Your application relies on a third-party API. How do you handle it when it unexpectedly fails?

To handle unexpected failures of a third-party API: 1. Error Handling and Logging: Capture and log errors. 2. Retry Mechanism: Implement retries with exponential backoff. 3. Circuit Breaker: Stop repeated failed attempts temporarily. 4. Fallback Mechanism: Use cached data or defaults. 5. Graceful Degradation: Maintain core functionalities. 6. Timeouts: Set reasonable request timeouts. 7. Monitoring and Alerts: Detect and respond to issues in real-time.

Error handling is very crucial for any API. Incase of any error, the API should provide the below details 1. Send response with the correct HTTP status code. 2.Provide info on the reason for failure. 3.Log the failures or send it for retry mechanism. 4.Use Circuit breaker if there is any downtime failures in the downstream API's. 5.Redirect request to a fault tolerant service if applicable

1. Error Handling: Catch failures gracefully with fallbacks like cached data and log errors. Communicate issues clearly to users. 2. Redundancy Plans: Use multiple APIs or local storage to ensure functionality during outages. Plan for redundant systems. 3. Monitoring Systems: Implement monitoring to detect API issues and track performance. Act quickly on alerts. 4. Communication Strategy: Inform users of issues and recovery steps through notifications and updates. 5. Failover Techniques: Use automatic failover to backup services and test regularly. 6. Recovery Procedures: Sync data and verify API functionality post-recovery to minimize data loss.

If a third-party API fails, have a backup plan. Use retries, show friendly error messages, and log the issue to fix it later. Always have a plan B to keep your app running smoothly.

That a big issue, It could be fatal. The first question here, is how did you connect to this API? Is there an easy way out to change to a working API? your response time to your customers matters here. In reality, third-party API connectivity is beyond your quick response unless the third-party provider has an alternative. Ultimately it's good to rely on a secure and trusted platform.

Redundancy in the cloud-native era can be implemented using fallback availability zones, and multi-region setups. This will require extra effort if you are trying to scale up across multiple regions and have low latency requirements in each region, but it is worth it.

One time at work, we faced frequent issues with a third-party API. We implemented multiple API providers for the same service, automatically switching to an alternative when the primary API failed. In my experience, local caching of essential data is crucial. This way, if the API goes down, your app can still function using recent data. Another strategy I’ve used is load balancing across different regions to ensure that if one region's service is down, another can take over. Geo-redundancy is also valuable, where critical systems are duplicated across various geographic locations, enhancing resilience against regional outages. These redundancy plans ensure your application remains operational during API outages.

While all of the suggestions are important, I would also look at a caching solution clearly identifying the time to live. This will not only provide the required data at the time it is needed, but also cut down on the actual API calls which may save money and resources, as well as allowing it to work without a live reliance on the API. Just something to add.

Setting up a continuous alerting/monitoring system is very crucial for your applications. It gives the alerts right when something starts failing so a hard and longer downtimes can be prevented. It not only alerts but as well can give us the details about the logs and the failures causing the issue. This will help us to navigate to the root cause at the earliest and avoid any further damages. I have an experience using Datadog for monitoring which not only tells us the traffic patterns flowing or if there are any odds in a specific time but also the Live Logs are quite useful. Datadog will also send alerts of the potential sudden large spikes or if anything's gone completely down.

Any API calls should have monitoring in place. Use monitoring to detect not only the obvious hard downtime but issues indicating impending failures: - Higher than normal latency - Errors and retries - Unexpected payloads And keep up to date on API versioning and deprecation notices. The key is to catch impending errors before hard downtime.

Inline monitoring should be included in your applications as they are best placed to understand reasons for failures from a business and internal context. Create monitoring functionality that can express technical issues but also highlight impacts from a business context as well.

