API integration is the process of connecting two or more software systems through their APIs so they can exchange data. That definition fits on a sticky note. What it leaves out: authentication takes longer than you'd expect, every API structures data differently, and edge cases will consume more time than the happy path ever did.

This guide skips the "APIs are like waiters" analogies and covers what actually happens when you build and maintain integrations. You're here because you need to connect System A to System B, and the documentation makes it sound simpler than it actually is

How API Integration Actually Works

Every API integration follows the same sequence:

1. Authenticate. Prove you're allowed to access the system.
2. Request. Ask for data or send data to a specific endpoint.
3. Receive. Get a response, ideally with the data you wanted.
4. Handle errors. Deal with everything that goes wrong.
5. Repeat. Keep the data flowing as systems change over time.

In practice, say you want to pull a contact from a CRM:

GET https://api.somecrm.com/v1/contacts/12345
Authorization: Bearer eyJhbGciOiJIUzI1NiIs...

The API returns something like:

{
  "id": "12345",
  "first_name": "Sarah",
  "last_name": "Chen",
  "email": "sarah@company.com",
  "created_at": "2024-03-15T09:30:00Z",
  "custom_fields": {
    "lead_source": "webinar",
    "score": 85
  }
}

One endpoint, one response. Now add dozens of endpoints, OAuth token refresh logic, rate limit handling, and the fact that created_at might be createdAt or date_created in other systems. Integration work expands to fill the time you didn't budget for it.

The Building Blocks

REST APIs dominate. Around 80% of web APIs follow REST conventions, using standard HTTP methods (GET, POST, PUT, DELETE) and returning JSON. Salesforce, HubSpot, Stripe, Slack: if it's a modern SaaS platform, it exposes a REST API.

Webhooks flip the model. Instead of your system polling for updates every few minutes, the external system pushes data to you when something changes. A payment succeeds, a form gets submitted, a ticket gets updated. The event fires, and you receive it instantly. Less load on both systems, real-time data. The tradeoff is that you need to expose an endpoint, validate incoming requests, and handle retries when your server is down.

Authentication varies wildly. Some APIs use simple API keys passed in a header. Others require OAuth 2.0 with token exchange flows, refresh tokens, and expiration handling. Enterprise systems might need SAML or custom auth schemes. Budget time for this. It's rarely the 10 minutes the docs suggest.

The Three Integration Approaches

When you need to connect systems, you've got three paths. Each has real tradeoffs.

1. Point-to-Point (Build It Yourself)

You write custom code to connect System A to System B. Direct API calls, custom data mapping, and your own error handling.

When it makes sense:

• One or two integrations that are core to your product
• You need deep customization, the API doesn't natively support
• You have engineering resources to build and maintain it

What you're signing up for: Every integration you build is another thing to maintain. APIs change. Deprecations happen. That Slack integration you built two years ago? The API version it uses is getting sunset. Multiply that by 15 integrations across your stack, and you've got a part-time job nobody budgeted for.

2. iPaaS and Low-Code Tools

Platforms like Zapier, Workato, Tray.io, and Make let you connect systems through visual interfaces. Drag, drop, connect, map fields.

When it makes sense:

• Simple workflows: "When X happens, do Y.”
• Non-engineers need to build automations
• Speed matters more than customization

Where it breaks down: These tools work great until they don't. Complex conditional logic gets awkward in visual builders. Debugging a failure midway through a 12-step workflow means clicking through screens instead of reading logs. Costs scale with usage, so high-volume integrations get expensive fast.

3. Unified APIs

A single API that normalizes data across multiple platforms. Instead of building separate integrations for Salesforce, HubSpot, Pipedrive, and Zoho, you build one integration against the unified API. It handles the translation.

Tools in this category include Apideck (CRM, HRIS, accounting, file storage), Merge (HR and recruiting focus), Codat (accounting and commerce), and Finch (payroll and benefits).

When it makes sense:

• You're building a product that needs to integrate with many systems in the same category
• You don't want to become an expert in 30 different API schemas
• Maintenance burden is a genuine concern

The tradeoff: You're adding a layer between you and the source system. The unified schema might not expose all the fields you need. Custom objects and edge-case functionality sometimes require direct API access. But for standard use cases, the time savings are significant, especially when customer number ten asks for "just one more CRM integration."

What Actually Goes Wrong

The happy path is easy. The rest of your time is spent on these problems.

