Log4Perf: suggesting and updating logging locations for web-based systems’ performance monitoring

Abstract

Performance assurance activities are an essential step in the release cycle of software systems. Logs have become one of the most important sources of information that is used to monitor, understand and improve software performance. However, developers often face the challenge of making logging decisions, i.e., neither logging too little and logging too much is desirable. Although prior research

Quality Properties of Execution Tracing, an Empirical Study

“…The majority of the publications with regard to the problem they address can be classified in three groups: (1) where to insert log statements in the source code [13,20,[23][24][25][26][27][28], (2) what to log to provide sufficient information for failure analysis [13,17,27,29], and (3) how to log [13,19,27]. Tool support for selecting the appropriate places in the source code for inserting log statements consistently or for achieving optimal performance by the trade-off in the amount of information logged and the speed of execution usually involve more than one group mentioned above [13,17,[25][26][27][28][29].…”

“…whether the performance of the trace is appropriate with regard to the storage, (10) whether the structure of the trace output is the same at the different components and applications in the same application domain, (11) whether the trace mechanism offers automation feature such as filtering duplicate entries, (12) whether standard trace implementations are used (e.g., log4j), (13) whether the trace mechanism can deal with increasing data volume, (14) whether the trace mechanism is capable of dealing with parallel execution, (15) whether the trace mechanism is capable of measuring performance (a) at different levels of the architecture (b) with different granularities and (c) not only the response time but also the quality of data returned can be investigated based on the trace, (16) whether the trace mechanism offers the possibility to make queries on timestamps, (17) whether the trace mechanism is capable of making a prediction about the system's availability based on the traces, (18) whether the trace mechanism is capable of generating usage statistics, (19) whether the trace mechanism is capable of measuring quality of service metrics for SLAs, (20) whether the trace code insertion can be done automatically in the application, (21) whether the trace mechanism is capable of replaying and simulating sequence of actions based on the traces, (22) whether the trace data are available as the events occur not only after the trace session is finished, (23) whether the trace data are available also through APIs, (24) whether the output format of the trace can be changed including DB and text file formats, (25) whether the trace code can be located in separate modules and not intermingled into the application code, (26) whether the trace mechanism is capable of correlating actions on different nodes in the case of distributed application, (27) whether the tracing mechanism is capable of keeping its perturbations on a possible minimum level with regard to the application, (28) whether the CPU usage can be traced, (29) the memory usage can be traced, (30) whether the trace mechanism is capable of tracing the following properties in the case of real-time applications: (a) task switches, which task, when, (b) interrupts, (c) tick rate, (d) CPU usage, (e) memory usage, (f) network utilisation, (g) states of the real-time kernel, which tasks are waiting to execute (waiting queue), which tasks are running, which tasks are blocked. Definition: The variable defines how secure the execution tracing mechanism and its outputs are, i.e., it shows to what extent the execution tracing mechanism and its outputs are exposed to vulnerabilities and how likely it is that sensitive information leaks out through them.…”

Intention-aware log automation

“…LogEnhancer 和 Log20 关注面向程序运行路径监控的日志, 而 SmartLog 关注面向故障诊断的日志. Yao 等 [5] 设计 了 Log4Perf, 推荐日志位置帮助网页系统监控性能. Ding 等 [6] 设计了 Log2, 一种代价敏感的日志机制 帮助程序进行性能诊断.…”

Characterizing and Detecting Duplicate Logging Code Smells

“…Previous studies show that software logs are extensively used and analyzed for various tasks, such as error diagnosis [73,71], deployment verification [57], load testing [15,28], understanding code quality [58], security monitoring [44], program comprehension [23,59], and performance analysis [14,69,45]. Comparing to their studies which provide logging understanding or solve particular problems by analyzing logs, we aim to improve the the logging practice.…”

“…Software logs are widely used in software systems to record system execution behaviors. Developers use the generated logs to assist in various tasks, such as debugging [73,71,20], testing [15,28,13], program comprehension [23,59], system verification [9,6], and performance analysis [14,69]. A logging statement (i.e., code that generates a log) contains a static message, to-berecorded variables, and log verbosity level.…”