Software Architects and Engineers make technical decisions based on their own experience, preferred technologies and non-functional requirements. But even the top engineers fail, when they forget to account for business context like user demand, internal expertise and budget constraints. Today I am sharing 3 real-life stories, where business context played crucial role in a software failure.
Death of Parse
Parse was a popular Mobile Backend as a Service (MBaaS), allowing app developers to quickly spin up backend infrastructure without much database knowledge. Initially, Parse used MongoDB extensively for scalability, speed, and ease of JSON-based storage. However, Facebook’s engineering teams had far stronger expertise and tooling around MySQL, a relational database. Post-acquisition, Facebook attempted to migrate Parse entirely from MongoDB to MySQL.
This decision was primarily driven by internal preference and tooling rather than Parse’s actual business context—ease of use and flexibility for external developers. The migration proved extremely challenging and time-consuming, significantly deteriorating Parse’s ease-of-use proposition.
Due to complexity and loss of user-friendly features, Parse lost developer trust and user adoption slowed dramatically. Eventually, Facebook completely shut down Parse in 2017, frustrating thousands of app developers.
Aligning database technology strictly with internal expertise or corporate standards—ignoring the product’s unique business context—can destroy the core value proposition of an acquired product.
Airbnb – React Native Misalignment
In 2016, Airbnb’s mobile engineering team embraced React Native, aiming to improve development speed by leveraging a single JavaScript codebase. Although technically promising, the team underestimated the complexity and challenges of adopting React Native at scale, especially around native performance, complex animations, and interactions that users expected in a premium app.
Despite significant investment (roughly two years), engineers found themselves frequently having to write custom native code for each platform anyway. The promised cross-platform efficiency never fully materialized, causing internal friction, slowdowns, and frustration across engineering teams.
After prolonged attempts, Airbnb publicly abandoned React Native in 2018, shifting back to native Android (Kotlin) and iOS (Swift). The failed experiment cost significant engineering resources, delayed feature rollouts, and temporarily slowed down Airbnb’s mobile innovation speed.
Choosing a seemingly convenient technical solution (cross-platform frameworks) without sufficient validation against actual business needs and customer expectations can lead to costly and frustrating setbacks.
GitLab – Insufficient Availability Investment
In early 2017, GitLab experienced a significant outage resulting from insufficient investment in redundancy and data backup strategies. A database engineer accidentally deleted a production database, and GitLab’s backup mechanisms failed because they were untested and improperly configured.
The incident exposed that GitLab had significantly underinvested in critical non-functional requirements—availability and disaster recovery—despite rapid growth and onboarding numerous paying enterprise customers.
GitLab.com went offline for approximately 18 hours. While GitLab’s transparency in resolving the issue was praised, the outage severely impacted customer trust, particularly enterprise clients. Immediate customer churn increased, and significant resources had to be rapidly allocated to fix reliability gaps, resulting in disrupted roadmap priorities.
Neglecting critical non-functional requirements like availability and disaster recovery—especially when serving enterprise or business-critical workloads—can quickly lead to business-impacting failures.
Call to Action
Don't want to make the same mistakes? To prevent such failures me and Anton Sidelnikov are running a Business Driven Technical Decision Workshop. Find out how best engineering teams make technical decisions in the near real-life example!
Details:
• Duration: 2 hours
• Delivery: Online
• Cost: €79 per participant
• Date: April 8, 4 PM UTC(6 PM Tallinn time)
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