# microservices architecture Published articles for microservices architecture. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Breathing New Life into Legacy Systems. The Artisan of the Day Is Elena Cañete. DevFeed: [Breathing New Life into Legacy Systems. The Artisan of the Day Is Elena Cañete.]() Original publisher: [Read original article]() Author: Ana Tavares Published: 2025-09-29T14:05:51Z Content type: article Language: en Sources: [Laravel Blog]() Topics: [Laravel](), [PHP](), [Microservices](), [Development](), [Architecture & Design]() Tags: [architecture](), [developer](), [laravel](), [legacy](), [legacy-code](), [microservices](), [microservices-architecture](), [php]() ### AI overview Elena Cañete specializes in modernizing legacy systems. Her work includes rebuilding vanilla PHP ERP systems with Laravel, migrating a TYPO3 monolith to a Laravel-based microservices architecture, and modernizing ERP and API systems for scalable, future-proof solutions. ### Source excerpt Elena Cañete modernizes legacy systems with Laravel, turning clunky code into scalable solutions while inspiring developers to embrace tough projects. ## Introducing Read-Only Database Attach for SQLite in Turso DevFeed: [Introducing Read-Only Database Attach for SQLite in Turso]() Original publisher: [Read original article]() Author: Glauber Costa Published: 2025-07-30T00:00:00Z Content type: article Language: en Sources: [Turso Blog]() Topics: [Turso](), [SQLite](), [Databases](), [Architecture & Design](), [Microservice]() Tags: [architecture](), [databases](), [microservices-architecture](), [operational](), [performance](), [safety](), [sqlite](), [turso]() ### AI overview Turso 0.1.3 introduces read-only database attachment for its SQLite rewrite, allowing multiple databases to be connected in one session and queried together. The release also improves write performance by reducing write amplification and reusing free space in B-Tree pages. ### Source excerpt Learn about the new ATTACH DATABASE feature in Turso's SQLite rewrite which allows you to connect to multiple databases at once. ## Order Dispatch Systems at Scale DevFeed: [Order Dispatch Systems at Scale]() Original publisher: [Read original article]() Author: Guest User Published: 2025-07-28T01:53:56Z Content type: tutorial Language: en Sources: [Kogan.com]() Topics: [Amazon Simple Queue Service (SQS)](), [event driven](), [Scalability](), [Amazon Web Services](), [Microservices](), [microservices architecture](), [Latency]() Tags: [aws](), [concurrency](), [event](), [event-driven](), [latency](), [microservices-architecture](), [scale](), [sqs]() ### AI overview This tutorial compares vertical and horizontal scaling, pull-based queues using AWS Simple Queue Service, and event-driven architecture for order dispatch systems. It describes queue trade-offs and explains how event subscribers can process orders independently and scale separately. ### Source excerpt How to load-balance like a seasoned waiter Software systems often parallel the real world. Imagine running a busy restaurant, where customers line up to make orders whilst the kitchen prepares the meals. In the software world, your users are the customers, and your backend services are the kitchen. With more people online than ever before, that line might start to grow out the front door. The ability to scale is no longer optional, it is essential. Know Your Options Vertical Scaling - Scale Up Horizontal Scaling - Scale Out Expanding your restaurant by adding more tables or a larger kitchen. In software terms, this means scaling up your infrastructure. More powerful CPUs, larger memory, increased throughput etc. This is a relative quick fix, but comes with diminishing returns and limits on how big everything can get. Opening new restaurant locations to serve more customers simultaneously and distribute existing flows. In software terms, this means adding more API servers, more worker nodes or creating many database replicas. This approach is more flexible and scalable than vertical scaling in the long term. A Steppingstone - Queues Just like how customers queue for their order, we create a pull-based task queue for our order management system using AWS Simple Queue Service (SQS). Tasks get queued into the SQS, and a consumer service will continuously poll this queue to process the tasks. This gives a lot of control for the queue consumer to dictate the frequency of polling, which works well in systems that cannot handle high throughput or requires non-concurrency like the SAP ERP (more on that later). SQS also provides built-in dead-letter-queues, retry policies, at least once delivery guarantee and scales automatically. Vertical scaling involves sizing up the compute power of the consumer (CPU, RAM etc). Horizontal scaling involves spinning up more consumers of the SQS. However, queues have limitations: Latency between order arrival and processing. Inefficient poll ## Seven Software Architectural Patterns: A Plain-English Guide DevFeed: [Seven Software Architectural Patterns: A Plain-English Guide]() Original publisher: [Read original article]() Author: Nelson Djalo Published: 2025-04-16T16:00:23Z Content type: tutorial Language: en Sources: [Amigoscode Newsletter]() Topics: [Architecture & Design](), [Software Engineering](), [Microservice]() Tags: [architecture](), [guide](), [microservices-architecture](), [monolithic-architecture](), [patterns](), [software-design]() ### AI overview A plain-English guide to seven software architectural patterns: monolithic, layered, microservices, SOA, MVC, event-driven, and master-slave. It explains how these patterns organize software and discusses tradeoffs such as simplicity, scalability, complexity, and collaboration. ### Source excerpt A simple guide to 7 software architectural patterns -- monolithic, layered, microservices, SOA, MVC, event-driven, and master-slave -- explained in plain English. ## How Dispatch speeds up development with Neon while keeping workloads on Aurora DevFeed: [How Dispatch speeds up development with Neon while keeping workloads on Aurora]() Original publisher: [Read original article]() Author: Carlota Soto Published: 2024-10-14T15:31:55Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [Development](), [Amazon Web Services](), [Architecture & Design](), [Microservice](), [Serverless](), [sdlc](), [Testing](), [Availability](), [Database]() Tags: [agile](), [architecture](), [availability](), [aws](), [backups](), [case-studies](), [cost](), [development](), [microservices](), [microservices-architecture](), [ops](), [pii](), [principal-engineer](), [sdlc](), [serverless](), [team](), [us](), [verification]() ### AI overview The article describes how Dispatch uses Neon branching to create isolated development and verification environments without copying large volumes of data. Dispatch is transitioning from a monolithic system to a microservices architecture, using replicated workload data with personally identifiable information excluded for testing. Neon's serverless writer endpoints are intended to address Aurora's single-writer bottleneck and reduce overprovisioning costs during spiky traffic, while Neon branches accelerate the software development lifecycle. ### Source excerpt "Neon's branching paradigm has been great for us. It lets us create isolated environments without having to move huge amounts of data around. This has lightened the load on our ops team, now it's effortless to spin up entire environments."Jonathan Reyes, Principal Engineer at Dis... ## Architectural Design for a Ride App such as OLA, UBER, RAPIDO DevFeed: [Architectural Design for a Ride App such as OLA, UBER, RAPIDO]() Original publisher: [Read original article]() Author: ratneshmaurya2311@gmail.com (Ratnesh Maurya) Published: 2024-07-30T00:00:00Z Content type: article Language: en Sources: [Ratn Labs]() Topics: [microservices architecture](), [Architecture & Design](), [gRPC](), [App]() Tags: [architecture](), [backend](), [microservices](), [microservices-architecture](), [queues](), [rest](), [software-architecture](), [system-design](), [system-design-backend](), [tracking](), [vs]() ### AI overview An overview of architectural design for a ride-sharing app, covering microservice boundaries, REST, gRPC, message queues, geolocation tracking, and the trade-offs between starting with a monolith and adopting microservices. ### Source excerpt Microservices architecture for ride-sharing: service boundaries, REST vs gRPC vs message queues, geo-location tracking, and trade-offs between monolith-first and microservices. ## How Intuit Handled their Busiest Time of Year with Apollo Router DevFeed: [How Intuit Handled their Busiest Time of Year with Apollo Router]() Original publisher: [Read original article]() Author: Ishwari Lokare Published: 2024-01-29T07:30:00Z Content type: article Language: en Sources: [Apollo Blog]() Topics: [GraphQL](), [GraphOS](), [API Platform](), [gateway](), [Architecture & Design](), [Microservice]() Tags: [announcement](), [api-platform](), [apollo](), [architecture](), [gateway](), [go](), [graphos](), [graphql](), [microservices](), [microservices-architecture]() ### AI overview The article describes how Intuit moved from multiple internal GraphQL gateways toward a single supergraph powered by Apollo GraphOS and Apollo Router. The transition was intended to improve self-service, standards compliance, performance during seasonal traffic peaks, and supergraph management, while the work remained ongoing. ### Source excerpt Millions of small to midsize businesses turn to Intuit's Quickbooks to manage their accounting, payroll, tax, and more. It is overwhelmingly the most popular accounting software on the market today. Intuit serves 100 million individuals and businesses through its leading products TurboTax, Credit Karma, QuickBooks and Mailchimp. ## To choreograph or orchestrate your saga, that is the question DevFeed: [To choreograph or orchestrate your saga, that is the question]() Original