It’s easy to lose your way when building an Agile roadmap.

If you get too detailed with your planning, you end up building a roadmap that is Agile in name alone but looks more like a traditional Waterfall roadmap. If you don’t perform enough planning, then you’ll produce a skeleton of a roadmap that sends you running in multiple directions without ever arriving anywhere meaningful. 

The correct approach lies somewhere in the middle. You keep things loose, nimble, and iterative but you also set a beacon that will guide each of your sprints to an impactful destination.

From our experience, one “beacon” that will keep your Agile product roadmap grounded, and your products moving in the right direction, is a simple function— the feature flag.

It isn’t fancy. It isn’t flashy. And it doesn’t look overly strategic. If you use feature flags properly, then they will keep your Agile roadmap focused on the outcomes that matter most without forcing you down a fixed path. Here’s why. 

First principles: The real benefit of Agile over Waterfall

It feels like a given these days: if you work as a Product Manager (especially in the tech sector) then you’re going to follow some kind of Agile methodology. Depending on your work history, you may never have worked with a Waterfall roadmap, let alone developed one, in your entire career.    

If that’s the case, it might even feel confusing why Waterfall was ever developed. The methodology is slow. It’s rigid. It’s opaque. On the surface, it looks inferior to Agile in every way. But once you dig into it a little, there is one area where waterfall trumps Agile. Waterfall is a better fit within a traditional corporate context than Agile.

While Agile and Waterfall are popular in software development, each one is best suited for different types of projects. 

For example, a Waterfall approach makes sense when a software project has clearly defined requirements with low probability that any changes will occur halfway through.

Waterfall fits really well into that broader corporate world’s standard operating procedures. It collects business requirements in a standard one-off phase and then sets them in stone with a concrete project. Waterfall adopts a more linear way of working so that development phases flow in one direction just like the flow of a waterfall, hence the name and tends to occur over a long period of time. 

It breaks that project into a clear, crisply defined plan and each step must be completed before moving onto the next phase. In the end, the project’s success will be defined by how well its leaders completed the milestones in the project’s plan, and if they delivered to the project’s requirements on-time and on-budget.

Waterfall methodology isn’t really about trying to create the most effective, efficient, or accountable system. It’s about having the product developers and managers operate in a way that makes sense to a large, lumbering corporation.  

A new approach—Agile— was only possible because it was developed outside of this legacy corporate context. In fact, Agile is an iterative approach that came about as a response and alternative to Waterfall’s rigid and linear structure. 

And here’s what they came up with: product management would deliver a greater impact if it stopped lining up to what a corporation wanted, and if it instead lined up to what actual real-world users want.

In an Agile approach, which introduces flexibility, teams work on multiple phases at the same time with the goal to enable faster software delivery for the purpose of collecting customer feedback. It does this by breaking down the software development life cycle into sprints, which could last from one to four weeks, that include regular feedback loops.

Incremental releases means teams can build better features much quicker that offer more value and optimize and iterate these features based on the feedback received. It aligns the product not only with the product vision but also with customer needs.

This is the real innovation of an Agile roadmap over a Waterfall one. It isn’t the increased speed & efficiency that everyone fixates on. It’s the simple but powerful fact that an Agile roadmap re-aligns the product manager’s focus onto the user. 

Here are some of the advantages of an Agile methodology:

• Faster feedback loops
• Higher customer satisfaction
• Reduced time-to-market
• Increased flexibility with more room for innovation
• Enhanced productivity by breaking down projects into smaller, more manageable chunks

And most of Agile methodology’s core user-alignment activities occur during Feature Release Management and are brought to life by the right feature flag tool.  

A quick caveat: Yes, business impact still matters in Agile

Before we move on, let’s make one point very clear.

When we say Waterfall aligns well to corporate context, we mean corporate operational context. But we don’t mean a Waterfall approach offers the best way to deliver results. 

Most often, these big Waterfall projects deliver poor results because they can take months—or even years—between their initial requirements collection and their project’s completion. During this time, the project’s alignment, and even its viability to its users, often shifts, reducing its chances of producing any meaningful business impact. 

