ServiceNow Cloud Observability Reviews

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.

The feature of the tool that is more impactful for cloud performance stems from the area revolving around analytics and reporting. It is an easy-to-use tool. There is something known as performance analytics within ServiceNow that offers complete analytics, which offers end-to-end analytics along with the KPI metrics with what we have in place and so on. With the aforementioned aspects of the tool, I think we should be able to create a dashboard according to the operations view called the operation dashboard view, specifically for C-level executives.

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.

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.

The benefit of using this tool is to monitor latency and find out possible performance problems in our services. 

Some of our services are designed in an event-driven architecture model, and others are called directly by other services; as we deal with billions of data and calls every day, it is really important to have good tools to help us pinpoint problems faster when they happen. 

On the other side, it is hard to use different tools for each part of the observability (traces, logs, and metrics), and it would be even better if we could use only one tool for everything. 

We use the product for traceability.

In terms of code, the tool is very easy to work with. It provides good libraries. The UI is very intuitive. It helps diagnose the traces and map information. It is easy to create new streams and patterns. It is quite easy and nice to use. We use the tool to find the latency and error rate in our services.