publisher: [Read original article]() Author: Emily Fortuna Published: 2023-07-13T15:30:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [distributed-systems](), [microservices architecture](), [Orchestration](), [Architecture & Design](), [business logic]() Tags: [architecture](), [backend](), [debug](), [decoupling](), [distributed-systems](), [how-to](), [microservices](), [microservices-architecture](), [monolith](), [orchestration](), [ordering]() ### AI overview This article explains the saga pattern for tasks that span microservice boundaries and compares choreography with orchestration. It describes how choreography uses message passing and local service knowledge, while distributed ordering requirements can make control flow harder to understand and debug. ### Source excerpt An explanation of orchestration and choreography of microservices, and how Temporal works under the hood. Find out how and why. ## Imperfect #14: How to map dependencies DevFeed: [Imperfect #14: How to map dependencies]() Original publisher: [Read original article]() Author: Pedro Gil Carvalho Published: 2023-07-07T13:33:59Z Content type: tutorial Language: en Sources: [Pedro Gil Carvalho]() Topics: [Architecture & Design](), [microservices architecture](), [Microservice](), [interfaces](), [API](), [Database]() Tags: [api](), [architecture](), [awareness](), [changes](), [database](), [dependencies](), [distributed](), [issue-tracker](), [map](), [microservices](), [microservices-architecture](), [monitor](), [monolith](), [pair-programming]() ### AI overview The article explains how to map service dependencies to help identify and avoid distributed monoliths. It recommends team-by-team architecture reviews, collaboratively maintained diagrams, monitoring connected interfaces, and tracking dependencies in a simple spreadsheet. ### Source excerpt Avoiding the distributed monolith antipattern requires great situational awareness. Today we go over what that means, how architecture reviews can help, and one simple way to anticipate dependencies. ## Imperfect #13: Killing the Distributed Monolith DevFeed: [Imperfect #13: Killing the Distributed Monolith]() Original publisher: [Read original article]() Author: Pedro Gil Carvalho Published: 2023-06-30T09:03:26Z Content type: opinion Language: en Sources: [Pedro Gil Carvalho]() Topics: [Architecture & Design](), [microservices architecture](), [Microservices]() Tags: [architecture](), [distributed](), [microservices](), [microservices-architecture](), [monolith]() ### AI overview The article argues that a distributed monolith can emerge when microservices teams develop thick networks of dependencies. Using a retailer settings-page example, it describes how ownership boundaries, cross-team requests, context switching, and coordination delays can slow delivery and create defects. It presents the problem as both organizational and technical, with healthier boundaries as the proposed direction. ### Source excerpt Going faster through healthier boundaries ## 5 Key DevOps Trends for 2022 DevFeed: [5 Key DevOps Trends for 2022]() Original publisher: [Read original article]() Author: Kirby Wadsworth Published: 2022-03-17T12:00:02Z Content type: article Language: en Sources: [ionir]() Topics: [DevOps](), [Kubernetes](), [Cloud Native Ecosystem](), [Microservice](), [Persistence]() Tags: [blog](), [cloud-native](), [containers](), [devops](), [devsecops](), [iac](), [kubernetes](), [microservices](), [microservices-architecture](), [persistence](), [recent-posts-featured]() ### AI overview The article discusses five DevOps trends for 2022, including rising Kubernetes adoption, increased use of cloud-native technology and containers, and continued growth of microservices architecture. It cites survey findings about stateful applications, data persistence, multi-cloud support, and the benefits of Kubernetes. ### Source excerpt In DevOps, each day brings new trends, challenges, and solutions to light. It's critical for all developers, platform engineers, and systems architects alike to stay on top of industry trends to continuously improve processes and drive innovation. Let's dive into the top 5 DevOps trends for 2022. The post 5 Key DevOps Trends for 2022 appeared first on ionir. ## Schema Services: Transitioning Towards a Federated Architecture DevFeed: [Schema Services: Transitioning Towards a Federated Architecture]() Original publisher: [Read original article]() Author: Andy Roberts Published: 2020-11-04T15:09:30Z Content type: tutorial Language: en Sources: [Apollo Blog]() Topics: [GraphQL](), [Architecture & Design](), [microservices architecture](), [Microservices]() Tags: [apollo-federation](), [architecture](), [backend](), [cloud](), [graphql](), [microservices-architecture](), [rest](), [services]() ### AI overview This article introduces schema services as a transitionary architecture for organizations moving toward a federated GraphQL architecture. It discusses how schema services can help bridge legacy and modern