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Rolling Review: Quest Software Foglight

Quest's offering is a bright spot in our search for truly holistic application performance management.

The Upshot


Claim
Quest Foglight provides deep insight into the service relationships that exist among end users, business services, IT resources, and critical infrastructure components such as applications and databases. Because it offers multiple data collection methodologies as well as intuitive and flexible dashboards, Foglight can provide models and views of the managed environment based on organizational roles.
Context
Most software vendors dictate a specific data collection methodology to organizations. In contrast, Quest offers the full spectrum: agents, network packet monitoring, synthetic transactions and application intelligence. IT can mix and match to build a customized service dashboard.
Credibility
Multiple data collection points and deep component integration do increase overall complexity and maintainability. Still, Foglight must be on your shortlist for holistic APM monitoring. While we look forward to tighter intra-suite integration, Quest delivers the information required to diagnose and troubleshoot pesky application performance issues.

Quest Software: Foglight

Lots of APM vendors talk about taking a holistic approach to application performance management, but the latest entry in our Rolling Review, Quest Software's Foglight, delivers. This product combines network packet capture data, in-depth analysis using intelligent agents and synthetic transactions to enable APM. The system comprises the Foglight Experience Monitor, or FxM; the Foglight Experience Viewer, or FxV; and a new implementation of the Foglight Server to offer views ranging from business services to those low-level traces only an application developer could love.

Information Week's Rolling Reviews
present a comprehensive look at a hot technology category, beginning with market analysis and wrapping up with a synopsis of our findings. See our kickoff and other reviews Application Performance Management .

Foglight's greatest strength is its ability to collect many different types of data and present it all in a meaningful way. There are literally thousands of metrics that are baselined and processed via the rules engine. Alarms may be generated when thresholds are crossed or rules are created. These alarms can be sent via several methods, including SNMP traps, or collected into dashboards. Foglight dashboards can be created easily and set to model high-level business and service views that clearly identify issues as they occur. Drill-down capabilities provide access to lower-level statistics, useful for troubleshooting. FxV offers user-session replay, click by click, for Web applications. This is incredibly valuable for diagnosing problems, as it illustrates the exact order of events that caused a performance glitch.

All that data does come with a price in terms of complexity. Still, though Foglight is not as plug-and-play as some of the other tools we've reviewed, in particular those from Indicative or Nimsoft, most IT organizations should be able to deal with the application as long as they have an effective deployment plan. Quest or third-party systems integrators are more than happy to help here, and while services costs may rival that of the actual software, the expense should be worth it.

The virtually infinite flexibility and vast amount of data collected by the various monitors can be overwhelming. To help here, Foglight Server uses models to represent services and applications. Models are the key to the system's flexibility and power because they group and assign dependencies to all metrics collected. As in other APM systems, you will require a pair of hands and some knowledge to choose the applications and services that will be modeled, then break them down into component pieces. Applicable metrics are identified along with their dependencies as each model is built. Knowledge of each component is essential, but many of the cartridges include default metrics and thresholds as a starting point.

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