Debugging of Performance Degradation in Distributed Requests Handling Using Multilevel Trace Analysis

Root cause identification of performance degradation within distributed systems is often a difficult and time-consuming task, yet it is crucial for maintaining high performance. In this paper, we present an execution trace-driven solution that reduces the efforts required to investigate, debug, and solve performance problems found in multinode distributed systems. The proposed approach employs a unified analysis method to represent trace data collected from the user-space level to the hardware level of involved nodes, allowing for efficient and effective root cause analysis. This solution works by extracting performance metrics and state information from trace data collected at user-space, kernel, and network levels. The multisource trace data is then synchronized and structured in a multidimensional data store, which is designed specifically for this kind of data. A posteriori analysis using a top-down approach is then used to investigate performance problems and detect their root causes. In this paper, we apply this generic framework to analyze trace data collected from the execution of the web server, database server, and application servers in a distributed LAMP (Linux, Apache, MySQL, and PHP) Stack. Using industrial level use cases, we show that the proposed approach is capable of investigating the root cause of performance issues, addressing unusual latency, and improving base latency by 70%. This is achieved with minimal tracing overhead that does not significantly impact performance, as well as O log n query response times for efficient analysis.

Pengaruh organizational citizenship behaviour terhadap kinerja anggota Kepolisian

≤ Performance problems of police members are influenced by a very heavy workload, incompatibility with passion, and personal issues. Those performance problems determine organizational citizenship behavior. Therefore this research was done to know the effect of organizational citizenship behavior toward the work performance of police members. This research is quantitative research with a survey design. The subjects are 200 members of the Indonesian National Police. The sampling technique used purposive sampling. The analysis in this study used simple linear regression analysis. The results of this study provided evidence to accept the hypothesis that there is a significant positive impact between organizational citizenship behavior on performance (β = 0.41, p<0.001), the higher organizational citizenship behavior, the higher the performance of police personnel. Keywords: Indonesian national police, organizational citizenship behaviour, performance

Scientific Approach Towards Knowledge Enhancement and Capacity Building for the Professionals Working in Water Sector Through Training Needs Analysis (TNA) Tool – A Case Study

Training Needs Analysis (TNA) is a tool designed by the Department of Personnel and Training (DoPT), Government of India, being useful for development of knowledge and skills of the officials of an organization. TNA can be undertaken for an organization as a whole, or for a particular section or function. It may include analysis of an organization’s current performance problems, or in anticipation of changes that are likely to require training. TNA focuses attention on ‘performance’ to identify training needs, along with other, non-training implications. Once performance problems have been identified and analyzed, they can be reviewed according to their priorities. After establishing the priorities, further, more detailed analysis can be done to identify precise training needs. These needs should concern everybody associated with a particular performance problem, irrespective of their status or number. TNA has been applied to solve the performance problem of the Hydrogeologists of Central Ground Water Board (CGWB), Northern Region, Lucknow, Uttar Pradesh. The TNA encompasses the components like Terms of Reference (ToR), SWOT analysis, SPIO analysis, Responsibility Mapping, EMB factors, PEST analysis, and Fishbone analysis followed by diagnosis of the collected data and recommendations. The proper identification of performance problem is a key to address the organizational development goals in right manner. Many performance problems in the hydrogeological discipline of client organization related to environmental, motivational and behavioural (EMB) factors influencing desired performance of CGWB, NR were identified during the interaction with the client and stakeholders and also through interview with set of questionnaire. To achieve the vision and mission of client organization and to improve its performance, training and non-training implications, Training Plan, Priority List and design brief have been proposed.

Using application benchmark call graphs to quantify and improve the practical relevance of microbenchmark suites

Performance problems in applications should ideally be detected as soon as they occur, i.e., directly when the causing code modification is added to the code repository. To this end, complex and cost-intensive application benchmarks or lightweight but less relevant microbenchmarks can be added to existing build pipelines to ensure performance goals. In this paper, we show how the practical relevance of microbenchmark suites can be improved and verified based on the application flow during an application benchmark run. We propose an approach to determine the overlap of common function calls between application and microbenchmarks, describe a method which identifies redundant microbenchmarks, and present a recommendation algorithm which reveals relevant functions that are not covered by microbenchmarks yet. A microbenchmark suite optimized in this way can easily test all functions determined to be relevant by application benchmarks after every code change, thus, significantly reducing the risk of undetected performance problems. Our evaluation using two time series databases shows that, depending on the specific application scenario, application benchmarks cover different functions of the system under test. Their respective microbenchmark suites cover between 35.62% and 66.29% of the functions called during the application benchmark, offering substantial room for improvement. Through two use cases—removing redundancies in the microbenchmark suite and recommendation of yet uncovered functions—we decrease the total number of microbenchmarks and increase the practical relevance of both suites. Removing redundancies can significantly reduce the number of microbenchmarks (and thus the execution time as well) to ~10% and ~23% of the original microbenchmark suites, whereas recommendation identifies up to 26 and 14 newly, uncovered functions to benchmark to improve the relevance. By utilizing the differences and synergies of application benchmarks and microbenchmarks, our approach potentially enables effective software performance assurance with performance tests of multiple granularities.