Lessons Learned from Ruby on Rails Projects: Common Challenges & Fixes

In my early Rails projects, I underestimated the depth of security measures needed for applications handling sensitive data and the difficulties of maintaining clear, efficient communication within large development teams. I quickly realized that overlooking security best practices could leave applications vulnerable, while miscommunication could slow progress and introduce costly errors. 

Working on Dalza and Cooleaf became a pivotal learning experience. These projects challenged me to master advanced security techniques, optimize performance for scalability, and adopt structured collaboration and documentation strategies. They strengthened my technical skills and reshaped my development approach, reinforcing the importance of proactive security, streamlined teamwork, and maintainable code in building robust Rails applications.

Every development project comes with unique challenges, and working with Ruby on Rails is no exception. I’d like to break down two major lessons learned from these projects. These lessons improved my approach to Rails development and provided actionable strategies to help developers build more secure, scalable, and well-organized applications. Let’s have a look.

Working on Dalza, an application handling sensitive personal information, reinforced a critical lesson: security must be a top priority from day one. In any application dealing with private user data, even minor vulnerabilities can lead to serious breaches, making robust security measures non-negotiable.

Throughout this project, I encountered and addressed key security challenges. Implementing the measures below strengthened the app’s security posture and deepened my understanding of proactively defending against emerging threats.

Here are some of the most effective security strategies I applied:

• Preventing enumeration attacks and data leaks: To prevent enumeration attacks, it’s essential to standardize error messages to avoid revealing any information about the validity of usernames or passwords. By returning generic error messages regardless of which credentials are incorrect, we reduce the risk of attackers identifying valid usernames and improve the overall security of the authentication system. This approach also prevents potential data leaks, safeguarding sensitive user information from being exposed.

• Mitigating timing-based attacks with constant-time comparisons: Traditional string comparisons can inadvertently expose subtle differences in response times, allowing attackers to infer valid credentials through timing-based side-channel attacks. We implemented constant-time comparison functions to prevent this, ensuring that authentication checks take the same time regardless of input. This way, we eliminated any measurable discrepancies attackers could exploit, significantly strengthening authentication security.

• Encrypting sensitive data with ActiveRecord::Encryption: Storing sensitive user information in plaintext, even in a secured database, poses a significant risk in data breaches. To safeguard critical data at the database level, we utilized ActiveRecord::Encryption, which provides built-in, transparent encryption for specified attributes. It ensures that personally identifiable information (PII), financial records, and other sensitive data remain unreadable without proper decryption keys, adding an extra layer of protection against unauthorized access.

Working on Cooleaf, a project involving a large, multi-unit team divided into business assurance and business development groups, underscored the importance of effective collaboration and maintaining high code quality. Challenges arose in documentation, communication, and coding consistency, which directly impacted productivity and the project's overall success.

To navigate these challenges, we adopted strategies that streamlined teamwork, reduced technical debt, and improved onboarding for new developers. Here are the key lessons we implemented to enhance collaboration and code quality:

• Importance of clear documentation: In large, divided teams, comprehensive documentation ensures that all team members, regardless of their unit, can understand the project's structure, logic, and goals. We adopted clear API documentation and internal wikis to bridge knowledge gaps and support smooth onboarding for new developers.

• Effective communication strategies: Effective collaboration required regular cross-team meetings, daily stand-ups, and asynchronous updates. We utilized tools like Slack for real-time communication and Jira for task tracking. Clear communication protocols ensured that dependencies between teams were addressed promptly, reducing blockers and misunderstandings.

• Consistent coding standards: Enforcing uniform coding standards was essential to maintaining code readability and reducing technical debt. We implemented style guides and linters, such as RuboCop, and enforced pull request reviews where peers provided feedback. This practice led to fewer bugs, better code maintainability, and a shared understanding of best practices.

Every development project has its own set of obstacles, and working with Ruby on Rails is no exception. Whether dealing with security vulnerabilities, scaling team collaboration, or optimizing performance, overcoming these challenges requires a combination of strategic thinking, best practices, and continuous learning. I’ll discuss three real-world obstacles while working on Dalza and Cooleaf and present a performance optimization case study from another project. These challenges offered valuable lessons that helped refine my Rails development practices.

