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Third-Party Service Integration: Best Practices and Risk Management

Integrating with third-party services has become a critical component for businesses looking to save development time and improve their product. By leveraging third-party services, companies can access a range of features — such as payment processing, user authentication, data analytics, and social media integration — that would be costly or time-consuming to build from scratch. While most are standardized and relatively straightforward to integrate, it’s essential to recognize that any instability or downtime in these external systems can directly affect our own applications. Consequently, by using these systems, we assume all associated risks. Let’s explore these risks further and see how we can minimize them.

Choosing the service

Assuming you already know what problem some third-party is supposed to solve, get a list of services that meet the business requirements, and evaluate them based on the following:

• Cost — Make sure that paying for a service is worth it over just developing it yourself, look at the service cost, functionality scope, development cost and internal resource availability. Be thorough when evaluating costs, be aware of any scaling or hidden costs as each provider might have their own way of increasing costs with time/usage.
• Risks — You are relying on an external company whose changes can directly impact your system. Over time, you will need to invest additional development resources to handle version updates, new features, and potential breaking changes. This dependency means you must be prepared for unexpected adjustments, which can lead to increased maintenance costs and possible disruptions to your service.
• Security — When integrating with a third-party service, it’s essential to thoroughly evaluate the security measures they have in place to protect your data. Investigate where your data is stored, how it’s stored, and whether it’s encrypted both in transit and at rest. Check their authentication methods, whether they use more secure options like Multi-Factor Authentication (MFA), OAuth, or something less secure. Review the provider’s compliance with security standards, relevant laws, policies, and examine their history of security issues to ensure they maintain high levels of protection for your data.
• Privacy — Check what data is required of you to provide, some providers prefer to get paid in customer data over money.
• Documentation — Insufficient or inaccurate documentation will drastically increase your development time or block you entirely. Documentation’s quality might be a reflection of the overall product quality.
• Choosing the integration — When selecting how to integrate with a third-party service, consider the available options such as APIs, Azure/AWS connectors, and ready-to-use SDKs or packages. While APIs and connectors from established platforms like AWS and Azure are typically reliable, you should be cautious when using SDKs or packages from unknown developers or third parties.
• Performance — Depending on your use case, you might want the best performance there is, but be aware that you might not need all that performance, so think about how performant it needs to be. Conduct stress testing to ensure it meets your performance requirements under expected workloads. This proactive testing helps identify potential bottlenecks.
• Reliability — Having confidence in the reliability of the service will save you a lot of headaches and time. Using unreliable services will force you into handling unexpected errors and downtimes. If your project is dependent on the service and can’t accept any downtime, you will need to develop something to handle that. Even if a service claims to be reliable, approach with the assumption that it is unreliable, we don’t want to leave anything up to chance.
• Rate limits — If you’re expecting high traffic, make sure the service can support it. If rate limits exist, ensure you implement logic in your application to manage these constraints, for example caching, retry with exponential back-off, throttling, queueing, batching, etc.
• Customer support — Responsive and competent customer support will get you out of some sticky situations, though the risk of getting into these situations is lowered by the documentation quality, high security scores, reliability and other non-functional requirements. On the other hand, customer support is often a part of a higher cost subscription package.
• Beyond marketing — Don’t blindly trust the marketing material, client testimonials and community feedback can provide valuable insights. Just go and search through the internet comments, you might get valid insights.
• Legal aspect — Carefully review the Terms of Service and ensure compliance with data protection laws, such as General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA) and the upcoming Cyber Resilience Act (CRA).
• Pre-integration testing — You can never be sure how something will work in practice, as something might be different than the marketing and documentation. So create a proof of concept that covers the main functionality to confirm your beliefs and uncover issues. After confirming that you are happy with the functionality, do some stress testing before committing to your choice. Essentially, make sure it fits your needs with the aforementioned proof of concept.

Implementation

Now that you have made your choice, let’s get to integrating. Your projects’ architecture will dictate where and how the code for using these services will look like. Most likely you have some form of an infrastructure layer that will contain code for using the services.

Diving into some implementation details. Different services will have different ways to respond with errors, whatever it is you will want to convert that to your error handling mechanism (result pattern, exceptions, tuples, etc.). This is done so when using these throughout your project, your code will stay consistent and be easy to work with.

Retry Mechanism

Third-party services may experience temporary failures (e.g., timeouts, transient errors). Implementing retries ensures that your application can handle these issues.

You can use an exponential back-off strategy to retry failed requests. Exponential back-off increases the delay between each retry attempt, reducing the risk of overloading the third-party service. Define a maximum number of retries to avoid infinite loops or long delays for users.

Retries will not help you if there is a longer downtime of the service, for look into caching or fallbacks.

