Use case scenarios

Obcerv solves some of the following pain points:

Log investigation

I need to investigate and see if the same error is in my other logs.

Large amounts of log data collected from log monitoring can be stored in Obcerv. Together with log data, Obcerv also has the ability to store and analyse metrics. This means a shift from monitoring error messages and log files to investigating problems across your IT estates. You have more visibility on patterns such as if similar problems have happened elsewhere, how many times has a particular error occurred before, and whether errors happen at a particular time of day. This reveals helpful context in identifying entities, attributes, and keywords that trigger alerts.

Logs use case

For more information, see Logs.

Alert aggregation

Help me reduce noise from all of my monitoring tools.

On any given day, monitoring tools can generate hundreds and hundreds of events. This is too much noise for any user who only wants to quickly sift through data and do what must be done. With Obcerv, you can group events together, search for affected entities, and look for entities that produce the most noise. Identifying and reconfiguring rules and thresholds can help reduce the alert fatigue.

Alerting use case

For more information, see Alerting.

Centralized dashboarding

Other teams need to see the Key Performance Indicators from my applications health.

With Obcerv, you can create and easily share native and Grafana dashboards with others. Since both logs and metrics are available in the same dashboard, more users can appreciate the rich sets of data and insights from Obcerv. Obcerv forecasting algorithms can also analyse historic data for future predictions. This in turn opens up possibilities for answering questions such as: what does normal behaviour look like? When will the threshold break? What can a single metric forecast for the day or the week?

Dashboards use case

For more information, see Dashboards and Grafana app.


I need a display to help me understand relationships between alerts coming from my different systems.

From a single pane, you’re provided with a high-level overview of your IT estate. Status indicators quickly inform of the overall health of your IT operations. You can customise which entities are monitored by Obcerv and drill-down into detailed metrics. Furthermore, through the Overview app’s Hierarchy and Classification functionalities, you can define rules and organise entities for targetted monitoring.

Overview use case

For more information, see Overview.

Capacity Planner integration

I need to efficiently get all my monitoring data into Capacity Planner to help me identify savings or potential outages.

With one-click sync from Obcerv, you can send all relevant data to ITRS Capacity Planner. Through the Capacity Planner app, you can easily publish data (such as CPU, memory, and disk utilisation) from Obcerv to a Capacity Planner instance. Obcerv boosts capacity planning capabilities by aggregating multiple data sources, such as Geneos, OP5 Monitor, AWS EC2, Kubernetes nodes, and Azure virtual machines.

Capacity Planner use case

For more information, see Capacity Planner app.

Interoperable data storage and access

Open-source tools only provide one piece in the storage system we need.

Since Obcerv is deployed in a Kubernetes platform, you can take advantage of the extensible nature of Kubernetes to easily install, expand, and manage deployment. The Obcerv platform uses scalable APIs at both ends–from sending data into Obcerv to exporting data for consumption. Obcerv gives you more control to decide on which data to publish to the platform. This lets you manage the scale of data storage vis-a-vis the huge amount of data collected from monitoring.

For more information, see Data Model.

["Obcerv"] ["User Guide"]

Was this topic helpful?