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Um, let’s see. My name is Chris Maddox, and I work at ZenPayroll, where we handle payroll.
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Failure is something that we think about a lot, especially since we transfer hundreds of millions of dollars every year, soon to be billions.
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Our growth team gets really excited about this, saying, 'Oh, billions of dollars!' But honestly, I just want to focus on doing my job well.
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Today, we're going to talk about failure and some ways we've preemptively addressed it. We have an agenda like a business meeting, which I think is great.
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We’ll discuss predicting failures, approaches we’ve implemented to avoid mistakes, particularly regarding database validations and user models. Then, we’ll cover recovering from failure, which is critical for us.
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While preventing failure is important, making sure that if something goes wrong, we don’t lose sensitive user information is our top priority.
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Finally, we’ll talk about embracing failure, which might sound odd, but I'm a philosophy major—so I'm excited to dive into this topic.
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Chapter one: changes. DHH, I’m a writer now, so we’re organizing this into chapters. My predictions, however, have been notably inaccurate.
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Robert Caro, a biographer, has been writing a four-part series on Lyndon B. Johnson for 30 years. I’m only 23, so I can’t fathom that length of time, but I wish him the best.
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I’ve encountered issues on the internet several times where errors aren't communicated well.
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For example, you might receive a message saying, 'There were some problems with your form; please fix the errors before submitting again,' yet the system fails to show what’s actually wrong.
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I'm certain many of you have faced situations where you try to submit your information, only to be confronted with vague error messages that lead to frustration.
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In the case of a payroll platform, incorrect validations can lead users to believe they’re on track, while the issues lie elsewhere.
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Unfortunately, this leads to confusion and frustration, not just for the users but also for the support team who may be unable to provide clear answers.
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This issue worsens as your application grows in complexity. Payroll is intricate, with a lot of information to process.
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For instance, I mistakenly misconfigured Mr. Vonnegut’s bank account, which means he won’t get paid the way he expects.
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Yet, the user is unaware of this mistake because they are editing a different section. They will face validations that don’t make sense to them.
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This ultimately frustrates users when they need support, leading to a snowballing effect of problems.
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As a result, users are prevented from fixing or even perceiving the real issue, which can lead to cascading errors across processes.
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Two main culprits behind these failures include using update_column and update_attributes with validate: false, which, while often necessary, can be detrimental.
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When certain situations arise, like needing to save information despite an error, these functions can be useful. However, they can also result in losing sensitive information.
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Preserving user information is critical for us, especially since losses could amount to tens of millions of dollars per single transaction. Getting this right is absolutely essential.
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From this, we’ve devised solutions to validate data upfront rather than relying on user input alone—this is achieved through Rails validations.
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I learned from a colleague, Nick Drivassi, that we could run validations for every model in the database every few hours. Initially, I thought it was a terrible idea.
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However, it turned out to be a game-changer, and we now validate every model in the database every three hours.
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This entails pulling production data to validate it against our merged but undeployed code, allowing us to catch future errors before they become problems for users.
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This proactive approach has been incredibly beneficial, providing us with the lead time necessary to address issues more calmly, rather than in the moment when users often feel frantic.
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Shifting gears a bit—this concept reminds me of the pre-cogs from the movie 'Minority Report.' In the film, these genetically modified individuals predict murders.
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While their ability to forecast rather grim events may raise ethical questions, it provokes thought about how we can foresee errors in our own systems.
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We’ve begun to create long-running jobs to understand the eventualities of errors in our applications, especially with complex transactions that involve multiple parties like the IRS.
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Managing financial transactions can be a convoluted process, especially considering the communication barrier with banks after a transaction has been initiated.
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After the transaction begins, responses regarding success are limited. You only know it’s complete if there isn't a failure notice days later.
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This means we must ensure that everything within our control operates smoothly prior to going live with any updates.
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Now let’s pivot to recovery from failure, which is actually a fascinating topic.
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Predictions about errors are interesting and beneficial, yet how we recover once an event occurs is something I believe requires more focus.
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Every other day in practice, I see that what makes you better is how you respond to failure, including ones caused by you!
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Mia Hamm once shared that failure happens to everyone, and it’s how you address it afterward that defines growth.
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Reflecting on the inception of our Rails app, it’s inspiring to remember the early excitement while also recognizing the intricacies involved in payroll systems.
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Managing a system of maintenance was overwhelming, with one very large method running for a long time, which sometimes led to unexpected errors.
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When the state becomes uncertain due to an error, regaining stability is challenging and often feels reminiscent of brain surgery.
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Many underlying dependencies can cause issues, leading us to confront situations we never anticipated with banks, the IRS, and various other integrations.
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As we developed our API-driven services, it seemed easy to demystify responsibility on components, but once they went wrong, chaos ensued.
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One particular pain point with the IRS came when the government shut down unexpectedly, leading to delayed faxes—an edge-case we hadn't accounted for.
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The struggles surrounding the possible failures we face continues to highlight the complexities present in our operations.
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To reduce the likelihood of complete system failure, we began dissecting existing processes into smaller, manageable pieces.
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By localizing issues, we can continue payments for users while fixing others, like syncing with external APIs.
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Our approach led to several new libraries we developed, like Ultramarathon, which helped understand connections and dependencies more clearly.
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The philosophy guiding various processes is about minimizing interruptions and focusing on granularity, where possible.
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We also incorporated infrastructure that allows us to recover from partial failures instead of completely snowballing an operation.
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Now, even if a job fails, we’re able to run other pieces without hassle or halting everything.
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Additionally, we implemented detailed instrumentation to better understand where issues arise.
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All this contributes to a more resilient system designed not just to handle growth but to accommodate errors as part of the lifecycle.
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Accepting that failure is a natural process in software development is critical, and I learned this lesson from my dad.
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Recognizing that we handle serious matters, the stakes can lead to unnecessary panic; people rely on us to manage their payroll effectively.
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While we started with a philosophy where failure is unacceptable, it became evident that such pressure isn’t conducive to a healthy work environment.
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Ultimately, I believe it’s our responsibility to not only avoid failure but also to mitigate its impacts when it does occur.
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Reflecting on experiences, I feel it’s crucial for our growth and learning to accept failure as part of our evolution.
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The philosophy to embrace failure allows us to nurture resilience and a culture of learning within the team.
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If there’s one takeaway today, it’s to recognize that failure is a part of the journey—something we can learn from, rather than fear.
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So, if your company is sponsoring you for this talk, take that advice with caution!
