How Neural Attention Detects Cluster-Wide Task Slowdowns in Cloud Systems

A new paper accepted at ACM SIGKDD2024 presents a neural‑network‑based framework that uses a skim‑attention mechanism and a picky loss function to accurately detect cluster‑wide task slowdown anomalies in large‑scale cloud platforms, achieving a 5.3% average F1‑score improvement over state‑of‑the‑art methods.

Cluster PerformanceNeural Networksanomaly detection

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How Neural Attention Detects Cluster-Wide Task Slowdowns in Cloud Systems

Architect

Feb 18, 2022 · Cloud Native

Large‑Scale etcd Cluster Performance Optimization and Pod Data Splitting in Ant Group’s Sigma

This article describes how Ant Group tackled the performance ceiling of its massive Sigma Kubernetes clusters by horizontally splitting etcd storage for Pods, Leases and Events, redesigning watch handling to avoid component restarts, and using snapshot‑based migration to preserve data integrity while reducing latency.

Cluster PerformanceData MigrationKubernetes

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Large‑Scale etcd Cluster Performance Optimization and Pod Data Splitting in Ant Group’s Sigma

MaGe Linux Operations

May 26, 2020 · Operations

How to Optimize Ceph Cluster Hardware: CPU, RAM, Storage & Network Guidelines

This guide explains how to plan Ceph hardware by balancing CPU, memory, storage, network bandwidth, and failure domains, offering practical recommendations for daemons, OSDs, monitors, managers, and SSD vs HDD choices to achieve cost‑effective, high‑performance large‑scale clusters.

CephCluster PerformanceHardware Planning

0 likes · 15 min read

How to Optimize Ceph Cluster Hardware: CPU, RAM, Storage & Network Guidelines