K8S中Prometheus+Grafana监控

1.介绍

        phometheus:当前一套非常流行的开源监控和报警系统。

        运行原理：通过HTTP协议周期性抓取被监控组件的状态。输出被监控组件信息的HTTP接口称为exporter。

        常用组件大部分都有exporter可以直接使用，比如haproxy,nginx，Mysql,Linux系统信息（包括磁盘、内存、CPU、网络等待）。

        prometheus主要特点：

  • 一个多维数据模型（时间序列由metrics指标名字和设置key/value键/值的labels构成）。
  • 非常高效的存储，平均一个采样数据占~3.5字节左右，320万的时间序列，每30秒采样，保持60天，消耗磁盘大概228G。
  • 一种灵活的查询语言（PromQL）。
  • 无依赖存储，支持local和remote不同模型。
  • 采用http协议，使用pull模式，拉取数据。
  • 监控目标，可以采用服务器发现或静态配置的方式。
  • 多种模式的图像和仪表板支持，图形化友好。
  • 通过中间网关支持推送时间。

        Grafana:是一个用于可视化大型测量数据的开源系统，可以对Prometheus 的指标数据进行可视化。

        Prometheus的体系结构图：

        Prometheus直接或通过中间推送网关从已检测的作业中删除指标，以处理短暂的作业。它在本地存储所有报废的样本，并对这些数据运行规则，以汇总和记录现有数据中的新时间序列，或生成警报。Grafana或其他API使用者可以用来可视化收集的数据。

2.部署prometheus

        2.1 使用RBAC进行授权

[root@k8s-node01 k8s-prometheus]# cat prometheus-rbac.yaml 
apiVersion: v1
kind: ServiceAccount
metadata:name: prometheusnamespace: kube-systemlabels:kubernetes.io/cluster-service: "true"addonmanager.kubernetes.io/mode: Reconcile
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:name: prometheuslabels:kubernetes.io/cluster-service: "true"addonmanager.kubernetes.io/mode: Reconcile 
rules:- apiGroups:- ""resources:- nodes- nodes/metrics- services- endpoints- podsverbs:- get- list- watch- apiGroups:- ""resources:- configmapsverbs:- get- nonResourceURLs:- "/metrics"verbs:- get
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:name: prometheuslabels:kubernetes.io/cluster-service: "true"addonmanager.kubernetes.io/mode: Reconcile
roleRef:apiGroup: rbac.authorization.k8s.iokind: ClusterRolename: prometheus
subjects:
- kind: ServiceAccountname: prometheusnamespace: kube-system[root@k8s-node01 k8s-prometheus]# kubectl apply -f prometheus-rbac.yaml 
serviceaccount/prometheus created
clusterrole.rbac.authorization.k8s.io/prometheus created
clusterrolebinding.rbac.authorization.k8s.io/prometheus created