services, mixed protocols, data-centric APIs, and GraphQL skills gaps during an Apollo Federation adoption. ### Source excerpt The reality for most large organizations adopting Federation is that the architecture sitting behind it is... messy. In this article, I will introduce the concept of schema services and demonstrate how they can provide an easier transition towards a federated architecture. From a jumble of modern and legacy services, different tech stacks, data sources, platforms, etc. most enterprise architecture diagrams look more like a grab bag of tech from the last couple of decades than anything else. ## From Project Oslo to AWS Simple Workflow and Azure Service Bus DevFeed: [From Project Oslo to AWS Simple Workflow and Azure Service Bus]() Original publisher: [Read original article]() Author: Samar Abbas Published: 2020-10-21T04:00:00Z Content type: opinion Language: en Sources: [Temporal Blog]() Topics: [distributed-systems](), [resiliency](), [Amazon Web Services](), [Microsoft](), [Messaging](), [Microservice](), [Azure](), [Open Source]() Tags: [announcements](), [aws](), [distributed-systems](), [messaging](), [microservices](), [microservices-architecture](), [microsoft](), [open-source](), [resiliency]() ### AI overview A personal account of a developer's career path from Microsoft's Project Oslo to AWS Simple Workflow and Microsoft Azure Service Bus. It describes how developers used low-level primitives to build resiliency and how managed services helped reduce that effort. ### Source excerpt In 2010, I was contemplating my next move after working on Microsoft's Project Oslo. This inspired me to set the criteria for my next job. Read more here. ## Presto at Zuora DevFeed: [Presto at Zuora]() Original publisher: [Read original article]() Author: Manfred Moser Published: 2020-06-16T00:00:00Z Content type: article Language: en Sources: [Trino Blog]() Topics: [Architecture & Design](), [Microservice](), [Microservices](), [data-architecture](), [Query (disambiguation)](), [big-data]() Tags: [analytics](), [architecture](), [big-data](), [data-architecture](), [distributed](), [microservices-architecture](), [presentation](), [technical](), [update](), [webinar]() ### AI overview The article announces a Presto Summit virtual event about using Presto as a query layer in Zuora's distributed microservices architecture. It explains how Zuora used Presto to separate a monolithic data architecture, provide access to production data across services, and support complex queries over live data. ### Source excerpt The Presto Summit is morphing into a series of virtual events, and we already started with the State of Presto webinar recently. Next up is a talk about Presto with lots of practical insights at Zuora presented by Henning Schmiedehausen: Using Presto as Query Layer in a Distributed Microservices Architecture Update: We had a great event with lots of questions from the audience, taking us beyond the planned time frame. Check out the recording to learn more: ## The Road to an Envoy Service Mesh DevFeed: [The Road to an Envoy Service Mesh]() Original publisher: [Read original article]() Author: Snow Pettersen Published: 2019-03-29T15:36:51Z Content type: article Language: en Sources: [Square Corner Blog - Medium]() Topics: [microservices architecture](), [Architecture & Design](), [interoperability](), [Remote Procedure Call (RPC)](), [Go Language](), [Java](), [Ruby](), [Ruby on Rails](), [gRPC](), [Code]() Tags: [architecture](), [automatic](), [discovery](), [engineering](), [envoy-proxy](), [failover](), [go](), [http](), [interoperability](), [java](), [microservices](), [microservices-architecture](), [routing](), [rpc](), [ruby](), [service-mesh]() ### AI overview Square describes its evolution from a Ruby on Rails monolith to a microservices architecture and explains the interoperability challenges created by its Java, Ruby, and Go stack. The article outlines its Protobuf-based Sake RPC framework, its routing, failover, traffic-shaping, and service-discovery features, and Square's migration toward a full service mesh. ### Source excerpt Heads up, we've moved! If you'd like to continue keeping up with the latest technical content from Square please visit us at our new home https://developer.squareup.com/blog At Square we've been running a microservices architecture for years, primarily using three different languages: Java, Ruby and Go. Running such a diverse stack can make interoperability between the different languages/frameworks challenging, and in this post I'll talk about how Square has handled this in the past and where we're at today -- actively migrating towards a full service mesh. The Old World Square started off, like many other companies, just running one large monolith. For Square this was a big Ruby on Rails service, that handled everything that Square did. A monolith makes service to service communication completely unnecessary: everything runs in the same code base on a single database, so everything