 organizations.
- Covering: Service Oriented Architecture, Modern Tech Systems, Business Process Redesign, Application Scaling, Data Modernization, Network Science, Data Virtualization Limitations, Data Security, Continuous Deployment, Predictive Maintenance, Smart Cities, Mobile Integration, Cloud Native Applications, Green Architecture, Infrastructure Transformation, Secure Software Development, Knowledge Graphs, Technology Modernization, Cloud Native Development, Internet Of Things, Microservices Architecture, Transition Roadmap, Game Theory, Accessibility Compliance, Cloud Computing, Expert Systems, Legacy System Risks, Linked Data, Application Development, Fractal Geometry, Digital Twins, Agile Contracts, Software Architect, Evolutionary Computation, API Integration, Mainframe To Cloud, Urban Planning, Agile Methodologies, Augmented Reality, Data Storytelling, User Experience Design, Enterprise Modernization, Software Architecture, 3D Modeling, Rule Based Systems, Hybrid IT, Test Driven Development, Data Engineering, Data Quality, Integration And Interoperability, Data Lake, Blockchain Technology, Data Virtualization Benefits, Data Visualization, Data Marketplace, Multi Tenant Architecture, Data Ethics, Data Science Culture, Data Pipeline, Data Science, Application Refactoring, Enterprise Architecture, Event Sourcing, Robotic Process Automation, Mainframe Modernization, Adaptive Computing, Neural Networks, Chaos Engineering, Continuous Integration, Data Catalog, Artificial Intelligence, Data Integration, Data Maturity, Network Redundancy, Behavior Driven Development, Virtual Reality, Renewable Energy, Sustainable Design, Event Driven Architecture, Swarm Intelligence, Smart Grids, Fuzzy Logic, Enterprise Architecture Stakeholders, Data Virtualization Use Cases, Network Modernization, Passive Design, Data Observability, Cloud Scalability, Data Fabric, BIM Integration, Finite Element Analysis, Data Journalism, Architecture Modernization, Cloud Migration, Data Analytics, Ontology Engineering, Serverless Architecture, DevOps Culture, Mainframe Cloud Computing, Data Streaming, Data Mesh, Data Architecture, Remote Monitoring, Performance Monitoring, Building Automation, Design Patterns, Deep Learning, Visual Design, Security Architecture, Enterprise Architecture Business Value, Infrastructure Design, Refactoring Code, Complex Systems, Infrastructure As Code, Domain Driven Design, Database Modernization, Building Information Modeling, Real Time Reporting, Historic Preservation, Hybrid Cloud, Reactive Systems, Service Modernization, Genetic Algorithms, Data Literacy, Resiliency Engineering, Semantic Web, Application Portability, Computational Design, Legacy System Migration, Natural Language Processing, Data Governance, Data Management, API Lifecycle Management, Legacy System Replacement, Future Applications, Data Warehousing
API Lifecycle Management Assessment Dataset - Utilization, Solutions, Advantages, BHAG (Big Hairy Audacious Goal):
API Lifecycle Management
Moving to microservices or distributed architecture increases the number of APIs, complexifying their lifecycle management. Standardization, automation, and monitoring become crucial.
1. Improved Scalability: Allows for individual microservices to scale independently based on demand.
2. Faster Development: Enables development teams to work in parallel, reducing overall time to market.
3. Enhanced Flexibility: Supports the integration of new technologies and services.
4. Granular Monitoring: Allows for monitoring and management of individual microservices.
5. Streamlined Maintenance: Reduces the impact of changes, as modifications to one service do not affect the entire system.
6. Better Security: Enables the implementation of fine-grained security policies for each microservice.
API Security: How can organizations ensure API security when transitioning to modern architecture styles?
1. Implement Authentication: Use API keys, OAuth, or JWTs for authentication.
2. Rate Limiting: Limit the number of requests to prevent abuse and ensure fairness.
3. Input Validation: Validate all input data to prevent injections and other attacks.
4. Encryption: Utilize HTTPS for data in transit and encryption for data at rest.
5. Security Gateway: Employ a security gateway to enforce security policies and detect threats.
6. Regular Audits: Perform regular security audits and penetration testing.
API Documentation: What are the best practices for API documentation in modern architecture styles?
