Before You Build a Data Observability Tool, Read This
TL;DR: There are tradeoffs in building vs. buying, but it doesn't always make sense to go in-house, and there are questions every team should ask before making the call.

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If you're exploring data observability solutions, your organization likely already understands the value of reliable data. Maybe you've hit a breaking point with broken dashboards, emergency incident calls, or just a general sense that business users can't trust the numbers. You know you need observability, but the next big question is: should you build your own solution or buy one off the shelf?
It sounds simple, but the answer depends on more than just budget. Your long-term data strategy, team expertise, urgency, and tolerance for complexity will all shape the best path forward.
Let’s break it down.
Why Even Consider Building?
For some teams, building a data observability solution from scratch can be appealing. Maybe you want complete control. Maybe you think you can do it cheaper. Or maybe your needs are so unique that no vendor tool quite fits.
But those assumptions come with tradeoffs.
Before committing to building your own solution, ask:
- What’s motivating us? Is it cost savings, control, autonomy, or custom features you haven’t seen elsewhere?
- Are our needs simple or complex? If you only need basic monitoring and a few outlier alerts, building makes a lot more sense. But complex requirements can quickly snowball into scope creep.
- Can we actually afford it? Not just the initial cost, but the engineers, infrastructure, maintenance, and opportunity cost. Time to value is a real metric here.
The Reality of Building In-House
In theory, building your own solution offers total flexibility. In practice, it’s rarely that straightforward.
Unless you have the resources of a MAMAA company, your end result will likely be a scrappy MVP. You may get something that covers your most urgent needs, but it could lack the scalability, usability, and extensibility of a mature platform.
Even for enterprises with budget and talent, the key challenge is time. Building a robust, secure, and user-friendly observability platform will take quarters, even years. That’s time your team could be spending fixing issues, delivering value, and supporting more pressing business initiatives.
When Building Might Make Sense
Building in-house can be the right choice in some specific situations:
- You need a competitive differentiator and observability is part of your core product.
- Your architecture is highly custom or legacy-heavy, and existing tools don’t integrate well.
- You have a clear strategy to avoid vendor lock-in.
- You need fine-tuned control and customization, especially for non-technical users.
- You already have a mature, well-resourced data engineering team with domain expertise.
If those describe your org, and you have the appetite for ongoing development and maintenance, building may be viable. But you still need to answer some tough questions first.
Critical Questions Before You Build
Before you decide to build your own observability solution, make sure you can confidently answer the following:
- What’s the exact problem we’re solving? Is it something vendor tools can’t do?
- Will our internal solution actually be better, faster, or more reliable? Or just different?
- Do we have a roadmap for data collection, storage, processing, and automation?
- What specific monitoring, anomaly detection, and data quality capabilities do we need?
- Does our team have the technical depth to build and maintain this?
- How much time will it take, and does that timeline align with our business goals?
- How will we ensure accuracy and reliability compared to proven vendor solutions?
- How will we handle ongoing updates, feature requests, security patches, and scale?
Final Thoughts?
Build if you must, buy if you can.
Most organizations that choose to build are optimizing for independence and control. But most organizations that choose to buy are optimizing for time to value, proven reliability, and lower maintenance overhead.
There’s no one-size-fits-all answer. But unless data observability is core to your competitive advantage, investing in a vendor solution can often save you months of effort and deliver better outcomes in the long run.
Need help evaluating your options? We've created a vendor-neutral evaluation guide and an RFI template to help your team assess what's best for your business.
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