There are several ways we can minimise the impact of third party API failure on our system. Below are some key points architect should consider Have monitoring and alert in the first place so such failures are noticed early by the tech team We can implement a circuit breaker pattern Exponential backoff and retry will help We have to gracefully degrade some features of our system which are strictly based on third party API Catching of static response will minimise impact on our system to some extent We should check with the API provider if they have an alternative API for disaster recovery so our system can point to an alternative endpoint (automated DNS failover) Keep track failed transactions to queue for later processing

To start, I would check status of the third-party api to see if this was system-wide or just our problem. If it is out globally, I would reach out to the API provider support telling how soon they think it should be fixed. A backup plan would be to use cached data or an alternative API if permitted. If the third-party API is crucial to the system, I would also disable / limit a few features affected by it to reduce user impacts. I will also communicate with the stakeholders and make sure to keep an eye on the situation until the API is up again.

Verify the Issue: Confirm whether the issue is with the third-party API or your integration by checking logs and monitoring tools. Test API endpoints manually using tools like Postman or cURL.Check API Provider Status:Look for outage notifications on the API provider's status page or social media. Contact the API provider's support team for updates.Implement Temporary Workarounds Fallback Mechanisms: Switch to cached data if available and applicable. Use a backup provider or alternative service, if pre-configured. Graceful Degradation: Limit features dependent on the API, providing users with partial functionality. Display meaningful error messages to keep users informed.

To handle third-party API downtime, a resilient system design can include several best practices. Implement a circuit breaker pattern to temporarily halt requests and avoid overloading the API during downtime, combined with a retry mechanism using exponential backoff to gradually reattempt connections. For critical features, enable graceful degradation by using fallback responses or queuing data for later processing. An event-driven, asynchronous architecture with message queues can help maintain workflow, while proactive monitoring and alerts ensure quick detection of outages. Finally, caching static data can provide continuity, reducing impact on the user experience.

Ever had your AI endpoints throw a tantrum? Last week our Modal functions went dark mid-way through LangChain agent processing. Murphy's law in action! Core server logs showed our setup was fine, but the AI provider was serving 503s. Thankfully, our paranoia paid off - Redis keeping hot completions warm, RabbitMQ queueing failures, and local embeddings picking up slack. The real MVP? LangGraph orchestration playing traffic cop, gracefully routing to simpler tasks when the fancy AI got moody. Ninja tip: Keep Modal configs version-controlled with multiple AI providers ready to swap. Like having backup bands for when your headliner bails. Expensive? Sure. Better than dead air? Absolutely.

To handle third-party API outages: Diagnose the Issue: Confirm whether the problem lies with the API provider or your system. Implement Fallback Mechanisms: Use cached data or alternative APIs to maintain basic functionality. Monitor API Status: Stay updated on provider communications for resolution timelines. Communicate with Users: Inform them about the issue and expected resolution. Plan for Future Resilience: Introduce redundancy and better error handling to mitigate future disruptions.