Use case scenarios

ITRS Analytics solves some of the following pain points:

Alert aggregation Copied

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 ITRS Analytics, 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.

For more information, see Alerting.

Dynamic thresholding Copied

I need alert limits that follow how our metrics actually behave across trading days, batch windows, and seasonality, not one static threshold that either fires on ordinary variation or stays so loose that we miss drift until something breaks downstream.

With Dynamic Thresholds, business and operational metrics become adaptive alert boundaries instead of fixed OK, Warning, and Critical lines. The application learns from recent history, updates upper and lower bounds as patterns change, and raises signals when values depart from that learned norm in a statistically meaningful way. Monitoring stays aligned with real trading-day cycles, batch jobs, market hours, and seasonal load.

For more information, see Dynamic Thresholds.

Automated notifications Copied

I need to be notified of important alerts in my existing tool.

You do not need to be logged in and constantly reviewing the Web Console to get notified when your IT estate needs attention. With integration into third-party tools such as Slack, you can receive important messages in your preferred channel. Depending on your requirements, you can track a single entity or a group of entities and set triggers for when severity thresholds are breached.

For more information, see Notifications.

Centralized dashboards Copied

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

With ITRS Analytics, 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 ITRS Analytics. ITRS Analytics forecasting algorithms can also analyze historic data for future predictions. This in turn opens up possibilities for answering questions such as: what does normal behavior look like? When will the threshold break? What can a single metric forecast for the day or the week?

For more information, see Dashboards.

Capacity planning Copied

I need real-time capacity visibility, forecasts, and reporting so we can plan ahead, catch breaches before they hit production, and show regulators we run capacity management properly, including where SEBI regulations apply.

The ITRS Analytics Capacity app is a real-time capacity monitoring, forecasting, and reporting application that gives you operational transparency and predictive insight for infrastructure management. You can track historical performance alongside forecasted utilization, identify potential capacity breaches before they occur, and maintain service continuity while supporting compliance-oriented capacity reporting—for example, alignment with regulatory capacity management guidelines such as SEBI (Securities and Exchange Board of India).

For more information, see Capacity.

Signal forecasting Copied

Predictive forecasts, such as if my disk usage will go over 90% in the next two hours, are crucial to managing my IT operations.

Make informed decisions with ready access to usage-based and real-time forecasts on any metric of interest. The Forecaster app generates signals following the thresholds you have set. You will get relevant alerts when there is a probable or ongoing breach: choose a set of servers and a metric, select a lookback period, and then specify warning thresholds. The most suitable forecast model is automatically selected for the observed metric.

For more information, see Forecaster.

Interoperable data storage and access Copied

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

Since ITRS Analytics is deployed in a Kubernetes platform, you can take advantage of the extensible nature of Kubernetes to easily install, expand, and manage deployment. The ITRS Analytics platform uses scalable APIs at both ends–from sending data into ITRS Analytics to exporting data for consumption. ITRS Analytics 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.