Project Manager at a tech vendor with 10,001+ employees
Reseller
Top 5
Apr 15, 2026
ServiceNow Cloud Observability's main use case is end-to-end automation starting from the trigger in the cloud. Currently, it focuses more on self-healing and understanding the complete uptime of end-to-end services, particularly services and application availability rather than just servers. My focus is on enabling this by integrating it with any monitoring tools, understanding how events trigger, and handling the whole lifecycle with recent AI initiatives. ServiceNow itself has AI agents that I use as an orchestrated layer to define workflows for evaluating and taking appropriate actions, which helps reduce overall manpower and human errors. When discussing ServiceNow Cloud Observability, the major aspect is seamless integration with all enabled services and monitoring services. It allows me to look at the overall picture, capturing and integrating it with platform analytics and the numbers. It provides a real-time view of metrics and traces, enabling more real-time visibility. Looking at MTTR, earlier we were getting MTTR, but this gives us faster visibility into where we are, where the issue would be, and how we can quickly reduce the overall impact. One use case I had done recently with cloud and hybrid environments as part of transformation includes workloads still on-premises and others transitioning in three-tier architecture. When the backend remains on-premises or is hosted elsewhere and the applications or front end are on the cloud, it allows for a single-pane view to see end-to-end and correlate. Monitoring tools do help, but this gives us a placeholder to view an end-to-end application stack or workflow in a single pane of view. With a few customizations, such as integrating multiple monitoring tools for the cloud, we can either use cloud-native tools to capture and understand, notify where we see latencies, and then it also integrates with on-premises, which is more aligned with the hybrid cloud model. One of the recent features I found valuable is the plugins that ServiceNow provides, integrating it with Grafana dashboards or other open-source dashboards.
I use the solution in my company since it has multiple tenants available. Basically, what happens in business is that you have a hybrid setup model, and for that, you extensively use a cloud platform, so for that purpose, AWS and Azure are used.
We use Lightstep/ServiceNow to monitor the traces in our distributed applications and microservices. Our services were instrumented using open telemetry and then we sent the data to the configured microsatellites. We also use this tool to send alerts to our slack channels when something is not right according to our expected SLAs. This solution is used primarily for those who are working on call in our teams and need to investigate performance problems and deviations in our production environment.
Senior Software Engineer at a retailer with 10,001+ employees
Real User
Aug 30, 2023
In use cases, we have tons of microservices. So, we need observability. We heavily rely on LightStep streams for monitoring as well as alerting purposes. For example, suppose we don't expect traffic in a certain period. If we are getting more traffic, we get alerted. Basically, it is for monitoring our microservices and creating some alerts out of those so that if something goes wrong, we get alerted. We are also helpful in case of any errors because there is an option called streams, which can create it, and we can go through the streams to see what calls were made in that single request. Where was the error? What was the error? That's helpful.
Learn what your peers think about ServiceNow Cloud Observability. Get advice and tips from experienced pros sharing their opinions. Updated: April 2026.
ServiceNow Cloud Observability offers advanced monitoring and alerting capabilities, leveraging AI-driven automation and seamless integrations to enhance visibility and performance in hybrid environments.ServiceNow Cloud Observability empowers teams with real-time metrics and tracing capabilities, essential for managing numerous microservices across hybrid environments. It integrates seamlessly with popular tools like Grafana, offering a single-pane view of application health and performance....
ServiceNow Cloud Observability's main use case is end-to-end automation starting from the trigger in the cloud. Currently, it focuses more on self-healing and understanding the complete uptime of end-to-end services, particularly services and application availability rather than just servers. My focus is on enabling this by integrating it with any monitoring tools, understanding how events trigger, and handling the whole lifecycle with recent AI initiatives. ServiceNow itself has AI agents that I use as an orchestrated layer to define workflows for evaluating and taking appropriate actions, which helps reduce overall manpower and human errors. When discussing ServiceNow Cloud Observability, the major aspect is seamless integration with all enabled services and monitoring services. It allows me to look at the overall picture, capturing and integrating it with platform analytics and the numbers. It provides a real-time view of metrics and traces, enabling more real-time visibility. Looking at MTTR, earlier we were getting MTTR, but this gives us faster visibility into where we are, where the issue would be, and how we can quickly reduce the overall impact. One use case I had done recently with cloud and hybrid environments as part of transformation includes workloads still on-premises and others transitioning in three-tier architecture. When the backend remains on-premises or is hosted elsewhere and the applications or front end are on the cloud, it allows for a single-pane view to see end-to-end and correlate. Monitoring tools do help, but this gives us a placeholder to view an end-to-end application stack or workflow in a single pane of view. With a few customizations, such as integrating multiple monitoring tools for the cloud, we can either use cloud-native tools to capture and understand, notify where we see latencies, and then it also integrates with on-premises, which is more aligned with the hybrid cloud model. One of the recent features I found valuable is the plugins that ServiceNow provides, integrating it with Grafana dashboards or other open-source dashboards.
I use the solution in my company since it has multiple tenants available. Basically, what happens in business is that you have a hybrid setup model, and for that, you extensively use a cloud platform, so for that purpose, AWS and Azure are used.
We use the product for traceability.
We use Lightstep/ServiceNow to monitor the traces in our distributed applications and microservices. Our services were instrumented using open telemetry and then we sent the data to the configured microsatellites. We also use this tool to send alerts to our slack channels when something is not right according to our expected SLAs. This solution is used primarily for those who are working on call in our teams and need to investigate performance problems and deviations in our production environment.
In use cases, we have tons of microservices. So, we need observability. We heavily rely on LightStep streams for monitoring as well as alerting purposes. For example, suppose we don't expect traffic in a certain period. If we are getting more traffic, we get alerted. Basically, it is for monitoring our microservices and creating some alerts out of those so that if something goes wrong, we get alerted. We are also helpful in case of any errors because there is an option called streams, which can create it, and we can go through the streams to see what calls were made in that single request. Where was the error? What was the error? That's helpful.