Netflix Microservices Activity PDF

JHON PAUL D.G. MALUBAG BSIT 4B MICROSERVICES ACTIVITY 10/3/2024 NETFLIX This diagram depicts what Netflix uses for its microservices architecture. Beginning with the clients, which...

JHON PAUL D.G. MALUBAG BSIT 4B MICROSERVICES ACTIVITY 10/3/2024 NETFLIX This diagram depicts what Netflix uses for its microservices architecture. Beginning with the clients, which could be phones, laptops, or browsers, it interfaces with the system. Requests from such clients first hit AWS ELB, which distributes the traffic to the Gateway Service. Gateway acts as a central point for all requests coming from different applications and routes them to the most appropriate microservices-based APIs of either Signup API, Play API, or Application API. These microservices are registration for the user, video playback, and application logic. Data travels through a stream processing pipeline because microservices communicate with each other and data in datastores. The backend infrastructure runs on AWS, and there is a cache for frequently accessed data and, of course, on microservices to handle the task. With this architecture, Netflix can scale services in a very efficient manner, handle high volumes of traffic, and deploy new features rapidly. 1. How They Uses Microservices?  Netflix has moved from this monolithic architecture to using a microservices-based model where the system is split up into hundreds or thousands of smaller, independent deployable, and scalable services. In other words, each microservice would encapsulate a single piece of functionality, such as billing, recommendations, user management, or content delivery. This allows much greater speed in development while ensuring faster and more efficient deployment of new features by Netflix, thereby reducing times for downtime while addressing shifting demand fluctuations. 2. Microservices in Architecture The microservices architecture of Netflix allows huge applications to break down into smaller, modular components; they are designed around business capabilities. The architecture supports scalability as the different services are maintained, updated, and scaled differently. For example, Netflix runs about 700 microservices, it uses various databases like DynamoDB and Cassandra, enhancing modularity and ease of maintenance. It is also designed to be stateless, so each service can react very rapidly, and it can deploy itself across the cloud environment, with regard to making it work the correct way in Amazon Web Services. 3. Impact on Business and Scalability This shift towards the use of microservices had dramatically altered the face of innovation and the scalability of Netflix. Since Netflix started using this architecture back in 2008, the fault tolerance and reliability of the system have been dramatic in increasing, meaning that it is now able to withstand millions of requests daily without producing significant disruptions in its services. For example, by 2013, the API gateway of Netflix had reached more than 1 billion requests every day. From here, the rate of exceptions was a good indication that the design of the microservices is standing the tests and serving robust business operations and high user engagement. 4. Challenges and Solutions Many challenges Netflix faced because of the transition to microservice architecture. With services interacting to causing cascading failures, dependency issues cropped up. Netflix set out to rectify this with circuit breaker patterns and fallback mechanisms. Furthermore, as they scaled for stateful as well as stateless services, they were compelled to adapt auto-scaling technologies, as well as consistent hashing. Variance was dealt with through constant learning and automation-allowing modifications to be made with little to no disruptions. 5. Lesson Learned from the Companies?  Key lessons are to be heard from Netflix's experience with microservices: first, the advantages of one database per microservice lie in stronger fault isolation, so a change on one service does not disturb other services. All code at the same level of maturity in a microservice keeps the entire microservice stable and minimizes operational risk. The treatment of servers as interchangeable components rather than unique ones maintains system resilience by maintaining constant availability. Finally, an intelligent content delivery and predictive caching strategy that encourages the use of Open Connect Appliances (OCAs) is highly important in terms of performance optimization and development of user experience. Conclusion Netflix extensively utilizes microservices architecture to scale, improve reliability, and optimize service delivery. These effects have influenced its business for better on- road service delivery and user experience. However, like most transforming processes, the road to becoming a microservices-based system was not easy after all, and Netflix reacted innovatively. Valuable lessons learned continue to shape the operational strategies at Netflix. UBER  The microservices architecture of Uber is depicted in this diagram. It takes care of its various source requests, such as from the passenger web UI or driver web UI, through a central API Gateway. These requests are routed by the API Gateway to yet another set of microservices that manage passenger management, driver management, billing, payments, and trip management, to name a few functions. All these microservices have REST APIs with the intent of communicating with each other. It also allows adapters for the connection to external systems that can be used for notifications and the like. This architecture scales the system out further by developing and independently deploying each microservice. 