Architecture decisions
A Checklist for Custom or Third-Party Services
Quick Answer
Custom builds belong in the features that define a product's value, while commodity functions fit third-party services. The choice trades development speed, system ownership and operational overhead. An eight-factor evaluation weighs core competency, strategic importance, build and integration cost, technical debt, operational burden, vendor lock-in and long-term flexibility. Authentication for an analytics product shows why a non-core, security-critical function often favors buying.
When integrating functionality into a new product, evaluate whether the component is core to the product's value proposition. Build custom for unique, differentiating features. Use third-party services for commodity functions. This optimizes resource allocation for critical development pathways.
Why Build or Buy Decisions Get Hard
Engineering teams operate under finite resource constraints. Trade-offs occur between development speed, system ownership, and operational overhead. Building custom components increases control and intellectual property. It also incurs full development, maintenance, and scaling costs. Third-party services offer rapid integration. They externalize operational burden but introduce dependencies and potential vendor lock-in. Companies aim to maximize differentiation where it creates competitive advantage. They minimize investment in non-differentiating, common functionalities. This strategic allocation of engineering effort drives the build vs. buy dichotomy. Production issues directly affect engineering velocity. Using reliable third-party services can mitigate some operational burdens.
How to Evaluate Custom and Third-Party Options
- Define Core Competency. Identify functionalities central to your unique value proposition. These are your differentiating features. Prioritize custom development for these.
- Assess Strategic Importance. Determine if the functionality provides a competitive advantage. If it directly impacts user acquisition or retention, build it. If it is a generic utility, consider a third party.
- Evaluate Development Cost (Build). Estimate engineering effort for initial development. Include ongoing maintenance, scaling, and potential feature enhancement. Account for opportunity cost of diverting resources from core features.
- Evaluate Integration Cost (Buy). Estimate engineering effort for integrating and configuring the third-party service. Include ongoing subscription fees, usage-based costs, and potential data migration expenses. Consider future integration challenges.
- Analyze Technical Debt. Custom solutions can accumulate internal technical debt over time. Third-party services shift technical debt to the vendor. However, they can introduce integration-specific technical debt for your system.
- Consider Operational Burden. Building custom implies your team handles monitoring, scaling, and incident response. Third parties typically manage this for their service. Understand their SLAs and support models.
- Assess Vendor Lock-in and Exit Strategy. Evaluate the difficulty and cost of switching vendors later. Understand data portability and API limitations. Building custom avoids direct vendor lock-in but creates internal dependency.
- Evaluate Long-Term Flexibility. Custom solutions offer complete control over future modifications. Third-party services limit flexibility to their API and roadmap. This can constrain product evolution.
If you are weighing custom software development against a vendor, apply these eight factors first. For a shorter rule of thumb, see buy the commodity, build the moat.
A Practical Example With Authentication
A new SaaS product requires user authentication and authorization. The core value of the product is specific data analytics, not user management. An initial engineering team of three needs to deliver an MVP quickly. They could build a custom authentication system using a framework like Node.js with Passport.js. This would require designing a database schema, handling password hashing, session management, and OAuth flows. The estimated effort is several weeks for robust implementation and testing. Alternatively, they could integrate a third-party Identity-as-a-Service (IDaaS) provider such as Auth0 or Firebase Authentication. Integration involves SDK installation, configuration, and callback handling. This typically takes a fraction of that time. The IDaaS provider handles security, scaling, and multi-factor authentication. While there's a monthly cost and reliance on an external service, the engineering team can focus their remaining time on developing the differentiating data analytics engine. In this scenario, the utility of rapid deployment and offloading a non-core, security-critical function favors using a third-party service. Avoiding this production toil improves engineer retention.
Common Mistakes in Build or Buy Decisions
- Over-engineering non-core features. Spending significant engineering effort building a custom version of a widely available commodity service. This diverts resources from unique product value. For instance, building a custom email sending service instead of using SendGrid or Mailgun.
- Underestimating integration complexity. Assuming third-party integration is trivial. Complex APIs, incompatible data models, or poor documentation can consume significant engineering time. This negates the 'buy' advantage.
- Ignoring long-term costs of 'free' services. Opting for a free tier of a third-party service without projecting future usage or hidden costs. These can escalate unexpectedly. It can also lead to an expensive migration later.
- Failing to assess vendor viability. Integrating a critical third-party service from an unstable or poorly supported vendor. This risks future outages, lack of feature development, or service discontinuation.
- Choosing 'buy' for core differentiation. Using a third-party service for a feature that defines the product's unique selling proposition. This makes the product less defensible and harder to differentiate.
- Poorly managing vendor lock-in. Not having a strategy for migrating away from a third-party service if necessary. This can trap your product in an unfavorable dependency.
Key Takeaways on Custom and Third-Party Services
- Build custom for core, differentiating features only.
- Use third-party services for commodity functions.
- Prioritize speed for features not central to value.
- Evaluate total cost, including maintenance and risk.
- Understand vendor lock-in implications early.
See how Better Software helps founders build products.
Frequently Asked Questions
When Should You Build Custom Instead of Buying?
We build custom for functionality central to the unique value proposition, the differentiating features that affect user acquisition or retention. We use third-party services for generic utilities and commodity functions, so engineering effort goes where it creates competitive advantage rather than into non-differentiating work.
What Costs Should You Compare Between Building and Buying?
We estimate initial development, ongoing maintenance, scaling and the opportunity cost of diverted resources on the build side. On the buy side we count integration and configuration effort, subscription or usage fees, possible data migration and future integration challenges, then add technical debt and operational burden to both.
What Is Vendor Lock-In and How Do You Manage It?
We mean the difficulty and cost of switching vendors later. We evaluate data portability and API limits up front and keep an exit strategy. Building custom avoids direct vendor lock-in but creates an internal dependency, so we weigh both before choosing.
Why Might Authentication Be Better to Buy?
We use authentication as our example. For an analytics product, user management is not the core value. Buying an identity service offloads security, scaling and multi-factor authentication, and lets a small team spend its time on the differentiating analytics engine instead of a non-core, security-critical function.
What Mistakes Do Teams Make in Build or Buy Decisions?
We see over-engineering non-core features, underestimating integration complexity, ignoring the long-term costs of free tiers, failing to assess vendor viability, buying core differentiation, and poorly managing lock-in. Each one either diverts resources from unique product value or traps the product in an unfavorable dependency.
About the author
Better Software Team
Product and engineering team
Better Software Team is the product and engineering team at Better Software. We build new software products and improve existing applications and systems, with deeper experience in healthcare, finance and energy.