In my presentation, I'll discuss how we've integrated CI/CD pipelines to automate the deployment of both low and high-interaction honeypots. By tailoring these honeypots to mirror our customers' technology stacks, we've been able to gather more relevant threat data. I'll explain how we've used HASH (https://github.com/DataDog/HASH) to quickly deploy low-interaction honeypots and delve into how container technology allows us to deploy high-interaction honeypots capable of running any technology stack. Additionally, I'll highlight how the data we collect enhances our understanding of threats and enriches our customers' logs with valuable security insights. Our approach stands out because it combines DevOps methodologies with cybersecurity practices to create a dynamic and responsive honeypot deployment system. By integrating CI/CD pipelines, we're able to respond rapidly to emerging threats, deploying honeypots in real-time as new vulnerabilities surface. We customize these honeypots to reflect our customers' actual environments, making the data we collect more relevant. This integration also streamlines the entire process from deployment to data analysis, reducing manual effort and minimizing potential errors. I'll share recent case studies to illustrate the effectiveness of our approach. For example, I'll talk about how we quickly deployed honeypots to capture exploit attempts on a newly discovered Confluence vulnerabilities, Docker API exploitation, Log4J, and Redis exploitation. I'll also discuss how our high-interaction honeypots allowed us to monitor attackers' behavior after they gained initial access. Additionally, I'll highlight instances where the intelligence we gathered significantly improved our customers' ability to detect and respond to threats. These real-world examples will demonstrate the impact of our methods.