Authentication Complexity

OAuth 2.0 sounds standardized until you implement it across five different providers. One uses client_credentials flow, another requires PKCE, a third has refresh tokens that expire in 30 days, while the rest last 90. Token storage, refresh logic, and revocation handling: this is infrastructure work that has nothing to do with the actual data you're trying to sync.

Rate Limiting

Every API has limits. Salesforce gives you a daily call budget. HubSpot throttles per 10-second windows. Shopify uses a leaky bucket. Hit those limits during a critical sync, and your integration stops working.

You need queuing. Exponential backoff. Retry logic. And monitoring to know when you're approaching limits before you hit them.

Schema Inconsistency

Here's what a "contact" looks like across three CRMs:

System A:

{"firstName": "Sarah", "lastName": "Chen", "emailAddress": "sarah@co.com"}

System B:

{"name": {"first": "Sarah", "last": "Chen"}, "emails": [{"value": "sarah@co.com", "primary": true}]}

System C:

{"full_name": "Sarah Chen", "contact_email": "sarah@co.com"}

Same concept. Three different structures. Your integration code becomes a translation layer, mapping fields, handling nulls, deciding what to do when System B has multiple emails and System A only accepts one.

Maintenance Burden

APIs aren't static. New versions ship. Fields get deprecated. Endpoints change. That integration you built and forgot about? It'll break eventually, usually when someone important is demoing to a customer.

Versioning strategies vary. Some APIs let you pin to a version indefinitely. Others force upgrades on a schedule. Either way, you need a process for tracking changes and updating your code.

Error Handling

Things fail. Servers return 500s. Connections time out. You get rate limited. A record you're trying to update got deleted between your read and write.

Good integrations handle this gracefully. Retry transient failures with backoff. Log permanent failures with enough context to debug. Make operations idempotent so retrying a failed request doesn't create duplicate records. This isn't glamorous work, but it's the difference between an integration that works and one that "works."

Security and Compliance

Authentication gets you in the door. Security keeps you from getting kicked out.

Secrets management is the first concern. API keys and OAuth tokens shouldn't live in your codebase, environment variables on developer laptops, or Slack messages. Use a secrets manager (AWS Secrets Manager, HashiCorp Vault, or your platform's equivalent). Rotate credentials on a schedule and immediately after any team member leaves.

Transport security means TLS everywhere. If an API offers HTTP alongside HTTPS, use HTTPS. Validate certificates. Pin them if you're paranoid and the API is critical.

Data handling gets complicated when you're syncing PII across systems. Know what data you're pulling, where it's stored, and who can access it. If you're operating in the EU, GDPR applies to that customer data flowing through your integration. California users bring CCPA requirements. Healthcare data means HIPAA. Your integration code doesn't exist in a compliance vacuum.

Audit logging matters more than you think. When something goes wrong, or when a customer asks "who accessed my data and when," you need answers. Log API calls with timestamps, user context, and enough detail to reconstruct what happened.

Testing Before Production

The "build it and ship it" approach fails predictably. APIs behave differently under production conditions than they do in development.

Use sandbox environments when available. Most major platforms (Salesforce, Stripe, HubSpot) offer sandbox or test accounts. Use them. Create test data that covers your edge cases, not just the happy path.

Mock responses for APIs without sandboxes. Tools like WireMock, Mockoon, or Prism let you simulate API responses locally. This also lets you test error handling without waiting for real failures.

Contract testing catches breaking changes before they hit production. If the API you depend on changes its response format, contract tests fail. Pact is the common tool here. It's more setup than mocking, but it's insurance against silent failures.

Load test your integration before high-volume usage. That rate limit you read about in the docs? Find out where it actually bites. Test with realistic data volumes, not the three records in your dev environment.

Data Consistency and Caching

Data moves between systems. Sometimes it doesn't arrive. Sometimes it arrives twice. Sometimes System A says "Sarah" while System B says "Sara" and you need to decide which one wins.

Eventual consistency is the norm for distributed systems. Accept that data won't be perfectly synchronized at every moment. Design your integration to handle temporary inconsistencies without breaking.

Caching reduces API calls and helps you stay under rate limits. Cache reference data that rarely changes (product catalogs, user lists). Invalidate caches when you receive webhooks indicating changes. Be explicit about cache TTLs and document them.

Conflict resolution needs a strategy. Last-write-wins is simple but loses data. Timestamps help but clock drift exists. Some integrations need manual conflict resolution queues. Decide your approach before you're debugging a production incident at midnight.

