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What if someone tells you that software development aren’t just factors in generating innovative edge applications but also stimulating them in opposition to the ever-evolving landscape of cyber threats? Yes, it is possible with DevSecOps. Utilising AI and machine learning has become crucial in this dynamic environment for improving the effectiveness and security of DevSecOps practises.
Welcome to the fantastic realm of DevSecOps where innovation and security pass the seamless harmony with the increasing requirement for cyber security professionals who deeply understand integrating security practices into the software development lifecycle.
As a cyber-security fanatic, you might be excited about the DevSecOps certification that boosts your professional career. Don’t worry, we got you. Here you will get every detail you are looking for.
DevSecOps stands for Development, Security and Operations. It’s the extension of DevOps practices where each team has various roles and responsibilities of software groups when they develop the applications.
DevSecOps is the practice of integrating security testing at each phase of the application development process. It covers tools and procedures that motivate collaboration among developers, operation groups, and security specialists to develop efficient and secure software. It provides the cultural transformation that contributes to security with the shared responsibility for everyone developing the software.
DevSecOps is differentiated into 5 phases: Plan, Develop, Test, Release and Operations.
- The first plan stage includes the three essential security tasks that must be considered to generate and analyse the security essentials, develop threat models and implement a roadmap for success control.
- Developing the code and getting peer review is part of the development phase.
- Testing the security of the things that are planned and developed is the aspect of the Test phase of the DevSecOps cycle. In testing phase, the Static Application Security Test is conducted.
- The software is developed, released and deployed in the non-production phase and the production circumstances in the release and deployment. Dynamic application security testing, red testing, etc., are performed in release phase.
- Once the application is deployed in production, maintaining and monitoring the application occurs in the operations phase.
In today’s era, AI and Machine Learning are sophisticated technologies that are becoming the mainstream faster than we had predicted. Now, DevSecOps is more AI-driven and ready to provide advanced, secure applications and keep up with today’s fast development cycle.
AI/ML in DevSecOps uses highly sophisticated systems for processing and learning from a wide range of data, making them adept at sorting with the help of information to spot patterns and irregularities.
This significant feature makes Artificial Intelligence and Machine Learning useful for security for cyber security and DevSecOps applications.
Following are the notable examples of DevSecOps’s transformation through AI/ML.
- Automated software security testing
- Effective security triaging
- Continuous monitoring of production
- Actionable DevSecOps metrics
We know how powerful Artificial Intelligence technology is, and it is rapidly increasing and improving to make our lives better with its exclusive features and practices. Hence, it also significantly enhances DevSecOps by improving security, mitigating security and automating different processes and tasks throughout the software development cycle.
AI/ML in DevSecOps helps teams to predict the potential barriers or issues, allows them to identify the patterns and helps them make data-driven decisions to enhance their applications before any problem becomes complex. It also automates security testing and analysis, which leads to quicker and more accurate detection and remediation of vulnerabilities.
This also helps DevSecOps to monitor systems in real time and analyze information through logs, alerts, and other resources to detect anomalous behavior and potential security problems. Hence, integrating AI/ML in DevSecOps brings various benefits along with security and contributes to providing more secure software faster.
Now, let’s get closure look to understand in which ways the AI is used DevSecOps. From the planning phase, Artificial Intelligence can be integrate into DevSecOps and the algorithms of AI can generate the different scenarios, threat models and suggest the secured coding choices.
The AI powered tool successfully analyses the code for vulnerabilities and recommends the different ways to measure in the implementation phase. Artificial Intelligence can also take test phase and its tools automates the testing and analyse the wide amount of data. Then, the tools identifies the patterns and brings the proactive security measures.
Then, the operation teams gets advantage from it as they are the one who normally performs the repetitive and monotonous tasks. The algorithm of AI generate the baseline and perform analysis on logs, generate the alerts. Hence, the use of AI in DevSecOps comes in variety of methods. Through DevSecOps Certification you will understand how Artificial Intelligence (AI) and Machine Learning (ML) plays significant role in DevSecOps.
- Vulnerability detection and assessment
- Behavioural analysis and anomaly detection
- Continuous learning and adaption
- Threat intelligence
- Security training and awareness
These are the few methods through which AI/ML is developed and applied within DevSecOps. To get to know further, you must visit GSDC. You will get to know different aspects of DevSecOps.
In today’s business circumstances, DevSecOps is useful in reducing the increased frequency of cyber-attacks. With the help of solid security initiatives, the application in various sectors gained different advantages.
Following are some of the sectors where DevSecOps are used.
- Government
- Information Technology
- Healthcare
- Finance and Banking
- Telecommunication
- Aerospace
Scope of DevSecOps For you
As an experienced individual, you have an excellent opportunity to work as a DevSecOps professional. It is one of the promising career prospects as it integrates security practices into the DevOps Pipeline.
The high requirement for certified devsecops professionals is increasing as businesses seek to integrate the security into their development. The following image helps you to understand between 2021 and 2028, the market of DevSecOps is expected to grow at a CAGE of 24.1%. DevSecOps professionals have different job opportunities as a result of this quick growth. Also, the demand is expected to increase as more businesses adopt DevSecOps practices.
Now, it’s becoming the most essential factor for Information technology fields. Therefore, you can quickly get a wide range of roles and responsibilities under the DevSecOps once you have done the DevSecOps certification.
Attractive DevSecOps salary
As the requirement for DevSecOps professionals grows, their salaries also increase. In the United State, the average salary for this position is $140,000 per year or $67.31 per hour. The basic pay for entry-level employees is $119,080 annually, and the yearly average wage for experienced employees is around $177,47
DevSecOps is an essential part of the future of software implementation, which provides a wide range of benefits for businesses that seek to improve their security practices. Hence, companies are integrating with AI to reap the benefits of DevSecOps and ensure their application’s security in the coming years. This blog will help you to understand DevSecOps and how AI and machine learning plays a significant role in DevSecOps.
Also read our previous blog on The Benefits of Earning a DevOps Certification for Your Professional Development