Systems | Development | Analytics | API | Testing

AI has come as a game-changer in plenty of industries, with OpenAI’s GPT series setting the pace in natural language processing and decision-making abilities. The latest edition, GPT-4, promises even more powerful features, like enhanced accuracy, enlarged context window, and improved performance for grape tasks. However, before the adoption of this avant-garde technology, it is necessary to understand how much GPT-4 costs.

Since 5G networks began rolling out commercially in 2019, telecom carriers have faced a wide range of new challenges: managing high-velocity workloads, reducing infrastructure costs, and adopting AI and automation. Because data management is a key variable for overcoming these challenges, carriers are turning to hybrid cloud solutions, which provide the flexibility and scalability needed to adapt to the evolving landscape 5G enables.

Managing and accessing massive datasets is increasingly challenging as the pace of data generation accelerates. Enterprises face growing difficulties in ensuring secure, scalable, and high-performance interaction with data systems while adapting to dynamic requirements. This blog explores how Apache Iceberg and DreamFactory address these issues.

Static sentiment analysis is a groundbreaking theoretical approach that could reshape the software development process. Here we explain what is static sentiment analysis and how it has the potential to understand developer intent. Read along or jump ahead to the section that interests you most.

Cybersecurity is one of the top concerns for businesses today. Vulnerabilities make the news when they turn into expensive breaches. With the cloud so prevalent in today's digital landscape, much attention has turned to API security. Network attacks aimed at APIs increased by an incredible 681% in 2022. Considering the continued popularity of SOAP (simple object access protocol) APIs, it is now a top priority for global IT leaders to learn SOAP's security best practices.

According to Ruby tradition, the core team will release Ruby 3.4 on December 25—but the preview has been out since May! If you're anticipating the release like we are, you're probably wondering what's new in Ruby 3.4. There aren't any huge changes in this release, but you'll want to be aware of a few really cool things. Let's dig into some of the language changes first.

The demand for food delivery services is skyrocketing, driven by our busy lifestyles and the need for convenience and variety. Apps like Uber Eats, Zomato, and DoorDash have changed how we order food, giving us access to countless restaurant options and smooth delivery experiences. For entrepreneurs, developing an app similar to DoorDash is a great opportunity to tap into this booming market.

The API Waterfall is a sequentially and methodically defined approach for managing data flows and integration of services in software development. Aligned to the traditional waterfall methodology, the architectural model essentially targets a step-wise flow of events where each stage depends on the completion of the previous step.

In k8s world every resource created via controller. Like there are inbuilt controllers for pods, deployments , replica set etc. So basically, Controllers are nothing but a control loop that continuously monitor the state of the cluster and take actions to bring the cluster into the desired state. The resources have a spec that provides the desired state. The controller checks the current states.

In the last year, we’ve seen the explosion of AI in the enterprise, leaving organizations to consider the infrastructure and processes for AI to successfully—and securely—deploy across an organization. As we head into 2025, it’s clear that next year will be just as exciting as past years. Here, Cloudera experts share their insights on what to expect in data and AI for the enterprise in 2025.