can be implemented without making any outbound network calls (except to third parties outside of Square). After a while, Square decided to move more towards a service oriented architecture to reduce the reliance on a single, large application. To do this Square decided to build their own Protobuf based RPC framework, inspired by Google's Stubby. This was years before gRPC was created, so there weren't any open source options at the time. This RPC framework, called Sake, was implemented for Java and Go as these were the languages used for higher availability services, while regular REST HTTP was used between services that didn't understand Sake. (Incidentally, Sake became a part of gRPC's DNA) Over time this framework became fairly sophisticated, with many features not generally available: Smart retries with automatic failover Prioritized routing based on upstream health Traffic shaping and service discovery This ended up working well, but relied on fat client/server libraries, so extending support to other languages was hard. Attempts were made to bring feature parity between languages i ## Practical Microservices Problems: Isolating the Messaging Layer DevFeed: [Practical Microservices Problems: Isolating the Messaging Layer]() Original publisher: [Read original article]() Author: Ivan Ursul Published: 2018-10-01T00:00:00Z Content type: opinion Language: en Sources: [Ivan Ursul]() Topics: [Microservice](), [Architecture & Design](), [Messaging](), [Kafka]() Tags: [api](), [async](), [java](), [kafka](), [mapping](), [messaging](), [microservices](), [microservices-architecture](), [migrations](), [mongodb]() ### AI overview An experienced practitioner describes problems encountered while working with microservices, focusing on an isolated messaging layer. The article explains how a proprietary communication service can mediate Kafka-based asynchronous messaging through topic-to-endpoint mappings, while noting that each organization faces different problems. ### Source excerpt Today is the starting of the fourth year since I began my journey with microservices. I started with a theoretical knowledge about this architecture and now I ended up with a more deep and practical experience. While I still believe I can find news problems in microservices, I prepared an article... ## Avoiding Overengineering: Choose Architecture and Databases for the Job DevFeed: [Avoiding Overengineering: Choose Architecture and Databases for the Job]() Original publisher: [Read original article]() Author: umer Published: 2017-08-19T00:00:00Z Content type: opinion Language: en Sources: [Code Ahoy - Articles]() Topics: [Databases](), [Architecture & Design](), [MySQL](), [NoSQL](), [Microservice](), [Apache Cassandra]() Tags: [architecture](), [cassandra](), [databases](), [microservices-architecture](), [mysql](), [nosql]() ### AI overview The author reflects on choosing technologies based on actual needs rather than hype. They describe replacing a monolith and MySQL with service-oriented architecture and Cassandra, concluding that the resulting system was too complex for a small startup team to maintain. ### Source excerpt It was April. Year was probably was 2010. The cold, snowy winter was finally coming to an end and the spring was almost in the air. I was preparing for my final exams. The review lectures were going on for the RDBMS course that I was enrolled in at my university. Around the same time, I had started hearing and reading about the shiny, new technology that was going to change the way we use databases. The NoSQL movement was gaining momentum. I was reading blogs about how MongoDB is big time outperforming ancient, non web scale relational databases. After the lecture, I asked my professor: Me: So, between RDBMS and NoSQL databases, which one do you think is the best? Professor: Well, it depends. Me: Depends on what? Professor: Depends on what you are trying to achieve. Both have their pros and cons. You pick the right tool for the job. Me: But MySQL can't really scale. Professor: How do you think we got this far? Send me an email and I'll send you some papers and practical uses in the industry. SQL was hard for my brain, especially the joins. I loved NoSQL. Simple key->value model without any joins! RDBMS systems that were designed in 1960's were simply not enough to keep up with modern demands. I had lost all interest in RDBMS and predicted they'll just fade off in the next few years. It's 2012. We're redesigning my employer's flagship product. The first version was a monolith that used the boring MySQL. Spending too much time reading blogs and Hacker News comments section, we convinced ourselves that we need to go big and modern: Break monolith into service-oriented architecture, aka, the SOA. Replace MySQL with Cassandra (MySQL to Redis to Cassandra) And we built it. There was nothing wrong with the new system... except one major flaw. It was too complex for a small startup team to maintain. We had built a Formula One race car, that makes