For some years now, the “everything as code” model has been establishing itself as the standard practice among software development companies. That’s because these businesses are now seeing that using these external assets and resources to automate tasks, streamline processes, and avoid maintenance activities is the best way to increase their flexibility and achieve resilience.
What Is Everything As Code
In a nutshell, the “everything as code” model means that many aspects of the development process are treated as code, from infrastructure to policies to data and beyond. This approach has the goal of improving efficiency, standardizing practices, increasing scalability, and minimizing errors, as well as aiding agility.
With their adoption of “as code” approaches, software companies leverage a practice that enables them to use code-based configuration files to make certain tasks more efficient and improve processes across the software delivery pipeline. The “as code” approach seeks to automate different tasks within the software development lifecycle, from infrastructure provisioning (probably the most widely known “as code” solution) to deployment pipelines.
What Are “The Everything As” Code Benefits?
The “as code” model can really streamline a software development project, relieving developers from rote or boring tasks, reducing overall time to market, and decreasing costs, among other benefits. That’s why it’s important for development teams and software engineers to know the “as code” models reshaping the sector since they are changing how these teams and individuals work.
Using the “Everything as Code” method has a number of advantages:
- Automation: You can automate different jobs and processes by writing everything as code. This makes things run more smoothly and makes mistakes less likely. Automation also makes deploys, scaling, and setting up tools faster and more reliable.
- Version control: When you treat infrastructure, settings, and operations like code, you can use version control systems (like Git) to keep track of changes, work with other people, and go back to older versions if you need to. This makes it easy to find out where something came from, helps people work together better, and makes fixing easier.
- Reproducibility: Since everything is written down in code, it’s easy to copy and paste whole environments, settings, and deploys. This is especially helpful when setting up platforms for development, testing, or production, as it ensures stability and gets rid of setup mistakes made by hand.
- Consistency and standardization: When you use code to describe and handle resources, you make sure that they are the same in all environments and deployments. This lowers configuration drift, makes sure best practises are followed, and improves the general security of the system.
- Scalability and flexibility: Infrastructure and operations that are built on code are both scalable and flexible by nature. It becomes easy to add more resources, grow or shrink, and react to changing needs. When infrastructure can be defined by code, systems can be more flexible and changeable.
- Collaboration and sharing of knowledge: putting everything into code makes it easier for teams to work together. Developers, operations, and other partners can work together, share code, look over changes, and give comments. This encourages a mindset of working together and sharing information, which boosts total productivity.
- Infrastructure as Code: is a subset of Everything as Code, provides additional benefits. IaC enables infrastructure provisioning and configuration using code, making infrastructure changes easier to manage and document. It also allows for the use of infrastructure testing, which aids in the identification of issues prior to deployment and assures the dependability of infrastructure improvements.
Overall, the “Everything as Code” method has many benefits, such as automation, version control, repeatability, uniformity, scalability, freedom, teamwork, and sharing of knowledge. These benefits help make software creation and release faster, more reliable, and easier to handle. That’s why we wanted to review 3 of the “as code” approaches that are getting more and more attention in 2023 and which are on the path to becoming industry standards.
#1 Data as Code
As we move deeper and deeper into the age of data, a lot of people are starting to wonder how we can better use the insane amount of information available to us. Big data platforms and methodologies have helped us clean, refine, and sift through vast data sets, but we still need it to be more manageable, more flexible, and more convenient to use. In other words, we need data capable of moving around in different environments, ensuring immediate availability and shareability.
In the current DevOps-centric landscape, sharing data between different teams, colleagues, and systems is often a manual activity that requires DevOps experts to grant access and ensure the availability of data to everyone that might need it. That’s far from being ideal.
That’s why data as code is such a good approach: because it allows companies to automate the continuous integration and deployment of data pipelines, making data available through different clouds and workspaces. It’s like what happens with code when developers are working on it.
That’s precisely what the data-as-code approach is here to do. Through it, teams can process, manage, use, and share data easily. The ultimate goal is to accelerate the development of iterations while increasing collaboration and tearing down the request-and-wait flow of current processes.