By contrast, a properly developed and managed Agile roadmap will maintain alignment with its users throughout its entire lifecycle and deliver concrete, measurable, and accountable results. 

Feature release management, and feature flags, can also drive this tight connection between user-centered development and KPI improvement. We’ll get to how in just a minute.

Feature release management: The heart of any effective Agile roadmap

From a user-alignment perspective, feature releases are the key point that differentiates an Agile roadmap from a Waterfall roadmap.

Agile looks different from Waterfall in many areas of activity.

In Waterfall, new products and features are released to all users at once, in a single big bang, after a very long development cycle. In an Agile roadmap, new products and features can be—and should be—released at a much faster rate. 

This is the key functional difference that makes Agile more user-centered than Waterfall. Rapid and effective feature release management lets you:

• Keep your users top-of-mind at all times.
• Regularly collect your users’ data and feedback.
• Use up-to-date feedback to guide your development cycles.
• Repeat the cycle, to make sure you correctly incorporated user feedback in your next round of features and product updates.

If you want to keep your development user-centered then feature release management is critical to effectively incorporate into your Agile product roadmap. Here’s how.

The 5 key elements to include in your Agile release planning

Agile release planning is key to building customer-centric products by allowing you to prioritize and release product requirements as needed. In other words, it allows you to plan your product’s incremental releases- your features- and helps ensure your project is headed in the right direction and following the Agile methodology. 

It differs from a product roadmap in that release planning focuses on one sprint at a time (on short-term goals) while a product roadmap looks further ahead in the future and focuses on long-term objectives.

Put simply, the goal of a release plan is to help you prioritize features of your product and focus on releasing specific features in less time to improve the customer experience. Thus, teams use this kind of planning when they’re dividing a project into short sprints or increments instead of planning for one major product release. 

It is a unique approach to planning as it takes into account the flexible nature of software development by leaving room for any necessary adjustments as you go through the development lifecycle to incorporate customer (and stakeholder) feedback. 

The idea is to be open to prioritizing tasks to provide improved value to your customers.

Here are the key elements to include in each of your feature releases that will turn them into a critical, recurring touchpoint between you and your users.

1. User segmentation

At a basic level, you need to carefully select which user audiences you will first release (and test) new features and products to. 

At a deeper level, user segmentation can flow throughout every step of feature release management. You can personalize the experience of your new products and features to each segment you test them with. In other words, you try out different versions of each new product or feature with different segments. 

During testing, you can rapidly toggle features off for segments who are not responding well to them. And you can even guide the ongoing development of your products and features depending on which user segments respond the best to them.

2. KPIs measurement

However you measure product or feature success, you must quantify it, and measure those metrics in real-time during each release. 

Doing so serves two purposes: First, it gives you the ability to produce an accurate, objective measure about which products and features are succeeding with which segment (and whether or not you are actually improving their performance during each development sprint). 

Second, they let you demonstrate concrete, measurable, and accountable results for your business—to both report on the success of your most recent development, and to create meaningful justifications for more robust rollouts.

3. Governance

You need some formalized way to make decisions off the data that you produce. When do you toggle a feature on or off and for who? When do you roll out the product or feature to new segments? When is a product or feature ready to deploy to your entire user community? 

To make these decisions, you must have established definitions for success (see “KPIs”), and defined procedures for monitoring and acting on release performance data both in real-time and during post-release recaps.

4. A/B testing

Any time you are segmenting audiences, testing multiple variations on products and features, and collecting copious amounts of real-world user data, then you are setting the stage for multiple A/B tests. 

By performing comprehensive A/B tests during each of your feature releases, you will eliminate multiple developmental dead ends and narrow the list of viable “next steps” for your next sprint.

5. Automation

If you incorporate these four elements, then your feature release management process will get pretty complex, pretty quickly. But if you select the right tool to automate as many of these elements and their internal processes,as possible, then you can let go of most operational elements. Afterwards, you would simply sit back during feature releases and focus on making informed decisions before, during, and after each of your releases.