1. Clear and Concise Descriptions: Use clear and concise language to describe the API′s functionality.
2. Example Requests and Responses: Provide example requests and responses for each endpoint.
3. API Schema: Include an OpenAPI or RAML schema to define the API.
4. Versioning: Implement a versioning system for the API.
5. Testing: Provide a testing environment for API clients.
6. Code Samples: Include code samples in multiple programming languages.
CONTROL QUESTION: How does moving to microservices or distributed architecture impact the API lifecycle?
Big Hairy Audacious Goal (BHAG) for 10 years from now: A Big Hairy Audacious Goal (BHAG) for API lifecycle management in the context of microservices or distributed architecture could be:
To enable seamless, secure, and scalable API lifecycle management across a diverse and dynamic ecosystem of microservices, driving a 10-fold increase in API reusability and a 50% reduction in API development and maintenance costs within the next 10 years.
Moving to microservices or distributed architecture requires a significant shift in how APIs are designed, developed, deployed, and managed. Instead of a monolithic architecture with a single, centralized API, there could be hundreds or even thousands of fine-grained APIs spread across multiple services.
This shift has several implications for API lifecycle management:
1. **Design:** APIs need to be designed to be stateless, idempotent, and loosely coupled. This requires a shift away from RPC-style APIs to resource-oriented APIs.
2. **Development:** API development needs to be automated and standardized, using tools like OpenAPI, RAML, or gRPC. This enables collaboration and reusability of APIs across teams and services.
3. **Testing:** API testing needs to be automated and integrated into the CI/CD pipeline. This ensures that changes to one microservice do not break the APIs of other services.
4. **Deployment:** API deployment needs to be automated, using containerization, orchestration, and service discovery technologies like Docker, Kubernetes, and Istio. This enables seamless deployment of APIs and ensures high availability and load balancing.
5. **Security:** API security needs to be strengthened, using authentication, authorization, encryption, and API gateways. This ensures that APIs are secure and only accessible to authorized users and services.
6. **Monitoring:** API monitoring needs to be real-time, using tools like Prometheus, Grafana, or ELK stack. This enables proactive identification and resolution of issues, ensuring high availability and performance of APIs.
7. **Governance:** API governance needs to be centralized, using tools like Apigee, Tyk, or Kong. This enables policy management, versioning, and lifecycle management of APIs across services and teams.
By addressing these challenges, organizations can unlock the full potential of microservices and distributed architecture, enabling faster innovation, greater agility, and lower costs in API development and maintenance.
Customer Testimonials:
"The prioritized recommendations in this dataset have added tremendous value to my work. The accuracy and depth of insights have exceeded my expectations. A fantastic resource for decision-makers in any industry."
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"I am thoroughly impressed with this dataset. The prioritized recommendations are backed by solid data, and the download process was quick and hassle-free. A must-have for anyone serious about data analysis!"
API Lifecycle Management Case Study/Use Case example - How to use:
Case Study: API Lifecycle Management in a Microservices ArchitectureSynopsis:
A mid-sized e-commerce company, E-Com, was struggling to keep up with the demands of a growing customer base and increasingly complex application landscape. With a monolithic architecture, E-Com was finding it difficult to quickly develop, test, and deploy new features and services. In order to address these challenges, E-Com decided to migrate to a microservices architecture and implement API lifecycle management to ensure the smooth operation of the new system.
Consulting Methodology:
In order to help E-Com with this transition, a team of consultants from XYZ Consulting followed a four-phase approach:
1. Assessment: The consultants conducted a thorough assessment of E-Com′s current architecture, identifying the key pain points and areas for improvement. They also evaluated the company′s readiness for a move to microservices, taking into account factors such as organizational structure, development processes, and infrastructure.
2. Design: Based on the assessment findings, the consultants worked with E-Com to design a microservices architecture that addressed the company′s specific needs. This included identifying the appropriate granularity of services, defining the boundaries between them, and selecting the right technologies and tools for implementation.
3. Implementation: The consultants helped E-Com implement the new architecture, providing guidance on best practices for service development, testing, and deployment. They also assisted with the integration of existing systems and data sources into the new architecture.