1. How They Uses Microservices? Uber went to the microservices architecture and broke its complex operations down into much smaller services, independently deployable, with every service managing a specific functionality-for example, requests, user management, payments, or notifications-and thus small teams in Uber work solely on specific functionalities. This independence assures better, faster development cycles and the possibility of updating in one spot without affecting the rest of the system. 2. Microservices in Architecture Uber architecture is a microservices architecture that has hundreds of APIs talking to one another. That integrates the work of hundreds of APIs overall. A microservice does one business function, and it could be developed using any technology that fits that function. The API gateway helps in managing client requests, messaging format helps in service communication, and each microservice has its database. The architecture is entirely capable of supporting both synchronous and asynchronous communication, thereby making efficient the act of retrieving data and interacting between services. 3. Impact on Business and Scalability It means all the changes that Uber has experienced with regards to scalability and the general business running has had roots in the adoption of microservices. This architecture allows it to serve millions of ride requests daily, facilitative in terms of rapid growth and global expansion. Additionally, microservices facilitate the company to update its individual components fast, which enhances its reliability and minimizes downtime. Therefore, it has been able to react very fast and promptly to the needs of their users and market changes that have placed it on a winning pedestal in the industries. 4. Challenges and Solutions It has brought to itself many issues the company faces in transitioning to microservices, such as the system being very complex regarding the number of services it needs to handle. The first reasons for decentralized architecture led to problematic practices concerning service trust and dependency management, which might trigger a cascade failure. To solve these problems, Uber standardized practices for the development of services to make teams follow globally standardized practices that promote reliability. But with the growth of the company, Uber shifted towards "macroservices." Macroservices consist of rather deeper services to reduce the complexity of operations and thereby enhance the efficiency of management. 5. Lesson Learned by the said companies Uber's journey in microservices has learned several useful lessons. While microservices architecture carries with it some meticulous planning and very good business understanding, its adoption does come with the drawbacks in this case-quick scalability and managing multiple services, both of which have their overhead. Establishing common practices across many teams can significantly enhance service reliability and efficiency in operations. On the company scale, it is increasingly being understood that fewer, more clearly bound services are likely to be more tractable than an enormously large number of microservices. These lessons are informing ongoing work at Uber and represent lessons for other organizations contemplating similar architectural changes. Conclusion Uber has effectively used microservices architecture toward the betterment of its operational efficiency, scalability, and adaptability in the fast-ride-hailing market. The architectural model facilitated the breaking down of services into manageable components thus enhancing its responsiveness to user demands and rapid innovation. On the other hand, however, transition to microservices also posed challenges that would require thoughtful solutions as well as adjustments. Valuable lessons from this journey continue to shape Uber's ongoing development and operational strategies. GCASH This diagram includes the structure of a microservice architecture for a mobile payment platform, like GCash. Interaction of user's phone with API Gateway and further interaction between API Gateway and other services to forward all requests made through it are the main interfaces. Services include User Service, Wallet Service, Payment Service, Merchant Service, and Transaction Service. These microservices interact with services, which include the Notification Service, Security Service, Analytics Service, and Integration Service within which some of the functionalities are activities like sending notifications, securing the system, analyzing data, and integration with the outside systems. The whole system would be attached to the central database and accessing other interfacing entities like banks, payment gateways, and government agencies. This above architecture might allow flexibility and scalability systems for various transactions as well as operations yet keep these efficacious. 1. How They Uses Microservices? GCash applied microservices to enable it to break down its complex systems into smaller modules, each focusing on different functionalities such as account users, payments, and notifications. This modular design approach makes the system much more flexible and easier to maintain, affording several teams to work on their services independently. The outcome is that this microservice allows fast feature deployment without bringing down the total system, hence making it agile and innovative. 