Microservices Examples

1. Microservices Examples

2. Table of Content Lyft introduced local development for faster iterations Twitter used a decoupled architecture for fast releases Capital One migrated to AWS and used containers Uber’s DOMA architecture improved productivity A two-layer API structure improved Etsy's rendering time PayPal built open-source framework for microservices adoption Goldman Sachs chose containerization for automation Reddit applied deduplication for caching problems Lego went serverless with a set-pieces approach Gilt mitigated with Java Virtual Machine (JVM) Nike’s configurational and code management issues Groupon built a reactive microservices solution

3. Lyft introduced localization of development & automation for improved iteration speeds Lyft moved to microservices with Python and Go in 2018, by decomposing its PHP monolith. The migration from a monolith to microservices allowed the company to deploy hundreds of services each day through separation of concerns. The Lyft engineering team decided to look at critical touchpoints in the development process instead of relying on the environments. They identified three workflows that needed investments and maintenance for improvements. Lessons from Lyft’s microservice implementation Enable development localization and an efficient developer’s loop to improve iteration time. Enable testing automation to improve delivery time for code changes.

4. Twitter leveraged a decoupled architecture for quicker API releases Twitter ran its public APIs on the monorail, which became one of the largest codebases in the world. As a result, it was challenging to update Twitter teams, so the company migrated to 14 microservices running on Macaw (An internal Java Virtual Machine (JVM)-based framework). Though migration to microservices helped the teams improve deployment times, it also created a disjointed and scattered public API for Twitter. Developers at Twitter can use such pluggable components, and the platform helps with the HTTP needs of the APIs resulting, developers at Twitter can quickly release new APIs without creating new HTTP services. Lessons from Twitter’s microservice implementation Manage microservice fragmentation through internal APIs scaled to large end-points of the system. Leverage the independent microservice approach by using dedicated resources making the entire architecture efficient. Optimize API release by using pluggable components.

5. Capital One migrated to AWS and enabled containerization of services Capital one reduced the time needed to build new application infrastructure by 99% with the migration to AWS services. Similarly, with the help of containerization of microservices, Capital One solved its decoupling needs. They used Docker and Amazon ECS to containerize the microservices which helped them with application automation that simplified the containerization of microservices. Lessons learned from Capital One’s microservice implementation Employ microservice containerization to improve time-to-market, flexibility, and portability. Utilize Docker to further manage containers and automate deployments Leverage Amazon ECS as a platform to manage, scale, and schedule container deployments.

6. Uber’s DOMA architecture helped improve productivity One of the early adopters of microservices, Uber, scaled to 2200 critical microservices with decoupled architecture, improving the system’s flexibility. Also, Uber used Domain-Oriented Microservice Architecture(DOMA) to build a structured set of flexible and reusable layered components. By implementing the DOMA architecture, Uber reduced the feature onboarding time by 25-30% and classified 2200 microservices into 70 domains. Lessons learned from Uber’s microservice implementation DOMA architecture can help reduce the feature onboarding time with dedicated microservices based on the feature domain. Integrate a shared business logic by defining a gateway for each domain.

7. A two-layer API structure that helped Etsy improve rendering time Etsy implemented a two-layer API with meta-endpoints for better concurrency and processing time. They also used the CURL requests in parallel for HTTPS calls with a custom Etsy lib curl patch to build a hierarchy of request calls across the network. This solution helped Etsy achieve 1000 ms time to glass. Simply put, Etsy’s website is rendered within 1 second and is visible within a second. Lessons learned from Etsy’s microservice implementation API-first architecture improves processing time for user requests. Combination of microservices with decoupled meta-endpoints in the architecture to improve server-side performance.

8. PayPal built open-source framework to accelerate microservices adoption PayPal started structuring the releases to optimize deployments and developed small apps that could be deployed faster. They accelerated its microservices adoption in 2009 by developing an open-source framework called “Kraken.” And then, “Altus” was introduced which provided tools to push deployment-ready applications without the hassle of dependency management. Finally, Paypal created a common platform for all of its services through Paypal as a Service(PPaaS) which allowed them to use REST for all the communication between microservices, internally and externally. Lessons learned from Paypal’s microservice implementation Individual services and automation can help improve release time for services Building ingenious tools can accelerate microservice implementations that can split configurations and execute code organizations.

