Send this to your CTO
You already test
in production.
Your customers are your QA team. Every deploy without tests is a live experiment on paying users. Here's what that actually costs.
The real cost
Anatomy of one
production bug.
5:00 PM
A developer pushes three lines of code. No tests — "it's obvious what it does." CI passes because there's nothing to run. Deploy goes out. Everyone goes home.
11:00 PM
Payment endpoint starts returning 500s. On-call engineer gets paged, opens laptop, starts digging.
12:00 AM
Two more engineers join. No way to reproduce it — nobody documented expected behavior.
2:00 AM
Root cause found: a null check removed in the "trivial" change.
4:00 AM
Fix deployed. Team monitors to make sure it holds. Nobody sleeps.
7:00 AM
System stable. 340 customers affected, 23 support tickets, 12 users never come back.
Next week
Post-mortem, incident report, process review. Team derailed from sprint for 2 days.
One trivial change. No tests. Five hours of downtime, three engineers on a call, hundreds of affected customers, and a week of cleanup. One Spark test would have caught it before deploy.
Industry data
You're not alone.
$2.41T
Annual cost of poor software quality in the US alone
CISQ — The Cost of Poor Software Quality, 2022
16%
Of developer time actually goes to writing code. The rest is debugging, maintenance, and overhead.
IDC — How Do Software Developers Spend Their Time, 2024
80%
Of serious outages could have been prevented with better management and processes
Uptime Institute — Annual Outage Analysis, 2024
8x
Higher change failure rate for low-performing teams vs elite teams (40% vs 5%)
DORA — Accelerate State of DevOps Report, 2024
The new reality
AI made it worse.
Your team ships more code than ever. AI copilots, faster pipelines, more deploys. But more code without more verification just means more bugs reaching production faster.
AI generates code, not confidence
Copilot doesn't know your database schema or edge cases. The code compiles, the review looks fine. It breaks in production.
Speed without verification is liability
Your team ships 5x more code than two years ago. Test coverage hasn't changed. That's 5x more unverified assumptions in production.
The safety net is gone
PRs are smaller, reviews are faster, AI-generated code looks clean. The bugs that slip through are subtler and harder to find after deploy.
Sound familiar?
The excuses.
"We don't have time to write tests"
Your team spent 24 engineer-hours last month on a single production incident that one test would have prevented. Then days on the post-mortem. A Spark test takes 5 minutes to write.
"E2E tests are too hard to set up"
Docker-compose files, bash scripts, sleep timers — that was 2020. A Spark test is one YAML file. No infrastructure. No framework. No glue code.
"We'll add tests later"
There's a "write tests" ticket in your backlog right now. It's been there since 2022. It has no assignee, no priority, and no chance of getting done unless something changes.
The business case
The math.
10-person engineering team. Average salary $120K. 50 deploys per month. Here's what changes when you add test coverage.
Without tests
Production incidents (6/year × $51,800)$310,800
Unplanned debugging (2 hrs/dev/week × $58/hr)$60,300
On-call compensation$7,800
Annual cost$378,900
With Spark
Test writing (1.5 hrs/dev/week × $58/hr)$45,200
CI execution costs$3,000
Remaining incidents (1/year)$4,500
Annual cost$52,700
Annual savings
$326,200
That's almost 3 developer salaries. Every year.
The answer
Spark.
Your team doesn't skip tests because they're lazy. They skip them because testing was always too hard, too slow, and too fragile. Spark changes that.
One YAML file per test
Zero boilerplate
No test framework. No programming language. Define services, requests, and assertions in plain YAML. Anyone on your team can read and write tests.
Automatic infrastructure
Zero setup
Spark creates isolated Docker networks, starts services, waits for health checks, runs tests, and cleans up. Your developers just describe what to test.
Runs everywhere
< 60 seconds
Same command on a developer's laptop, in GitHub Actions, or on Jenkins. JUnit XML output for CI. HTML reports for humans.
Cloud mode for scale
10x faster
Add --cloud and tests run on distributed workers. No Docker needed on CI. Live results streamed to the terminal.
Free forever
$0
Open source. No per-seat licensing. No vendor lock-in. Run locally with zero cost, no limits, no strings attached.
Premium to go fast
Cloud
When you need speed at scale, upgrade to cloud execution. Distributed workers, parallel runs, live streaming — pay only for what you use.
$curl -fsSL https://get.spark.dev | sh