An organization’s technical debt grows when it opts for a short-term solution instead of an overall solution that would take longer to implement. Technical debt is a term used in the DevOps vocabulary to refer to the mistakes made by software development teams during the course of the project and the lack of follow-up.
DevOps adoption has led to a surge for debt that must be addressed.
Inadequate code, out-of-date architecture, shoddy infrastructure, and slack development practices are all causes of technical debt. It is difficult to update or add new code until the development process stalls because of the accumulation of cruft.
What is Technical Debt?
Technological debt is the accumulation of poor technical decisions made over the course of an application’s lifecycle. Things get more and more difficult to change as time goes on, and this is what causes IT projects to grind to a standstill.
Poor state management in an application, for example, might make horizontal scaling difficult. Rewriting the state management section of the code is required before you can horizontally extend your application in order to handle increased traffic. You might think of technical debt as the amount of time it takes to perform what is necessary in order to get to what you want.
Not only may technical debt emerge during the development process, but it can also exist during daily operations. Windows Server 2008 or Ubuntu 11.04 are no longer supported operating systems. That is a form of technical debt. Leaving your servers open to cyber-attack and ransomware by not keeping them patched and up to date? No doubt about that.
How can DevOps tackle the problem of technical debt?
- Create product teams for DevOps
Small, interdisciplinary teams (i.e., Dev + Ops) are a core element of DevOps, and they take responsibility for every stage of a product or service’s lifetime, from “inception to retirement.” These teams, especially product managers, have a strong desire to alleviate the burden of technical debt because it affects them on a day-to-day basis.
Identifying and tracking the quantity of technical debt in your products is the first step.
Work items (in Jira, Azure DevOps, or GitHub) might be labeled as “TechDebt” in order to keep track of the debt. For the next step, you need to schedule some time for technical debt items in each sprint’s backlog. At the very least, we recommend committing to at least 20% of a sprint.
Do a quick thumbs up/down (or planning poker) on the current amounts of technical debt within each team, then. You should prioritize additional payback work in the next sprint if you receive too many “thumbs down” (unacceptable levels). When your team is confident that technical debt is not an impediment to accomplishing your product’s objectives, keep on.
Finally, when developing new products, strive to avoid accruing greater technological debt. Use the technical debt quadrant to evaluate design decisions and minimize the amount of new debt that is created. Keep track of your technical debt and allocate effort to repay it in the future if you need to generate sensible, planned technological debt.
- With the help of Inner Source, you may create shared self-service platforms
Sharing self-service platforms to help product teams is becoming more commonplace in the workplace. These platforms alleviate the burden of building and maintaining a toolchain, hence reducing the risk of technical debt. An alternative is to have your teams use self-service platforms (e.g., internal or external SaaS-style solutions). In the next section, we will discuss containerization.
Platform teams to fulfill the demands of product teams build these services, along with best-practice templates, reference architectures, and other code building blocks.
There should be no “we and them” silos between platform providers and their customers in self-service systems. The development of platforms is a team effort. In order to do this, it is best to learn from the experience of huge open-source initiatives, which is known as “Inner Source.”
- Automate your DevOps processes to pay off your tech debt
Any DevOps strategy relies heavily on automation. Even the most prevalent DevOps paradigm has automation at its core — CALMS Culture, Automation, Lean, Measurement, Sharing. In many cases, automation would be used to build and administer the platforms outlined earlier. In addition, platforms frequently provide product teams with automated toolchains they may employ to speed up the development process.
Take environment management and look at how infrastructure and configuration may be used to pay off technical debt while preventing future debt from being accrued by the same system.
Snowflake environments, which are characterized by their inconsistency, are a common type of technical debt that almost everyone has encountered. Inconsistency is commonly to blame when your program functions properly in development but fails miserably in pre-or post-production. This can be found in a variety of places, such as the operating system’s configuration, an app’s dependencies, or any number of other configuration parameters the program makes use of. It is the time you spend resolving difficulties like these that add up to your technical debt.
Using infrastructure-as-code and configuration-as-code, you may explicitly define your desires for the environment. With the help of Terraform and Puppet, you can then (declaratively) “make it so” in every instance of that environment.
Technical debt can be paid back more quickly if you do not spend time troubleshooting deployments because of snowflake environment concerns. In this way, automation creates a ‘virtuous circle’.
As-code automation also has a secondary advantage. Instead of specifying configuration settings in lengthy Word documents or Visio diagrams, DevOps automation can be held and improved on in a repository like GitHub. As a result, anyone may readily find and use the code, as well as contribute to it via pull requests or even fork the source, updating and expanding it to match their own requirements. Automation code is less likely to go “out of date” because of this iterative capability, which means less technical debt.
- To make app deployment and management easier, consider using containers
Our explanation film about containers is an excellent place to get started learning about them. To put it succinctly, containers are lightweight bundles of your application’s settings and operating system dependencies that can be easily deployed and provisioned.
The portability of containers, like the environment management automation example stated before, makes things easier. Kubernetes and other container orchestration solutions go a step further, allowing DevOps teams to work on higher-value tasks while the containers are in production (like re-architecting applications to reduce technical debt).
Companies developing innovative, cloud-native apps to enhance adaptability and scalability while lowering the total cost of ownership (TCO) commonly use containers. Small, multidisciplinary DevOps product teams can benefit from the microservices architectural pattern, which works well with containers as well as containers. Small, well-defined contexts and long-term teams are the hallmarks of a microservices architecture. As a result, it’s easier to identify and fix the technical debt. Everyone wins in this situation.
- Building an API-centric model with DevOps
An API-centric application strategy can be implemented using the microservices model outlined above. If you do not use APIs to interact between your systems, Jeff Bezos will fire you.
It is possible that your company is not as strict as you think. However, encouraging teams to design and consume APIs with well-defined, versioned interfaces is an excellent strategy to reduce technical debt. Most of the time, technical debt can be generated by a lack of communication between different systems. Directly reading data from a table maintained by another team is an example. As a result, TeamB may unwittingly disrupt TeamA’s application by altering that table’s structure to match their own demands.
APIs make these interfaces more accessible and less susceptible to attack. In order to support “semantic versioning,” each product should adhere to an API that has been publicly released. A ‘breaking change’ in the API specification can be implemented by releasing a new major version of the API, which includes a pre-determined support period for the “old” API. As a result, there will be less technical debt because of this.
Code pipelines like those used in Continuous Integration and Continuous Deployment allow teams to move more quickly and with less risk while also reducing the amount of technical debt they have.
Traceability from user story to code commit to the released package is another benefit of using code pipelines. That means that technical debt is easier to track and control. You can witness the impact of technical debt on your customers and live systems if you have tracked and tagged it as discussed earlier. This helps prioritize technical debt payback activities based on client needs.
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