2. Microservices in Architecture The architecture of GCash is microservices, thus providing for a de-centralized design where each component can be separately developed, deployed, and managed. For instance, payment processing, user account management, among others, are encapsulated in well-defined APIs that interoperate through individual microservices. The design hence ensures consistency and reliability yet allows GCash to phase in legacy systems into a modern microservices architecture. 3. Impact on Business and Scalability The business operations for GCash have fundamentally changed with the implementation of microservices. More particularly, during huge spikes in users, having real-time scalability enabled GCash to handle increased volumes of transactions extremely well, especially during the COVID-19 scenario where usage on the platform really surged. This scalability was critical because transaction volumes became over 1 trillion pesos within a year. As an aftermath, GCash was able to become a leading provider of financial services and achieved over 65 million users and provided diverse financial services. 4. Challenges and Solutions Despite GCash's successful transition into microservices architecture, the services firm faced a lot of problems with the handling of rapid growth of users while keeping the system stable. One of GCash's greatest problems at first was the legacy on-premises platform that could not scale well, facing downtime and service disruptions. It overcame the above hurdles by partnering with Alibaba Cloud and embracing cloud-based solutions, scaling their infrastructure in real time. Moreover, this scale-up security management, which was pivotal during peak demands. It also utilized an API gateway to enforce security and rate limiting across all services. 5. Lesson Learned by the said companies The experience in GCash provides several important lessons for organizations migrating to microservices. The most important thing is good communication and collaboration across various departments during transition, which is significant in microservice architecture. In addition, successful migration should focus more on user experience and trust, especially at scale where there is an increasing number of users. Besides, incremental exposure of legacy services like APIs allows organizations to gradually modernize without causing significant disruptions that often accompany the process. Finally, good practices in monitoring and governance are important: something that cannot be overlooked, as these are enablers for establishing and maintaining API standards, and also maintaining system reliability. Conclusion The microservices architecture has, therefore, been implemented very well by GCash and furthered their operations to enable delivery of diverse financial services efficiently to millions of clients. This architectural change, not only scalable but also useful in the context of overcoming some significant challenges that are encountered in rapid growth, has proved valuable insights and lessons learned from its journey in adopting microservices would be continual development and a lesson for other organizations. SPOTIFY This diagram depicts the architecture of Spotify as microservices. It is structured in three layers, that is: Frontend, Backend, and Git repos. It concerns Frontend with user interface issues and interfaces it with the various microservices that constitute the Backend. These are three types: Base, Capacity, and Deployment, each addressing some specific aspects of the platform. The Base layer consists of the services that are foundational, the Capacity takes care of the resources and scaling, and Deployment deals with the deployment of the service. All these microservices rest on a common Sysmodel and sit atop the Git repos, where the code for the services resides. This makes the architecture of the platform scalable, flexible, and responsive to meet the very dynamic needs of users at Spotify. 1. How They Uses Microservices?  The company uses microservices to design the highly flexible architecture that will enable different teams of developers, deployment, and management of services separately. Such an application achieves the ability of the platform to process different functionalities, such as music streaming, user management, and playlist services, within separate services that can be updated without any impact on the entire system. Using microservices, Spotify derives the decreased complexity in the code base; their ability to give room for specific functionalities gives teams a chance to concentrate on efficiency in deployment. 2. Microservices in Architecture The architecture of the company has, instead, been contingent to its design of microservices which comprise over 800 active services that are loosely coupled in nature. Every microservice is independent and works out specific business capabilities, such as recommendation engines and user profile management. This kind of architectural choice not only guarantees better scalability and maintainability of services but also allows for rapid testing and deployment. The company has further employed containerization technologies such as Docker to optimize the processes of deployment and operation of its microservices. 3. Impact on Business and Scalability The microservices architecture at Spotify fundamentally changed the business ways of doing things and thus allows it to scale efficiently with the growth of demand for the platform by its users. The platform has been able to grow to over 320 million monthly active users. The ability of architecture to accommodate over 20,000 deployments per day illustrates how microservices allow rapid delivery of features and applications while keeping the platform relevant in a fast-paced marketplace. Thanks to this scalability, Spotify can be consistent with the trends of the industry as well as customer needs in a rapid and efficient manner, thus being at the top position in music streaming services. 