By incorporating each of these five elements into your feature release process, you will ensure that each of these critical touch points brings you and keeps you as close as possible to your users.

And, thankfully, there is one single function that incorporates each of these elements and makes them a practical and effortless habit in your Agile roadmap— feature flags.

Bringing it all home: Feature flags

At their core, the goal of feature flags is to enable you to toggle features on or off, with a single click on your dashboard, without having to adjust your codebase. 

That may seem very basic at first glance but buried in this simplicity is a lot of depth, and a lot of room to easily deliver on each of the above elements of user-centered feature release management.

With the right feature flag tool, you can:

• Perform sophisticated real-time control over which user segments get new products and features.
• Attach core KPIs to your releases and immediately kill products and features that are not performing well while immediately expanding the release of those that are knocking it out of the park.
• Monitor your results (and take action) in real-time.
• Easily manage and act on complex A/B tests.
• Bundle feature flags in with a complete suite of feature release functionality to wrap the whole exercise up in a single, highly-automated platform.

We kept each of these functions in mind when we built our own Feature Flag function, and release management platform. 

If you’d like to take it for a test run and see how easy you can incorporate the core actions of Feature Flagging, feature release management, and user-centered Agile product management into your roadmap, drop us a line!

In modern software development, teams often have to prioritize speed and less than ideal solutions to put out products quickly to keep up with fast-changing consumer demands. 

Unfortunately, taking such shortcuts could have dire consequences in the form of heavy costs or technical debt that could take a toll on your code quality and your whole software development and delivery processes if left unattended.

In this article, we’ll explore what technical debt is, the causes and different types of technical debt as well as how to manage it, largely through the use of feature flags.

What is technical debt?

The term “technical debt” was first coined by Ward Cunningham, one of the authors of the Agile Manifesto, in the early 1990s. Since then, the term has gained momentum and is a serious issue that many tech teams today still struggle to manage properly.

His reason for its name is that technical debt bears direct correlations with financial debt. Software development teams can take shortcuts to satisfy immediate business requirements, but the debt plus accrued interest will have to be paid at a later stage.

Technical debt is the consequence of action taken by software development teams to expedite the delivery of a software application or specific feature which later needs to be refactored or redeveloped.

Put simply, technical debt refers to the build up of technical issues during software development due to a number of causes which we’ll discuss in the next section. 

If not attended to, technical debt can spiral out of control, resulting in the total breakdown of the software development and maintenance lifecycle.

Therefore, it is critical to ensure that DevOps and software development teams pay close attention to technical debt management and technical debt reduction methods.

Here are some warning signs to look out for:

• Buggy, difficult to maintain code
• Unstable production environments
• Bug fixes introduce more bugs
• Data inconsistency 
• Decreased development pace and bottlenecks 

What causes technical debt?

We can deduce that technical debt comes mainly as a result of delivering a release quickly at the expense of “perfect” code.

In other words, it often comes as a consequence of ineffective and inadequate practices to build software for a short-term benefit in the interest of saving time.

That is one major cause but it’s also more complex than that as technical debt can be due to a number of other reasons. 

Some causes behind technical debt include:

• Time pressure: Teams today are under great pressure to deliver releases quicker than ever before to remain competitive and meet consumer demands fast.
• Poor code: This could be due to a number of reasons including use of tools without proper documentation or training.
• Insufficient software testing: Lack of QA support or automated testing means a lot of bugs could remain in the code undetected which gives rise to technical debt.  
• Outdated technology: Over time, many technologies become obsolete and are no longer supported and could become a source of debt.
• Lack of skill: Teams can sometimes unknowingly incur debt because they lack the skills to write better code. For example, having junior developers working on building complex software beyond their skill and experience level is a sure way to accumulate debt fast.

Over time, all these factors could result in accumulation of debt that will need to be addressed. The real danger is not actually having the debt in the first place- as often that’s inevitable- but it’s allowing this debt to build up with no plan or strategy to pay it off in the future. 

