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This paper presents AUGURY, an application for the analysis of monitoring data from computers, servers or cloud infrastructures. The analysis is based on the extraction of patterns and trends from historical data, using elements of time-series analysis. The purpose of AUGURY is to aid a server administrator by forecasting the behaviour and resource usage of specific applications and in presenting...
In this paper we consider a root-cause analysis framework for NFV infrastructure. As monitoring machinery for NFV has matured the next step is to leverage on such data to automatically optimize failure detection, analysis, and overall resiliency. The complex architecture and dynamics of NFV poses significant challenges from the point of view of causality inference. In particular, the need for an approach...
Identification of VMs exhibiting similar behavior can improve scalability in monitoring and management of cloud data centers. Existing solutions for automatic VM clustering may be either very accurate, at the price of a high computational cost, or able to provide fast results with limited accuracy. Furthermore, the performance of most solutions may change significantly depending on the specific values...
Data protection using backup is one of the most critical IT management operations to ensure business continuity, which is also constantly evolving due to the emerging challenges in the “Big Data Era.” In this paper, we introduce our ongoing research effort in designing intelligent enterprise backup management solutions by obtaining actionable insights from voluminous backup job metadata across data...
Cloud computing has become increasingly popular by obviating the need for users to own and maintain complex computing infrastructures. However, due to their inherent complexity and large scale, production cloud computing systems are prone to various runtime problems caused by hardware and software faults and environmental factors. Autonomic anomaly detection is a crucial technique for understanding...
This article presents results of designing a Content Delivery Network monitoring system for resource limited applications. CDN monitoring is important both for content providers (media companies) and administrators (Internet Service Providers). It is a challenging task since network traffic may generate huge volume of data which must be parsed and analysed in real-time. This paper describes the design...
Software systems continuously running over a long time may suffer gradual performance degradation or failure rate increasing. This phenomenon, known as ¡®Software Aging', has become a great challenge to dependability-critical software systems. Researchers have made remarkable achievements in predicting resource exhaustion time and designing optimal rejuvenation plan. However, limited works focus on...
Effective characterization of workload could be used to drive Capacity Planning and Performance Management in IaaS Cloud. There are different workload metrics (e.g. CPU, memory usage, throughput, response time) which could be modeled along with relationships between them. Similarly, we could model relationships across a set of workloads. Analyzing and characterizing this would enable decision making...
Data centers are growing in size and complexity driven by trends such as cloud computing and on-line services. Such large data centers pose several challenges for system management. Key among them is anomaly detection which is required to monitor and analyze metrics across several thousands servers and across multiple layers of abstractions to detect anomalous system behavior. In practice, multiple...
This document describes the architecture of a distributed Content Delivery Network (CDN) monitoring system and its deployment in a research environment in one of the biggest telecommunication company in Poland and involves about fifty nodes distributed in the country and database system located on dedicated storage cluster working in RD center in Warsaw.
The recent emergence of clouds with large, virtualized pools of compute and storage resources raises the possibility of a new compute paradigm for scientific research. With virtualization technologies, consolidation of scientific workflows presents a promising opportunity for energy and resource cost optimization, while achieving high performance. We have developed pSciMapper, a power-aware consolidation...
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