Building your own tooling feels efficient. You know your stack and your needs, and your team has the technical acumen to ship something that works. A homegrown system can unblock an experiment, ship a feature, help you avoid procurement headaches, and keep your code under your own control.
But that early momentum can fade when releases move faster than your ability to react in production. The tool you built to solve a problem can become a problem in itself if its functionality breaks down under real-world conditions. Growing complexity can create edge cases, and unclear ownership of the tool itself makes it harder to respond when something goes wrong. When production issues arise, teams often scramble to trace changes, untangle assumptions, and regain control over a system that wasn’t designed to scale.
As organizations grow, internal tools pull engineers into continuous maintenance, debugging, and support work that compounds over time.
Production control isn’t optional
Deploying code is easy, but releasing features isn’t. Homegrown systems might be able to toggle flags, but they don’t provide expanded control around releases. Releasing successfully often requires more specific, hands-on work that simple homegrown tools can’t manage. The following issues might emerge during release:
- You need to see which team member made a specific change
- A rollback requires a code push
- Kill switches are inconsistent without teams standardizing them
- Targeting by cohort or environment requires manual work
When teams lack real-time insight and recovery tools for such scenarios, every release can incur risk. This is why many incidents drag out, and MTTR stays high.
LaunchDarkly customers who previously relied on internal tooling report having struggled with the same patterns: shipping delays, firefighting, and rollout fears that kill deployment velocity. Without control over releases after deployment, even your best workflows can be fragile.
The governance gap grows with each release
The larger your org gets, the more scrutiny your releases face. Internal risk teams need to know what's changing and why. Homegrown tools rarely offer the traceability or access control required to support this. Without built-in governance, release processes rely on memory and manual steps; in some cases, visibility depends on someone remembering to update a spreadsheet or ping a channel.
These workflows are usually sufficient until they’re tested under pressure. When an audit or regression occurs, gaps in your release process can escalate from “just a tooling issue” to a business blocker.
LaunchDarkly provides role-based access, audit logs, and version tracking by default; essential features for teams working in high-trust environments.
When tooling fails, recovery is slow and expensive
In many incidents, even a five-minute rollback can feel like an eternity. A feature flag that can't be traced to its impact in production slows everything down. And if your system can’t catch regressions early, you lose time twice: once during the incident, and again during the retro when you're trying to rebuild trust with your stakeholders.
The engineering hours lost to slow rollouts and unclear ownership are rarely tracked, but they add up. One missed alert, an incomplete test, or a forgotten toggle can put your team on call over the weekend if a partial rollout affects a VIP segment.
The real cost of internal tools
Engineering leaders are responsible for testing, documentation, observability, governance, and onboarding. They’re also often relied on to oversee performance, scale, and edge-case logic across teams and environments. When teams build internal tools for release management, all of those engineering responsibilities carry over. The team is solving a technical problem by building an internal tool, but that tool quickly becomes another entity that must be maintained and supported.
This is where costs start to compound. Teams end up paying (invisibly) for:
- Time spent fixing rollout errors instead of building product features
- Delay caused by lack of access for PMs, designers, or risk reviewers
- Bugs being introduced by stale or inconsistent flag behavior
- Engineering burnout from owning a tool that’s critical but under-resourced
None of these factors emerges in the company’s original “build vs. buy” discussion, but they can be reflected in shipping velocity, developer morale, and incident history.
Tooling that doesn’t scale becomes a liability
As more teams rely on your internal system, expectations increase. Everyone wants visibility, reliability, and flexibility. What started as a few scripts becomes a service. A service becomes a platform. And now you’re in the business of supporting internal infrastructure that has no roadmap, no dedicated owner, and no clear path to maturity.
This is where internal tools start to fall apart. Requests pile up. Engineers become gatekeepers. Trust in the tool erodes. Instead of speeding up delivery, it slows you down.
LaunchDarkly was built to solve this, with sub-200ms propagation of changes across environments, plus built-in governance and targeting. Teams use it to reduce incident volume, improve MTTR, and scale release workflows without burning cycles on tooling overhead.
Your tool is never "done"
If you build your own system, you take on full responsibility for every edge case, failure path, and visibility gap, regardless of whether that work aligns with your team's priorities. What starts as a quick solution can become a long-term burden. Tools that seem inexpensive upfront can introduce delays, instability, and hidden costs that grow with every release.
Before you invest more engineering time into maintaining internal release tooling, make sure you understand the tradeoffs. The Build vs. Buy(er's) Guide breaks down the total cost of ownership, hidden operational burden, and the long-term impact of homegrown tools on velocity, governance, and reliability.
Like what you read?
Get a demo