Caching

Caching improves performance and reduces the number of requests sent to the third-party service, which helps stay within rate limits and lowers latency by serving responses faster. This is particularly important for frequently accessed, unchanging data.

Implement caching by storing the results of frequently accessed responses in-memory (e.g., Redis, Memcached) or in your database for a defined period. When a request is made, first check the cache for a valid response; if none is found, make a call to the third-party service and store the response in the cache.

Define a Time-to-Live (TTL) for cached data to ensure it is valid. Be careful with data that changes frequently, you might want to set very low TTL or even none. Be mindful of your infrastructure capacity for this data.

Fallback

A fallback mechanism can maintain continuity in your application’s functionality, even when a third-party service fails or becomes unavailable. By having fallback solutions, you can ensure a consistent user experience and reduce dependency on external services. Consider the primary functionality that relies on the third-party service and design alternative pathways to deliver a similar or equal experience.

Sometimes, offering a reduced version of your feature set is better than interrupting the entire service. Design your app to gracefully degrade, if a third-party service fails, allow the application to continue operating in some capacity until it is restored.

Throttling

Throttling protects both your system and the third-party service from excessive traffic, which could lead to service disruption or being rate-limited by the provider. This is especially important if your application experiences sudden spikes in traffic.

Implement throttling by limiting the number of requests sent within a given time frame. Be aware of the third-party service’s rate limits and adjust your throttling rules accordingly. During throttling you can serve cached data or display messages that the service is temporarily unavailable. Throttling can be implemented in multiple places within your system, be aware that if implemented in the wrong place, some parts of your system will go around the throttling and be left out of check.

Scheduling

Some tasks, such as syncing data between your system and the third-party service, can be performed on a scheduled basis to optimize resource usage and reduce load during peak hours.

Use job schedulers (e.g., cron jobs, or cloud-based services like AWS Lambda or Azure Functions with time triggers) to automate periodic tasks like data synchronization and batch processing. Ensure that scheduled jobs have error-handling logic and alerting mechanisms if they fail.

Batching

Instead of making multiple small requests, batching allows you to combine several requests into one, reducing network overhead and improving efficiency, especially when dealing with rate limits or bulk operations.

This may increase latency, so be mindful of waiting to accumulate enough data for your batch size. This can be an issue for time-sensitive operations. Batching possibility is dependent on your context and the third-party service support for it.

Versions

You’re done with writing your code and are able to use the service, but that’s not it. These services are subject to change, so let’s do something about these potential changes that could cause issues.

Write integration tests, make sure the service is doing what you are expecting it to do. As the service changes there will be different versions of it available, our tests will come in handy here. Usually the service will have some sort of versioning available (e.g., /v2/… in URLs), so as the service releases new versions you will keep using the old one. This is a good thing, automatically accepting updates to your production environment can bring breaking changes.

To avoid this, create some mechanism for updating versions, be it manual or automated you need to run your tests with the new version and if they pass update the version.

Monitoring

Even if you do everything right and make all the right decisions, some risk will always be there. Now if something goes unexpectedly, let’s be aware of it so we can act proactively. Implement some passive monitoring:

• Availability monitoring — Do regular checks to verify that the service is available, if not you can trigger your mechanisms when it is down.
• Performance monitoring — Take note of the average latency, longest 1% and the exceptionally high spikes. This will help you predict your own performance while using the service.
• Error monitoring — Monitor the rate of different types of errors (e.g., HTTP 4xx client errors and 5xx server errors) returned by the service. This can highlight issues like unauthorized access, not found errors, and server-side problems. This can uncover some design or usage issues.
• Usage monitoring — Track the number of requests you are making to a service. By doing this you can make sure you are staying within the rate limits and can optimize costs.
• Logging — Log the request and response when running into errors, this will help you resolve issues quickly.

Active Monitoring proactively tests third-party services by regularly sending synthetic requests:

• Synthetic Testing — Simulate key user actions to catch potential issues early.
• Heartbeat Checks — Regularly ping endpoints to verify connectivity.
• Transaction Monitoring — Simulate complete workflows to ensure critical functions work smoothly.
• Load Testing — Test the service with your expected peak-loads.

Cloud solutions like Amazon CloudWatch, Azure Monitor, Google Cloud Monitoring, Datadog, and New Relic offer out-of-the-box monitoring for third-party integrations with features like synthetic testing, uptime checks, and custom metrics, enabling proactive and responsive tracking.

Conclusion

Integrating third-party services can enhance your product by saving development time and providing access to specialized features. However, these benefits come with risks that must be managed carefully. Successful integration goes beyond simply connecting services — it requires a strategy focused on risk management, security, and long-term performance.

By thoughtfully selecting services and implementing strong safeguards, you can leverage external tools while maintaining control over your product’s reliability. This approach ensures that your product remains adaptable and resilient in a constantly evolving industry.