Idempotency keys prevent duplicate operations. If a request fails mid-flight and gets retried, an idempotency key ensures you don't create two records or charge a customer twice. Many APIs support this natively. For those that don't, build it into your integration layer.

API vs. Everything Else

If you're evaluating integration approaches, you'll hit these comparisons.

API vs. Webhooks

APIs are pull-based. Your system asks for data when it needs it.

Webhooks are push-based. The external system sends data when events occur.

Use APIs when: You need to query historical data, fetch specific records on demand, or the external system doesn't support webhooks.

Use webhooks when: You need real-time updates and the source system supports them. Handle delivery failures carefully. Most webhook providers retry, but if your endpoint is down for hours, you might miss events.

In practice, most integrations use both. Webhooks for real-time updates, API calls to backfill or fetch additional data.

API vs. EDI

EDI (Electronic Data Interchange) is the legacy standard for B2B data exchange, especially in retail, logistics, and healthcare. It's batch-based. Files get generated, transmitted (often via FTP or VAN), and processed on a schedule.

APIs enable real-time, on-demand data exchange.

EDI still exists because: Entire industries have decades of infrastructure built around it. Walmart isn't ripping out their EDI systems tomorrow.

APIs are winning because: Real-time visibility matters. E-commerce moves fast. Modern systems expect instant data.

Many B2B companies run both: EDI for legacy partners, APIs for everything else.

REST vs. SOAP

SOAP is the older protocol. XML-based, strict contracts via WSDL, built-in standards for security and transactions.

REST is the modern default. Lighter weight, uses JSON, relies on HTTP conventions, easier to learn and implement.

SOAP still appears in: Enterprise systems, financial services, legacy integrations that haven't been modernized.

REST is standard for: Basically everything else. If you're integrating with a SaaS platform launched after 2010, it's REST.

You can read the detailed guide on REST vs. SOAP here.

SFTP vs. API

SFTP is file-based batch transfer. Generate a CSV or XML file, drop it in a folder, let the other system pick it up and process it.

APIs are live connections. Request data, get a response.

SFTP works for: Large batch exports, systems that genuinely can't support APIs, scenarios where you need a full data dump.

APIs work for: Everything that needs to happen in real-time or near-real-time, which is increasingly everything.

Building Your First Integration

If you're about to build an integration, here's the sequence that actually works.

1. Read the Docs (Actually Read Them)

Not skim. Read. Find the authentication section. Find the rate limit policy. Find the API changelog. Identify whether they version their API and how. Fifteen minutes here saves hours later.

2. Get Authentication Working First

Before you write any business logic, get a successful authenticated request. Use Postman, curl, whatever. Just prove you can get a 200 response. OAuth flows in particular have a way of eating entire afternoons when you try to figure them out while also building the actual integration.

3. Map Your Data

What fields do you need from the source system? What format does the destination expect? Build a clear mapping document. Decide upfront how you'll handle missing fields, type mismatches, and fields that exist in one system but not the other.

4. Handle Errors Like They're Inevitable

Because they are. Wrap API calls in retry logic. Log failures with request/response details. Build alerts for repeated failures. Make your operations idempotent where possible. If a request fails halfway through and gets retried, it shouldn't create chaos.

5. Monitor in Production

An integration that "works" in development will eventually fail in production. Different data volumes, different edge cases, different timing. Set up monitoring. Know when requests start failing before users report it.

When to Build vs. Buy

Build custom when:

• The integration is core to your product's value proposition
• You need functionality that the API exposes, but no existing tool supports
• You have the engineering team to build and maintain it long-term
• You're integrating with one or two systems, and they're unlikely to change

Use a platform or unified API when:

• You need to integrate with multiple systems in the same category
• Speed to market matters more than absolute customization
• You don't want to become an expert in 15 different API schemas
• Your team would rather spend time on product features than on integration maintenance

There's no universal right answer. But be honest about the maintenance cost. That "quick" custom integration still needs someone to fix it when the API changes, handle the support tickets when syncs fail, and build the new integration when your fifth customer uses a CRM you don't support yet.

Conclusion

API integration connects systems. That's the simple version. The full version involves authentication headaches, schema translation, error handling, rate limits, security considerations, and ongoing maintenance. But get it right, and data flows where it needs to go, processes are automated, and your systems actually talk to each other instead of existing as isolated islands.

The choice isn't whether to integrate. It's how much time you want to spend on plumbing versus building the thing your users actually care about.