Github: https://github.com/argoproj
一、简介#
目前Argo项目中有如下几个子项目:
argoproj
Common project repo for all Argo Projectsgitops-engine
Public Democratizing GitOpsargo-workflows
Workflow engine for Kubernetesargo-cd
Declarative continuous deployment for Kubernetes.argo-events
Event-driven automation frameworkargo-rollouts
Progressive Delivery for Kubernetes
cd和rollouts一个是持续交付工具,一个是渐进式发布工具,与原子能力关系不大。
workflows和events一个是基于容器的任务编排工具,一个是事件驱动框架。都与本次原子能力相关。
这样,就可以设计出一个由新建扫描任务事件触发,实例化经过编排可实现扫描全流程的方案。
流程如下:![[book_architecture/content/docs/programmer/base/argo_events_workfows.png]]
sensor作用#
- 使事件转发和处理松耦合
- Trigger事件的参数化,比如根据事件内容动态生成
二、Argo Workflow编排#
点击展开Yaml
apiVersion: argoproj.io/v1alpha1
kind: Workflow
metadata:
generateName: coinflip-recursive-
spec:
entrypoint: coinflip
templates:
- name: coinflip
steps:
- - name: flip-coin
template: flip-coin
- - name: heads
template: heads
when: "{{steps.flip-coin.outputs.result}} == heads"
- name: tails
template: coinflip
when: "{{steps.flip-coin.outputs.result}} == tails"
-
name: flip-coin
script:
image: python:alpine3.6
command: [python]
source: |
import random
result = “heads” if random.randint(0,1) == 0 else “tails”
print(result)
-
name: heads
container:
image: alpine:3.6
command: [sh, -c]
args: [“echo "it was heads"”]
三、Argo Events使用#
- 定义一个webhook(名称: webhook_example)路径/webhook, 端口12000, 接收 POST 方法.
apiVersion: argoproj.io/v1alpha1
kind: EventSource
metadata:
name: webhook
spec:
service:
ports:
- port: 12000
targetPort: 12000
webhook:
webhook_example:
port: "12000"
endpoint: /webhook
method: POST- 定义
Sensor指定行为
点击展开yaml文件
apiVersion: argoproj.io/vlalpha1
kind: Sensor
metadata:
name: webhook
spec:
template:
serviceAccountName: argo-events-sa
dependencies # 订阅的事件
- name: test-dep
eventSourceName: webhook
eventName: webhook_example
triggers:
- template
name:webhook-workflow-triaae
k8s: # 定义触发器为创建一个workflow资源
group: argoproj.io
version: vlalpha1
resource: workflows
operation: create
source:
resource:
apiVersion: argoproj.io/vlalpha1
kind: Workflow
metadata:
generateName: webhook-
spec:
entrypoint: whalesay
arguments:
parameters:
- name: message
value: hello world
templates:
- name: whalesay
serviceAccountName: argo-events-sa
inputs:
parameters: # 参数替换
-name: message
container:
image: docker/whalesay:latest
command:[cowsay]
args :["{{input.parameters.message}}"]
parameters:
- src:
dependencyName: test-dep
dest: spec.arquments.parameters.0.value
Yaml说明:
i. 定义了订阅的EventSource以及具体的Webhook(一个EventSource可以定义多个Webhook,因此指定俩参数)
ii. Trigger中定义了对应Action 创建一个werkflow, workflow的spec在respirce中配置
iii. parameters定义了workfolw的参数,从event中获取,如上将整个event都作为input(只获取body部分可通过: dataKey: body.message)
iv: 此时 curl -X POST -d '{"message": "Hello"}' 127.0.0.1:12000/webhook,可见argo workflow中创建了一个实例. 如传入整个请求,获得的数据可能经由base64编码的,需要解码后使用{"context": "", "data": "包含header和body"}
v: 其他用法查看: 这里
需验证的问题#
- workflow并行处理多个不同参数的相同任务效率需要验证
四、部署#
1. 运维命令#
argo submit hello-world.yaml # submit a workflow spec to Kubernetes
argo list # list current workflows
argo get hello-world-xxx # get info about a specific workflow
argo logs hello-world-xxx # print the logs from a workflow
argo delete hello-world-xxx # delete workflow2. 安装和启动#
kubectl create namespace argo
kubectl apply -f https://raw.githubusercontent.com/argoproj/argo-workflows/master/manifests/quick-start-postgres.yaml # 最全-精简安装看别的
# 查看运行状态
kubectl get pods -n argo
kubectl get svc -n argo
# 将svc改为nodeport方便访问Web UI
kubectl edit svc -n argo argo-workflow-argo-workflows-server # 或者argo-server 名字会变但是差不多这意思 进去手动将ClusterIP改为NodePort
# 查看argo server pod在哪个node上运行 端口映射到了node哪个端口
kubectl get pods -n argo -o wide
# 查看该node IP
kubectl get node -o wide
# http//nodeip:nodePort访问
# 提交任务
argo submit https://github.com/argoproj/argo-workflows/blob/master/examples/coinflip.yaml --watch -n argo # 将yaml下载下载执行为佳权限问题#
User "system:serviceaccount:argo:default" cannot patch resource "pods" in API group "" in the namespace "argo": RBAC: role.rbac.authorization.k8s.io "argo-workflow" not foundConfusing, possibly erroneous RBAC warnings ("Failed to get pod")点击展开-kubectl apply -f auth.yaml可解决
---
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
name: argo-invocation
namespace: argo
rules:
- apiGroups:
- "argoproj.io"
resources:
- "workflows"
verbs:
- get
- list
- watch
- create
- update
- patch
- delete
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: default-default-invocation
namespace: argo
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: Role
name: argo-invocation
subjects:
- kind: ServiceAccount
name: default
namespace: default # give workflows (as argo:default) permissions to run things # see https://github.com/argoproj/argo/blob/master/docs/workflow-rbac.md
