mtarng Goto Github PK
Name: Michael Tarng
Type: User
Michael Tarng's Projects
active-learning-detect
Active learning + object detection
active-learning-shared
Shared library for active-learning-detect
adventofcode2021
advent of code 2021
azdo-terraform-test
azdo test repo
azure-docs
Open source documentation of Microsoft Azure
bedrock
Automation for Production Kubernetes Clusters with a GitOps Workflow
bedrock-demo-gitops-repo
GitOps Repo for flux
blobr
blobr script, bc i am dumb
config
etl-synthea
Conversion from Synthea CSV to OMOP CDM
experiments
fabrikate
Making GitOps with Kubernetes easier one component at a time
fabrikate-cloud-native
An opinionated cloud native infrastructure stack
fabrikate-definitions
A centralized and curated repository of Fabrikate definitions
fabrikate-istio
Fabrikate component to generate Kubernetes resource definitions for an Istio installation
fabrikate-kafka-sample
Sample Fabrikate Components for Kafka on AKS
fabrikate-prom2azure-hld
Fabrikate HLD for Prometheus Azure Monitor exporter service
fabrikate-prometheus-grafana-thanos
Prometheus grafana component for Fabrikate with Thanos exporter sidecar
foundation
Automation for Serverless Applications with a GitOps Workflow
helm-charts
Helm charts used in Azure documentation
homebrew-core
🍻 Default formulae for the missing package manager for macOS
kamus
An open source, git-ops, zero-trust secret encryption and decryption solution for Kubernetes applications
kao.moji
Kaomoji for your thoughts?
kubemlops
The sample that serves as a template for doing MLOps with open source projects and tools on K8s platform
lockpick
Nintendo Switch encryption key derivation homebrew
lockpick_rcm
Nintendo Switch encryption key derivation bare metal RCM payload
ml-test-flux
testing repo for flux
omop-cdmv5-boostrap
osm
Open Service Mesh (OSM) is a lightweight, extensible, cloud native service mesh that allows users to uniformly manage, secure, and get out-of-the-box observability features for highly dynamic microservice environments.
seldon-core
A framework to deploy, manage and scale your production machine learning to thousands of models
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