DevOps and DevSecOps: Key Benefits & Components | Alpacked

DevOps and DevSecOps are terms we regularly hear in the IT industry. About 47% of companies reported using DevOps and DevSecOps for software development in 2022 (up from 11% increase from 2021). Yet, despite being commonplace, many professional developers have a surface-level understanding of these methodologies. 

But we're ready to fill you in. In this article, you'll learn about the components, tools, and benefits of DevOps and DevSecOps. We’ll also tell you which practices you need to apply to make the most of your software development.

DevOps is a methodology that combines practices and tools that enhance cooperation between developers and IT operation teams across the software development life cycle (SDLC). It aims to improve the quality of the software and shorten the development cycle with continuous feedback, automation, and shared ownership.

The DevSecOps model, as opposed to DevOps, integrates cybersecurity and risk mitigation into the SDLC. You imbue security practices, automated testing, and a shared responsibility culture into your application development from the very beginning. That’s in contrast with traditional development models, where teams usually perform security checks close to the product's release date.

DevOps and DevSecOps models work hand in hand. Outdated security can derail even DevOps initiatives, resulting in hidden system vulnerabilities and laborious code rewrites. Companies that want to make the most out of DevOps should strive to implement DevSecOps practices into their pipelines.

These practices are effective as you can incorporate them into your business. So, let’s look at their components in greater detail.

Here are some of the common DevOps practices and solutions your departments can incorporate to work collaboratively:

• CI/CD pipeline. Continuous integration (CI) tools check for bugs and dependencies issues in code releases, while continuous delivery (CD) delivers validated code into production. This allows multiple contributors to develop simultaneously in one production environment without disruptions. About 62% of advanced DevOps teams relied on CI/CD workflows in 2022.
• Automated code review. AI-powered software and machine learning technologies can analyze test data to identify inefficient coding practices, and the root causes of errors, and predict issues. Over 47% of GitLab’s 2022 Global Survey by GitLab respondents said their testing is fully automated (a 25% increase from 2021).
• Source code management. Source code (version control) systems take regular snapshots of your files to help your teams track code changes. It ensures your departments can work in a single application environment. About 21% of DevOps teams in 2022 used source code management to release code faster.
• Public cloud infrastructure. Many cloud computing platforms support DevOps practices and provide efficient CI/CD tools. To boot, public cloud providers take care of the infrastructure maintenance, letting your IT teams focus on development. Moreover, about 56% of DevOps practitioners had already adopted public cloud infrastructures by 2022.
• Container orchestration (Kubernetes). Containerization means packaging your operating systems and supporting libraries into portable, lightweight executables. Organizations also need to invest in container orchestration platforms (like Kubernetes) to facilitate updating, deployment and scaling of containerized systems across environments.
• NoOps. NoOps is a highly automated serverless IT environment where cloud vendors take care of computing, storage, and memory-based tasks for higher-order services. Although the concept is still evolving, it may eventually help companies manage infrastructures with smaller teams, so they can focus their efforts on development.
• Database load balancers. Load balancer services automatically distribute the network traffic and workload over database nodes. This optimizes the resource usage across your systems to maintain stable performance and reduce the risk of downtime.
• SQL management. SQL DevOps solutions help your teams develop and deploy databases along with the code. They include command-line tools and automation methods that make SQL development a part of your CI/CD pipeline.
• GitOps. Infrastructure as a Code (or GitOps) is an operational framework that applies DevOps practices to infrastructure provisioning. It relies on a dedicated repository as a single source of truth for configurations, merges requests for tracking updates, and uses automated tools to ensure the environment stays in the desired state.

Does all of this seem like a lot of work? To understand if DevOps model is worth it, let’s see how these practices can strengthen overall project development.

These are some of the advantages you can expect by incorporating efficient DevOps practices into your pipeline.

• Productivity enhancements. Automation tools root out repetitive processes and minimize disruptions, freeing up your engineer’s workload. About 60% of developers state that they can release the code twice as fast with DevOps model. 
• Better collaboration. Containerized environments, infrastructure automation, source code management, and CI/CD software help development and operations teams collaborate more efficiently and continuously.
• Higher code quality. Nearly 60% of developers state that DevOps is invaluable for code quality and security. That’s mainly because CI/CD tools and practices help companies accelerate code reviews, which results in more refined releases.
• Smaller technical debt. Automated testing helps you identify needless dependencies and spaghetti code early on, enforcing higher quality standards across the SDLC. You can reduce your organization’s technical debt—the cost of reworking and refactoring caused by inefficient technologies and practices.
• Fewer development costs. Defects found earlier in development are less costly to fix than those discovered closer to the deployment. Additionally, over 83% of respondents in the 2020 Micro Focus study agree that defects found in DevOps environments take less time and money to fix (than in traditional development methodologies).

You shouldn’t expect immediate results, though. Gartner reports that over 75% of DevOps initiatives through 2022 will fail to meet business expectations. Successful transformation relies on your ability to change your organizational culture, which is something that should be implemented gradually.

Next, let’s see how your teams can build DevSecOps model into your product’s lifecycle.

• Continuous security tests. Your CI/CD pipeline should run automated validation tests, scan pre-built container images for vulnerabilities, and have automated verification and authentication tests. This will help reduce human error and ensure secure coding practices.
• Application security scans. Over 50% of security professionals perform regular static application security testing (SAST) tests, container scans, and license compliance checks. Doing so helps identify and remediate issues early in the SDLC before they become more complex.
• Network security. Network control and segmentation tools help you isolate software modules and control traffic in containerized Kubernetes. Larger enterprises may adopt software-defined networking technology that uses application programming interfaces (APIs) for more visibility into the data packet flows.
• Configuration management. Automated DevSecOps tools help you manage resource deployment and configuration options. As a result, you reduce security vulnerabilities and maximize performance across your production environments (acceptance testing, system testing, load testing, and others). 
• Threat modeling. Security teams can evaluate security risks by modeling an attack. For example, threat modeling solutions help detect the system’s faults and predict the attacker’s behavior (including possible entry and exit points, critical assets, and vulnerable data flows).
• Data encryption. Organizations should minimize the chances of unauthorized access to their databases, files, and containers with encryption (encoding information into a code) and tokenization (replacing data with a generated number) tools.
• Role-based access control. Restricting access to data, environments, and microservices based on your employees’ responsibilities and roles reduces the risk of data breaches and simplifies onboarding. About 67% of companies also implement a dedicated headcount to address security problems.
• Monitoring and logging. You might incorporate a Security Information and Event Management (SIEM) platform to centralize data logging from distributed services, applications, and other security software. Additionally, you can set up alerts to immediately notify your teams about high-priority anomalies and security incidents.
• Data backup and recovery. Data backup and disaster recovery tools can back up your high-risk data and monitor your storage systems for errors. That way, you can continue development if a server crashes, data is corrupted, or ransomware makes critical files inaccessible. 

So how do these tools help you during software development?