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Securing Multi-Cloud Environments: Challenges and Best Practices

The adoption of multi-cloud environments has increased as businesses recognize their numerous advantages. A company is considered multi-cloud when it leverages cloud services from two or more providers for its applications and operations. Unlike a single-cloud setup, multi-cloud systems often involve the integration of both private and public clouds or a combination of the two.

Why Accessibility Training Deserves Equal Time in Professional Development

Accessibility training isn’t an optional add-on—it’s an essential part of professional development. @AmyJuneHineline explains why accessibility should be prioritized just like learning new programming standards: Watch the latest episode of Test Case Scenario to learn why making accessibility training a priority is crucial for all development teams.

How Solid Queue works under the hood

Whether or not you're active in the Rails ecosystem, you might already have heard some of the buzz around Solid Queue, a new database-backed backend for ActiveJob. Solid Queue is a simple and performant option for background jobs that lets you queue large amounts of data without maintaining extra dependencies like Redis. We've already talked about how to deploy, run, and monitor Solid Queue, but we haven't yet explored how Solid Queue works.

How to Ensure API Quality with API Testing Using Postman in 2024

Whether you’re a Software Developer, DevOps Engineer, or Quality Assurance (QA) specialist, mastering API testing with tools like Postman is essential, especially during development. API testing using Postman makes it possible to increase security, provide better user experiences, and minimize the possibility of losses through bugs or vulnerabilities.

Build and Manage ML Features for Production-Grade Pipelines with Snowflake Feature Store

When scaling data science and ML workloads, organizations frequently encounter challenges in building large, robust production ML pipelines. Common issues include redundant efforts between development and production teams, as well as inconsistencies between the features used in training and those in the serving stack, which can lead to decreased performance. Many teams turn to feature stores to create a centralized repository that maintains a consistent and up-to-date set of ML features.

The Fall and Rise of Embedded Plugins: APIs For Embed Frameworks

Although important to see alternatives to iframes, iframes are still a valuable and commonly applied method for successful embed frameworks. And even if considering alternatives, iframes help to understand possibilities, along with design and technical details to consider for a successful platform. There’s more to embed Frameworks than letting partners appear in your interface.

What's New in Ruby on Rails 8

The first Rails 8 beta has officially been released, bringing an exciting set of features, bug fixes, and improvements. This version builds on the foundation of Rails 7.2, while introducing new features and optimizations to make Rails development even more productive and enjoyable. Key highlights include an integration with Kamal 2 for hassle-free deployments, the introduction of Propshaft as the new default asset pipeline, and extensive ActiveRecord enhancements.

SQL Transformations for Optimized ETL Pipelines

Table of Contents SQL (Structured Query Language) is one of the most commonly used tools for transforming data within ETL (Extract, Transform, Load) processes. SQL transformations are essential for converting raw, extracted data in CSV, JSON, XML or any format into a clean, structured, and meaningful format before loading it into a target database or cloud data warehouse like BigQuery or Snowflake.

Unleashing the Power of Amazon Redshift Analytics

Table of Contents Amazon Redshift has become one of the most popular data warehousing solutions due to its scalability, speed, and cost-effectiveness. As the data landscape continues to evolve, businesses are generating and data processing increasingly large datasets. Efficient analysis of these datasets is essential to making informed, data-driven decisions. Amazon Redshift allows companies to extract meaningful insights from vast amounts of structured and semi-structured data.