Types of technical debt

There are many ways to classify technical debt. One of the most popular ways comes from Martin Fowler’s technical debt quadrant.

The quadrant is based on the idea of not whether something should be considered debt per se but rather whether this debt can be considered prudent.

What does this mean exactly? Think of it as a way of answering the question of whether all technical debt is bad and the answer, according to the quadrant, would be “it depends.”

Martin Fowler’s technical debt quadrant seeks to categorize the types of technical debt according to intent and context.

Generally speaking, there are two overarching types of technical debt: intentional and unintentional (deliberate vs inadvertent).

Intentional technical debt occurs when software development teams choose to leave their code as it is, without refactoring or improving it, to reduce the time-to-market metrics. In other words, they choose to incur technical debt.

Unintentional technical debt, for its part, occurs when poor code is written and so the code quality will need to be improved over time.

Suffice to say, as soon as these technical debt-causing issues are highlighted, it is imperative to fix them as quickly as possible.

Let’s take a closer look at the 4 main types of technical debt, according to Martin Fowler:

• Reckless/deliberate: Teams possess the knowledge to carry out the task but decide to go for a “quick and poor quality” solution to save time and for quick implementation.
• Prudent/deliberate: Teams are aware of the debt they’re taking on but decide that the payoff for an earlier release exceeds the costs. However, in this scenario unlike the above, teams have a plan on how to deal with the repercussions of taking on this debt.
• Reckless/inadvertent: This is arguably the least desired form of debt where teams don’t have enough experience and blindly implement a solution without applying best practices. As a result, they’re unconscious of the fact that technical debt is being accumulated. Thus, no real plan to address this debt can be formulated.
• Prudent/inadvertent: This occurs when teams apply best practices during software development but still accumulate debt due to unexpected coding mistakes. Thus, this type of debt is unintentional. Teams have the necessary skill and knowledge to identify and pay off the debt but the experience serves as a learning opportunity for developers to optimize and improve the code for future projects.

When it comes down to it, deciding what to classify as technical debt is not always black or white. It requires putting things into context first. This is especially important when you think of the pressure on teams to put out products quickly to meet consumer and market demands. 

This means that they will constantly have to deal with the dilemma between taking on technical debt or delaying a release. However, it’s more of a matter of how to deal with and manage this debt rather than avoiding it completely- which may not always be possible- to minimize negative impact as much as possible.

Types of technical debt to avoid

At this juncture, it is reasonable to conclude that teams should avoid technical debt. Additionally, it is imperative to minimize and eliminate tech debt, particularly reckless and deliberate code debt.

Over time, technical debt could become too expensive to fix the longer it remains unfixed as “interest” builds up the same way that financial debt accrues interest. Eventually, technical debt can lead to a code becoming harder to maintain as the foundation of the codebase deteriorates. This will ultimately result in lower-quality products with the company reputation taking a major hit. 

Prudent tech debt is the partial exception to this rule. This form of code debt can benefit software development organizations as part of the reducing time-to-value methodology. 

In other words, the advantages of delivering a product to market as soon as possible can outweigh the cost incurred by technical debt. However, it is critical to monitor the tech debt to ensure that its value does not spiral out of control, negating the benefits of the reduced time-to-value exercise.

How feature flags can help with technical debt

Feature flags can help reduce the technical debt accumulated during the development, testing, and deployment of a software application.

However, if feature flags are not monitored and maintained, they can increase the application’s technical debt. 

Before we look at how feature flags reduce technical debt, let’s take a quick look at what a feature flag is:

“Feature toggles [feature flags] are among the most powerful methods to support continuous integration and continuous delivery (CI/CD)… [They] are a method for modifying features at runtime without modifying code.”

One of the most common sources of technical debt is the pressure to release a version of the software application.

The business demands that the software be deployed, and they don’t care how the developers make it happen. Feature flags are a valuable tool to help manage the “pressure-cooker” release environment.

