Maintaining a high-performance, scalable database requires careful planning and adherence to best practices. Whether you're managing schema design, database migrations, or compatibility checks, following a set of core principles can prevent common pitfalls and keep your database running smoothly. This post highlights essential do’s and don’ts for database management to guide you in making informed decisions. The Do’s of Database Management 1. DO Isolate Application Databases Isolating application databases provides flexibility and control over performance. When each application has its own dedicated database, schema changes can be implemented without impacting other applications, and resource usage is easier to monitor and optimize. Database isolation also improves security by limiting access to a single application, reducing the risk of data breaches. 2. DO Use Explicit Schemas for All Data Defining explicit schemas is critical for data integrity and maintainability. Explicit schemas specify data structure upfront, enabling validation as data is written. This approach minimizes data inconsistencies, making it easier for developers and analysts to interpret and analyze the data. Schemas also allow you to check for compatibility issues early on, helping maintain stable application performance. 3. DO Automate Schema Migrations Schema migrations are an inevitable part of database management, and automation reduces [...]

Refactoring is an essential part of maintaining a healthy codebase, but it doesn’t have to be an overwhelming process. The key is to refactor incrementally—making small, manageable changes over time rather than attempting to overhaul everything at once. Why incremental refactoring works: It reduces risk: Small changes are easier to test and less likely to introduce new bugs. If something does go wrong, it’s much easier to pinpoint the cause. It keeps the codebase stable: Large refactoring efforts can destabilize the entire system. By making incremental changes, you can improve the codebase without disrupting ongoing development. It’s more manageable: Developers are less likely to get overwhelmed by small, frequent changes than by a massive, time-consuming refactoring project. Best practices for incremental refactoring: Keep refactoring commits separate from feature commits. This ensures that your changes are easy to track and review. Refactor code in small, focused chunks. Tackle one method, class, or module at a time. Always leave the code cleaner than you found it. Even small improvements can make a big difference over time. Refactoring doesn’t have to be a monumental task. By making small, incremental changes, you can improve your codebase over time without the risk and disruption of [...]

When developers rewrite a system, they often try to fix everything that was wrong with the original version. This is a natural instinct, but it can lead to what Fred Brooks called “Second System Syndrome.” In The Mythical Man-Month, Brooks described how the second iteration of a system is often over-engineered, filled with unnecessary features and complexity. The original system, though imperfect, was simple and served its purpose. The second system, designed with the benefit of hindsight, often suffers from the desire to add too much. The result? A bloated, difficult-to-maintain codebase that doesn’t perform any better than the original. How to avoid Second System Syndrome: Keep it simple: Resist the urge to over-engineer the new system. Focus on solving the core problems and avoid adding extra features just because they seem useful. Test incrementally: Instead of rewriting the entire system at once, break it down into smaller components that can be tested and deployed incrementally. Don’t underestimate the cost: Rewriting an entire system is time-consuming and risky. Make sure that the potential benefits outweigh the costs before you commit to a rewrite. Remember, the goal of a rewrite is to improve the system, not to make it more complex. [...]

In the fast-moving world of software development, it’s easy to be tempted by the newest technologies. Every day, new tools, languages, and frameworks emerge, promising increased productivity and exciting new features. However, some of the most successful companies stick with “boring” technology—proven, mature tools that may lack the excitement of something new, but offer unparalleled reliability. As Dan McKinley points out in his presentation Choose Boring Technology, “failure modes of boring technology are well understood.” In other words, all technology will eventually fail, but older, more mature tools tend to fail in predictable ways. This predictability makes them easier to manage and debug. Why choose boring technology? Stability: Mature technologies have been tested over time and in a variety of scenarios. They are less likely to have hidden issues that can surprise your team. Community support: Older technologies have larger, more established communities. This means more resources, better documentation, and more people who can help when things go wrong. Compatibility: New technology often introduces compatibility issues with existing systems. By using well-established tools, you can avoid spending valuable time fixing integration issues. Choosing the latest and greatest technology may seem exciting, but when it comes to building long-term, scalable systems, [...]

When working with legacy code, the temptation to start from scratch can be strong. It’s natural to want to clean up the mess and create something shiny and new. However, rewriting code can often do more harm than good. It comes with high risks and costs, and it’s important to weigh the benefits carefully. In his book The Hard Thing About Hard Things, Ben Horowitz states, "The primary thing that any technology startup must do is build a product that’s at least ten times better at doing something than the current prevailing way." This same principle applies to code rewrites—if the new system isn’t significantly better, then the effort isn’t worth it. Here’s why rewrites can be dangerous: They destabilize the codebase: A rewrite can introduce new bugs and make the code less stable, especially if the old system worked reliably. They come at the cost of new features: When time is spent rewriting existing code, it’s not spent on adding new features that could benefit users. Coding standards matter: Even if certain standards seem outdated or unnecessary, they are there for a reason. Diverging from established patterns can make code harder to read and maintain. Instead of jumping into [...]

