Digital Transformation & Enterprise IT Strategy


Build Trust, Transparency & Accountability With Security Automation.

It stands for Development, Security, and Operations, with AI playing a pivotal role. Its slogan is to hold everyone accountable for security, with the goal of implementing security choices and actions on the same scale and speed as development and operations decisions and actions are implemented. AI-powered solutions can enhance security by providing real-time threat detection and proactive risk mitigation within the DevSecOps framework. 

"The absence of security in the initial stages of System Engineering is the single most significant cybersecurity gap and risk in modern system development."

Every DevOps-enabled firm should strive to adopt a DevSecOps attitude and raise the degree of security competency among personnel from all technological disciplines and skill sets. A DevSecOps framework that makes use of DevSecOps technologies makes ensuring security is incorporated into programmes rather than being slapped on randomly later. This includes testing for potential security vulnerabilities and developing business-driven security services. 

Benefits Of DevSecOps

Simple benefits of DevSecOps, enriched by AI and data-driven decision-making in enterprise IT transformation, include automating the software delivery pipeline to reduce errors, vulnerabilities, and downtime. Additionally, by implementing the right DevSecOps tools and procedures, teams can seamlessly integrate security into their DevOps architecture.  

This approach allows organizations to collaboratively work towards the shared goals of higher code quality, improved security, and enhanced compliance. With a test-driven development environment supported by automated testing and continuous integration as integral parts of the workflow, companies can achieve greater efficiency and security in their software development and deployment processes while fostering a culture of innovation and compliance. 

Need For DevSecOps

Over the last decade, the IT infrastructure landscape has witnessed exponential changes. The transition to flexible cloud computing platforms, shared storage and data, and dynamic applications has brought significant benefits to enterprises looking to thrive and expand through innovative apps and services. While DevOps applications have made strides in speed, scalability, and functionality, they often lag in terms of robust security and compliance. Consequently, DevSecOps was introduced into the software development lifecycle to harmonize development, operations, and security. 

In this evolving landscape AI plays a crucial role. Any organization involved in creating and distributing applications must accord security the same importance as development and operations. The integration of DevSecOps and DevOps ensures that every developer and network administrator approaches app development and deployment with security in mind. AI-powered tools and solutions further enhance security by providing real-time threat detection, proactive risk mitigation, and data-driven insights, reinforcing the importance of security within the entire software development and deployment process. 

Best Practices For DevSecOps

Delivering software quickly is a fundamental element of DevOps, and adding security need not compromise this objective. By integrating automated security controls and testing early in the development cycle, you can ensure the swift delivery of your applications. AI plays a pivotal role in this process, as it can enhance the efficiency of security measures by providing real-time threat detection, automating security testing, and offering data-driven insights, thereby reinforcing both speed and security in the software delivery process. 

Incorporating security into your workflows is essential for multiple reasons. Firstly, by utilizing tools capable of scanning code as it’s written, you can identify security issues at an early stage. Secondly, by integrating security measures into your workflows, you bolster safeguards against unauthorized access or tampering with your work. Thirdly, by implementing security measures within your workflows, you can assist in ensuring that your work complies with regulatory requirements. AI can greatly enhance these efforts by providing advanced code analysis, real-time threat detection, and automated compliance checks, strengthening security and compliance in a streamlined manner. 

Engaging in threat modeling exercises is instrumental in identifying vulnerabilities within your assets and addressing security control gaps. By leveraging technologies like Dynamic Data Protection from Forcepoint, powered by AI, you can pinpoint the riskiest activities occurring across your infrastructure. Moreover, you can seamlessly integrate the necessary security measures into your DevSecOps workflows. AI-driven data governance and Data Architecture further enhance your threat modeling efforts, ensuring comprehensive and proactive security management in your organization. 

Challenges With DevSecOps And How We Solve It

Resistance may be fruitless, but it may certainly keep things going. Changing the way people operate is difficult for many individuals, especially if it entails a mentality shift from ‘security as an afterthought’ to ‘security-first.’ Some will definitely object, but by establishing ‘security champions’ in your teams, powered by AI, you may help disprove the misconception that higher security stifles growth and stifles innovation. 

How we solve it – Bring individuals on board early, integrating AI, to build new processes that benefit everyone. It’s all about teaching employees across the organization that code can be provided quickly and safely at the same time, with AI-driven security measures in place, and encouraging teams to collaborate toward that common objective. AI can provide real-time threat detection, automated security controls, and data-driven insights, ensuring security doesn’t hinder innovation but supports it. 

Many conventional security procedures, such as compliance auditing, architectural risk analysis, threat modeling, and risk management, require security personnel to conduct tests, evaluate findings, and then collaborate with developers to implement adjustments. This extended process often conflicts with the fast-paced nature of DevOps, and some of these procedures can be challenging to automate, creating a tension between security and DevOps. 

How we solve it – To overcome this time-consuming challenge, you can leverage DevSecOps technologies, enhanced by AI, to make standards, rules, models, and service-level agreements more testable and automated. AI-driven solutions can streamline and automate the evaluation of security standards and compliance, accelerating the security integration process within DevOps workflows. 

The primary focus for DevOps is rapid release, yet security teams emphasize secure software through processes that often conflict with quick release cycles. This apparent misalignment of security with DevOps can impede the adoption of DevSecOps. 

How we solve it – Developers, with the aid of AI, can identify security vulnerabilities early in the development process, alleviating the burden on security professionals and reducing costs in later stages. By proactively identifying vulnerabilities, teams can implement AI-driven security patch management to resolve issues swiftly, ensuring that security is integrated seamlessly into the DevOps workflow without compromising release speed. AI empowers more efficient and effective security measures that align with DevOps objectives.