So, data as code pushes us to treat data in the same way we treat code. This means using the same best practices we use in software development but applied to data and all its related processes: versioning, automated testing, CI, and more, with the ultimate goal of delivering relevant and updated data fast.
Doing so requires a mindset shift that stops treating data as if it were an immutable asset and starts seeing it as a dynamic resource that needs to be everywhere, at all times. Some experts and enthusiasts are already proposing principles and paths to explore when moving forward but it definitely feels like data as code is about to take off during 2023.
#2 Software Intelligence As Code
The importance of software in today’s world is impossible to understate. Basically, digital tools are essential for most of our daily activities, from work to entertainment and beyond. That’s why companies developing them are pushing development teams to provide better and more sophisticated solutions: the race to offer the best tech apps is on.
That pressure leads developers (and the entire team, to be honest) to start considering aspects that go beyond the code itself. Scalability, security, and observability are but a few of those aspects. To guarantee that, software engineers need to improve their development processes, reducing complexities without harming the quality of the end products. It’s a tricky task.
That’s when software intelligence as code comes in. Behind that name hides a process through which the best practices for developing, testing, delivering, and managing software intelligence get coded into the software code itself. Using dependencies, libraries, classes, and functions through API connections, software intelligence as code can easily extend the best practices for syntax, configuration, and architecture, guaranteeing easy deployment across environments.
The idea is for teams to use those connections to bring sophisticated and well-developed software intelligence capabilities into the applications the developers are working on. Integrating software intelligence as code resources into the development process, engineers can automate configurations, implement corrective actions to ensure service-level objectives, and lay down the foundations for scalability and observability.
Ultimately, what software intelligence as code is after is providing an easy way to develop applications in a smart way. It does so by removing obstacles, streamlining the use of best practices, and providing additional capabilities across environments in no time.
#3 Policy As Code
If software intelligence allows developers to automate the implementation of best practices, then policy as code is the best way to automatically enforce development policies. The idea behind policy as code is to provide code written in a high-level language to control, manage, and automate policies across the entire application development cycle.
Using this approach, development teams can reduce the number of potential mistakes due to human errors. That’s because the code itself (rather than an individual or team) is the one enforcing the policies and their related rules and conditions. While that might sound a lot like what software intelligence as code can do, the reality is that policy as code is mostly about compliance and security while software intelligence as code extends beyond that.
Automating the enforcement of policies is key to achieving a more efficient, visible, and faster software development life cycle. That’s not all: policy as code increases the collaboration capabilities of a team, as it provides a uniform means to manage policies that anyone can quickly understand and implement.
Another thing about policy as code is that there are several tools that natively support it, even to the point of specializing in specific policy fields. For instance, there are services to apply policy as code for security, deployment, and even software versioning. And while there are certain frameworks that are trying to encompass it all, the reality is that they haven’t beaten the abilities of native support.
Challenges
While the as-code model offers numerous advantages, there are still some challenges associated with it.
For example, the model is somewhat complex and requires experts to minimize the risk of error. The learning curve is steep, and even knowledgeable professionals may need training and education to improve their skills. Additionally, the approach means that software requires maintenance and upkeep to keep it up to date with the times and trends in the field. Moreover, your organization will need to integrate the systems and components with the others you use in-house.
Everything As Code, Deconstructed
While reading here, you might get the impression that the safest bet is to use an everything-as-code approach and avoid using separate models. It’s reasonable. However, everything as code is more of a general approach that, while it might serve to encompass some of these models, still needs further definitions.
Using the approaches above can get you closer to more precise definitions of how you use as-code approaches. They help you manage the as-code model with more granularity, giving you more control over your entire software development life cycle but offering you the possibility of working with different approaches in tune and with no integration issues.
That’s why we’re saying that these “as code” approaches are reshaping software development: because they give teams the ability to manage their operations better, streamlining the whole workflow. That’s a major advantage right there, something that will definitely change the development sector for the better.
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