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.

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.

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.

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.

Observability refers to understanding a system’s internal state by examining its external outputs, like logs, metrics, and traces. Borrowed from control theory, it’s the ability to infer what’s happening inside a system without direct access. To visualize observability, consider the human body. We don’t need to open it up to understand its internal state. By measuring external signals like body temperature, heart rate, or blood pressure, we can infer what’s happening inside.