9. Goldman Sachs chose containerization for deployment automation and higher availability Goldman Sachs leveraged containers as a lightweight alternative to virtual machines and enabled deployment automation. With containers, Goldman Sachs could rapidly make new software iterations and reduce the provisioning time from hours to seconds. It also helped them optimize infrastructure utilization, automate business continuity, improve DevOps efficiency, and manage infrastructure updates. In addition to that, they used a telemetry-type tool that helped monitor network connections across clouds, regions, data centers, and entities. Lessons learned from Goldman Sachs’s microservice implementation Containerization of microservices for deployment automation and reduced downtime is a good practice. You can build a custom telemetry-like tool to monitor communications between containers for higher security.

10. Reddit applied deduplication approach to solve its caching problems The Reddit team used a solution to deduplicate requests and cache responses at the microservices level. First, they used the deduplication process, which means reordering the requests to be executed one at a time aiming to approach reducing the concurrent request execution. Further, Reddit built a decorator which ensures that no two requests are executed concurrently. Finally, it used a caching decorator that uses the request hash as a cache key and returns the response if it hits. Lessons learned from Reddit’s microservice implementation Deduplication of requests and caching of reponse at microservice level can reduce the load on the underlying architecture. Reduce concurrency of request processing locally by creating a unique identity of each user request through hashing.

11. Lego went serverless with a set-pieces approach to microservices Lego used an approach known as “Solution Design,” which helps with the translation of products into architectural visualization of granular microservices. They designed a serverless event-driven application that uses Amazon EventBridge as an event bus with this approach. Event bus allows Lego to handle each type of event in the environment required for downstream analytical service. Lessons learned from Lego’s microservice implementation Adopt serverless with Lego’s ‘set-pieces’ approach to build an agile system. Use the solutions design approach for granular microservice visualizations for improved implementation.

12. Gilt mitigated overloaded database and long integration cycles with Java Virtual Machine (JVM) Gilt chose to move towards microservices based on JVM (Java Virtual Machine) in order to cope with the peak traffic daily, development monoliths, and deployment delays. The reason behind adopting JVM was the compatibility and acquaintance of in-house developers with the Java language. Gilt teams decided to double down on the microservices adoption, taking the ten services to 400 for their web apps. It also solved 90% of its scaling problem during the flash sale with JVM-based microservices. Lessons learned from Gilt’s microservice implementation Choose an environment that is familiar for the in-house teams to deploy microservices. Use microservice deployments with object-relational database system like Postgres to solve 90% of the scaling problems.

13. Nike’s configurational and code management issues Nike first switched to the phoenix server pattern and microservice architecture to reduce the development time. In addition, Nike used immutable deployment units with the phoenix server pattern to reduce configuration drift with the phoenix pattern. Furthermore, Nike chose Cassandra to leverage their database’s share-nothing design and data clustering. Nike reduced the 4,00,000 code lines to 700-2000 lines within a project due to the deployment of immutable units. Lessons learned from Nike’s microservice implementation Leverage the share-nothing design and create a fault-tolerant system for your business. Build a distributed system with a data clustering approach and immutable units to reduce the codebase size.

14. Groupon built a reactive microservices solution to cope with the peak traffic Groupon teams decided to break their monoliths into Reactive microservices. It offers isolation and autonomy of services, which is impossible in a monolithic architecture. In addition, reactive microservices have a single responsibility and can be upgraded more frequently without disturbing the system’s operations. Groupon was able to handle more than 600,000 requests per minute regularly. Mission-critical marketing campaigns can now be delivered within hours, even during the flash sale with 7- 10X peak traffic. Lessons learned from Groupon’s microservice implementation Use the single responsibility principle with reactive microservices for enhanced concurrency and scalability. Leverage the underlying microservice architecture with an asynchronous layer for higher app uptime.

15. Contact Us Website www.simform.com Email Address contactus@simform.com Social Presence twitter.com/simform facebook.com/simform linkedin.com/company/simform/