---
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
name: argo-workflow
namespace: argo
rules: # pod get/watch is used to identify the container IDs of the current pod # pod patch is used to annotate the step's outputs back to controller (e.g. artifact location)
- apiGroups:
- ""
resources:
- pods
verbs:
- get
- watch
- patch # logs get/watch are used to get the pods logs for script outputs, and for log archival
- apiGroups:
- ""
resources:
- pods/log
verbs:
- get
- watch
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: argo-default-workflow
namespace: argo
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: Role
name: argo-workflow
subjects:
- kind: ServiceAccount
name: default
namespace: argo
ETCD#
因为k8s状态都在etcd集群中,所以需要关注一下大量workflow会不会占用过多的容量资源
ETCDCTL_API=3 etcdctl --cacert /etc/kubernetes/pki/etcd/ca.crt --cert /etc/kubernetes/pki/etcd/healthcheck-client.crt --key /etc/kubernetes/pki/etcd/healthcheck-client.key --write-out=table endpoint status
+----------------+------------------+---------+---------+-----------+------------+-----------+------------+--------------------+--------+
| ENDPOINT | ID | VERSION | DB SIZE | IS LEADER | IS LEARNER | RAFT TERM | RAFT INDEX | RAFT APPLIED INDEX | ERRORS |
+----------------+------------------+---------+---------+-----------+------------+-----------+------------+--------------------+--------+
| 127.0.0.1:2379 | 871f72e4ab5a28e8 | 3.5.0 | 104 MB | true | false | 35 | 348058564 | 348058564 | |
+----------------+------------------+---------+---------+-----------+------------+-----------+------------+--------------------+--------+根据提供的信息,可以看到以下解释:
- ENDPOINT: etcd集群的地址为127.0.0.1:2379。
- ID: etcd集群的唯一标识为871f72e4ab5a28e8。
- VERSION: etcd的版本为3.5.0。
- DB SIZE: etcd数据库当前占用的空间大小为104 MB。
- IS LEADER: 当前节点是否为etcd集群的Leader节点,这里显示为true。
- IS LEARNER: 当前节点是否为etcd集群的Learner节点,这里显示为false。
- RAFT TERM: 当前etcd集群的Raft Term为35。
- RAFT INDEX: 当前etcd集群的Raft Index为348058564。
- RAFT APPLIED INDEX: 当前etcd集群已应用的Raft Index为348058564。
- ERRORS: 没有显示任何错误信息。 总体上,这些信息展示了etcd集群的状态,包括节点角色、版本、数据库大小等。
大量Workflows优化建议#
You have at least 230 completed workflows. Reducing the total number of workflows will reduce your costs. Learn more at https://argoproj.github.io/argo-workflows/cost-optimisation/
创建时缺少安全上下文问题#
This workflow does not have security context set. You can run your workflow pods more securely by setting it. Learn more at https://argoproj.github.io/argo-workflows/workflow-pod-security-context/
修改执行器#
点击展开-Argo server读取的configmap
apiVersion: v1
data:
artifactRepository: |
s3:
bucket: argo
# modify 根据实际修改
endpoint: x.xxx:9000
insecure: true
accessKeySecret:
name: my-minio-cred
key: accesskey
secretKeySecret:
name: my-minio-cred
key: secretkey
containerRuntimeExecutor: emissary // docker这里切换Executor 有的特性需要emissary才能执行
executor: |
resources:
requests:
cpu: 10m
memory: 64Mi
links: |
- name: Workflow Link
scope: workflow
url: http://logging-facility?namespace=${metadata.namespace}&workflowName=${metadata.name}&startedAt=${status.startedAt}&finishedAt=${status.finishedAt}
- name: Pod Link
scope: pod
url: http://logging-facility?namespace=${metadata.namespace}&podName=${metadata.name}&startedAt=${status.startedAt}&finishedAt=${status.finishedAt}
- name: Pod Logs Link
scope: pod-logs
url: http://logging-facility?namespace=${metadata.namespace}&podName=${metadata.name}&startedAt=${status.startedAt}&finishedAt=${status.finishedAt}
- name: Event Source Logs Link
scope: event-source-logs
url: http://logging-facility?namespace=${metadata.namespace}&podName=${metadata.name}&startedAt=${status.startedAt}&finishedAt=${status.finishedAt}
- name: Sensor Logs Link
scope: sensor-logs
url: http://logging-facility?namespace=${metadata.namespace}&podName=${metadata.name}&startedAt=${status.startedAt}&finishedAt=${status.finishedAt}
metricsConfig: |
enabled: true
path: /metrics
port: 9090
namespaceParallelism: "200" // 单个nm下最大工作流并发数
persistence: |
connectionPool:
maxIdleConns: 100
maxOpenConns: 0
connMaxLifetime: 0s
nodeStatusOffLoad: true
archive: true
archiveTTL: 7d
# modify 根据实际修改,需要为argo创建单独的数据库,并修改下方的host. port. database 三个配置
postgresql:
host: xx-base-postgresql.ez-plus
port: 5432
database: postgres
tableName: argo_workflows
userNameSecret:
name: argo-postgres-config
key: username
passwordSecret:
name: argo-postgres-config
key: password
retentionPolicy: |
completed: 10
failed: 3
errored: 3
kind: ConfigMap
metadata:
annotations:
meta.helm.sh/release-name: argo
meta.helm.sh/release-namespace: argo
labels:
app.kubernetes.io/managed-by: Helm
name: workflow-controller-configmap
namespace: argo