Systems | Development | Analytics | API | Testing

Company systems need regular testing because cyber threats are developing continuously. Vulnerability seekers find company security weaknesses while businesses are still unaware of their existence. Active security measures must be implemented to prevent your business from becoming a new target. Pen tests are a crucial self-defense method that detects system vulnerabilities before cyber attackers can exploit them.

Why would a well-running business consider DevOps Implementation? Implementing DevOps promotes swift software building and shipping through iterative outcomes and individual changes. For instance, the team scheduled a midnight deployment. However, an unexpected bug caused a system crash. The team spent hours fixing the issues and restoring services. The next question is, could we have prevented this?

Open source LLMs continue to compete with proprietary models on performance benchmarks for natural language tasks like text generation, code completion, and reasoning. Despite having fewer resources than closed models, these open LLMs offer cutting-edge AI without the high costs and restrictions of proprietary models. However, running these open-source models in production and at scale remains a challenge.

Nowadays, Agile and DevOps practices demand rapid iterations and continuous testing to ensure software quality. Manual testing alone can’t keep up with this speed, making test automation important to continue delivering high-quality products at a rapid rate. Despite its advantages, test automation isn’t as simple as writing and running a few scripts.

Learn how Fivetran’s GenAI-Ready Data Model & Snowflake Cortex can accelerate your AI initiatives.

“Which MRR metric should I be looking at?” “What’s the best dashboard to track our sales performance?” “Where can I find our marketing goals?” Sound familiar? As we spoke with our customers to learn more about how they collaborate around data, we kept hearing the same challenges – growth creates a need for better data management. What starts as a few key dashboards and metrics quickly becomes hundreds, spread across different teams, projects, and platforms.

What it means to be a fan is changing. Whether the fandom focuses on a sports team, a streaming drama series, or a musical artist, fans no longer want to be passive consumers. Instead, they’re looking to feel as though they are a part of the action through channels such as live chat, realtime stats, and behind the scenes insights. But there’s a tension in delivering those fan engagement experiences. Without the right strategy, technology costs can quickly make them economically unviable.

Software testing methodologies have evolved over time. In this article, we'll go through the most common methodologies that QA teams around the world follow.

Non-functional testing is the process of testing the non-functional aspects of a system, including its performance, security, accessibility, or usability. Its counterpart is functional testing. Functional testing checks the system's features, while non-functional testing checks how well it operates.

As real-time data processing becomes a cornerstone of modern applications, the ability to integrate machine learning model inference with Apache Flink offers developers a powerful tool for on-demand predictions in areas like fraud detection, customer personalization, predictive maintenance, and customer support. Flink enables developers to connect real-time data streams to external machine learning models through remote inference, where models are hosted on dedicated model servers and accessed via APIs.