Today’s enterprise networks are complex. Potential attackers have a wide variety of access points, particularly in cloud-based or multi-cloud environments. Modern threat hunters have the challenge of wading through vast amounts of data in an effort to separate the signal from the noise. That’s where a security data lake can come into play.
This session covers opportunities for API development with and without AI, and consequently where AI opportunities are really appearing in practice - not in theory. What’s more, we will go over the latest AI trends and API Gateway enhancements.
It's 2024, and the HyperText Transfer Protocol (HTTP) is 35 years old. The fact that the vast majority of web traffic still relies on this simple, stateless form of communication is a marvel in itself. A first set of content retrieval optimizations were added to the protocol when v1.0 was published in 1996. These include the infamous caching instructions (aka headers) that the client and server use to negotiate whether content needs refreshing.
Unit tests are essential to verify the behavior of small code units in a Node.js application. This leads to clearer design, fewer bugs, and better adherence to business requirements. That's why Test-Driven Development (TDD) and Behavior-Driven Development (BDD) have become so popular in the backend development community. In this tutorial, we'll dive into unit testing and understand why it's needed in your backend.
We are excited to announce the launch of our AI Infrastructure Control Plane, designed as a universal operating system for AI infrastructure. With this launch, we make it easier for IT teams and DevOps to gain ultimate control over their AI Infrastructure, manage complex environments, maximize compute utilization, and deliver an optimized self-serve experience for their AI Builders.
Leveraging Insights from Over 2.6 Million Tests, 600K Devices, and 5 Billion Cumulative End Users to Drive Advanced AI, New Decision Aids, and Expanded DevOps Integrations. Austin, TX – August 14, 2024 – Testlio, a leading quality management company, today unveiled the fourth generation of its software platform. This innovative update includes advanced AI, robust data analytics, expanded device access, and more DevOps software integrations.
Artificial Intelligence (AI) technology has been transforming industries and our day-to-day lives alike. Its undeniable impact has led to significant effort and investment into making AI more accessible to everyone, everywhere. Open-source AI technology and AI APIs are two examples of our commitment to AI democratization. AI APIs democratize AI by providing access to pre-trained AI models, even for developers without extensive machine learning expertise.
You’ve built an incredible AI API and are ready to release this functionality to your users. The issue is that you’re not sure exactly how to monetize it. Generally, monetizing APIs is challenging at scale, but monetizing AI APIs can be even more difficult. Some AI APIs may be charged on a “per API call” basis, but many AI APIs require charging users for input and output tokens used within an API call. Others may charge per unique user or API key.
On July 19th, 2024, the world witnessed a large-scale computer outage caused by a faulty update from cybersecurity giant CrowdStrike. This incident, affecting millions of Windows devices globally, serves as a stark reminder of the domino effect that software errors can have. In part one of this series, we discussed the role QA methodologies can play in preventing future outages.