Quest在2012年Gartner应用性能监控魔力象限中被评为领导者
Quest（已被戴尔收购）
在
2012年
Gartner应用性能监控魔力象限中被评为领导者
阅读完整的
应用性能管理报告
并详细了解我们的
APM解决方案——Foglight。
阅读报告 »

应用
性能监控

了解怎样从
业务和终端用户的角度
来改进应用性能。

马上阅读 »

技术简报

详细了解
Foglight can help you can gain
掌控对业务关键的
Java应用程序。

马上阅读 »
索取信息或接洽销售代表
想要了解更多信息？ 想索取报价？ 有何具体的产品问题？ 我们将一一为您解答。
马上开始 »

Foglight for Java

Production-ready Java EE application performance monitoring

Get production-ready application performance monitoring (APM) of your Java apps, regardless of whether problems reside in the Java code or the container. Foglight for Java helps first responders isolate application problems in the transaction path and enables java specialists to identify the root cause. With Foglight for Java, you'll have an integral component of the Foglight APM solution, a fully integrated architecture providing comprehensive end-to-end monitoring. Rely on Foglight for dynamic run-time architecture visualization, application flow maps with client browser and network response time breakdowns, end-user session replays, and linkage to supporting virtual or physical infrastructure to facilitate triage and root-cause workflows.

  • 监控从终端用户到数据库的Java性能和可用性
  • 识别可细化到违规代码行的性能和内存问题
  • 减少解决故障的平均时间（MTTR），范围覆盖整个应用程序栈
  • 利用精确的诊断功能追踪生产中发生的具体用户问题

功能

  • Production-ready 24x7 Java transaction monitoring – Improve monitoring flexibility with multi-level byte code instrumentation options to provide high value with limited overhead.
  • Real-time alerts and intuitive workflows to speed triage and diagnosis – Get alerts on slow web requests impacting end users and click through to visualize the transaction path and response time breakdown across the runtime architecture. Plus, trace individual requests for method-level details to aid triage and diagnosis.
  • Application flow maps to help visualize transaction paths – See a full picture of the transaction flow from the client browser to the network via application flow maps when you combine Foglight for Java with Foglight User Experience Monitoring.
  • Auto-detection of application run-time architecture – Ensure you can always visualize accurate transaction paths as the production environment changes dynamically through automation. 
  • Java container and JVM monitoring – Collect data on state, alarms and events by server, application, or Java EE artifact (such as an EAR file). Deep visualizations support second level application support teams with root cause analysis. Tile based views provide key data supporting triage workflows.
  • Memory leak detection – Monitor the heap, allocated objects and garbage collection activity by transaction and user to pinpoint memory leaks.
  • Unmatched comprehensive APM coverage – Access transactional, application component and infrastructure visualizations of the run time architecture by combining Foglight for Java with other Foglight monitoring capabilities. This enables the right APM view for the right APM user and facilitates collaboration between application operations, application support and application development.

视频

截屏

截图之旅

开始Foglight for Java屏幕截图之旅

屏幕截图数：5

Monitor from the end-user perspective

Monitor from the end-user perspective

Application support first responders use auto-detected run-time architectures and response time breakdowns that extend from client and external network to database in order to identify and isolate the source of end-user performance problems.

Pinpoint challenging performance problems

Pinpoint challenging performance problems

Application support can pinpoint performance problems associated with specific transaction executions by visualizing the path flow and response time breakdown of aggregated and individual transaction executions. Drill to transaction replay to visually replay the end-user session to capture the context of the user activity and drill to a transaction trace to evaluate the method level details.

Identify virtualization impacts on web application performance

Identify virtualization impacts on web application performance

Combine with virtualization monitoring for the only APM solution takes application support from the end-user transaction to JVM to VM to ESX host in order to identify the effects of virtualization and shared resource conflicts for web applications.

Specialists use expert dashboards for deep dive analysis

Specialists use expert dashboards for deep dive analysis

Java specialists use expert dashboards designed to evaluate transactional activity purely from the application layer.

Perform code level root cause analysis

Perform code level root cause analysis

Java specialists evaluate method level code detail to find the source of code based performance problems

文件

支持文档、备注和指南

发布公告和用户指南 返回页首
 

了解详情

相关产品

本产品相关支持