Amazon AppStream 2.0 Monitoring Software

Focus on NICE DCV metrics such as network latency, frame rate and bandwidth at the individual session level.

AppStream 2.0 leverages a proprietary Amazon protocol using technologies acquired from the NICE DCV acquisition. Since the acquisition, Amazon has invested heavily in this protocol, including some industry leading work on audio synchronization, particularly relevant for rich media and VFX editing like applications. eG Enterprise supports deep monitoring and alerting for NICE DCV alongside all other major protocols, including:

• KPIs and metrics that provide an indicator of real user performance: network latency, frame rate and bandwidth used.
• Metrics are reported for each desktop/user session enabling rapid help and service desk service.

Retain the logon simulator and full-session simulation content. This is an important differentiator and directly supports monitoring-platform intent.

With a purpose-built logon simulator for AppStream 2.0, track desktop availability and logon performance from any location 24x7. Measure time taken for every step of the logon process from browser access, authentication, session establishment to desktop launch. Be the first to know about issues and troubleshoot whether you need to fix the problem or escalate to AWS.

Use Full Session Simulation to go beyond logon. Simulate real users accessing AppStream 2.0 delivered applications 24x7 to ensure applications and the underlying infrastructure are not only available but also performant.

Report on compliance to SLAs and compare historical performance across locations and applications.

Explain real-time dashboards, topology views, historical reporting, help-desk views and mobile access.

Using a lightweight agent on each virtual desktop, track all aspects of the experience seen by real users.

• Out-of-the box interactive dashboards provide thorough overviews with color-coded overlays alerting of detected issues.
• Rich auto-discovered topology maps allow complex application and infrastructure dependencies to be visualized.
• Out-of-the-box live and historical reports designed for a wide-range of users in an organization ensure transparency.
• Kiosk / TV-screen and help desk specific views.
• Mobile apps for iOS and Android allow access to the monitoring platform overviews on smartphones and tablets whilst on-the-move.

Retain usage, resource consumption, cost optimization, dormant resources and capacity-planning content.

• Monitor and report on application access and usage for compliance reporting and trending.
• Track and report on who logged in, for how long and what applications they used.
• Identify the top resource consuming users and what applications they use.
• Analyze application usage patterns and identify potential areas for optimizing resource usage and reduce billing.
• Improve security by identifying dormant and orphaned resources and dormant users.
• Forecast and plan for future capacity needs. Identify if additional CPU/memory resources are required for specific users.

Effective AppStream 2.0 monitoring should cover more than service availability. Monitor application launch time, user input delay, session latency, frame rate, bandwidth, session activity, resource utilization and supporting AWS services. Use synthetic monitoring to validate availability from different locations, real-user monitoring to identify user-specific issues, and historical analytics to identify capacity and usage trends. Correlating these metrics helps teams identify performance problems before they significantly affect users.

Add a concise metric list: Application launch time, logon time, user input delay, network latency, frame rate, bandwidth usage, session availability, active/idle time, resource utilization and AWS dependency performance.

Combine the existing reporting and AWS optimization content into a clear commercial use case: performance trends, application usage, resource consumption, cost optimization and future capacity planning.

eG Enterprise provides AppStream 2.0 monitoring across user experience, application delivery, protocol performance, AWS infrastructure and supporting services. Synthetic and real-user monitoring, automated baselining, anomaly detection, root-cause diagnostics and historical reporting help IT teams detect issues, troubleshoot faster and optimize AppStream deployments.