There are several benefits to the use of feature flags as a software release and deployment aid, including:

• The risk of deploying a bug-ridden application is substantially reduced. Developers can simply switch off features that are not yet complete or thoroughly tested.
• By implementing a CI/CD methodology (continuous integration/continuous delivery), developers can often use feature flags to deploy new features without waiting for the next release to be deployed. In summary, this functionality reduces the time-to-value and increases customer satisfaction: A win-win for all.
• Implementing feature flags is also a means to negotiate with management about which functionality to complete before specified deadline dates, increasing the flexibility to develop and test features thoroughly before deploying them.

In summary, feature flags help manage and reduce technical debt by helping software development teams manage the development/testing/deployment lifecycle more effectively.

Feature flags are useful for dark launching, a practice of releasing specific features to a subset of your user base to determine what the response is to a new feature or set of new features. As an aside, this is also known as a canary deployment or canary testing.

Testing in production is another form of dark launching. By utilizing this option, you can assess the application’s health, collect real-world app usage metrics, and validate that the software application delivers what your customers want.

Feature flags can also create technical debt. While they play a significant role in mitigating technical debt in all other areas of the software development lifecycle, implementing them is usually via a set of complex if-else statements.

Therefore, in practice, a feature flag is an if statement defining the path between at least two different code paths depending on one or more conditions.

The following simple scenario describes how to implement feature flags.

Let’s assume that an e-commerce site offers free shipping for all customers that spend more than a specified minimum amount at one time.

This code sample is an example of a feature flag. If the total amount paid is more than $50, then the shipping is free. Otherwise, the shipping amount is the amount spent multiplied by the rate (a percentage of the total amount).

def ShippingYN(amt, rate) :
  if amt > 50.0 :
    shipping = 0.0
  else :
    shipping = amount * rate

  return shipping

 

Best practices using feature flags to avoid technical debt

As with all aspects of software development and deployment, it is vital to observe the following feature flag best practices:

1. Feature flag management

As your organization matures in its use of feature flags as an integral part of the software development/testing/deployment lifecycle, it is vital to be mindful of the fact that some of the feature flags are short-term and should be removed; otherwise, they will add to the application’s complexity, resulting in more technical debt. 

Consequently, it is imperative to have a plan in place to remove the flags before even setting them. 

It is also possible, and a good idea, to track and measure different metrics for each feature flag, such as how long it has been active, its states (on/off), different configurations, and how many code iterations it has been through.

Once your feature flag has been through the required number of iterations to code and test a feature, this flag must be removed and the code merged into your code repository. 

Note: Before removing a feature flag, it is a good idea to evaluate its function and purpose; otherwise, there is a risk, albeit slight, that the flag might still be needed and is erroneously removed. 

A vital part of the feature flag management process is to define and implement temporary and permanent flags.

1.1 Temporary feature flags

As highlighted above, if a feature is designed to be rolled out to every application user or you are using the feature as a short-term experiment, it is critical to attach a monitoring ticket to this flag to make sure it is removed once the feature has been deployed or the experiment is concluded. 

Examples of these temporary flags which can last weeks, months, or even quarters, include:

• Performance experiments: A performance experiment is similar to A/B testing, where two versions of the feature are deployed with the idea of determining which one performs better. A/B testing employs the same construct in that it deploys two versions of an element to the application’s user base to select which one users prefer. 

• Painted-door experiments: These experiments are only used in the early phases of the software development lifecycle and are User-Interface mock-ups to determine any customer interest. Once the consumer interest has been determined, these flags can be removed.

• Large-scale code refactoring: It is a good idea to deploy code refactoring changes behind a feature flag until you are positive that the functionality has not been changed or broken. Once the refactoring exercise is complete, you can remove these feature flags.

1.2 Permanent feature flags

Permanent feature flags are used to implement different features or functionality for different groups of users.

As a result, it is reasonable to assume that these flags will remain in the software application indefinitely or at least for a very long time.