Good commit messages are essential for a healthy codebase. They provide context, aid in collaboration, and make the history of a project much easier to follow. When you’re revisiting code after months (or even years), well-structured commit messages can help you understand what was changed and why. To write an effective commit message, follow these practices, as recommended by Chris Beams: Separate the subject from the body: Your subject line should be clear and concise, but if you need to provide more detail, separate the subject from the body with a blank line. Limit the subject line to 50 characters: A short subject line ensures that it is easy to read and doesn’t get cut off in most interfaces. Capitalize the subject line: Start your subject line with a capital letter to maintain consistency and readability. Avoid periods at the end of the subject line: Since the subject is a brief summary, there’s no need to use a period. Use the imperative mood in the subject line: This makes it easier to read and conveys a sense of action. For example, write "Add feature" instead of "Added feature" or "Adding feature." Wrap the body text at 72 characters: This ensures [...]

Many engineers are naturally focused on technical challenges, but one of the most important skills you’ll need throughout your career is communication. Whether you’re explaining a complex feature to a non-technical stakeholder or giving feedback in a code review, your ability to communicate effectively will shape your success. Here are some tips on how to improve your communication skills: 1. Be Clear and Concise When writing code, you aim for clarity and simplicity—and the same should apply to your communication. Whether it’s an email, a design document, or a code review, ensure your message is clear and to the point. Avoid unnecessary jargon, and always consider your audience. 2. Give and Receive Feedback Effectively Feedback is crucial for growth, but it can be challenging to navigate, especially in a technical environment. When giving feedback, focus on being constructive, specific, and respectful. When receiving feedback, be open-minded and see it as an opportunity to improve, not as a personal critique. 3. Documentation Is Key Clear documentation is a form of communication that often goes overlooked. Whether you’re writing an API spec or documenting a process, remember that well-written documentation can save hours of frustration for your team. It’s especially helpful for [...]

As a software engineer, learning from others is crucial for developing new skills and growing professionally. One of the best ways to achieve this is by shadowing experienced engineers and engaging in pair programming. 1. Shadowing: Learn by Observation Shadowing allows you to follow a senior engineer and observe their approach to solving complex problems. It's an active process where you take notes, ask questions, and learn how experts handle various scenarios. To maximize the benefits of shadowing, plan sessions ahead of time and have a follow-up discussion afterward to reflect on your learnings. Once you feel more comfortable, try the reverse: have a senior engineer shadow you. This method offers invaluable feedback and provides a safety net if something goes wrong, especially in high-pressure situations like interviews. 2. Pair Programming: Learning Through Collaboration Pair programming involves two engineers working together to write code. One types, while the other reviews and thinks ahead. It takes time to get used to, but the benefits are significant: quicker learning, better communication, and higher code quality. Pair programming isn’t just for new engineers. Teammates at all levels can benefit from exchanging ideas and perspectives. The collaborative environment fosters mutual growth, making it one [...]

Two psychological challenges can slow your growth as a software engineer: impostor syndrome and the Dunning-Kruger effect. Both can affect how you perceive your abilities, and understanding them is key to overcoming these growth obstacles. 1. Impostor Syndrome: Feeling Like a Fraud Impostor syndrome occurs when highly capable engineers feel like they don’t deserve their success. Every mistake reinforces their self-doubt, while their achievements are attributed to luck. This self-perpetuating cycle can be hard to break. To overcome it, start by recognizing your accomplishments—no matter how small. Reframe negative thoughts to highlight the progress you’ve made. Talking to trusted colleagues about your self-doubt can also provide valuable reassurance and feedback. 2. The Dunning-Kruger Effect: Overconfidence Despite Incompetence On the flip side, the Dunning-Kruger effect is when individuals overestimate their abilities because they don’t yet know what they don’t know. These engineers might reject feedback and believe their approach is always right, leading to frustration among teammates. To combat this, foster curiosity and humility. Engage in discussions about design decisions, even when you disagree. Ask for feedback and embrace the idea that there are often trade-offs rather than one “right” solution. A mindset of continuous learning will help you grow.