--- title: "Anatomy of a Dumpster Fire Rescue - George Rios" description: "A case study in rescuing a failing enterprise C# project. What went wrong, what we fixed, and lessons learned." url: https://georgerios.com/articles/dumpster-fire-rescue author: George Rios --- [ All articles](https://georgerios.com/articles) War Stories # Anatomy of a Dumpster Fire Rescue A case study in rescuing a failing enterprise C# project. What went wrong, what we fixed, and lessons learned. Published 2025-07-10 Reading time 4 min Topic War Stories Author George Rios The VP of Engineering's opening line: "We're six months past deadline, $2M over budget, and the demo still crashes. Can you help?" This is what I call a Category 5 dumpster fire. Here's how we rescued it—and what you can learn from their mistakes. ## The Situation A mid-sized financial services company was building a new customer portal to replace a 15-year-old legacy system. The project was critical—their largest customers were threatening to leave if they didn't modernize. **Original plan:** 12 months, $1.5M budget, team of 8 developers **Reality at month 18:** - Core features still incomplete - Application crashes under load testing - Data migration from legacy system not working - Original lead architect had quit - Team morale in the basement - Executive leadership losing confidence ## Phase 1: Triage (Week 1) Before fixing anything, you need to understand what you're dealing with. I spent the first week doing rapid assessment: ### Code Review The codebase was... creative. Some lowlights: - 22 different approaches to error handling across the application - Database queries with N+1 problems causing 10,000+ queries per page load - No unit tests (they had test files, but they were all empty or commented out) - Dependency injection configuration that took 45 seconds to run on app startup - Three different ORM libraries used in the same solution (EF Core, Dapper, and hand-rolled ADO.NET) ### Architecture Review The architecture was technically "microservices," but only in the sense that they had a lot of services. They had no clear boundaries, services calling each other in circular dependencies, and shared databases. Basically, they'd taken a monolith and chopped it into pieces without understanding what microservices actually solve. ### The Real Problem After a week of digging, the root cause was clear: **architecture astronauting without pragmatism.** The original architect had read too many blog posts and wanted to use every pattern: Event Sourcing, CQRS, microservices, DDD, the works. But the team didn't understand these patterns, the problem domain didn't need them, and they were drowning in accidental complexity. ## Phase 2: Stabilization (Weeks 2-4) You can't move forward when everything's on fire. First priority: stop the bleeding. ### Kill the Microservices (Sort Of) We consolidated 12 "microservices" back into 3 logical modules within a single deployable application. This: - Eliminated network latency and circular dependency issues - Made debugging possible again (one process, not 12) - Simplified deployment We kept clean module boundaries and interfaces so we could split things out later if needed. But for now, monolith was the right choice. ### Fix the Performance Disasters We attacked the worst performance issues: - Added a caching layer (Redis) for frequently accessed data - Rewrote the 10 slowest database queries to eliminate N+1 problems - Implemented pagination (they were loading thousands of records and filtering in memory) - Lazy-loaded the DI container registrations to cut startup time from 45s to 3s **Result:** The application went from unusable to "slow but functional." ### Establish a Deployment Pipeline They were deploying manually. As in, copying DLLs to servers manually. In 2025. We set up: - GitHub Actions CI pipeline - Automated testing (even though there weren't many tests yet) - Containerized deployment to Azure Container Apps - Blue/green deployment for zero-downtime updates Now they could deploy in 10 minutes instead of 4 hours. ## Phase 3: Feature Completion (Weeks 5-12) With the foundation stabilized, we could actually build features. The key was ruthless prioritization: ### The MVP Exercise I sat down with the product owner and asked: "If you could launch with only 5 features, which ones?" This was painful. They wanted 30 features. But we forced the conversation. The result: 1. 01 Customer account overview 2. 02 Transaction history 3. 03 Make a payment 4. 04 Update contact information 5. 05 Secure document upload Everything else went into a "phase 2" backlog. We'd ship the MVP first, then iterate. ### Velocity Improvement With the architecture simplified and the team unblocked, velocity improved dramatically: - **Months 0-18 (before rescue):** \~0.5 features/month - **Weeks 5-12 (rescue mode):** \~2 features/week Same team, simpler architecture, clearer priorities. ## Phase 4: Launch (Weeks 13-16) We launched a beta to 100 customers in week 13\. It wasn't perfect, but it worked. We: - Monitored like hawks (logging, metrics, alerts everywhere) - Fixed bugs as they came in - Collected feedback - Iterated weekly By week 16, we rolled out to all customers. No major incidents. ## The Lessons ### 1\. Complexity Is the Enemy The project failed because it was too complex. Microservices without clear boundaries. Event Sourcing without understanding the trade-offs. CQRS for simple CRUD operations. Simplicity is a feature, not a bug. ### 2\. Ship Something, Then Iterate They spent 18 months trying to build the "perfect" system and shipped nothing. We shipped an MVP in 16 weeks and iterated from there. Perfect is the enemy of done. ### 3\. Team Morale Matters When we started, the team was defeated. They'd worked nights and weekends for months with nothing to show for it. Early wins matter. We celebrated every feature completion. We demoed progress weekly. By week 8, the energy had completely shifted. ### 4\. Sometimes You Need Outside Help The team was too close to the problem. They'd been fighting the same battles for months and couldn't see the forest for the trees. Fresh eyes and experience with similar situations made all the difference. ## The Aftermath Six months after launch: - Application running in production with 99.9% uptime - Customer satisfaction scores up 40% - Team shipping new features every two weeks - Two major clients who were threatening to leave stayed and signed renewals Was it a perfect system? No. But it was a working system that delivered business value. We could iterate from there. ## If You're in a Dumpster Fire... Here's what to do: 1. 01 **Admit it's a problem.** Denial wastes time. 2. 02 **Get outside help.** Fresh perspective is invaluable. 3. 03 **Simplify ruthlessly.** Cut scope, cut complexity, cut tech debt. 4. 04 **Focus on one thing at a time.** Stabilize, then ship, then iterate. 5. 05 **Communicate constantly.** Keep stakeholders informed. _Dealing with a troubled C# project? I offer [dumpster fire rescue services](https://georgerios.com/cto#dumpster-fire) and can usually start within 24-48 hours. [Get in touch](mailto:george@georgerios.com?subject=Urgent: Project Rescue)._ ## References [ Back to articles](https://georgerios.com/articles) [Book a call ](https://cal.com/georgerios/30min) --- Contact: george@georgerios.com · Book a call: https://cal.com/georgerios/30min · Services summary for agents: https://georgerios.com/llms.txt