Therefore, it is vital to ensure that they are monitored, documented, and reviewed regularly. As with the temporary flags, there are several different types, including:

• Permission flags: These feature flags are helpful when your product has different permission levels, such as the ability to create journal entries in an online financial general ledger or whether users can view a list of these entries. A second use case for these flags is your SaaS application has different subscription models like Basic, Professional, and Enterprise.
• Promotional flags: These flags help implement regular promotions. For instance, let’s assume your e-commerce store offers a Mother’s Day promotion every year where specific products bought include the shipping costs.
• Configuration-based software flags: Any software driven by config files will benefit from using feature flags to implement the different possible configurations. A typical use case for config flags is the layout of the User Interface.
• Operational flags: These feature flags help manage a distributed cloud-based application. For example, additional compute engines can be spun up when the workload reaches a specific level.

2. Use a central code repository

Feature flags or toggles are most commonly stored in config files.

Another option is to keep them in a database table. However, let’s look at how to manage these config files. Large systems can have many if not hundreds of feature flag settings. Apart from using a database table, the only way to manage these settings is to store them in config files.

The best way to maintain the config files is to upload these files to a feature flag library in a central code repository like Git.

Not only is Git good for keeping control of these files, but it is also a valuable version control system. Developers can use it to create feature branches of config files used during the software development process without negatively affecting the production version of these files.

Once the config files have been updated and tested, they can be merged back into the Git master branch using a merge request.

3. Adhere to naming conventions

It is absolutely critical to give your flags intuitive, easy-to-understand names, especially for long-term flags, although it is a good idea to include short-term flags in this best practice.

Naming the feature flags, flag 1, flag 2… flag 100 will not help people who have to work with these flags in the future.

A good example of wisely named feature flags can be found in the scenario highlighted above.

It is reasonable to assume that the flag, AdvancedSearchYN, is one of hundreds of flags used in our eCommerce application. Even if they are the only two flags used, it is still advisable to give them intuitive, related names.

For more details on the best way to manage feature flags to keep technical debt at bay, download our feature flag best practices e-book.

4. Use a feature management system

Using a dedicated feature flagging system is a great way to manage flags in your code so you don’t find yourself with piles of technical debt from unused or stale flags.

AB Tasty’s server-side feature enables you to remotely manage feature flags and take control over how, when and to who features are deployed to mitigate risk while optimizing user experience.

To help with technical debt management, AB Tasty provides dedicated features to keep control over your feature flags. Two of them are especially useful in this regard:

• The Flag Tracking dashboard lists all flags setup in the platform, with their current values (ex: on/off) and campaigns that reference them. This way, you can easily keep track of every single flag purpose (ex: flag 1 is used in progressive rollout campaign X, while flag 2 is used in feature experiment Y). When you manage hundreds of flags, it turns out to be a real time saver.
• The Code Analyzer is an advanced Git integration to see where your flags are used in your repository. In conjunction with the flag tracking dashboard, you can quickly find flags in your code that are not referenced in any campaigns. It also deeply integrates with your current CI/CD pipeline. As a CLI and a Docker image, it analyzes your codebase and detects the usage of flags everytime code is pushed to a specific branch or tag. This way, your flag dashboard is always in sync with your codebase. On one hand, you can safely remove flags if they are not referenced in campaigns, and on the other hand you make sure that flags your campaign is relying on are indeed available in your code. View code on Github.

Try it for free!

Final thoughts

As described throughout this article, feature flags in DevOps and software development play a fundamental role in managing and reducing technical debt.

Consequently, it is vital to implement a feature flags framework as a foundational part of the software development lifecycle.

Cobbling it on afterward can increase the risk of incurring more technical debt, especially once the system grows in scale. Thus, these feature flags must be carefully maintained and monitored to ensure that they don’t amass additional technical debt.

Finally, it is essential to be mindful that, while technical debt is primarily seen as a negative, there are instances, as described by Martin Fowler’s technical debt quadrant, where incurring prudent and deliberate tech debt can be beneficial.

It is also worth noting that both Agile and Scrum use the concept of technical debt in a positive way to reduce the time-to-value of a new application or feature release, driving sustainable growth through customer satisfaction.