Modern organizations are increasingly leveraging DevOps and CI/CD methodologies in a software-centric world to improve their ability to innovate, develop, test, and release quality applications to the market quickly.
So much so that according to MarketWatch, the global CI/CD tools market size is projected to reach Multi-million USD by 2028.
For forward-thinking enterprises, building robust and future-ready CI/CD pipelines will be critical as custom applications become a competitive differentiator.
However, building the CI/CD of the future will be challenging due to complexities involving performance issues, communication, version control, flawed testing, security vulnerabilities, CI/CD scale-ups, and misconfigurations, among others.
In this article, we’ll share how organizations and development teams can build the CI/CD of the future.
What is CI/CD?
Continuous Integration/Continuous Delivery (CI/CD) is a DevOps practice that helps ensure that code changes are integrated quickly, frequently, and thoroughly tested before shipping into production.
CI/CD comprises two significant software practices:
Continuous Integration (CI) — Code is continually built, run, tested, and integrated into a centralized and easily accessible repository location. This helps identify and reduce potential problems early in the software development life cycle.
Continuous Delivery (CD) — Picks up from CI to ensure automatic code building, testing, and configuration. All code changes in a build are initially released to a staging or testing environment, which can be released to the production environment as needed.
Key Elements of CI/CD Pipeline
From source code to production, CI/CD pipelines are usually broken down into the following phases:
Commit: Developers commit code changes to version control systems such as Git.
Build: The code is compiled into executable programs or artifacts such as Docker images or packages for deployment environments. Teams can also integrate new code while quickly determining any execution bottlenecks.
Test: Teams perform CI/CD testing to evaluate code for quality, behavior, and performance via automated integration, unit, system, UI, and regression tests.
Deployment: Successful and approved codebase is automatically pushed to a staging production environment, after which the final release is shipped to end-users.
Monitor: continuous performance and stability checks on production systems to ensure functions are running as expected.
Pros and Cons of CI/CD Pipelines
Major benefits of a CI/CD pipeline include the following:
- Better quality code: By automating tests, developers can be sure that the code they’re committing meets all quality standards before it goes into production. This means fewer bugs in production and a better overall product for end-users.
- Speed and efficiency: CI/CD helps drastically reduce the time needed to build and release applications. By eliminating repetitive procedures like server configuration and database setup, developers can focus on creating quality code, quick debugging, and adding new features—faster.
- Reduced costs: By lowering the time DevOps engineers spend on mundane manuals and using automated testing tools early in development, businesses can save more time and money.
- Better team collaboration: Having a well-defined CI/CD pipeline allows for better collaboration and innovation between different teams working on a project since everyone knows exactly where their code should go next and how to test it before being released into production.
Some disadvantages of a CI/CD Pipeline can be:
- Complex implementation: Lack of clarity on the best CI/CD tools and how to use these tools and platforms, resulting in complication issues while constructing and running CI/CD pipelines.
- Lack of interoperability across the mushrooming CI/CD technologies
- Lack of qualified personnel: Developing a fully automated CI/CD pipeline requires skills that require you to hire or train specialists.
- Investment and training costs: CI/CD pipelines require a significant upfront investment in infrastructure resources and time.
The Future of CI/CD and Data-Driven DevOps
This past decade has seen rapid digital transformation innovation and acceleration due to technological advances and the pandemic’s impacts.
With the tech landscape rapidly and constantly changing, there will be continuing evolution around CI/CD tools, approaches, and strategies. As CI/CD approaches and tools mature, CI/CD platforms and expert assistance will become integral to automating developer workflows.
We can expect even more mutual communication and collaboration between operations, design, and partnerships in software development.
For DevOps teams, it means a need to improve and continuously become high performers.
DevOps is also poised to reap significant benefits as more companies move their operations to the cloud and base their strategies and future decisions on the data they generate.
With vast volumes of data at their disposal, businesses have quickly realized the value of collecting, analyzing, deriving insight, and making data-driven decisions. That means there’ll be more focus and growth towards data-driven DevOps to achieve successful and impactful CI/CD pipelines that deliver faster results.
Data-driven DevOps (or DataOps) is applying Agile and DevOps best practices to data management to quickly transform data-driven insights into software products that unlock the commercial value of data.
Cloud-native app developers will also have a more robust environment to work with and integrate Big Data to create data-intensive apps. Expect to see CI/CD platforms and pipelines leverage big data and analytics that yield a more robust understanding of software delivery status and quality benchmarks.
CI/CD Trends and Predictions for 2023 and Beyond
CI/CD will continue to develop at the same swift pace as technology. As we transition into 2023 and beyond, organizations can keep an eye on the following CI/CD trends:
AI-Driven Operationalization and Development
In 2023 and beyond, the velocity at which software is delivered will undoubtedly shift as AI-based automation, intelligent, and low-code solutions continue to rise and streamline development processes.
Increasingly, DevOps teams will look to monitoring and observability tools to help them better understand, evaluate, and define the performance and functionality of applications.
Furthermore, DevOps teams will be compelled to think about achieving more with less, employing AI to bridge operation gaps and reduce risks given the current economic climate and talent shortages.
Given the benefits provided by AI solutions, CI/CD will be better equipped to produce quality software, predict flaws and vulnerabilities as well as provide reports and remediate issues faster than before.
Because developers need real-time information about application attacks and threats, DevOps security must stay caught up to the CI/CD process of the future.
Collecting and analyzing software log data will make it possible to determine app features that malicious actors seek to exploit. Data-driven DevSecOps will progressively help teams comprehend what cybercriminals are doing to their apps and be able to decide which security safeguards to include in their upcoming releases.
It will be critical for high-performing dev teams to implement automated solutions incorporating app security safeguards through data-driven DevSecOps from within the CI/CD pipeline.
Rise of Platform Engineering
Historically, IT has used a top-down approach to deciding organizational development tools and resources. In 2023 and beyond, IT and developers will forge closer ties through platform engineering —the discipline of designing and building toolchains and workflows that enable self-service capabilities for software engineering organizations in the cloud-native era.
Developers will be able to tell IT the tools they want to use, and IT will be able to fulfill their demands smoothly, thanks to platform engineering. This will help free up developers, so they focus less on infrastructure maintenance and more on software development, increasing business productivity and value.
Cloud Native CI/CD and Distributed Frameworks
With the popularity of cloud-based solutions, CI/CD has become the focal point of an ongoing effort for application modernization using microservices and container orchestrators.
However, most CI/CD tools aren’t built, especially for Kubernetes and the cloud-native environment.
So, as more workloads turn cloud-native, so will CI/CD systems of the future. Organizations aiming to build fast cloud-native CI/CD pipelines will employ frameworks like AgroCD and Tekton that run natively on Kubernetes.
AI and ML will also aid businesses with harmonizing metrics with business CI/CD goals, driving suitable data-driven actions with visibility into the CI/CD pipeline, and providing new insights into software release quality.