Systems | Development | Analytics | API | Testing

Today, Confluent announced a $200 million commitment over the next three years designed to supercharge the growth and impact of its global partner ecosystem. This investment expands on Confluent’s partner-centric strategy; well over 20%* of the data streaming pioneer’s business in the past year has been partner-sourced, underscoring the ecosystem’s vital role in unlocking real-time use cases at scale.

Have ever opened up a dashboard or report, and not known where to start exploring? Finding meaningful conclusions from a sea of charts and tables can be challenging and time-consuming. It's not always easy to see and understand the story your data is trying to tell, especially when you’re presented with a lot of information at once.

The future of analytics is conversational, and with Yellowfin 9.16, it's here today. This release introduces a suite of AI-powered features designed to fundamentally change how you interact with your data. Forget complex queries and manual report building; now, you can simply click a button and get instant insights, charts, and narratives. Let's explore how.

Fivetran brings its enterprise-grade replication capabilities to unstructured data, unifying data integration across all formats.

In this series, we will take a close look at the architecture of ActiveStorage for Rails. In this first part, we will examine how ActiveStorage treats uploaded data and how to extend this process. The second part will explore how to augment the presentation of uploaded assets. But first, let's quickly define what ActiveStorage does.

For years, Automock was a popular framework for defining mocks and stubs in backend test environments. As technology has evolved, new methods and techniques for streamlining the simulation of dependencies in testing have emerged. That's why Automock has been succeeded by Suites, a more modern and robust library. In this article, we'll explore the transition from Automock to Suites, understand what Suites offers, and see it in action in NestJS through a complete example.

Apache Parquet has become the de-facto standard for storing data used in analytics workloads, and has seen very broad adoption as a free and open-source storage format. When used as the underlying storage layer for Apache Iceberg, Parquet is also a foundational building block in modern lakehouse architectures, which enable warehouse-like capabilities on cost effective object storage. Let’s take a closer look at what Parquet actually is, and why it matters for big data storage and analytics.

In a technologically dominated world, producing top-notch software isn’t merely a competitive edge – it’s a must. Whether creating a mobile application, a website, or a large-scale enterprise system, consumers anticipate that your software be secure, responsive, and flawless. That’s where Quality Assurance (QA) Testing comes in. It doesn’t just make your software work – it work well, do what users need it to do, and meet world-class standards of excellence.

At Bitrise, we continually invest in security best practices to ensure that our customer’s data stays safe and secure. As a part of an on-going effort, we are excited to announce that we’ve successfully completed our SOC 2 report. The examination was conducted by A-LIGN, a technology-enabled security and compliance firm trusted by more than 4,000 global organizations to help mitigate cybersecurity risks.

The software and product life cycle is fraught with pitfalls and tradeoffs. While testing applications under production-like load is critical to ensuring the reliability, performance, and security of your data storage and software services, you need to do this testing without actually affecting the production data and systems. In essence, you have to pull off the impossible – be as close to production as you can without actually being production.