4. Challenges and Solutions This comes with several obvious benefits, but the journey towards such an implementation has been ridden with a plethora of problems in Spotify. For example, Spotify has had limited infrastructures that accommodate its legacy systems, hence curtailing the scaling of its services. The company, therefore, resorted to cloud services and started to use Kubernetes for its container orchestration to ease the orchestration of its services. In addition, issues regarding service deployment and management have been solved through investments in monitoring tools. Standardizing development practices into teams has also helped solve problems concerning the service deployment and management. 5. Lesson Learned from the said companies Spotify has come up with several important understandings regarding the lessons it learned from its experiences involving microservices to help other companies. The first important lesson is that it should work on the culture of autonomous teams where every unit can take ownership of separate services. The second important lesson is embracing community-driven technology like Kubernetes, which enhances scalability and efficiency while aligning with the industry's best practices. However, continuous learning and agility are very important; Spotify mentions that organizations have to "fail faster" while iteratively coming up with new ideas to keep the energy going and innovation moving. Lastly, in relation to the microservices architecture, strong investment goes into monitoring and cost management tools for managing complexity and expenses of operations. Conclusion The successful application of the microservices architecture by Spotify has transformed its operational capabilities to where it has the ability to scale and efficiently deliver service to millions across the world. The architectural framework supports independent scalability as well as rapid development cycles, which are stimuli for business performance. However, the journey has been full of challenges in need of solutions that can continue to improve this system. There are lessons to be gleaned from Spotify's selection of microservices adoption for other businesses interested in innovation and scaling. AIRBNB This figure represents the microservices architecture for Airbnb/Booking.com, showing various components, including the interactions between these components. The system is broken into independent services used by hotel managers as well as customers: UI/APP, search services, booking services, payment services, and booking management services. These services use databases such as MySQL, Elastic Search, Cassandra, and Redis to store and retrieve information. The architecture uses Kafka for message queuing and Apache Spark for processing streaming data. Further, the system has used a load balancer for traffic management and various authentication/authorization layers for security. 1. How They Uses Microservices? Its platform breaks down this big monolithic architecture into various smaller, more manageable pieces using microservices architecture, making it way beyond simple monolithic architecture. Such different teams can develop and deploy individual services independently while developing specific business functionalities like search, booking, and payments. Modularity enhances agility, making possible the rapid deployment of new features without disruption of the entire application-a competitive edge in the online accommodation market. 2. Microservices in Architecture  The architecture of Airbnb is SOA-based, composed of many loosely coupled services; each service may contain special business logic, and scaling as well as development are independent operations. All services communicate with each other via well-defined APIs, which reduced interdependencies and thus is easier in terms of maintenance and updates. Additionally, the approach has been using a hybrid approach comprising microservices and macroservices for smoothing data fetch mechanisms within the platform. 3. Impact on Business and Scalability Consequently, Airbnb has had a dramatic impact on the core business-related and scalability factors pertaining to microservices. Having left monolithic architecture aside, it improved the handling of user requests - AirBnB can process millions of bookings and profile interactions concurrently. Microservices make it possible for the company to give customers customized experience while enhancing the reliability of the system and operational efficiency. The reason why scalability is of importance in maintaining competitiveness in a rapidly changing market is clearly demonstrated by the scale of growth and the ability of the platform to serve an increasingly large global user base. 4. Challenges and Solutions The process of transforming the Airbnb system into microservices was challenging in several ways. A monolithic system meant that there were slow initial deployments, while the complexity of the components prevented scalability. Challenges: AirBnb started a gradual move towards microservices architecture: It classified services into data fetching, business logic, and user interface components. Introducing cloud infrastructure and investing in monitoring tools helped them handle services better; things became more stable. Moving to configuration as code enables deployment and organizational efficiency. 