Problem: When working on Dalza, an application that handles sensitive medical data, I quickly realized that security could not be an afterthought. Due to the highly sensitive nature of patient data, medical applications are prime targets for attackers, and even minor vulnerabilities could lead to data leaks, compliance violations, and reputational damage.

One key risk was enumeration attacks, in which attackers attempt to identify valid usernames or emails through subtle variations in system responses. Another was timing-based attacks, which exploit differences in response times to infer sensitive information. Finally, storing unencrypted personally identifiable information (PII) poses a risk in case of a data breach.

Solutions & Implementation:

Standardized Error Messages to Prevent Enumeration Attacks

To limit enumeration attacks, it is crucial to use standard and generic error messages that do not reveal whether a username, email address, or other sensitive information exists on the system. Attackers often exploit inconsistencies in authentication responses to identify valid accounts, which can be used for further attacks such as credential stuffing or phishing. For example, instead of returning different messages for “Invalid username” and “Invalid password,” the system should respond with a generic message such as “Invalid credentials,” regardless of whether the username exists. Similarly, password reset and account registration flows should avoid revealing whether an email address is registered with the system.

Constant-time comparisons 

to mitigate timing-based attacks. Timing attacks exploit the fact that string comparisons used in authentication can take slightly different amounts of time depending on how much of the input matches the correct value. Attackers can measure these differences to deduce valid credentials. To counteract this, I implemented constant-time comparison functions for authentication, ensuring that password and token verification always take the same amount of time, regardless of input. 

Encryption with ActiveRecord::Encryption 

for all necessary database attributes, ensuring that all personally identifiable information (PII) data was securely encrypted at the database level. Storing unencrypted personally identifiable information (PII), such as names, addresses, or medical records, poses a massive security risk. Even if the database is breached, proper encryption ensures the data remains unreadable without the correct decryption keys. I implemented ActiveRecord::Encryption, which provided transparent, field-level encryption for sensitive attributes. This ensured that PII remained securely encrypted even if someone accessed the raw database.

Problem: One of the biggest challenges I faced while working on Cooleaf was managing knowledge in a growing team. As the application scaled, so did the technical and business logic complexity. New developers joining the team often relied on senior engineers to explain systems, processes, and decisions, creating a bottleneck. Without proper documentation, critical knowledge was stored in developers’ heads rather than inaccessible resources.

Solutions:

Establishing Cross-Team Communication Processes: 

To improve collaboration and knowledge sharing, we introduced regular sync meetings between development, business assurance, and business development teams to align on goals and priorities. We also introduced retrospective sessions that allowed us to review challenges, successes, and areas for improvement. Meanwhile, asynchronous updates via Slack and Confluence allowed developers to document changes, issues, and insights in a structured, searchable way.

Developing Robust Onboarding Guides & Coding Standards

To prevent new team members from relying solely on senior developers for information, we created a structured onboarding guide outlining the application architecture, workflows, and key systems. We also enforced clear coding standard documentation, including style guides and best practices, through tools like RuboCop. In addition, we launched a mentorship program in which experienced engineers helped new hires get up to speed without being the sole source of knowledge.

Implementing Visual Documentation for Better Clarity 

Technical documentation can sometimes be overwhelming, especially for non-technical team members. Visual documentation is more accessible and easier to understand for non-technical team members, significantly improving team communication and decision-making. To make information more digestible, we introduced:

• Flowcharts and system diagrams to visually represent application workflows and dependencies.

• Annotated architecture diagrams, making it easier to understand system design at a glance.

• Process maps that detail how different teams interact with the application.

Leveraging Collaborative Documentation Tools

To ensure that documentation remained up to date and wasn't just a static document, we adopted Confluence for real-time, collaborative documentation. By having a single source of truth, we eliminated knowledge silos and ensured that documentation was always accessible and continuously maintained.