4. Management: To ensure the long-term success of the new architecture, the consultants worked with E-Com to establish an API lifecycle management process. This included defining the stages of the API lifecycle, establishing governance and security policies, and setting up monitoring and reporting mechanisms.
Deliverables:
The main deliverables of the engagement were:
1. A detailed architecture design, including a decomposition of the monolithic application into microservices and a definition of the communication patterns between them.
2. A set of best practices and guidelines for service development, testing, and deployment.
3. An API lifecycle management process, including definitions of the stages of the lifecycle, governance and security policies, and monitoring and reporting mechanisms.
4. Training and mentoring for E-Com′s development teams on the new architecture and tools.
Implementation Challenges:
The implementation of the new architecture and API lifecycle management process was not without challenges. Some of the key challenges included:
1. Cultural shift: The move to microservices required a significant shift in the way that E-Com′s development teams worked. This included a greater emphasis on collaboration, a shift from monolithic thinking to a service-oriented mindset, and the adoption of new tools and processes.
2. Skills gap: The new architecture and tools required a different set of skills than those that the development teams already possessed. This required significant investment in training and mentoring.
3. Infrastructure: The new architecture required a more robust infrastructure than the existing one. This included investments in containerization, orchestration, and service discovery tools.
4. Data management: The new architecture introduced new challenges around data management, including data consistency, transaction management, and eventual consistency.
KPIs:
In order to measure the success of the engagement, the following KPIs were established:
1. Reduction in deployment time: The time it takes to deploy a new feature or service should be reduced by at least 50%.
2. Increase in development productivity: The number of features or services developed per developer per month should increase by at least 20%.
3. Improvement in system reliability: The number of system outages and incidents should be reduced by at least 30%.
4. Reduction in mean time to recovery: The time it takes to recover from a system outage or incident should be reduced by at least 50%.
Other Management Considerations:
In addition to the KPIs, there were several other management considerations that needed to be taken into account, including:
1. Governance: A clear governance structure needed to be established to ensure that the new architecture was being used effectively and efficiently. This included defining roles and responsibilities, establishing policies and procedures, and setting up monitoring and reporting mechanisms.
2. Security: With the increased number of services and APIs, security became a critical concern. This required the implementation of measures such as authentication, authorization, and encryption.
3. Scalability: The new architecture needed to be scalable to support the growth of the company. This required the implementation of measures such as load balancing, auto-scaling, and caching.
4. Monitoring: With the increased complexity of the system, monitoring became even more critical. This required the implementation of measures such as log aggregation, tracing, and alerting.
Conclusion:
The move to a microservices architecture and the implementation of API lifecycle management significantly improved E-Com′s ability to quickly develop, test, and deploy new features and services. By following a structured approach and addressing the implementation challenges, E-Com was able to achieve significant improvements in deployment time, development productivity, system reliability, and mean time to recovery.
Sources:
* Newman, S. (2015). Building Microservices. O′Reilly Media.
* Richardson, C. (2018). Microservices Patterns. Manning.
* Smith, M. (2015). Monolithic versus Microservices Architecture. O′Reilly Media.
* Masse, J. (2018). APIs: A Strategy Guide. O′Reilly Media.
* Microservices Best Practices. (n.d.). Retrieved from u003chttps://auth0.com/resources/ebooks/microservices-best-practicesu003e
* Microservices vs Monolithic Architecture: Pros and Cons. (2021). Retrieved from u003chttps://dzone.com/articles/microservices-vs-monolithic-architecture-pros-and-cu003e
* Microservices Architecture - A Definition from TechTarget. (n.d.). Retrieved from u003chttps://internetofthingsagenda.techtarget.com/definition/microservices-architectureu003e
* Microservices Security Best Practices. (2020). Retrieved from u003chttps://www.nginx.com/blog/microservices-security-best-practices/u003e
* Microservices vs Monolithic Architecture: Pros and Cons. (2021). Retrieved from u003chttps://dzone.com/articles/microservices-vs-monolithic-architecture-pros-and-cu003e
* Microservices: Breaking Down the Monolith. (2017). Retrieved from u003chttps://www.redhat.com/en/resources/microservices-breaking-down-monolith-whitepaperu003e
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