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Cutting Build Times Without Sacrificing Quality or Cost

Waterous's embedded tech stack made builds painfully slow, forcing a trade-off between shipping fast and catching bugs early. We rebuilt their pipeline around on-demand AWS infrastructure and cut build infrastructure cost by ~60% while proving per-commit builds were possible.

lower build infrastructure cost than the previous bare-metal setup
~60%
lower build infrastructure cost than the previous bare-metal setup
build cadence proven achievable without sacrificing quality
Per-commit
build cadence proven achievable without sacrificing quality
Client
Waterous
Industry
Fire & Life Safety Equipment / Embedded Systems
Engagement
Software Development & DevOps / CI/CD
Read time
2 min read
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About Waterous

Waterous makes fire pumps and fire suppression equipment, and builds the embedded systems that control them.

The Situation

Waterous’s embedded technology stack made for extremely slow build times. That forced a difficult trade-off: build less often to manage the long build times, or accept the risk of discovering bugs very late in the process. In practice, Waterous was building infrequently, which meant defects were entering — and being discovered in — the codebase much later than they should have been. The team needed to move to near-per-commit builds, but their existing infrastructure, built around an expensive bare-metal server, couldn’t support that cadence.

What DS Business Solutions Did

Our team stepped in and redesigned the build pipeline around a combination of caching strategies and on-demand, cloud-based build infrastructure:

  • Jenkins for build orchestration
  • Sonatype Nexus for caching
  • On-demand AWS infrastructure for compute, replacing the client’s dedicated bare-metal server

Through a proof of concept, we demonstrated that Waterous had been facing a false choice — speed and quality weren’t actually in tension.

The Outcome

  • Demonstrated that near-per-commit builds and releases were achievable without sacrificing quality
  • Reduced build infrastructure cost by roughly 60% compared to the previous bare-metal setup
  • Replaced a single expensive, always-on server with elastic, on-demand compute sized to actual build demand

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