InfoQ Homepage Architecture Content on InfoQ
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Building & Operating High-Fidelity Data Streams
At QCon Plus 2021 last November, Sid Anand, chief architect at Datazoom and PMC Member at Apache Airflow, presented on building high-fidelity nearline data streams as a service within a lean team. In this talk, Anand provides a master class on building high-fidelity data streams from the ground up.
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InfoQ .NET Trends Report 2022
Every year, all InfoQ editors invite seasoned developers and practitioners from the industry to discuss the current trends in the entire software development landscape. In this article, we discuss some of the .NET Trends for 2022, divided into four stages of adoption.
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DevOps at Schneider: a Meaningful Journey of Engaging People into Change
Adopting DevOps at Schneider started with building a case for change. Tech people were engaged into change by organizing learning and collaboration sessions and getting feedback from the front lines. Change is hard and without leadership support, dedicated time for developers to really digest it and continual reinforcement and conversation, it will be challenging to be successful.
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Location, Location, Location: MVA Considerations for Distributed Processing and Data
Even when designing a Minimum Viable Architecture (MVA), developers must consider resource location, especially when mobile apps are part of a distributed system. Distributing the data and processing can introduce new challenges if location is not part of the decision-making criteria.
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Migrating Netflix's Viewing History from Synchronous Request-Response to Async Events
In a web-based service, a slowdown in request processing can eventually make your service unavailable. Chances are, not all requests need to be processed right away. Some of them just need an acknowledgement of receipt. Have you ever asked yourself: “Would I benefit from asynchronous processing of requests? If so, how would I make such a change in a live, large-scale mission critical system?”
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Choosing the Right Cloud Infrastructure for Your SaaS Start-up
As a solutions architect, I have been designing SaaS applications for years and I have seen start-ups struggle to find the right cloud infrastructure and improve their product offering. These experiences prompted me to write this article as a tool to help companies make a pragmatic fact and data-driven decision.
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Article Series: Continuous Architecture
In this series of articles, the authors reframe software architecture in terms of decisions that teams make about how their system will handle its quality attribute requirements (QARs). In their view, software architecture, reframed in terms of decisions, completes the picture of how the system works by making clear the choices that the team has made, and why.
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Building Workflows with AWS Step Functions
AWS Step Functions use a state machine to represent the workflow. A workflow consists of a set of tasks, each of which represents a discrete activity to be performed. Each task is defined by a state of the state machine. In this article, we will learn about the main concepts of AWS Step Functions and apply those to build a workflow for a sample business process: Order Fulfillment.
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The Implication of Feedback Loops for Value Streams
Lead time and throughput are dynamic variables which impact flow in a value stream. Capacity, processing time and feedback loops (such as error conditions) have a significant impact on WIP and flow and need to be mapped and measured when building value stream maps.
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Business Systems Integration is about to Get a Whole Lot Easier
A new breed of integration software is arising that syncs business data into a simplified data hub and then syncs that data to the destination system. The benefit of this integration pattern is that it reduces the number of manual transformations required (often to zero) and makes it easier to write manual transformations when you have to.
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Streaming-First Infrastructure for Real-Time Machine Learning
This article covers the benefits of streaming-first infrastructure for two scenarios of real-time ML: online prediction, where a model can receive a request and make predictions as soon as the request arrives, and continual learning, when machine learning models are capable of continually adapting to change in data distributions in production.
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Chipping Away at the Monolith: Applying MVPs and MVAs to Legacy Applications
Legacy applications actually benefit the most from concepts like a Minimum Viable Product (MVP) and its related Minimum Viable Architecture (MVA). Once you realize that every release is an experiment in value in which the release either improves the value that customers experience or doesn’t, you realize that every release, even one of a legacy application, can be thought of in terms of an MVP.