        2.2 配置管理

        使用Configmap保存不需要加密配置信息，yaml中修改对应的NODE IP即可。

[root@k8s-node01 k8s-prometheus]# cat prometheus-configmap.yaml 
# Prometheus configuration format https://prometheus.io/docs/prometheus/latest/configuration/configuration/
apiVersion: v1
kind: ConfigMap
metadata:name: prometheus-confignamespace: kube-system labels:kubernetes.io/cluster-service: "true"addonmanager.kubernetes.io/mode: EnsureExists
data:prometheus.yml: |rule_files:- /etc/config/rules/*.rulesscrape_configs:- job_name: prometheusstatic_configs:- targets:- localhost:9090- job_name: kubernetes-nodesscrape_interval: 30sstatic_configs:- targets:- 11.0.1.13:9100- 11.0.1.14:9100- job_name: kubernetes-apiserverskubernetes_sd_configs:- role: endpointsrelabel_configs:- action: keepregex: default;kubernetes;httpssource_labels:- __meta_kubernetes_namespace- __meta_kubernetes_service_name- __meta_kubernetes_endpoint_port_namescheme: httpstls_config:ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crtinsecure_skip_verify: truebearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token- job_name: kubernetes-nodes-kubeletkubernetes_sd_configs:- role: noderelabel_configs:- action: labelmapregex: __meta_kubernetes_node_label_(.+)scheme: httpstls_config:ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crtinsecure_skip_verify: truebearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token- job_name: kubernetes-nodes-cadvisorkubernetes_sd_configs:- role: noderelabel_configs:- action: labelmapregex: __meta_kubernetes_node_label_(.+)- target_label: __metrics_path__replacement: /metrics/cadvisorscheme: httpstls_config:ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crtinsecure_skip_verify: truebearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token- job_name: kubernetes-service-endpointskubernetes_sd_configs:- role: endpointsrelabel_configs:- action: keepregex: truesource_labels:- __meta_kubernetes_service_annotation_prometheus_io_scrape- action: replaceregex: (https?)source_labels:- __meta_kubernetes_service_annotation_prometheus_io_schemetarget_label: __scheme__- action: replaceregex: (.+)source_labels:- __meta_kubernetes_service_annotation_prometheus_io_pathtarget_label: __metrics_path__- action: replaceregex: ([^:]+)(?::\d+)?;(\d+)replacement: $1:$2source_labels:- __address__- __meta_kubernetes_service_annotation_prometheus_io_porttarget_label: __address__- action: labelmapregex: __meta_kubernetes_service_label_(.+)- action: replacesource_labels:- __meta_kubernetes_namespacetarget_label: kubernetes_namespace- action: replacesource_labels:- __meta_kubernetes_service_nametarget_label: kubernetes_name- job_name: kubernetes-serviceskubernetes_sd_configs:- role: servicemetrics_path: /probeparams:module:- http_2xxrelabel_configs:- action: keepregex: truesource_labels:- __meta_kubernetes_service_annotation_prometheus_io_probe- source_labels:- __address__target_label: __param_target- replacement: blackboxtarget_label: __address__- source_labels:- __param_targettarget_label: instance- action: labelmapregex: __meta_kubernetes_service_label_(.+)- source_labels:- __meta_kubernetes_namespacetarget_label: kubernetes_namespace- source_labels:- __meta_kubernetes_service_nametarget_label: kubernetes_name- job_name: kubernetes-podskubernetes_sd_configs:- role: podrelabel_configs:- action: keepregex: truesource_labels:- __meta_kubernetes_pod_annotation_prometheus_io_scrape- action: replaceregex: (.+)source_labels:- __meta_kubernetes_pod_annotation_prometheus_io_pathtarget_label: __metrics_path__- action: replaceregex: ([^:]+)(?::\d+)?;(\d+)replacement: $1:$2source_labels:- __address__- __meta_kubernetes_pod_annotation_prometheus_io_porttarget_label: __address__- action: labelmapregex: __meta_kubernetes_pod_label_(.+)- action: replacesource_labels:- __meta_kubernetes_namespacetarget_label: kubernetes_namespace- action: replacesource_labels:- __meta_kubernetes_pod_nametarget_label: kubernetes_pod_namealerting:alertmanagers:- static_configs:- targets: ["alertmanager:80"][root@k8s-node01 k8s-prometheus]# kubectl apply -f prometheus-configmap.yaml 
configmap/prometheus-config created

        2.3 有状态部署prometheus

        这里使用storageclass进行动态供给，给prometheus的数据进行持久化

[root@k8s-node01 k8s-prometheus]# cat prometheus-statefulset.yaml 
apiVersion: apps/v1
kind: StatefulSet
metadata:name: prometheus namespace: kube-systemlabels:k8s-app: prometheuskubernetes.io/cluster-service: "true"addonmanager.kubernetes.io/mode: Reconcileversion: v2.2.1
spec:serviceName: "prometheus"replicas: 1podManagementPolicy: "Parallel"updateStrategy:type: "RollingUpdate"selector:matchLabels:k8s-app: prometheustemplate:metadata:labels:k8s-app: prometheusannotations:scheduler.alpha.kubernetes.io/critical-pod: ''spec:priorityClassName: system-cluster-criticalserviceAccountName: prometheusinitContainers:- name: "init-chown-data"image: "busybox:latest"imagePullPolicy: "IfNotPresent"command: ["chown", "-R", "65534:65534", "/data"]volumeMounts:- name: prometheus-datamountPath: /datasubPath: ""containers:- name: prometheus-server-configmap-reloadimage: "jimmidyson/configmap-reload:v0.1"imagePullPolicy: "IfNotPresent"args:- --volume-dir=/etc/config- --webhook-url=http://localhost:9090/-/reloadvolumeMounts:- name: config-volumemountPath: /etc/configreadOnly: trueresources:limits:cpu: 10mmemory: 10Mirequests:cpu: 10mmemory: 10Mi- name: prometheus-serverimage: "prom/prometheus:v2.2.1"imagePullPolicy: "IfNotPresent"args:- --config.file=/etc/config/prometheus.yml- --storage.tsdb.path=/data- --web.console.libraries=/etc/prometheus/console_libraries- --web.console.templates=/etc/prometheus/consoles- --web.enable-lifecycleports:- containerPort: 9090readinessProbe:httpGet:path: /-/readyport: 9090initialDelaySeconds: 30timeoutSeconds: 30livenessProbe:httpGet:path: /-/healthyport: 9090initialDelaySeconds: 30timeoutSeconds: 30# based on 10 running nodes with 30 pods eachresources:limits:cpu: 200mmemory: 1000Mirequests:cpu: 200mmemory: 1000MivolumeMounts:- name: config-volumemountPath: /etc/config- name: prometheus-datamountPath: /datasubPath: ""- name: prometheus-rulesmountPath: /etc/config/rulesterminationGracePeriodSeconds: 300volumes:- name: config-volumeconfigMap:name: prometheus-config- name: prometheus-rulesconfigMap:name: prometheus-rulesvolumeClaimTemplates:- metadata:name: prometheus-dataspec:storageClassName: managed-nfs-storage accessModes:- ReadWriteOnceresources:requests:storage: "1Gi"[root@k8s-node01 k8s-prometheus]# kubectl apply -f prometheus-statefulset.yaml 
Warning: spec.template.metadata.annotations[scheduler.alpha.kubernetes.io/critical-pod]: non-functional in v1.16+; use the "priorityClassName" field instead
statefulset.apps/prometheus created[root@k8s-node01 k8s-prometheus]#kubectl get pod -n kube-system |grep prometheus
NAME                                    READY   STATUS    RESTARTS   AGE
prometheus-0                            2/2     Running   6          1d

