What is your primary use case for Elastic Observability?

Elastic Observability correlates different sources and teams to provide a single, unified, achievable goal for businesses. We offer Elastic Observation and security as part of our managed services to our customers.

We have our workload in the cloud, and we take the data from the workload, put it in a data lake, and then analyze it. We keep track, build down anomalies, and so on.

I use Elastic more for monitoring integration. For instance, I have OpenShift tools implemented in my company, and I have some workloads to integrate, expose APIs, and perform transformations from a source to the target application. I am using Elastic to monitor integration capabilities and track messages.

Most of the time, we use it for security, cyber security, and monitoring tools. We add monitoring to it, mostly on-premises. It won't be on the cloud.

We use the solution to collect logs. It also helps us with application performance monitoring. We use it for centralized logs and visualizing them with Grafana.

Our clients use the product for monitoring and alerting.

As we have access to all the features offered by Elastic Observability, we utilize it for APM, to provide support and manage our infrastructure, and even leverage it for our CRM needs.

We use the product to monitor our infrastructure.

We use Elastic Observability for APM, basically. Right now, it is used only for application performance monitoring. In short, it is only the APM module that Observability is looked upon for by all our customers.

We use Elastic Observability for system monitoring, server monitoring, and application monitoring. I'm working on a project wherein I use the solution for capacity planning.

We are using Elastic Observability for monitoring.

We usually use the solution in our production environment to monitor production on Rancher. I'm a DevOps engineer.

I use this product in projects that we do for other companies. We use the most updated version of the solution. We're using Elastic to get information for several points of observability and several projects and solutions. We're using it broadly in lots of systems. For each solution, we're defining the observability points and the data we want to capture in each point. We're deploying Elastic as the tool to capture the data in each of these points in these transactions, and then putting that in the database. It allows us to analyze not only the number of transactions and quantities, but also the business content of each payload of the transactions in order to have business KPIs, not just technical KPIs. We have more than 300 data capture points in several systems. This has been used by an IO monitoring team. We have two types of users: technical guys that are monitoring the stability of the systems where this tool is used, to see if we are having issues on the operation. This is the IO management team, and there are around 40 users. The second category is people related to business that are actually using this to capture business information, like the amount of transactions, credit sales, the average value of each operation, and things like that. In that sense, there are about 100 people looking at business dashboards. The use is much heavier with the first group. They are tuning systems and deploying new data capture points, etc. Although there are more people in the second group, they are using it more to get the information and use it for tech and business decisions, but they are not heavy users in that sense.

We are using Elastic APM primarily for central logging.

We basically use Elastic APM for our metrics to look at our performance. Whenever people say that there's a latency of more than a certain amount, then we just open this APM and see why exactly the latency is high. We can choose that data set, and then we can go deeper.

We use it for monitoring the application performance and development.

The primary use case for our organization is handling login events. We also utilize it for some big data use cases.