InfoQ Homepage Data Content on InfoQ
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InfoQ Software Architecture and Design Trends Report - April 2024
The InfoQ Trends Reports offer InfoQ readers a comprehensive overview of key topics worthy of attention. The reports also guide the InfoQ editorial team towards cutting-edge technologies in our reporting. In conjunction with the report and trends graph, our accompanying podcast features insightful discussions among the editors digging deeper into some of the trends.
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Testing Machine Learning: Insight and Experience from Using Simulators to Test Trained Functionality
When testing machine learning systems, we must apply existing test processes and methods differently. Machine Learning applications consist of a few lines of code, with complex networks of weighted data points that form the implementation. The data used in training is where the functionality is ultimately defined, and that is where you will find your issues and bugs.
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Data-Driven Decision Making - Software Delivery Performance Indicators at Different Granularities
Optimizing a software delivery organization is not a straightforward process standardized in the software industry. Getting the organization to analyze the data and act on it is a difficult undertaking. This article presents insights into how a socio-technical framework for optimizing a software delivery organization has been set up and brought to the point of regular use.
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DynamoDB Data Transformation Safety: from Manual Toil to Automated and Open Source
Data transformation remains a continuous challenge in engineering and built upon manual toil. The open source utility Dynamo Data Transform was built to simplify and build safety and guardrails into data transformation for DynamoDB based systems––built upon a robust manual framework that was then automated and open sourced. This article discusses the challenges with Data Transformation.
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Data Manipulation with Functional Programming and Queries in Ballerina
Ballerina has been designed as a data-oriented programming language and supports a functional programming coding style. The Ballerina query language is similar to SQL in the sense that a query expression is made up of clauses. The Ballerina “Table” data structure can be more effective than maps in representing indexed data collections.
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Ballerina: a Data-Oriented Programming Language
Ballerina’s flexible type system brings the best of statically typed and dynamically typed languages in terms of safety, clarity, and speed of development. Ballerina treats data as a first-class citizen that can be created without extra ceremony, just like strings and numbers.
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Software Architecture and Design InfoQ Trends Report—April 2022
An overview of how the InfoQ editorial team sees the Software Architecture and Design topic evolving in 2022, with a focus on what architects are designing for today.
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Data Patterns for the Edge: Data Localization, Privacy Laws, and Performance
With growing competition to get data that power experiences to the end-user closer and closer and the advent of local data privacy laws, let's look at different enterprise data patterns like “synchronous data retrieval”, “subsequent data retrieval” and “prefetch data retrieval” on data center.
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Developing Deep Learning Systems Using Institutional Incremental Learning
Institutional incremental learning promises to achieve collaborative learning. This form of learning can address data sharing and security issues, without bringing in the complexities of federated learning. This article talks about practical approaches which help in building an object detection system.
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AI, ML and Data Engineering InfoQ Trends Report - August 2021
How AI, ML and Data Engineering are evolving in 2021 as seen by the InfoQ editorial team. Topics discussed include deep learning, edge deployment of machine learning algorithms, commercial robot platforms, GPU and CUDA programming, natural language processing and GPT-3, MLOps, and AutoML.
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GitHub’s Journey from Monolith to Microservices
This article explores GitHub's recent journey towards a microservices architecture. It takes a deeper look at GitHub’s historical and current state, goes over some internal and external factors, and discusses practical consideration points in how Github tackled their migration, including key concepts and best practices of implementing microservices architecture.
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Data-Driven Decision Making – Optimizing the Product Delivery Organization
The Data-Driven Decision Making Series provides an overview of how the three main activities in the software delivery - Product Management, Development and Operations - can be supported by data-driven decision making. Applying Hypotheses, CD Indicators and SRE’s SLIs / SLOs enables a software delivery organization to optimize for effectiveness, efficiency and service reliability.