frequent pit-stops and requires very specialized maintenance, when we needed a Toyota Corolla that goes on for years and years on j ## Inside a SoundCloud Microservice DevFeed: [Inside a SoundCloud Microservice]() Original publisher: [Read original article]() Published: 2017-07-28T00:00:00Z Content type: article Language: en Sources: [SoundCloud Backstage Blog]() Topics: [Microservice](), [Microservices](), [Architecture & Design](), [Back end](), [Finagle](), [Scala](), [API](), [JSON](), [Network](), [RSS Feed](), [telemetry](), [Messaging]() Tags: [api](), [architecture](), [backend](), [configuration](), [finagle](), [functional-programming](), [json](), [messaging](), [microservices](), [microservices-architecture](), [network](), [rss](), [scala](), [telemetry]() ### AI overview The article describes SoundCloud's transition from a monolithic backend to independently built and deployed microservices. It explains how the Creators Team implements services in Scala with Finagle, shared libraries, APIs, JSON or Thrift communication, configuration injection, telemetry, and service-to-service request aggregation. ### Source excerpt If you're a regular visitor to this blog, you might be aware that we have been transitioning to a microservices based architecture over the past four to five years, as we have shared insights into the process and the related challenges on multiple occasions. To recap, adopting a microservices architecture has allowed us to regain team autonomy by breaking up our monolithic backend into dozens of decoupled services, each encapsulating a well defined portion of our product domain. Every service is built and deployed individually, communicating with other services over the network via light-weight data interchange formats such as JSON or Thrift. What we haven't touched on so far is how a microservice at SoundCloud looks backstage. ## Microservices and the monolith DevFeed: [Microservices and the monolith]() Original publisher: [Read original article]() Published: 2016-08-26T00:00:00Z Content type: opinion Language: en Sources: [SoundCloud Backstage Blog]() Topics: [Architecture & Design](), [Microservice](), [microservices architecture](), [HTTP](), [Prometheus](), [Docker](), [Kubernetes](), [Finagle](), [telemetry](), [Testing]() Tags: [architecture](), [docker](), [finagle](), [http](), [kubernetes](), [microservices](), [microservices-architecture](), [monolithic-architecture](), [prometheus](), [telemetry](), [testing]() ### AI overview SoundCloud reviews its migration from a monolithic architecture to microservices and evaluates the strategy needed to decommission the monolith. The article reports that internal tools and libraries improved service creation and engineering productivity, while extraction projects remained difficult because they took months and depended on multiple teams. ### Source excerpt In a previous series of blog posts, we covered our decision to move away from a monolithic architecture, replacing it with microservices, interacting synchronously with each other over HTTP, and asynchronously using events. In this post, we review our progress toward this goal, and talk about the conditions and strategy required to decommission our monolith. ## Synchronous communication for microservices: current status and learnings DevFeed: [Synchronous communication for microservices: current status and learnings]() Original publisher: [Read original article]() Published: 2016-07-27T00:00:00Z Content type: article Language: en Sources: [SoundCloud Backstage Blog]() Topics: [Microservice](), [Architecture & Design](), [Finagle](), [Remote Procedure Call (RPC)](), [Scala](), [HTTP](), [JSON](), [Netty](), [Scalability](), [Prometheus](), [MySQL](), [Routing (disambiguation)]() Tags: [architecture](), [blog-post](), [finagle](), [framework](), [http](), [json](), [library](), [microservices](), [microservices-architecture](), [mysql](), [programming](), [prometheus](), [rpc](), [scala](), [scalability]() ### AI overview This article describes SoundCloud's use of synchronous request-response communication in a microservices architecture. It discusses Finagle and Scala-based services, the internal jvmkit library, non-blocking I/O, service discovery, routing, logging, Prometheus integration, and the use of HTTP/1.1 with JSON. It also explains the interoperability and debugging benefits of HTTP and JSON, along with their greater overhead compared with more optimized protocols. ### Source excerpt Since we started breaking our monolith and introduced a microservices architecture we rely a lot on synchronous request-response style communication. In this blog post we'll go over our current status and some of the lessons we learned. ## Testing AWS Scala Microservices DevFeed: [Testing AWS Scala Microservices]() Original publisher: [Read original article]() Author: Ben Darfler Published: 2016-04-27T11:56:52Z Content type: article Language: en Sources: [Localytics]() Topics: [Testing](), [Scala](), [Microservices](), [Amazon