5. Lesson Learned from the said companies Through this experience with microservices, Airbnb has taken away a few very valuable lessons. First of all, with a more DevOps culture, there is collaboration and quicker releases across service boundaries. Also, the more complex things are, the more relevant you must have healthy monitoring and alerting systems, keeping it alive and healthy. Companies should also start with monolithic architecture to understand their requirements deeply before transitioning to microservices. Good communication and observability between teams should be prioritized to ease most of the problems scaling microservices entail. Conclusion  The transition to microservices architecture has dramatically increased the operational capabilities of the company. Microservices architecture has allowed Airbnb to increase scalability, accelerate the speed of deployment, and manage the complexity of its services much better. Clearly, this transition is not only a prerequisite for serving a growing user base but also dovetails with many worthwhile experiences regarding the pains and triumphs associated with microservices. Key takeaways from this experience can serve as guiding lessons for other organizations that embark upon their own similar architectural transformations. AMAZON This is a microservice deployment architecture on Amazon Web Services; and users interact with this system through devices and SDK by giving requests to the Application Load Balancer. Thereby, the balancer serves these requests to different microservices running on AWS Fargate, which is a serverless computing engine. Among those are Search, List, PriceGraph, and Select functions that interact with the data stored in Amazon RDS, Amazon DynamoDB, and Amazon S3. The architecture further exploits AWS Elastic Container Registry (ECR) and AWS Elastic Container Service (ECS) for the containerized deployments, ElasticCache for Redis for caching, and Amazon CloudWatch for monitoring. It is configured with settings and features, a robust and scalable system through the AWS Systems Manager Parameter Store. 1. How They Uses Microservices? Amazon is employing microservices within its architecture, which will allow different services to be developed and deployed in isolation. This will lead to the fact that different teams work on specific functionalities, such as managing inventories, processing payments, writing reviews, and so on. This will allow them to update even innovative components separately without influencing the entire system. This will help Amazon scale each service based upon the demand for it, which will result in higher efficiency in operations. 2. Microservices in Architecture Its architecture rests on microservices that should be as independent and loosely coupled as it is possible. Such an approach allows the fundamental architectural decision of splitting functionalities into cohesive verticals with implications to maintainability to scale the isolatable parts. Microservices use APIs to communicate to each other, which was a key requirement to provide flexibility and nonintrusive update opportunities-a critical requirement for an operation of this scale. Continuous integration and continuous delivery (CI/CD) is also supported, and new features can be easily added by Amazon. 3. Impact on Business and Scalability The impact that microservices architecture has made in business operations and scalability is deep. This architecture would allow Amazon to increase traffic during holiday and event sales, as services are scaled at a dynamic rate; thus, greater resiliency and a stronger platform maintaining millions of transactions while maintaining performance. The other endowment of microservices is the agility that will enable Amazon to innovate fast and rapidly adapt to the dynamics of the market, bringing excellent customer experience and sharpening its competitive advantage. 4. Challenges and Solutions Despite the many benefits of microservices, Amazon has encountered problems related to architecture changes. Most crucially, managing very independent services results in increased communication overhead and consequently potential latency issues. On these challenges, Amazon has strong tools for monitoring and orchestration techniques for high performance in efficiency and quality of services. Strategic investment in cloud infrastructure can smoothen operations and make better resource allocation possible. 5. Lesson Learned from the said companies What Amazon has learned about microservices other companies have learned as well. First of all, flexibility in the design of the services can definitely speed up development in great ways and make it more efficient to deploy. Of course, the model should be kept aligned with the project goals of the organization and the needs of the customer. Proper means of internal communication and strong monitoring systems for maintaining the complexity of microservices should also be developed. Finally, organizations need to be set up with proper flexibility in order to change according to their microservices strategy in place over time, hence to the unknown experiences in place and to the ever-changing market demand. Conclusion Microservices are an architectural approach adopted by Amazon, making them improve their operational capabilities-it thus makes them scalable and agile, thereby improving its production environment. The introduction of a microservices approach has brought many advantages to the company; however, this also has its challenges that Amazon has successfully passed through strategic solutions. The Amazon experience with the adoption of the microservices architecture approach gives important lessons for other organizations envisioning similar architectural transitions.