Systems | Development | Analytics | API | Testing

How Confluent Helps Software Providers Build Real-Time Products and SaaS Faster

Bringing real-time capabilities to your product or software-as-a-service (SaaS) is no longer a nice-to-have; it’s a competitive necessity. Whether you're building a real-time payment platform, a patient monitoring system, or any product where instant data processing fuels great user experiences and artificial intelligence (AI)-driven innovation, Apache Kafka data streaming is likely at the core.

Announcing the Confluent Cloud Fully Managed Sink Connector for ClickHouse

Data is in motion, and it’s moving faster than ever. For developers and data architects building modern real-time data platforms, the ability to get data from anywhere and analyze it instantly is a superpower. That’s why we’re excited to announce a major step forward in this journey: the fully managed sink connector for Clickhouse, now generally available on Confluent Cloud.

Accelerate Gradle testing on Bitrise: Test Distribution private beta now open

We’re excited to announce the launch of our Gradle Test Distribution private beta on Bitrise. Starting today, Bitrise users can contact us to join the program and dramatically speed up Gradle test execution through scalable, parallel test distribution. This release is a major step forward for Android teams with large test suites and growing complexity. By hosting the Bitrise Build Cache, Test Distribution workers, and CI runners within the same data center fabric, we’re able to offer.

Performance Testing in Agile: Optimizing Workflows with Xray

Today, users expect software to be not only functional but also fast, reliable, and scalable. And that’s where performance testing comes in. It focuses on evaluating how an application behaves under expected or extreme workloads. Traditionally, performance testing was reserved for the final stages of development. But with the rise of Agile and DevOps, this approach no longer fits.

Tariff Pain from a Data Point of View

If you’re in procurement, finance, or operations at a mid-sized ecommerce or retail company, tariffs aren’t just a political talking point - they’re a silent force eating into your profitability. And the real problem isn’t always the tariffs themselves. It’s the lag between policy changes and when your data catches up. If any of it sounds familiar, we’d love to hear your point of view in the short survey below.

Page Object Model In Automation Testing: A Complete Guide

Page Object Model in Automation Testing is one of the most popular design patterns for building maintainable and scalable test scripts. It is widely used by QA teams who want to write clean, reusable, and easy-to-maintain code when automating tests for web applications. The idea is simple yet powerful. Instead of mixing locators and actions directly in test scripts, the page object pattern in Selenium and other frameworks groups all the elements and actions of a page inside a dedicated class.

Manual Vs Automation Testing: A Comparative Analysis

Imagine that you are baking a cake. You can do everything the hard way, manually: measuring flour, mixing batter, preheating the oven just right, or you can use a smart kitchen device that measures, mixes, and bakes for you with one touch of a button. Both are capable of making a great cake, but both have control, labor, and consistency sacrifices.
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The Silent API Killer: Data Coupling in Your Tests

In API testing, speed, accuracy, and confidence in test results are everything. Regardless of whether you're validating functionality, testing performance under load, or ensuring compliance with your security posture and standards, the ultimate goal is the same: catching problems before they reach production. But what if your tests are lying to you? Lurking beneath even the most sophisticated test suites is a subtle, pervasive threat: data coupling. Data coupling is a silent API killer that doesn't throw immediate errors or break builds in obvious ways.

Top 5 Digital Analytics Platforms that Offer Customer Engagement Features

Knowing how customers behave is the unrefined oil of the data world, so having a tool that lets you understand and process it into measurable, actionable data can help keep the customers you have just as much as finding new ones. But how do you use customer engagement to maximize your product's value? There are three key steps: These key steps and more all come together to turn engagement metrics into an actionable source of data. Learn more about it here.

Cache Miss Handling in Microservices

When a cache miss occurs in a microservices architecture, the system fails to retrieve requested data from the cache, leading to slower performance as the data must be fetched from the database or other sources. Handling these misses efficiently is key to maintaining system speed and reliability. Here's a quick summary of the main strategies: Cache-Aside Pattern: The application fetches data from the database on a miss, stores it in the cache, and serves it to the user.