SIOS iQ learns the behavior of each individual object across different metrics in the environment leveraging the principles of machine learning and topological behavior analysis. SIOS iQ identifies the anomalies in the behavior that potentially cause the performance issues to the application, correlates the anomalies to derive the relationships and determine the root cause of the problem (such as object or event), and recommends the solution to address it. SIOS iQ then presents any infrastructure component events that may affect performance through the Performance Root Cause Analysis Dashboard (Not Available in SIOS iQ free edition).
The Impact Analysis tab provides information regarding the impacted and associated object(s) for each Issue in the PERC Issue and Performance Root Cause Lists. In List View, these objects are sortable by Name, Type or Impacted status. Properties and Impact data (for impacted objects) for a specific object can be accessed by selecting it in the list and clicking the Properties or Impact button, respectively. Topology View (the default) provides a comprehensive, interactive graphical representation of the relationships among the root cause, impacted and associated objects or events, each indicated as shown in the legend. Selecting any object in the graph provides access to its Name, Type, Properties and Impact Details as shown in the given screenshot.
Symptom Graphs and Learned Behavior
SIOS iQ machine learning develops behavior patterns that appear in the Symptoms graph and Impact Analysis graph which show the learned behavior vs anomalous behavior. The highlighted Learned Behavior region (Best Practices region, when iQ is still in a learning state) represents the expected behavior of the symptom being displayed. Depending upon the Sensitivity setting selected by the user, the learned behavior and its underlying statistical features are combined to determine a decision region, where any data point lying outside this region is identified as an anomaly. Below is a sample image of a symptom graph and a summary of all of its individual parts.
- The Issue Type
- The object displaying the symptom
- The anomalous metric identified as having the most impact to the impacted object
- The history of the given metric
- The red highlighted section shows the duration of the selected event
- The blue highlighted section shows the learned expected behavior
- The observed values of the given metric
- The legend for the symptom graph
Infrastructure Event Correlation
In Performance Root Cause analysis, performance issues may be identified whose true root cause(s) consist of virtualization and infrastructure related events (such as VM migration and VM provisioning). Such events will be correlated and will appear in the list of Root Cause Objects as well as in the Symptom Graph as illustrated below.
|Infrastructure Event Type||Description|
|VM Migration event||Migrated VMs have the potential to introduce greater work load (cpu/memory usage, IOPs, etc) on underlying resource layers (Compute, Storage or Network) and may eventually cause a negative impact on the performance of the related objects (host, datastore, VM, etc).|
|Newly Provisioned VM||Provisioning of the new VM has the potential to introduce greater work load (cpu/memory usage, IOPs, etc) on underlying resource layers (Compute, Storage or Network) and may eventually cause a negative impact on the performance of the related objects (host, datastore, VM, etc).|
Utilizing the topological relationship of corresponding objects, SIOS iQ correlates VM migration and provisioning events with identified Performance Root Cause Issues and identifies whether each event constitutes a true root cause of a related performance issue.
Performance Impact Graph & Symptoms
The Performance Impact graph provides chart information and symptoms metrics regarding the Impacted and Root Cause object(s) for each issue in the PERC Issue and Performance Root Cause lists. The Performance Impact data for Impacted and Root Cause objects can be accessed by selecting Root Cause Object link on the Details tab or selecting the object on the Impact Analysis tab and clicking the Impact button.
What does that mean? And what should I do with this information?
For detailed information about each possible Root Cause event, please see the description in the Specific Issue Details topic.