Operations | Monitoring | ITSM | DevOps | Cloud

Modern AI applications are having a dramatic impact on our industry, but there are still certain hurdles when it comes to bringing ML models to production. The process of building ML models is so complex and time-intensive that many data scientists still struggle to turn concepts into production-ready models. Bridging the gap between MLOps and DevSecOps workflows is key to streamlining this process.

“How can we turn our DevOps data into useful DevSecOps data? There is so much of it! It can come from anywhere! It’s in all sorts of different formats!” While these statements are all true, there are some similarities in different parts of the DevOps lifecycle that can be used to make sense of and unify all of that data. How can we bring order to this data chaos? The same way scientists study complex phenomena — by making a conceptual model of the data.

As cyber attacks have become ever more sophisticated, the means of protecting against cyber attacks have had to become more stringent. With zero trust security, the model has changed from “trust but verify” to “never trust, always verify.” Joining D2iQ VP of Product Dan Ciruli for an in-depth discussion of zero trust security was Dr. John Sahlin, VP of Cybersolutions at General Dynamics Information Technology (GDIT), and David Sperbeck, DevSecOps Capability Lead at GDIT.

DevSecOps is a philosophy that integrates security practices within the DevOps process. DevSecOps involves creating a ‘security as code’ culture with ongoing, flexible collaboration between release engineers and security teams. The main aim of DevSecOps is to make everyone accountable for security in the process of delivering high-quality, secure applications. This culture promotes shorter, more controlled iterations, making it easier to spot code defects and tackle security issues.

DevOps and DevSecOps have gained more attention in recent years in the world of software development. While both of these methodologies emphasize the agile development process and team collaboration, there are some key differences that distinguish them. Understanding these distinctions is critical for software development teams and organizations to determine which methodology is best suited to their requirements. In this article, we’ll learn about the difference between DevOps and DevSecOps.

For today’s software organizations security has never been more top of mind. On one side there is the present and growing threat of being hacked by malicious actors, set out in Crowdstrike’s recent Global threat report. And, on the other, there is a wave of cybersecurity regulation from the government to mitigate such cybersecurity vulnerabilities.

More than 26,000 software vulnerabilities were discovered in 2022 – a new record – and critical vulnerabilities were up 59% over 2021, the previous record-high year. In other words, despite years of DevSecOps, software doesn’t seem to be getting more secure. Release management can help. A crucial goal of release management is vulnerability-free software.

Developers and security experts are now tasked with bolstering, extending, and adjusting cloud and Kubernetes security to protect against cyberattacks that are ever more complex, volatile, and frequent. To foil attacks and create a secure foundation for applications and infrastructure from the beginning, DevSecOps (Development, Security, and Operations) has become the trending development and operations practice. In the DevSecOps model, security becomes a shared responsibility.