        2.4 创建service暴露访问端口

[root@k8s-node01 k8s-prometheus]# cat prometheus-service.yaml 
kind: Service
apiVersion: v1
metadata: name: prometheusnamespace: kube-systemlabels: kubernetes.io/name: "Prometheus"kubernetes.io/cluster-service: "true"addonmanager.kubernetes.io/mode: Reconcile
spec: type: NodePortports: - name: http port: 9090protocol: TCPtargetPort: 9090nodePort: 30090selector: k8s-app: prometheus[root@k8s-master prometheus-k8s]# kubectl apply -f prometheus-service.yaml

        2.5 web访问

        使用任意一个NodeIP加端口进行访问，访问地址：http://NodeIP:Port

3.部署Grafana

        

[root@k8s-master prometheus-k8s]# cat grafana.yaml
apiVersion: apps/v1
kind: StatefulSet
metadata:name: grafananamespace: kube-system
spec:serviceName: "grafana"replicas: 1selector:matchLabels:app: grafanatemplate:metadata:labels:app: grafanaspec:containers:- name: grafanaimage: grafana/grafanaports:- containerPort: 3000protocol: TCPresources:limits:cpu: 100mmemory: 256Mirequests:cpu: 100mmemory: 256MivolumeMounts:- name: grafana-datamountPath: /var/lib/grafanasubPath: grafanasecurityContext:fsGroup: 472runAsUser: 472volumeClaimTemplates:- metadata:name: grafana-dataspec:storageClassName: managed-nfs-storage #和prometheus使用同一个存储类accessModes:- ReadWriteOnceresources:requests:storage: "1Gi"---apiVersion: v1
kind: Service
metadata:name: grafananamespace: kube-system
spec:type: NodePortports:- port : 80targetPort: 3000nodePort: 30091selector:app: grafana[root@k8s-master prometheus-k8s]#kubectl apply -f grafana.yaml

访问方式：

使用任意一个NodeIP加端口进行访问，访问地址：http://NodeIP:Port ，默认账号密码为admin

4.监控K8S集群中Pod、Node、资源对象数据的方法

Pod：
kubelet的节点使用cAdvisor提供的metrics接口获取该节点所有Pod和容器相关的性能指标数据，安装kubelet默认就开启了

Node：

需要使用node_exporter收集器采集节点资源利用率。

使用node_exporter.sh脚本分别在所有服务器上部署node_exporter收集器，不需要修改可直接运行脚本

[root@k8s-master prometheus-k8s]# cat node_exporter.sh 
#!/bin/bashwget https://github.com/prometheus/node_exporter/releases/download/v0.17.0/node_exporter-0.17.0.linux-amd64.tar.gztar zxf node_exporter-0.17.0.linux-amd64.tar.gz
mv node_exporter-0.17.0.linux-amd64 /usr/local/node_exportercat <<EOF >/usr/lib/systemd/system/node_exporter.service
[Unit]
Description=https://prometheus.io[Service]
Restart=on-failure
ExecStart=/usr/local/node_exporter/node_exporter --collector.systemd --collector.systemd.unit-whitelist=(docker|kubelet|kube-proxy|flanneld).service[Install]
WantedBy=multi-user.target
EOFsystemctl daemon-reload
systemctl enable node_exporter
systemctl restart node_exporter
[root@k8s-master prometheus-k8s]# ./node_exporter.sh[root@k8s-master prometheus-k8s]# ps -ef|grep node_exporter
root       6227      1  0 Oct08 ?        00:06:43 /usr/local/node_exporter/node_exporter --collector.systemd --collector.systemd.unit-whitelist=(docker|kubelet|kube-proxy|flanneld).service
root     118269 117584  0 23:27 pts/0    00:00:00 grep --color=auto node_exporter

