April 24, 2024

Improving ServiceNow DevOps Flow: Mean Time To Resolve

Scott Willson

A key DevOps metric is MTTR, or Mean Time To Resolve an issue once detected. For ServiceNow development, MTTR takes on a different meaning than traditional software. Rather than committing code to a Git repository, ServiceNow developers complete work in a Development instance. Changes are then migrated downstream through QA, Staging, and finally, Production instance(s). Reducing MTTR is crucial but poses challenges due to this sequential process. 


Time Exacerbates MTTR

Errors detected in downstream environments mean significant delays before developers can troubleshoot and resolve them. It is much easier to resolve errors when developers are still building update sets or apps. Since the changes are still fresh in their mind, it's relatively quick to fix even complex problems. As time passes and the changes move to higher instances, developers need to remember work and context from days, weeks, or months earlier to gain the appropriate context to aid in hunting down fixes to errors.


There are two big reasons, among others, why time kills the ability to resolve errors:

  • Memory Fades - The longer the time between writing code and discovering an error, the harder it is for developers to remember what they did. Details get fuzzy, making it difficult to retrace steps.
  • Context Shifts - Developers frequently have to context switch between various projects and tasks. When a lot of time passes before an error surfaces, developers have likely switched mental contexts multiple times. Ramping back up on the code takes significant effort.


Stranger in a Strange Land

Time is not the only MTTR killer. The differences or inconsistencies between instances mean developers must troubleshoot errors in a foreign environment. Non-development instances don't have the same plugins, records, XML, or update sets. These differences must be accounted for and considered in the resolution process. Environment inconsistencies contribute to the time lag in MTTR.


Preemptive MTTR

Benjamin Franklin famously said, "An ounce of prevention is worth a pound of cure." What if you could preemptively prevent errors from happening in the first place? xtype's bidirectional synchronization provides that "ounce of prevention" to your ServiceNow landscape. xtype's controlled synchronization propagates changes in downstream instances upstream.


xtype's controlled synchronization of your ServiceNow instances ensures changes are propagated across your landscape. For example, a developer's completed update set in their Dev instance is immediately migrated to all other Dev instances. Any conflicts, errors, or unexpected behaviors are caught immediately while the changes remain fresh in the developer's mind. 


Shift Problems Resolution Left

This shift-left of troubleshooting efforts significantly reduces MTTR in ServiceNow projects. When changes can take days or weeks to reach Production environments, finding the root cause and resolving issues becomes challenging. With xtype synchronization, these issues are detected and resolved in minutes or hours because they see errors (if any) instantly in their instance and can take immediate action. 


Faster resolution of issues also leads to greater productivity. There is less need to context switch between projects or sprints within projects since most errors occur as changes are made rather than later in downstream deployments. Multiplying this efficiency across all developers results in faster delivery of high-quality updates and applications.


Shrinking the Gap

For organizations relying on ServiceNow, xtype delivers an easy way to improve MTTR. xtype's Controlled Synchronization closes the gap between Development and Production environments. It brings troubleshooting and resolution efforts to the earliest possible stage in the delivery pipeline - development. This shift-left ultimately enables faster time-to-value for ServiceNow projects. Developers spend less time firefighting and more time building innovations that drive the business forward.


Conclusion

So, in summary, by synchronizing ServiceNow instances with xtype:

  • Errors and unexpected behaviors surface instantly upon update set completion.
  • Developers see issues at the earliest point of the delivery pipeline - development environments.
  • Because all instances are as production-like as possible, ServiceNow teams resolve problems faster and produce high-quality updates and apps.
  • Errors are found in context, which reduces long MTTR due to context switching.
  • Drives accelerated delivery of higher-quality applications.


Leveraging synchronization is a simple but impactful way to achieve excellent MTTR metrics. For ServiceNow teams looking to enhance developer efficiency, xtype is an easy win. Controlled synchronization shifts troubleshooting as far left as possible, setting up ServiceNow teams for DevOps success.

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