#JPROFILER 5.2.1 PORTABLE#
#JPROFILER 5.2.1 SOFTWARE#

Traditional capacity management strategies are rather static and pessimistic: resources are provisioned for anticipated peak workload levels. The goal is to continuously provide adequate capacity, i.e., service level agreements should be satisfied while keeping investment and operating costs reasonably low.

#JPROFILER 5.2.1 SOFTWARE#

It comprises the provisioning of data center resources and the deployment of software components to these resources. Based on this data, developers and system integrators can better understand the current state-of-the-art and the implications of choosing or implementing different dynamic interaction extraction techniques.Ĭapacity management is a core activity when designing and operating distributed software systems. We give performance and functional considerations and contrast them against each other by outlining their relative advantages and disadvantages. We also take a critical look at the different available implementations of the various techniques presented. For each approach we detail the needs it addresses, and the technical requirements for building an implementation of the approach. We present a range of representative approaches for dynamically obtaining and using component interactions. They pose specific challenges while raising interesting opportunities for component level interaction extraction tools. This paper focuses on component based Java applications, currently widely used by industry. Obtaining component level interactions which show the relationships between different software entities is a necessary prerequisite for such efforts. These tasks are essential in solving and preventing performance and quality problems. Monitoring, analysing and understanding component based enterprise software systems are challenging tasks.

#JPROFILER 5.2.1 PORTABLE#

The portable and extensible architecture yields a versatile and adaptive basic instrumentation facility for a variety of potential applications that need a flexible solution for monitoring long running enterprise applications. This is addressed in this thesis by proposing an adaptive approach to monitoring which uses execution models to target profiling operations dynamically on components that exhibit performance degradation this ensures a negligible overhead when the target application performs as expected and a minimum impact when certain components under-perform.Įxperimental results obtained with the prototype tool demonstrate the feasibility of the approach in terms of induced overhead. For long running applications, a constant overhead profile is undesirable and typically, such a solution would only be used for the duration of a performance audit, sacrificing the benefits of constantly observing a production system in favour of a reduced performance impact. Most instrumentation solutions exhibit static behaviour by targeting a specified set of components.

Based on this instrumentation infrastructure, a complete performance management framework including modelling and performance prediction is proposed. The use of component meta-data for target analysis, together with standards-based implementation strategies, ensures the complete portability of the instrumentation solution across different application servers.

By leveraging the component platform infrastructure, the described solution can non-intrusively instrument running applications and extract performance statistics. The thesis presents a methodology and tool for approaching performance management in enterprise component-based systems. This situation is aggravated by the fact that although application servers vary greatly in performance and capabilities, many advertise a similar set of features, making it difficult to choose the one that is the most appropriate for their task. They often make incorrect assumptions about the behaviour of the middleware, which may lead to design decisions that cause severe performance problems after the system has been deployed.

The resulting complexity of the execution environment in such systems makes it difficult for architects and developers to understand completely the implications of alternative design options over the resulting performance of the running system. In order to provide the required services, the application servers implementing the corresponding middleware specifications employ a complex run-time infrastructure that integrates with developer-written business logic. In addition, using a component-oriented development model brings benefits such as increased reusability and flexibility in integrating with third-party systems. Developers leverage enterprise services provided by such platforms to speed up development and increase the robustness of their applications. Most large-scale enterprise applications are currently built using component-based middleware platforms such as J2EE or.

Jprofiler 5.2.1