9.1.3 Using Analytics for Capacity Planning and Performance Optimization

Analytics module delivers the granular data necessary to support data-driven decisions regarding infrastructure scaling and resource allocation.

Leveraging Analytics for Capacity Planning

Analyzing Historical Session Trends: Administrators can review session history to identify patterns such as peak usage periods, average session durations, and concurrent session loads. This is key information for increasing the availability of VDI instances and maintaining performance.

Monitoring Connection Behavior: Connection data—including frequency, timing, and source IP addresses—provides valuable insight into access patterns across the organization. Recognizing when and from where users typically connect allows for proactive scaling of Gateway and Broker resources to handle anticipated traffic spikes and maintain seamless user access.

Evaluating Login Activity: Login attempts data, particularly successful authentications, acts as a real-time barometer of platform usage. Spikes in login activity can highlight periods of elevated demand, prompting timely adjustments in system capacity. On the other hand, patterns of failed login attempts may uncover access issues or security anomalies that could impact system load indirectly.

Assessing Browser and Client Environments: While browser usage doesn’t directly influence capacity, understanding which browsers and versions are most commonly used can inform compatibility planning and reduce potential support issues. Ensuring optimal client compatibility also contributes to consistent performance and user satisfaction.

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Utilizing Analytics for Performance Optimization

Analytics plays a critical role in identifying and addressing performance bottlenecks. The module offers a range of data points that enable administrators to target and resolve inefficiencies within the Thinfinity Workspace deployment.

Examining Session Duration and Activity: By analyzing session durations and user activity, administrators can identify resource-intensive applications or workflows. For instance, consistently long sessions associated with particular applications might signal backend performance issues, prompting further investigation or the provisioning of dedicated resources.

Analyzing Connection Details: Connection logs within each session can reveal latency issues or protocol-related problems. Frequent connection failures or delays in establishing connections may point to network congestion or misconfigurations in components such as Gateways or Brokers.

Reviewing File Transfer Activity: Monitoring file transfers—including their size, frequency, and origin—can help assess network bandwidth utilization. High volumes of file transfers during peak hours may degrade overall system responsiveness, indicating a need for bandwidth optimization or policy enforcement to manage data flow.

Integrating Broker Monitoring for Deeper Insights: While the focus here is on historical Analytics data, it’s important to note that Thinfinity Workspace’s Broker Monitoring and Health Checks provide real-time performance metrics. Correlating these with Analytics trends offers a more comprehensive view of system health, making it easier to pinpoint root causes of performance issues and proactively maintain optimal operation.