In my experience, implementing real-time monitoring tools like Prometheus and Grafana is invaluable. These tools not only track uptime but also measure API response times and error rates, providing a comprehensive view of performance. One thing I’ve found helpful is setting up alerts for specific thresholds, such as latency spikes or increased error rates, which enables proactive responses before users are affected. I've also used synthetic monitoring, which involves sending regular test requests to the API to ensure it's functioning correctly and within acceptable performance limits. Another useful approach is log aggregation with tools like ELK Stack, helping to identify patterns and recurring issues with the third-party API.

Effective communication during API failures is crucial. Consider implementing a tiered notification system: - Immediate automated alerts for critical issues - In-app status indicators for ongoing problems - Dedicated status page with real-time updates - Proactive email notifications for prolonged outages Avoid jargon and overly technical terms in error messages. Acknowledge the issue, explain the impact, and, if possible, provide workarounds. Users understand systems can fail, but when they do, they want clear, concise, and jargon-free error messages.

In my experience, integrating status pages like StatusPage.io can centralize communication during API outages. These pages provide real-time updates to users and stakeholders, reducing support ticket overload. One thing I’ve found helpful is templated responses for customer support teams. These predefined messages ensure consistency and accuracy in updates across different communication channels. Using incident management tools such as PagerDuty or OpsGenie facilitates coordinated responses and escalation workflows during API disruptions. Regular post-mortem reviews after incidents help refine communication strategies and improve response times in future outages. This iterative approach builds user confidence and loyalty.

One fateful day, the API faltered, leaving my users stranded. But our failover techniques sprang into action like an emergency response team. With a load balancer at the helm, traffic seamlessly diverted to a secondary API, keeping our services running without a hitch. It was a testament to preparedness—our standby system quietly kicking in to save the day, ensuring continuity and restoring confidence in our digital haven.

In my experience, active-passive failover setups are effective. Using Azure Traffic Manager for DNS-based failover automatically directs traffic to a secondary API endpoint during primary API failures. Azure Application Gateway with health probes ensures continuous monitoring, automatically redirecting traffic when the primary API is down. Circuit breaker patterns with libraries like Polly in .NET provide resilience, temporarily halting requests to failing APIs and using alternatives. Chaos engineering experiments in Azure DevTest Labs simulate failures to validate and strengthen failover strategies proactively.

I've navigated the turbulent waters of third-party API failures with well-orchestrated recovery procedures. When our critical API unexpectedly went offline, our application gracefully switched to a cached data mode, keeping essential functionalities alive. Behind the scenes, automated alerts fired off, notifying our team of the outage. We swiftly activated our recovery playbook: syncing cached data with the API upon its return, ensuring no transactions were lost. Rigorous testing validated the API's full functionality before traffic resumed, seamlessly restoring our application to its robust operational state.

An external API and indeed every resource your application consumes WILL FAIL at some point. There's a reason why services claim 99.99 uptime, not 100%. That single failure could be catastrophic under the right (pun intended) conditions. Ok, it could at least inconvenience that one user. The diligent way to build is to anticipate errors by identifying probable points of failure and 'catching' them. My goto steps: 1. Identify probable points of failure. 2. Catch for the possible error, log it. The more specific, the better the recovery action taken where possible. 3. Determine who needs to know (starting from the user) and alert accordingly. Customize feedback per consumer to make them useful: technical vs non-technical.

Back up services…but that stacks up in terms of cost but the current pricing models of pay-as-you-use helps…just design to consumer multiple APIs or services from the ground up

Perfect, I would only add that in your feedback you should try as much as possible to suggest next steps, or work arounds if possible. This applies to both technical and even more to non-technical feedback.

API-based errors can originate at the client-end or the developer-end. It can also impact one or more different levels such as code, system and services. In my experience, the best way to handle unexpected failure is to plan for it at the onset of the project. This helps to reduce panic and avoid further issues when responding to the event. In the case where the issue source is outside the control of the team, it can be debilitating. It is important to check for any security breaches caused by the API failure as well as review the compensation plan provided by the vendor.

Look for alternatives. Do you really need to use cloud APIs for mission critical tasks? On-device, edge computing is complementing and even replacing cloud APIs in many cases.