What do you do if you're a software designer trying to innovate while maintaining system stability?

Easy: 1. keep your innovations separate from the production system 2. test, test, and test 3. be prepared for your boss saying, "Innovation isn't part of your job specification."

Opt for incremental change if innovation is deemed necessary. Introduce new technologies gradually to maintain stability while progressing. Start with a small module or feature and expand as confidence and expertise grow. This approach allows testing without full commitment and offers a safety net for unforeseen challenges.

Break system into smaller, manageable modules. This allows you to innovate within specific components without risking the stability of the entire system. Invest in comprehensive testing strategies, including unit tests, integration tests, and regression tests. Maintain strict version control practices to track changes to your software over time. This makes it easier to identify the source of stability issues and roll back changes if necessary. Establish a feedback loop with your users to gather input on new features and identify any stability issues early on. By incorporating these strategies into your software design process, you can foster innovation while ensuring the stability and reliability of your system.

I would like to breakdown the system in the module, Then implement my innovations, Understanding that innovation doesn't always mean throwing out the old system entirely. It's about finding ways to improve upon existing processes while maintaining stability. I will take the feedback of impact is it positive or negative.

Balancing innovation with system stability is a common challenge for software designers and engineers. Here's how you can navigate this situation effectively - Establish Clear Goals - Incremental Change - Testing and Validation - Feedback on feature adoption At the end, I will avoid over engineering that is very common in software industry.

The key to writing object oriented code that will outlast you, is to deeply embrace loose coupling and high cohesion. This style of code leads to modularity and enables testability. Each module should implement an interface that defines its contract. The interface is ideally as small as reasonable to enable the desired functionality. The module (in its implementation) should avoid instantiating objects that it depends on, and instead look to have interfaces to those objects passed in so that they can be mocked, thus enabling true unit testability.

Embrace Modularity is very important in software designing. When we separate responsibilities module wise then software becomes easy to maintain and parallelly innovate. With modularity there is always a clear separation and allows to make changes in software at any level while innovating. When following microservices and API, at any point of time it is easy to innovate/ design new feature as well as maintaining the existing software without affecting it.

Feature flag is an established way to rollout new functionality or code changes to production by providing a switch which enables us to switch to previous implementation. This is very useful to safeguard in any escaped defects to production and also helps in rolling-out the functionality gradually when needed. It can be applied for both backend changes that are not transparent to end users or UI changes which user can see them selves. Feature toggle is also great for prototyping new functionality which might not be complete and running it by customer/stake holders for acceptance. It helps in getting early feedback for features from specific set of users without effecting others.

Implement feature flags to control the rollout of new features to a specific user group or percentage of users. This allows for testing and gathering feedback on new features before a full release, minimizing risk while enabling innovation.

On a similar concept, a backed system can innovate using the shadow code paths. Feature flags are like toggle switches to run either code path A or code path B. Shadow code path is like executing the things in parallel but not affecting the main path. Monitor and measure the performance of the shadow path by logging the required comparison data. If the shadow path results are better than the main path the flip the path and clean up the main path. This can be done using feature flags. This is a convenient way for evaluating performance enhancements without affecting the live traffic.

Feature flags provide the following benefits: 1. Gradual Rollouts: We can gradually introduce new features to a subset of users using feature flags. 2. Risk Mitigation: Feature flags allow us to reduce the risks of introducing new functionality by simply turning off features that may cause instability or problems. 3. Real-time Control: Feature flags provide real-time control over feature availability. For example, introducing a new payment processing feature can be restricted by a feature flag and initially available only to internal testers. Based on feedback, adjustments are made before a broader release, ensuring a stable and well-received update when fully launched.

If you develop your software with modular feature set, you can enable/disable any feature based ont customer requirement and you can sell it as an addon. This modular architecture helps you to not maintain whole code you can work on only required module. To gain this benefit you should gave beautiful architectural design to see big picture.

Most positives already mentioned, but will add making the flag database driven allows better control across widely distributed applications.

Feature flag is really handy when experimenting and also saves one in case of failures/fallback. I prefer to derive value/user feedbacks before spending efforts if at all there is an option. Sometimes there are performance values/modular/stability benefits with this as well where its useful. Invoking this as well via different means is useful ex. Config/api's driven etc.

Feature Flags are useful only in one module / software binary. If there are multiple softwares running on different systems (like client calling APIs), the feature flag on both sides will be difficult to keep coherent Versioning software and sending the software version in APIs also helps. This is like sending the feature flag to other software components that interact

The only sustainable way to move fast with the development is to avoid manual steps. It requires investing time in writing automated test for your app. This saves you from introducing regressions and manual testing. Automated integration tests is one of the acceptance criterias. Any application feature does not exist, unless one can show tests, proving that it works.

For me, the best and fastest way to innovate is when test cover my back. Having a good automation tests encourage me and my team to always strive to refractor the code constantly while not worry about stability

Automated Testing helps in executing set of tests effectively which saves a lot of time and helps in producing more quality softwares. Automated tests should be part of the development plan. From my experience I have found the following areas where it plays a crucial role. 1) Browser testing, we can run the same tests tar getting different browsers different versions/env etc. 2) Integration testing which is always challenging and with code changes automation testing helps in findings issue early. 3)Refactoring code, if we want to refactor an existing code and want to make sure it does not cause any regression issues automation testing is very helpful 4)Performance improvement related changes can also easily traced by automated tests.

New innovations that break established conventions should be detected automatically. In this way you as a developer need not worry about introducing breaking changes and can focus on the innovating part of things.