资源对象：

kube-state-metrics采集了k8s中各种资源对象的状态信息，只需要在master节点部署就行

        1.创建rbac的yaml对metrics进行授权

[root@k8s-master prometheus-k8s]# cat kube-state-metrics-rbac.yaml
apiVersion: v1
kind: ServiceAccount
metadata:name: kube-state-metricsnamespace: kube-systemlabels:kubernetes.io/cluster-service: "true"addonmanager.kubernetes.io/mode: Reconcile
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:name: kube-state-metricslabels:kubernetes.io/cluster-service: "true"addonmanager.kubernetes.io/mode: Reconcile
rules:
- apiGroups: [""]resources:- configmaps- secrets- nodes- pods- services- resourcequotas- replicationcontrollers- limitranges- persistentvolumeclaims- persistentvolumes- namespaces- endpointsverbs: ["list", "watch"]
- apiGroups: ["extensions"]resources:- daemonsets- deployments- replicasetsverbs: ["list", "watch"]
- apiGroups: ["apps"]resources:- statefulsetsverbs: ["list", "watch"]
- apiGroups: ["batch"]resources:- cronjobs- jobsverbs: ["list", "watch"]
- apiGroups: ["autoscaling"]resources:- horizontalpodautoscalersverbs: ["list", "watch"]
---
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:name: kube-state-metrics-resizernamespace: kube-systemlabels:kubernetes.io/cluster-service: "true"addonmanager.kubernetes.io/mode: Reconcile
rules:
- apiGroups: [""]resources:- podsverbs: ["get"]
- apiGroups: ["extensions"]resources:- deploymentsresourceNames: ["kube-state-metrics"]verbs: ["get", "update"]
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:name: kube-state-metricslabels:kubernetes.io/cluster-service: "true"addonmanager.kubernetes.io/mode: Reconcile
roleRef:apiGroup: rbac.authorization.k8s.iokind: ClusterRolename: kube-state-metrics
subjects:
- kind: ServiceAccountname: kube-state-metricsnamespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:name: kube-state-metricsnamespace: kube-systemlabels:kubernetes.io/cluster-service: "true"addonmanager.kubernetes.io/mode: Reconcile
roleRef:apiGroup: rbac.authorization.k8s.iokind: Rolename: kube-state-metrics-resizer
subjects:
- kind: ServiceAccountname: kube-state-metricsnamespace: kube-system
[root@k8s-master prometheus-k8s]# kubectl apply -f kube-state-metrics-rbac.yaml

        2.编写Deployment和ConfigMap的yaml进行metrics pod部署，不需要进行修改

[root@k8s-master prometheus-k8s]# cat kube-state-metrics-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:name: kube-state-metricsnamespace: kube-systemlabels:k8s-app: kube-state-metricskubernetes.io/cluster-service: "true"addonmanager.kubernetes.io/mode: Reconcileversion: v1.3.0
spec:selector:matchLabels:k8s-app: kube-state-metricsversion: v1.3.0replicas: 1template:metadata:labels:k8s-app: kube-state-metricsversion: v1.3.0annotations:scheduler.alpha.kubernetes.io/critical-pod: ''spec:priorityClassName: system-cluster-criticalserviceAccountName: kube-state-metricscontainers:- name: kube-state-metricsimage: lizhenliang/kube-state-metrics:v1.3.0ports:- name: http-metricscontainerPort: 8080- name: telemetrycontainerPort: 8081readinessProbe:httpGet:path: /healthzport: 8080initialDelaySeconds: 5timeoutSeconds: 5- name: addon-resizerimage: lizhenliang/addon-resizer:1.8.3resources:limits:cpu: 100mmemory: 30Mirequests:cpu: 100mmemory: 30Mienv:- name: MY_POD_NAMEvalueFrom:fieldRef:fieldPath: metadata.name- name: MY_POD_NAMESPACEvalueFrom:fieldRef:fieldPath: metadata.namespacevolumeMounts:- name: config-volumemountPath: /etc/configcommand:- /pod_nanny- --config-dir=/etc/config- --container=kube-state-metrics- --cpu=100m- --extra-cpu=1m- --memory=100Mi- --extra-memory=2Mi- --threshold=5- --deployment=kube-state-metricsvolumes:- name: config-volumeconfigMap:name: kube-state-metrics-config
---
# Config map for resource configuration.
apiVersion: v1
kind: ConfigMap
metadata:name: kube-state-metrics-confignamespace: kube-systemlabels:k8s-app: kube-state-metricskubernetes.io/cluster-service: "true"addonmanager.kubernetes.io/mode: Reconcile
data:NannyConfiguration: |-apiVersion: nannyconfig/v1alpha1kind: NannyConfiguration
[root@k8s-master prometheus-k8s]# kubectl apply -f kube-state-metrics-deployment.yaml

