Efficient Multivariate Time Series Anomaly Detection Through Transfer Learning for Large-Scale Software Systems
Timely anomaly detection of multivariate time series (MTS) is of vital importance for
managing large-scale software systems. However, many deep learning-based MTS …
managing large-scale software systems. However, many deep learning-based MTS …
Multivariate Time Series Anomaly Detection based on Pre-trained Models with Dual-Attention Mechanism
In major tech companies, monitoring server performance data with anomaly detection
algorithms is crucial for assessing operational status. Existing models often require separate …
algorithms is crucial for assessing operational status. Existing models often require separate …
fKPISelect: Fault-Injection Based Automated KPI Selection for Practical Multivariate Anomaly Detection
IT services are now popularly hosted in cloud systems. In order to enhance the availability of
cloud services, an emerging approach for detecting failures of cloud components is to …
cloud services, an emerging approach for detecting failures of cloud components is to …
ENOVA: Autoscaling towards Cost-effective and Stable Serverless LLM Serving
Since the increasing popularity of large language model (LLM) backend systems, it is
common and necessary to deploy stable serverless serving of LLM on multi-GPU clusters …
common and necessary to deploy stable serverless serving of LLM on multi-GPU clusters …
On the Practicability of Deep Learning based Anomaly Detection for Modern Online Software Systems: A Pre-Train-and-Align Framework
Operation and maintenance are critical activities in the whole life cycle of modern online
software systems, and anomaly detection is a crucial step of these activities. Recent studies …
software systems, and anomaly detection is a crucial step of these activities. Recent studies …