Automatic Root Cause Analysis (RCA) systems aim to streamline the process of identifying the underlying cause of software failures in complex cloud-native environments. These systems employ graph-like structures to represent causal relationships between different components of a software application. These relationships are typically learned through performance and resource utilization metrics of the microservices in the system. To accomplish this objective, numerous RCA systems utilize statistical algorithms, specifically those falling under the category of causal discovery. These algorithms have demonstrated their utility not only in RCA systems but also in a wide range of other domains and applications. Nonetheless, there exists a research gap in the exploration of the feasibility and efficacy of multivariate time series causal discovery algorithms for deriving causal graphs within a microservice framework. By harnessing metric time series data from Prometheus and applying these algorithms, we aim to shed light on their performance in a cloudnative environment. Furthermore, we have introduced an adaptation in the form of an ensemble causal discovery algorithm. Our experimentation with this ensemble approach, conducted on datasets with known causal relationships, unequivocally demonstrates its potential in enhancing the precision of detected causal connections. Notably, our ultimate objective was to ascertain reliable causal relationships within Ericsson’s cloud-native system ’X,’ where the ground truth is unavailable. The ensemble causal discovery approach triumphs over the limitations of employing individual causal discovery algorithms, significantly augmenting confidence in the unveiled causal relationships. As a practical illustration of the utility of the ensemble causal discovery techniques, we have delved into the domain of anomaly detection. By leveraging causal graphs within our study, we have successfully applied this technique to anomaly detection within the Ericsson system. / System för automatisk rotorsaksanalys (RCA) syftar till att effektivisera process för att identifiera den underliggande orsaken till programvarufel i komplexa molnbaserade miljöer. Dessa system använder grafliknande strukturer att representera orsakssamband mellan olika komponenter i en mjukvaruapplikation. Dessa relationer lär man sig vanligtvis genom prestanda och resursutnyttjande mätvärden för mikrotjänsterna i systemet. För att uppnå detta mål använder många RCAsystem statistiska algoritmer, särskilt de som faller under kategorin orsaksupptäckt. Dessa algoritmer har visat att de inte är användbara endast i RCA-system men även inom en lång rad andra domäner och applikationer. Icke desto mindre finns det en forskningslucka i utforskningen av genomförbarhet och effektivitet av orsaksupptäckt av multivariat tidsserie algoritmer för att härleda kausala grafer inom ett mikrotjänstramverk. Genom att utnyttja metriska tidsseriedata från Prometheus och tillämpa Dessa algoritmer strävar vi efter att belysa deras prestanda i ett moln- inhemsk miljö. Dessutom har vi infört en anpassning i formen av en ensemble kausal upptäcktsalgoritm. Vårt experiment med denna ensemblemetod, utförd på datauppsättningar med kända orsakssamband relationer, visar otvetydigt sin potential för att förbättra precisionen hos upptäckta orsakssamband. Särskilt vår ultimata Målet var att fastställa tillförlitliga orsakssamband inom Ericssons molnbaserade systemet ’X’, där grundsanningen inte är tillgänglig. De ensemble kausal discovery approach segrar över begränsningarna av att använda individuella kausala upptäcktsalgoritmer, avsevärt öka förtroendet för de avslöjade orsakssambanden. Som en praktisk illustration av nyttan av ensemblens kausal upptäcktstekniker har vi fördjupat oss i anomalidomänen upptäckt. Genom att utnyttja kausala grafer inom vår studie har vi framgångsrikt tillämpat denna teknik för att detektera anomali inom Ericsson system

Hurricane Shoes and Other Stories is a collection of short stories that center on evolving and devolving relationships. The characters in these stories form tentative bonds with people in their lives while other relationships slip away. In "Hurricane Shoes," Katrina attempts to reinvent herself by ending an affair. Katrina's pregnancy and her mother's cancer pull the two women closer. "Da's Violets" is about Cheryl's changing relationship with her father. Just as he moves on from the wife who left him for her podiatrist, the wife returns with hopes to reconcile. These stories catch characters in moments when they must make difficult choices and endure the uncertainties and ambiguities of relationships. In "Lady Luck," Laurel is a cocaine addict and alcoholic on the verge of finalizing a divorce. She propositions a young man named River to exchange sex for money. River turns the table, and offers Laurel a deal where she'll have all the money and drugs she wants, as long as she helps him transport cocaine. "Bridges" is a coming of age story in which Linda and Kristin have a close call with a train, and Linda matures as she realizes love has limits. The catalyst for changing relationships is sometimes an exchange between characters. In "Special Son," Mark's father is dying of cancer. The father asks his son to take special care of his mother, and Mark needs his father to finally acknowledge Mark's sexuality. In "Swim or Sink," Doreen befriends her campground neighbor, Michael McBride. McBride has been living at the campground since he left his cheating wife, and he offers Doreen insight when she discovers her husband's infidelity. Together the stories function as a mosaic--each very different, but a complement to the others in forming a larger portrayal of relationships.

Yes / This report addresses the scientific and technological discoveries in the biological sciences that enabled the early interest in biological warfare to move from hurling infected corpses into enemy cities in ancient times, through use of small cultures of animal pathogens to sabotage enemy livestock in World War I, to the origins of organised military biological weapons (BW) programmes directed at humans, animals, and plants in the inter-war period. It builds on Dando¿s 1999 paper: The Impact of the Development of Modern Biology and Medicine on the Evolution of Offensive Biological Warfare Programs in the Twentieth Century.1 For the historical aspects of biological warfare programmes this report primarily draws from the Stockholm International Peace Research Institute volume: Biological and Toxin Weapons: Research, Development and Use from the Middle Ages to 1945.2

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