The source code of INFless，a native serverless platform for AI inference.

Probabilistic time series modeling in Python

Unofficial Implementation of RobustPeriod: Time-Frequency Mining for Robust Multiple Periodicities Detection

cluster data collected from production clusters in Alibaba for cluster management research

Official Implement of "ADBench: Anomaly Detection Benchmark".

Serverless Functions For Kubernetes

The GitHub repository for the paper: “Time Series is a Special Sequence: Forecasting with Sample Convolution and Interaction“.

Serverless optimizations

Anomaly detection related books, papers, videos, and toolboxes

An open source framework for big data analytics and embarrassingly parallel jobs, that provides an universal API for building parallel applications in the cloud.

Time series forecasting with PyTorch

This is an official implementation for "Are Transformers Effective for Time Series Forecasting?"

Multi-Objective Hybrid Autoscaing (MOHA)

Kubernetes Native Edge Computing Framework (project under CNCF)

KubeFire 🔥, creates and manages Kubernetes Clusters using Firecracker microVMs

QoS based scheduling system for hybrid orchestration workloads on Kubernetes, bringing workloads the best layout and status.

Implementation of DLinear (https://arxiv.org/abs/2205.13504) using TensorFlow as a Keras custom model. Supports multivariate time series prediction and DLinear-S & DLinear-I variants.

k8s oversold

This repository contains an ASL Workflow Engine that provides a Local Step Function implementation exposing the AWS Step Function API and supporting AWS CLI and SDK calls.

About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008

Help Rather Than Recycle: Alleviating Cold Startup in Serverless Computing Through Inter-Function Container Sharing

A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

Code for KDD'22: A meta reinforcement learning approach for predictive autoscaling in the cloud

An open source tool for testing and profiling FaaS platforms

The GitHub repository for the paper "Informer" accepted by AAAI 2021.