"The whole is more than the sum of its parts." Aristotle is credited with this quote, and it's true in the world of data. Legacy systems typically approached their role in a limited manner. Each system was intended to be used by a certain user set and handle well-defined processes and associated data. The result was a disintegrated environment with data being difficult to obtain, and frequently out of date. The parts couldn't easily cooperate to make a whole.

There are several ways to handle load spikes on a service. However, these methods are not cost-effective: you either pay for resources you don't use, or you risk not having enough resources to handle the load. Fortunately, there is a third way: horizontal autoscaling. Horizontal autoscaling is the process of dynamically adjusting the number of instances of a service based on the current load. This way, you only pay for the resources you use, and you can handle load spikes without any manual intervention.

Despite the transformative potential of AI, a large number of finance teams are hesitating, waiting for this emerging technology to mature before investing. According to a recent Gartner report, a staggering 61% of finance organizations haven’t yet adopted AI. Finance has always been considered risk averse, so it is perhaps unsurprising to see that AI adoption in finance significantly lags other departments.

We've just rolled out new trigger controls and enhanced YAML syntax so you can initiate your builds with unmatched precision.

In the age of digital transformation, enterprise continuous testing has become critical for agile and efficient software development. But enterprises often spend too much time managing a multitude of solutions and integrations with zero cohesion between solutions and an inability to gain clear insights. It takes so much time to manage the areas around testing that there is little time for the most important part — the testing itself.

We're excited to introduce Choreo Copilot (preview), which allows you to interact with Choreo. You can pose questions in natural language and Copilot will provide answers. Choreo Copilot enables you to grasp Choreo concepts, teaches you how to perform tasks in Choreo, and provides guidance when you encounter obstacles. Copilot is familiar with APIs in Choreo’s internal marketplace. Choreo already features an AI capability that enables API testing through natural language.

Watch how to use a multimodal LLM such as Gemini to analyze data in a BigQuery data lake and automatically generate schema layouts.

AI injects “intelligence” into automation, enabling systems to execute tasks, comprehend complex data, make informed decisions, and learn from outcomes. Unlike technologies such as robotic process automation (RPA), which follow predetermined rules, AI leverages data to evaluate situations and determine the best course of action. Now that we've explored how AI augments traditional automation tools, let's delve deeper into the realm of intelligent automation.