Automated testing in the frontend is essential for maintaining software stability and quality. It involves writing tests for the code that run automatically, verifying that new features do not negatively impact existing functionality. These tests act as a safety net when introducing changes, thoroughly reviewing the code to detect issues in the early stages of development. There are various types of tests, such as unit, integration, and UI tests, that ensure components and functionalities behave as expected, allowing developers to make changes with confidence.

Automate testing also helps in early bug detection, while feature development and test automation script are in parallel development mode, it is possible to detect the defect in the early stage. Early-stage bug detection is also less costly rather than fixing in the later stage.

Automated testing helps though when introducing new features, we need to sure good coverage of new code paths. This is possible with code coverage for unit tests and integrated tests

Develop a robust suite of automated tests that run with each build or deployment. This includes unit tests, integration tests, and end-to-end tests. Automated testing helps ensure that new features do not break existing functionality.

Continuous integration tests are required periodically across various software modules as well as end to end tests We also need load and stress tests, performance tests to be run on periodic basis

Continuous integration, when paired with great automated testing and results monitoring, is an excellent way to keep software at high quality. Automated testing that causes the CI process to fail if the tests fail, ensures that software continues to work as new changes are merged in. Having sufficient code coverage (>75%) is also required to make sure that the tests are providing significant results. Pass/fail tests are not sufficient by themselves, performance and stress tests that give results which can be monitored over time, also provide a measure of code health.

Continuous integration is a right way to maintain the system stability, especially if several software developers are involved in one project. Of course a rigorous testing is required after any such code change! This testing can be automatic, but very often the specific test cases are required - it depends how reliable is the automatic testing.

Utilize CI/CD pipelines to automate the testing and deployment processes. This helps catch issues early and reduces the manual overhead of deploying new changes.

Make it a habit—every time you add new functionality, develop a set of key metrics to track: - Whether your functionality has been activated at all (for example, payments are actually going through the new gateway). - Whether the outcome of its activation meets expectations (payments are completed successfully, within a reasonable time). - Performance (measured in terms of latency, throughput, etc.). In most cases, new changes should not affect the global trends of your application (for example, resource consumption should not increase by 20%, there should not be an unexpected drop in the volume of orders, and users should not start receiving negative responses from the system if such trends did not exist before).

Rather than pursuing radical changes all at once, teams can adopt an incremental approach to innovation. This allows for a steady stream of improvements and enhancements while minimizing the risks associated with major overhauls. By breaking down innovation into manageable steps, teams can maintain stability while gradually introducing new features and technologies.

Debuggability is an important aspects ot be considered in monitoring and logging, We should be able to trace using api ids's across various up stream / down stream calls

Establish channels for collecting user feedback on new features. This can guide further development and help prioritize bug fixes or adjustments based on actual user experiences.

Especially if you are in the startup, pay attention to what drives your business and those features has to always work. If you create new features, isolate them, test run with some known customers and then release to the user base. Always measure and monitor the impact of new feature, it will help you to set priorities right or at least identify problems early.

I call it the David Letterman top ten approach. For the sake of those who don’t know, David Letterman had a televised night time comedy show in the USA which featured his top ten monologue where he would critique or mock something in life or politics. So I usually suggest limit the change to say no more than ten items. About a third would be innovations, a third would be your market driven features and the final third would be customer service driven. The idea is to contain the extent of innovation with other needs to not have it dominate the effort, or be deferred either. There is only so much that can be done in a development cycle, so make a top ten punch list.

It has been my experience that balancing stability with innovation is more a _business_ question than technical. Getting the business to make their priorities clear, stability _or_ innovation, as opposed to expecting 100% investment in stability _and_ 100% in innovation, helps frame the whole effort. The transparency leads to breaking down work and establishing clear shared priorities and milestones. The the technical choices can be made: evolution versus revolution, new architecture versus enhancing what you have and so forth.

Balancing innovation with stability is perhaps a nonproductive way of thinking about the trade-off. It implies that innovation produces instability. If that's true, you may be doing innovation all wrong. When you do "innovation", you don't do it for fun. You do it because there is a business reason. Reasons could include increasing engineering velocity or system stability. So, when I tackle this trade-off, I focus the analysis on how I can move the trade-off curve higher and get the best of both innovation and stability. Doing this requires that your software development process follows all the usual engineering best practices so you can introduce innovation safely, and there are extensive resources on that subject.

Gradually roll out changes to a small percentage of users to ensure stability before a full deployment. Canary releases and blue/green deployments allow you to monitor performance and revert back if necessary.

Is it better than prod? This is the ONLY heuristic that truly matters. Everything else borders on overthinking and fear-based decision making. If you don't have data to inform your decision making, change that immediately. If you don't have confidence in risk mitigation when making changes, add enough test coverage to get to the point where you can ship more often. When all else fails, ask yourself, "Is it better than prod?" If the team is in agreement and the risk/reward balance is tolerable, send it!

Innovation is perhaps a bit misleading in this context. All the techniques mentioned here apply to any *changes* one would make to a system. To make changes safely, including "innovation" we have at our disposal a large variety of tools. At the most basic level, we need to be able to safely make changes to our code and deploy them to production with a basic set of quality controls (versioning, tests, linters, CI/CD, etc.). A level up from there, we need systems in place to monitor the production code (logs, dashboards, exceptions, alerts, on-call processes, etc.) Finally, we need to be able to manage complexity as our systems grow (team structure, architecture, couple and cohesion, domain modeling, etc.)