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Senior Cloud Data Engineer
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Since the emergence of generative AI, our work has undergone a significant transformation, and we need to adapt to this change. In the past, we could spend countless hours performing complex tasks to achieve a particular outcome. However, with generative AI tools, somebody on the other side can complete the same task in less time.
Generative AI is not intended to replace the workforce or substitute for human intelligence. Instead, it serves as a means of enhancing our decision-making abilities by offering proposed solutions.
Welcome to the era of generative AI!
This tool is a big player in the software development industry and has been trained using billions of lines of code, using the proposed code can help us make better decisions and boost our productivity, allowing us to save time and achieve great results. This code companion supports a set of languages such as:
As a cloud engineer, I wanted to ask Q some questions for the first time as a user, here they are
I asked Q what is Elastic Kubernetes Services (EKS) and here is the answer!
Amazon Q explaining EKS
The answer is synthetized and gives some links to the documentation, with such experience we can improve skills better and accelerate infrastructure as code with a wealth of knowledge at our fingertips.
Asking Amazon Q to explain a terraform script
Amazon Q provides a detailed answer
Amazon Q explained the terraform script with details and documentation to AWS, with such experience, it’s easy to understand some scripts quickly and we can gain more time.
The script is a snippet to provision an EC2 instance, the goal is to ask Q secure coding practices before provisioning the instance.
Asking Amazon Q to provide secure coding practices
Amazon Q provides secure coding practices
Such experience allows developers and network engineers to improve the script before it goes into production.
In the era of generative AI, we have the opportunity to improve our learning and achieve greater results. Those who insist on reinventing the wheel cannot keep pace with teams that prioritize agility. Additionally, working with infrastructure as code is challenging and demands skilled teams to maintain high-quality infrastructures.
With AI, we have an excellent opportunity to speed up infrastructure as code. We don't need to know everything; the AI will handle the rest!