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Development

Featured in Development

Compiled, Typed, Ruby-Inspired Crystal Language is Ready for Production - Q&A with Beta Ziliani

The Crystal language is ready for production, 12 years after inception. Crystal is compiled for performance, typed for safety, and Ruby-like for productivity. Due to the strong type inference, developers need only sparse type annotations. We interviewed the head of the Crystal team on the language tradeoffs, the present features and the language roadmap.

All in development

Architecture & Design

Featured in Architecture & Design

Change Data Capture for Distributed Databases @Netflix

Raghuram Onti Srinivasan covers the challenges associated with capturing CDC events from Cassandra, discussing the Flink ecosystem and the use of RocksDB.

All in architecture-design

AI, ML and Data Engineering

Featured in AI, ML & Data Engineering

Why a Serverless Data API Might Be Your Next Database

In this article, author Pieter Humphrey discussed database as a service (DBaaS) and serverless data API for cloud based data management.

All in ai-ml-data-eng

Culture & Methods

Featured in Culture & Methods

Increasing Developer Effectiveness by Optimizing Feedback Loops

We can think of engineering as a series of feedback loops: simple tasks that developers do and then validate to get feedback, which might be by a colleague, a system (i.e. an automation) or an end user. Using a framework of feedback loops we have a way of measuring and prioritizing the improvements we need to do to optimize developer effectiveness.

All in culture-methods

DevOps

Featured in DevOps

Key Metrics to Track and Drive Your Agile Devops Maturity

To promote DevOps and Agile process improvement, a meaningful set of metrics should be tracked. In this article we will discuss which metrics are appropriate based on the stage of the culture change. Coupling these metrics with strong support from leadership will ensure the best improvements in team measures such as cycle time, deployment frequency, and software quality.

All in devops

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QCon Plus May

Discover emerging software trends and validate your software roadmap. Virtual Event on May 17-28, 2021, 9 am EDT / 3 pm CEST

InfoQ Live June

Prevent Cloud and Serverless security challenges Virtual Event on June 22, 2021, 9 am EDT / 3 pm CEST

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Your monthly guide to all the topics, technologies and techniques that every professional needs to know about. Subscribe for free.

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Presentations

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SOA Masterclass: Definitions & Patterns

Miko Matsumura teaches SOA Foundations: Definitions, Patterns, and evolution toward SOA. An excerpt from webMethods SOA Master Class.

Miko Matsumura
on Feb 23, 2007 1

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37:33

Topics

Compiled, Typed, Ruby-Inspired Crystal Language is Ready for Production - Q&A with Beta Ziliani

Change Data Capture for Distributed Databases @Netflix

Why a Serverless Data API Might Be Your Next Database

Increasing Developer Effectiveness by Optimizing Feedback Loops

Key Metrics to Track and Drive Your Agile Devops Maturity

Helpful links

Choose your language

Presentations

SOA Masterclass: Definitions & Patterns

New Exploit Breaks Current Spectre Defenses; Fixes Hard without Performance Impact

Compiled, Typed, Ruby-Inspired Crystal Language is Ready for Production - Q&A with Beta Ziliani

Find Solutions to Your Software Challenges at QCon Plus

Airbnb Builds Himeji - A Scalable Centralized Authorization System

Change Data Capture for Distributed Databases @Netflix

Google Provides a Peek into the Architecture of Colossus - Its Storage Foundation

Variations on New Normal for Workplaces

Increasing Developer Effectiveness by Optimizing Feedback Loops

DEI Is Rooted in Justice. Let's Stop Making It about Profit

Researchers Publish Biologically Plausible AI Training Method

Why a Serverless Data API Might Be Your Next Database

Facebook Announces ZionEX Platform for Training AI Models with 12 Trillion Parameters

How GitHub Leverages Feature Flags to Ship Quickly and Safely

Key Metrics to Track and Drive Your Agile Devops Maturity

Atlassian Open DevOps Integrates Jira with Tools Like GitHub and Datadog

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