Operations | Monitoring | ITSM | DevOps | Cloud

In the expanding world of APIs, meaningful error responses can be just as important as well-structured success responses. In this post, I'll take you through some of the different options for creating responses that I've encountered during my time working at Raygun. We'll go over the pros and cons of some common options, and end with what I consider to be one of the best choices when it comes to API design, the Result Pattern. This pattern can lead to an API that will cleanly handle error states and easily allow for consistent future endpoint development.

In the world of software development, quickly finding and fixing errors drives better experiences for both end-users and developers. One key tool in this process is the symbol map, which records debugging information that was lost in the compilation process. Symbol maps (or source maps if we're talking JavaScript) connect the code developers write to the minified code in production, making it easier to decipher crashes by pinpointing the exact source code that caused the error.

In a world where Software as a Service (SaaS) products are integral to daily life, maintaining uninterrupted service for end-users is paramount. However, stuff happens. When it does, our most valuable response (other than restoring service ASAP) is to review the series of events that led up to the incident and learn from them. On August 25th, 2023, at 7:02 AM NZT, Raygun experienced a significant incident that impacted our API ingestion cluster, leading to an outage lasting approximately 1 hour and 15 minutes. While this wasn't fun for anyone involved, this incident did prove to be a valuable learning experience, shedding light on the importance of infrastructure management and resilience.

Understanding the impact of each of your deployments is crucial, especially as they become increasingly frequent. Chances are, your team is either aiming to increase shipping velocity or has already started deploying "continuously" (which is to say, multiple times a day). The biggest tech teams at the likes of Amazon and Google deploy thousands of times daily, and Atlassian has found that 75% of enterprise DevOps teams call deployment frequency their most important success criteria. And while CD comes with a host of well-established benefits, it also introduces a heightened risk of introducing new errors and issues.