Web Services](), [Amazon S3](), [Amazon Simple Queue Service (SQS)](), [DynamoDB]() Tags: [architecture](), [aws](), [bugs](), [dynamodb](), [hackathon](), [metrics](), [microservices](), [microservices-architecture](), [s3](), [scala](), [slack](), [sqs](), [testing]() ### AI overview The article describes how Localytics addressed slow, fragile, and overused end-to-end tests in an AWS-based Scala microservices architecture. It introduces three open-sourced SBT plugins--sbt-s3, sbt-dynamodb, and sbt-sqs--and explains the testing problems that motivated them. ### Source excerpt In January and February of this year we open sourced three SBT plugins that have had a huge impact on our ability to test our AWS based Scala microservices architecture: sbt-s3 sbt-dynamodb sbt-sqs This is our story. Stop me if you've heard this one before. ## Application visibility DevFeed: [Application visibility]() Original publisher: [Read original article]() Author: Square Engineering Published: 2015-07-10T07:00:00Z Content type: opinion Language: en Sources: [Square Corner Blog RSS Feed]() Topics: [Monitoring](), [dashboards](), [Microservices](), [Instrumentation](), [site-reliability-engineering]() Tags: [api](), [api-metrics](), [dashboards](), [ecosystem](), [engineering](), [instrumentation](), [metrics](), [microservices](), [microservices-architecture](), [monitoring](), [systems]() ### AI overview Square describes the monitoring and alerting systems it uses to improve application visibility as its technology stack grows from Rails monoliths to a microservices architecture. The article presents principles for usability, focused metrics, instrumentation, actionable alerts, and reproducible problems, and introduces tools for dashboards, dependencies, events, exceptions, capacity, and deployments. ### Source excerpt A sneak peek into various monitoring and alerting systems used at Square. ## Finn.no's architecture summit focused on breaking up its iAD monolith into microservices DevFeed: [Finn.no's architecture summit focused on breaking up its iAD monolith into microservices]() Original publisher: [Read original article]() Author: Audun Fauchald Strand Published: 2015-02-10T11:00:00Z Content type: article Language: en Sources: [Finn.no]() Topics: [microservices architecture](), [Architecture & Design](), [Domain-driven design (DDD)](), [event driven](), [Node.js](), [RxJava](), [reactive](), [real-time](), [legacy]() Tags: [architecture](), [architectures](), [development](), [domain-driven-design](), [event-driven](), [legacy](), [microservices](), [microservices-architecture](), [node-js](), [reactive](), [real-time](), [rxjava]() ### AI overview Finn.no organized a two-day architecture summit to coordinate its development teams around a microservices architecture after breaking up the iAD monolith. The program covered domain-driven design, event-driven architecture, CQRS, service properties, and implementation examples using Node.js, RxJava, and Reactive Streams. ### Source excerpt After working several years with (successfully) breaking up the legacy monolith, called iAD, Finn.no wanted to add structure to this process, and make sure that all 20 development teams work towards the same target. The target is a microservices architecture with small-ish autonomous services, owning their own data. With that in mind we arranged our own two-day architecture summit for all Lead Developers, with a combination of external and internal presenters. The focus was on microservices, domain driven design, event driven architectures and modern programming techniques. We started off the first day with a long session. Finn.no's Chief Enterprise Architect Sebastian Verheughe wanted to communicate his vision. This included topics such as strategic domain-driven-design, data-highways, and how to use event-driven architecture to further decouple our services. This theme continued, with the first external presenter. Jan Ove Skogheim from Particular Software talked about his experiences from Rikstoto, and how they had broken up a monolith into multiple small services. He also talked about the composite-UI pattern. After lunch we continued with a presentation by Karsten Mevassvik from finn.no, of the most important properties for a finn.no microservice. These include: Is RESTful Owns its own data-store Team ownership Consumer Driven The first day of the summit was concluded with a presentation of the CQRS architectural pattern. This presentation was held by Idar Borlaug and Andreas Berre from WebStep. They showed all the central concepts in CQRS, such as commands, event-stores, aggregates, sagas using very good examples to illustrate their concepts. The second day of the summit started off with some hardcore programming. The frameworks of choice was node.js and RxJava. Christopher Kolstad started with an example of how a microservice could be implemented using Reactive Streams and RxJava. After that Phillip Johnsen presented a case using node.js in a real time context