How to Choose an Algorithm

We often associate algorithms with machine learning or number-crunching, but in reality, algorithms are at the heart of every full-stack application—from authentication and scheduling to payments and notifications. Whether you’re handling user flows, database queries, or async processes, choosing the right algorithm for your workflow can determine how fast, scalable, and reliable your app becomes.

Here’s a practical guide on how to design and choose algorithms that fit the needs of your app’s workflow.

1. Start with the Scenario, Not the Code

Every algorithm in a full-stack app starts with a scenario. Ask yourself:

• What needs to happen?

• In what order?

• What are the edge cases?

• What must never fail?

For example, a subscription-based app might need:

1. User signs up

2. Email verification

3. Payment setup

4. Assign default workspace

5. Trigger onboarding email

These aren’t just steps—they’re workflow algorithms.

Pro Tip: Write this logic as a flowchart before touching code. It helps you uncover missing states (e.g. payment failed, email bounced).

2. Decide on Synchronous vs. Asynchronous

Some parts of your workflow should be immediate, while others can be deferred. For example:

• Sync: Login auth, password reset

• Async: Sending emails, generating invoices, Slack notifications

This is where queue-based systems (like Redis, Sidekiq, Bull, or Firebase Cloud Functions) come into play.

Research Note: In distributed systems, async task handling improves performance and fault tolerance (see: Dean & Barroso, Google Systems Infrastructure, 2013).

3.Use Proven Patterns for Reusability

A good workflow algorithm often fits a known software pattern. Examples:

Workflow Need

Recommended Pattern

Chained tasks

Pipeline / Chain of Responsibility

Conditional steps

State Machine (e.g. XState)

Retry & fallback logic

Circuit Breaker

Workflow with history

Saga Pattern

For example, Stripe uses state machines to handle subscription status changes and retries gracefully in distributed systems.

4.Think in Terms of Failure and Recovery

Good algorithms assume things will break. So build for:

• Retry logic (e.g., failed webhook delivery)

• Idempotency (so re-processing a task doesn’t duplicate it)

• Rollback strategies for partial failures (e.g., if payment works but workspace creation fails)

Industry Insight: Shopify and Airbnb use the Saga pattern to manage multi-step workflows with rollback on failure across microservices.

5.Measure and Refactor

Once your algorithm is live, track it. Use logs, metrics, and performance tracing.

• How long do tasks take?

• Where are users dropping off?

• What percentage of workflows fail?

Use these insights to optimize. Sometimes, replacing three microservices with one consolidated function improves speed and reliability.

Final Thoughts

Choosing or designing an algorithm for your app isn’t about picking the “best” one—it’s about crafting a workflow that aligns with your product’s logic, your user’s experience, and your system’s architecture.

Start with the real-world flow, decide what should be sync vs async, and build using repeatable patterns that are fail-safe. The goal? A workflow that’s not just functional, but dependable, scalable, and clear for your team to maintain.