A secure DevOps is highly beneficial for organizations. However, a secure DevOps environment shouldn’t be the end goal. When it comes to DevOps security, it’s important to integrate security right from scratch, secure the entire architecture, automate the security and use this technology to test the environment and the codes and respond to concerns immediately. This can help organizations safeguard their creations, protect the confidentiality of their customers and strengthen their applications, all before data breaches can occur.

Key Elements of the DevSecOps Environment

Microservice-Based Infrastructure

Single-function modules that contain well-defined interfaces and operations is essential for the success of focused DevSecOps. Constantly monitoring, upgrading and tweaking the microservice-based infrastructure will help organizations to be equipped for new developments.

Hybrid cloud environments, software-defined networking and network micro-segmentation must be integrated into the infrastructure, and these must be used to better define parameters, assess and identify connections, verify access and monitor the organization’s online assets.

Continuous Feedback Loop

The next most important element of the DevSecOps environment is feedback. Setting up a continuous feedback loop will help developers and machines get a comprehensive insight into system/platform vulnerability to security threats. This type of real-time, continuous feedback can help organizations set in place the right policies and rule sets, which can keep the application security testing tools updated and relevant regarding the security status of the organization’s software/network/platform, in addition to keeping all parties updated about the potential threats to the DevOps environment.

This type of continuous feedback loop acts as an enabler, as opposed to an inhibitor of business, by allowing organizations to stay well-equipped and constantly on guard.

Focused Automation

Finally, continuous and focused automation is essential to the success of the DevSecOps environment. Automation, when woven into the software development life cycle right from the start, can reduce the friction that may occur between development and security teams over software/platform security by quickly addressing existing and potential concerns at the lowest cost.

There are certain open source tools on the market that can help organizations automate their security:

Continuum Security: This tool works on a BDD-Security framework, which is compatible with unit testing frameworks, issue trackers, SAST and DAST. It offers an open IriusRisk API for anything the tool doesn’t natively support.
WhiteSource: This particular tool specializes in addressing open source vulnerabilities, alerting users about the existence of threats throughout the pipeline. It is compatible with 200 programming languages and it actively analyzes the license, quality and security of all open source codes.
ThreatModeler: This platform uses the functional information that developers input to analyze the software and provides information about potential threats. It also offers actionable inputs and security test cases to enable easy implementation of security.
Evident.io: This solution is designed for the deployment stage and helps assess and manage cloud security risk, particularly on Azure and AWS. Evident Security Platform (ESP) offers continuous monitoring, early threat identification and threat mitigation.
Aqua Security: This tool is ideal to manage end-to-end DevSecOps pipeline security. It has very tight runtime security processes and controls in place. It offers full control over the containerized environment and prevents any intrusion or vulnerability across the pipeline.

There are many other tools that organizations can use to automate their DevSecOps environment. These include: Dome9 (SaaS) Security, Contrast Security RASP & IAST tool, IMMUNIO RASP tool and Checkmarx SAST tool.

Shifting to the Left

In today’s agile world of development, following outdated waterfall philosophies is a death sentence for companies.

For successful implementation of DevSecOps, organizations should shift left. In other words, they should integrate deployments and testing right from the start, and these must continue till the very end when the software/platform in question is vulnerability-free. Etsy and Amazon, for example, conduct more than 1,000 deployments per day, each aimed at recognizing potential threats to their systems. Such a highly dynamic DevSecOps environment ensures that the velocity of new development isn’t slowed, and the quality of new developments is maintained at a high level.

This type of “shit left” philosophy not only accelerates new developments but also helps limit the security threats and addresses existing threats at the least cost with minimal damage to the software/platform.

Incorporating AI and Machine Learning into DevSecOps

Research shows that more than 50 percent of all companies will implement machine learning in their DevSecOps operations in 2019, due in part to the various benefits AI and ML offer to organizations that are actively maintaining a DevSecOps environment. These benefits include:

AI and ML will bring down DevSecOps security review time. They will do this by increasing the speed and quality of false positive identification, which will reduce the time spent on threat vector identification. This will help developers improve the speed at which they recognize the threats to their systems.
AI and ML will make up for the cybersecurity talent shortage, thereby ensuring that an organization’s DevSecOps environment isn’t left unmanned at any time. AI and ML will dip into human intelligence and use this to fuel their involvement in the DevSecOps environment. Additionally, AI and ML give organizations the ability to understand how other machines function, thereby helping cybersecurity personnel understand the psyche of cyberattackers.
AI and ML will actively find defects in the DevSecOps, help developers identify what they’re doing wrong and what they need to do to rectify these concerns. Constant monitoring is a core feature of DevSecOps, and AI and ML will serve to add more advanced technological backup to power this feature. AI and ML will also offer developers customized secure code patterns based on the organization’s unique DevSecOps landscape, which will assist in vulnerability detection.
AI and ML can help organizations move their DevSecOps from a small scale endeavor to large-scale. This will be a possibility because of the sheer technical prowess and the real-time information that AI and ML will furnish to developers and cybersecurity personnel.

7 Rules to Successfully Implementing a DevSecOps Environment

Integrate security from the start and across the pipeline.
Automate your security.
Track and monitor each software stack meticulously to identify which needs patching.
Implement code dependency checks such as the OWASP Dependency Check, vulnerability assessment and discovery tests regularly.
Put in place robust policies to manage the DevSecOps environment.
Break your tasks into manageable chunks—this will improve the consistency of deployments.
Set in place one-click compliance reporting to increase traceability and transparency of the pipeline, right from code planning to code changes to release.

Conclusion

DevSecOps will bring massive economic and technical advantages to organizations, apart from equipping them with the capabilities to create, run and offer state-of-the-art software/applications. Organizations wanting to remain relevant and competitive in the industry must consider DevOps security as their primary goal in 2019.

Nov	DEC	Jan
	07
2018	2019	2020