Problem

If you have big repo, you want to separate it into several small repos.

There are two approach you might google it, here is different

Subtree

git subtree split -P feature_a -b "branchA"

It will separate your code, but it will include whole git history. It will slow-down your CI/CD flow if your original repo history is very huge.

Filter-Branch

which rewrites the repo history picking up only those commits that actually affect the content of a specific subdirectory. (refer to refer 2)

git filter-branch --prune-empty --subdirectory-filter SUBDIR -- --all

Reference

• Splitting a subfolder out into a new repository
• Difference between git filter branch and git subtree?
• Using Git subtrees for repository separation

這幾天閱讀 Damian Gryski 的 blog post “Consistent Hashing: Algorithmic Tradeoffs” 整理出來的投影片 (第一版)

應該會找時間寫寫中文 blog

放上這次再 GTG (Golang Taipei Gathering 30)聚會的投影片，主要是介紹可能會放入 go 1.11 的新功能 vgo

Two ways to enable GPU in Kubernetes:

If you want to enable GPU resource in Kubernetes and want Kubelet to allocate it. You need config it as following ways:

• Kubernetes 1.7: Using NVidia container and enable Kuberlet config feature-gates=Accelerators=true
• Kubernetes 1.9: Using Device Plugin with Kuberlet specific config feature-gates=DevicePlugins=true

Check node if it has GPU resource:

Using kubectl command kubectl get node YOUR_NODE_NAME -o json to export all node info as json format. You should see something like:

## If you use Kubernetes Accelerator after 1.7
  "allocatable": {
        "cpu": "32",
        "memory": "263933300Ki",
        "alpha.kubernetes.io/nvidia-gpu": "4",
        "pods": "110"
    },

Detail defined in k8s.io/api/core/v1/types.go

## If you use Kubernetes Device Plugin after 1.9
  "allocatable": {
        "cpu": "32",
        "memory": "263933300Ki",
        "nvidia.com/gpu": "4",
        "pods": "110"
    }, ## Reference:

• Managing Compute Resources for Containers
• Kubernetes: Device Plugin
• NVIDIA-k8s-device-plugin

中文前言:

在使用 Kubernetes 的時候，可以選擇透過 Job 的方式來跑一次性的工作．但是如果希望你的工作在特定時間內一定得結束來釋放資源， 就得透過這個方式．

最近在研究這個的時候，發現有些使用上的小技巧，紀錄一下．

Preface:

If you want to force to terminate your kubernetes jobs if it exceed specific time. (e.g.: run a job no longer than 2 mins).

In this case you can use a watcher to monitor this Kubernetes jobs and terminate it if exceed specific time. Or you can refer K8S Doc:”Job Termination and Cleanup” use activeDeadlineSeconds to force terminare your jobs.

How to use activeDeadlineSeconds:

It is very easy to setup activeDeadlineSeconds in spec.

apiVersion: batch/v1
kind: Job
metadata:
  name: myjob
spec:
  backoffLimit: 5 
  activeDeadlineSeconds: 100
  template:
    spec:
      containers:
      - name: myjob
        image: busybox
        command: ["sleep", "300"]
      restartPolicy: Never

In this example, this job will be terminated after 100 seconds (if it works well :p )

Before you use activeDeadlineSeconds

• If you ever run a job with activeDeadlineSeconds, you will need delete job before you run the same job again.
• The job will not stop if you run the same job name with activeDeadlineSeconds
• You will need change job name to make activeDeadlineSeconds works again. (suggest add specific tag in postfix of job name)

Reference:

• Kubernetes: issue Job pod does not terminate within activeDeadlineSeconds spec
• Kubernetes document: Job Termination and Cleanup

由於之前”台北開放資料”中的流浪動物資料忽然無法連上，造成之前寫的 Line Bot: 台北流浪動物需要你” 無法正常運作． 只好去找找政府的資料，”動物認領養” 開放資料． (https://data.gov.tw/dataset/9842#r0)

修改好了，希望大家繼續愛用． 如果有過年需要人陪的，可以玩玩看，年後去領養可愛的小毛球家人．

簡單說明:

• 打任意字會隨機出現動物
• 打”狗” 或是 “貓” 會出現相關動物領養資料