While working on a project involving third-party vendor data synchronization, my team encountered severe performance bottlenecks in our background job processing. Each synchronization cycle generated an overwhelming 155,000 background jobs, leading to delays, resource inefficiencies, and increased infrastructure costs. The system struggled to keep up, with job queues clogging, API calls ballooning, and database operations consuming excessive processing power.

The core issues stemmed from redundant job creation, inefficient API usage, and non-optimized database operations. Vendor data and associated images were synchronized separately, resulting in unnecessary background jobs. The API requests fetched only 10 records per request, drastically inflating the number of network calls required. Database operations were also executed one record at a time, compounding the inefficiencies.

To address these problems, we needed to streamline job execution, reduce API overhead, and optimize database interactions.

A major contributor to the problem was the sheer volume of background jobs created for each synchronization process. Vendor data and associated images were processed separately, meaning that tens of thousands of redundant jobs were being enqueued unnecessarily. The result was a bloated queue that took significantly longer to process, delaying updates and affecting system responsiveness.

Solution: Inline Image Synchronization

To eliminate redundancy, we restructured the synchronization logic to process vendor data and images in a single operation rather than generating separate jobs. This approach removed the need for 50,000 additional background jobs, significantly reducing the job queue size while maintaining data accuracy.

Old Approach: 50,000 separate image synchronization jobs

New Approach: 0 additional jobs (images processed inline)

By handling image synchronization within the vendor data processing workflow, we cut down job volume and improved execution speed.

The integration relied on fetching vendor data from an external API. However, the system was making an excessive number of API calls due to an inefficient use of the per_page parameter. The default setting retrieved only 10 records per request, meaning thousands of API calls were necessary to synchronize all vendors. It increased network latency, unnecessary API overhead, and longer synchronization times.

Solution: Optimized API Calls

By adjusting the per_page parameter from 10 to 50, we dramatically reduced the number of API requests required per synchronization run. This optimization reduced API-related background jobs from 5,000 per run to 1,000, significantly improving efficiency.

Old Approach: ~5,000 API-related jobs per synchronization

New Approach: ~1,000 API-related jobs per synchronization

This change sped up synchronization and lowered API request costs, making the system more scalable and cost-effective.

A significant inefficiency in our system was the handling of database operations. Every vendor record and its associated data were inserted and updated one by one, resulting in 50,000+ individual database transactions. It led to an excessive load on the database, slowing down synchronization and consuming unnecessary computing resources.

Solution: Batch Processing & Efficient Updates

To optimize database performance, we implemented bulk insertion and updating techniques:

• Batch Insertions with insert_all—Instead of inserting records individually, we used ActiveRecord’s insert_all method to insert multiple records in a single operation.

Old Approach: ~50,000 jobs per run

New Approach: ~1,000 jobs per first run, ~0 jobs in subsequent runs

• Efficient Updates with upsert_all – Instead of updating records individually, we switched to upsert_all, which updates or inserts multiple records in a single atomic operation.

Old Approach: ~50,000 jobs per run

New Approach: ~1,000 jobs per run

These optimizations greatly reduced database overhead, making the synchronization process significantly faster and more scalable.

Working on Dalza and Cooleaf taught me that successful Rails development requires more than understanding its conventions. Security, performance optimization, effective team collaboration, and managing technical debt are vital components of scalable, maintainable applications.

Through my experiences, I’ve identified and described core lessons for building robust Rails applications in some of my previous articles:

• Security should be foundational, with strong encryption and proactive measures to prevent attacks.

• Performance optimization is essential, achieved through effective caching strategies, database indexing, and background processing.

• Clear documentation and streamlined communication enable teams to collaborate efficiently and avoid knowledge silos.

• Consistent refactoring and thoughtful dependency management help reduce technical debt and ensure long-term maintainability.

By continuously refining best practices, developers can deliver high-performing, resilient Rails applications that stand the test of time. The key to success isn’t just writing code—it’s about building applications that scale, perform efficiently, and remain maintainable as they grow.