ServiceNow Best Practices for Integration Error Handling

When integrating ServiceNow with other systems, one of the most critical considerations is integration error handling. Whether you’re connecting ServiceNow with external applications, cloud services, or legacy systems, error-free data replication is key to maintaining smooth business operations. 

However, despite your best efforts, errors inevitably occur in integrations. How you handle those errors can make the difference between a minor inconvenience and a major operational disruption.

In this blog post, we’ll explore the best practices for integration error handling in ServiceNow, and the solutions that support integration monitoring. 

We’ll also discuss how using the right integration solution—such as Perspectium DataSync—can help reduce the likelihood of errors by addressing common pitfalls associated with traditional point-to-point integrations.

ServiceNow Best Practices for Integration Error Handling

Proper error handling is essential to ensuring that your ServiceNow integrations work as expected, without causing data discrepancies or operational issues.

Below are some best practices for managing integration errors within ServiceNow:

1. Monitor Integration Processes in Real-Time

To handle errors efficiently, you must have visibility into the status of your integration processes. 

ServiceNow’s Integration Hub users have some functionality for real-time error monitoring. Users can create rules within the Flow Designer to check for errors at periodic intervals. 

Alternatively, users can retrospectively review System Logs for monitoring integration health. Both processes fall short of true real-time error monitoring as users can only get as close to real-time as the frequency of checks will allow.

Some purpose-built ServiceNow data integration and replication solutions also support periodic checks for errors, such as Perspectium’s DataSync.

DataSync also provides a dashboard that displays recent errors, as well as the status of data transfer queues.

2. Automate Error Recovery and Retrying

One of the best ways to mitigate the impact of integration errors is by building automated error recovery mechanisms.

For example, when an integration fails due to a network timeout or temporary data inconsistency, retry mechanisms can be triggered automatically to ensure the data is retried without manual intervention.

In ServiceNow, this could involve setting up scheduled jobs or leveraging Flow Designer to create retry logic for specific integration processes.

Some solutions support recovery and retrying mechanisms out of the box.

DataSync generates receipts for outbound messages that indicate the delivery status of shared records. From the Receipt Status table, users can use the Reshare Record(s) action to send another copy of the message associated with the corresponding receipt.

3. Implement Robust Logging and Alerts

Comprehensive logging is essential for troubleshooting. In ServiceNow, detailed logs can help you pinpoint the exact point of failure, whether it’s a data format issue, a system outage, or an authentication problem.

With DataSync, alerts can be triggered to notify users of failed record shares and connection errors. 

Record thresholds will trigger an alert if the number of queued records pass the indicated threshold. Connection thresholds trigger an alert if the instance fails to connect to the queue for the defined duration.

Setting up alerts ensures that relevant team members are notified immediately of integration failures. These proactive notifications help speed up the troubleshooting process, reducing system downtime and improving overall integration reliability.

Mitigating Integration Errors: The Challenges of Traditional Point-to-Point Integration Methods

While ServiceNow offers capabilities for integration error handling, the design of the integration itself plays a significant role in the likelihood of errors occurring. This brings us to a critical consideration: the integration model you choose.

Traditional integration methods, such as point-to-point APIs (including Integration Hub) and ETL (Extract, Transform, Load) tools can introduce new challenges that increase the risk of errors in integration processes.

1. Point-to-Point APIs: Multiple Points of Failure

API integrations involve directly linking ServiceNow with other systems via custom-built connectors. While this allows for flexibility, it also creates multiple points of failure and additional integrations to maintain to prevent failure.

Since APIs rely on external services, issues with authentication, rate limits, or network disruptions can all lead to integration errors.

Not only does having more integrations lead to more integrations that may fail, the competition for resources to facilitate API calls from each integration makes each integration more likely to fail.

2. ETL Processes: Complex and Error-Prone

ETL tools are designed to handle large batches of data but often require complex mapping, transformation logic, and custom configurations for each system.

As more systems are added, the integration complexity increases, leading to higher chances of mismatched data, transformation errors, or scheduling issues. Additionally, ETL’s reliance on scheduled batch jobs can result in latency between data transfers, which may lead to outdated or inconsistent data in the target system.

Both these traditional methods require constant oversight to monitor, troubleshoot, and resolve errors as they arise. This reactive approach increases the operational burden on your IT teams and slows down the resolution of integration failures.

Integration Error Handling and Reducing Integration Errors with Perspectium DataSync

While traditional integration methods focus on solving integration problems after they occur, Perspectium DataSync takes a more proactive approach.

Instead of relying on point-to-point APIs, DataSync uses a publish/subscribe (pub/sub) integration model, delivered and maintained as-a-service to significantly reduce the likelihood that errors occur.

API-Free Design

One of the primary advantages of DataSync’s API-free design is that it eliminates the need for external APIs. 

API is often at the root of integration failures and performance degradation on the platform, as the technology requires the same system resources that users require to interact with ServiceNow.

Related post: Why You Should Avoid API-Based ServiceNow Integrations

This competition can lead to significant latency in both users and connected systems retrieving data leading to time outs, and even downtime to ServiceNow itself.

DataSync avoids this issue by utilizing more efficient push technology to stream ServiceNow data into a message bus where it is queued for transfer to one or more target systems. This allows data to be streamed out of ServiceNow more quickly, in higher volumes and to more targets, without degrading performance. 

Real-Time Replication Monitoring

DataSync’s Replication Monitoring feature provides real-time visibility into the status of record replications. You can track:

• Pending Replications: See which records are waiting to be replicated.
• Successful Transfers: Confirm that data has been successfully transferred to the target system.
• Failed Replications: Quickly identify any errors and pinpoint their causes.

In the event of a failure, DataSync allows you to reprocess failed replications with just a few clicks, providing a simple and efficient way to resolve errors without needing to manually intervene or reconfigure integrations. 

The dashboard shows an overview of the status of records and queues of records. Clicking a record queue under the Shared Queues widget provides additional information – such as Queue History – that can be used to analyze the cause of errors and influence proactive solutions.

This level of error visibility and remediation makes DataSync a powerful tool for reducing the impact of integration failures.

Simplified Integration Architecture: Fewer Points of Failure

DataSync’s pub/sub model simplifies your integration architecture by eliminating the need for complex, point-to-point API connections.

Since DataSync uses a secure message bus to sync data across systems, you no longer need to rely on multiple API integrations that could each fail due to network issues, authentication errors, or API downtime. This reduces the number of potential failure points and ensures more reliable data transfers.

Further, if a data transfer fails because of an issue in ServiceNow or at the target system, data queued for transfer is not lost. Instead, it waits securely in the queue until the affected systems are again operational.

With the MBS, adding or removing systems doesn’t require significant changes to your existing integration setup. This scalability not only reduces the risk of errors due to configuration issues but also makes it easier to manage integrations as your environment grows.

Proactive Integration Error Handling with DataSync

While monitoring integration errors is a crucial part of any integration strategy, the right solution can help prevent errors from occurring in the first place.

By choosing an integration model that reduces complexity, eliminates external APIs, and offers real-time monitoring and error recovery, you can ensure smoother, more reliable integrations.

Perspectium DataSync provides a superior solution for handling ServiceNow integrations, thanks to its API-free, pub/sub design and powerful Replication Monitoring features.

By reducing the number of points of failure and giving you the tools to easily track and resolve errors, DataSync helps ensure that your integrations remain seamless and error-free.

With DataSync, you can proactively handle integration errors, reduce operational overhead, and focus on what matters most—delivering value to your organization.

If you’re looking to improve your ServiceNow integration strategy and minimize the risk of errors, talk to us is the solution you need.