        3.编写Service的yaml对metrics进行端口暴露

[root@k8s-master prometheus-k8s]# cat kube-state-metrics-service.yaml
apiVersion: v1
kind: Service
metadata:name: kube-state-metricsnamespace: kube-systemlabels:kubernetes.io/cluster-service: "true"addonmanager.kubernetes.io/mode: Reconcilekubernetes.io/name: "kube-state-metrics"annotations:prometheus.io/scrape: 'true'
spec:ports:- name: http-metricsport: 8080targetPort: http-metricsprotocol: TCP- name: telemetryport: 8081targetPort: telemetryprotocol: TCPselector:k8s-app: kube-state-metrics
[root@k8s-master prometheus-k8s]# kubectl apply -f kube-state-metrics-service.yaml[root@k8s-master prometheus-k8s]# kubectl get pod,svc -n kube-system
NAME                                        READY   STATUS    RESTARTS   AGE
pod/alertmanager-5d75d5688f-fmlq6           2/2     Running   0          9dpod/coredns-5bd5f9dbd9-wv45t                1/1     Running   1          9dpod/grafana-0                               1/1     Running   2          15dpod/kube-state-metrics-7c76bdbf68-kqqgd     2/2     Running   6          14dpod/kubernetes-dashboard-7d77666777-d5ng4   1/1     Running   5          16dpod/prometheus-0                            2/2     Running   6          15dNAME                           TYPE        CLUSTER-IP   EXTERNAL-IP   PORT(S)             AGE
service/alertmanager           ClusterIP   10.0.0.207   <none>        80/TCP              13dservice/grafana                NodePort    10.0.0.74    <none>        80:30091/TCP        15dservice/kube-dns               ClusterIP   10.0.0.2     <none>        53/UDP,53/TCP       14dservice/kube-state-metrics     ClusterIP   10.0.0.194   <none>        8080/TCP,8081/TCP   14dservice/kubernetes-dashboard   NodePort    10.0.0.127   <none>        443:30001/TCP       17dservice/prometheus             NodePort    10.0.0.33    <none>        9090:30090/TCP      14d
报错一：进行2.1步骤时报错：ensure CRDs are installed first

[root@k8s-node01 k8s-prometheus]# kubectl apply -f prometheus-rbac.yaml
serviceaccount/prometheus unchanged
resource mapping not found for name: "prometheus" namespace: "" from "prometheus-rbac.yaml": no matches for kind "ClusterRole" in version "rbac.authorization.k8s.io/v1beta1"
ensure CRDs are installed first
resource mapping not found for name: "prometheus" namespace: "" from "prometheus-rbac.yaml": no matches for kind "ClusterRoleBinding" in version "rbac.authorization.k8s.io/v1beta1"
ensure CRDs are installed first

使用附件的原yaml会报错，原因是因为api过期，需要手动修改 apiVersion: rbac.authorization.k8s.io/v1beta1为apiVersion: rbac.authorization.k8s.io/v1

本文来自互联网用户投稿，该文观点仅代表作者本人，不代表本站立场。本站仅提供信息存储空间服务，不拥有所有权，不承担相关法律责任。如若转载，请注明出处：http://www.mzph.cn/web/16564.shtml

如若内容造成侵权/违法违规/事实不符，请联系多彩编程网进行投诉反馈email:809451989@qq.com，一经查实，立即删除！

相关文章

C++质数的那些事（判断指数、区间筛质数、互质等等）

C++质数的那些事（判断指数、区间筛质数、互质等等）

质数的定义&#xff1a;若一个正整数除了1和它自身之外不能被任何自然数整除&#xff0c;则该数称为质数&#xff0c;也叫素数。否则为合数。 质数的性质&#xff1a;质数的分布较为稀疏&#xff0c;对于一个足够大的数S&#xff0c;不超过S的质数大约有个&#xff0c;也就是说…
阅读更多...
有趣的css - 水波纹按钮

有趣的css - 水波纹按钮

大家好&#xff0c;我是 Just&#xff0c;这里是「设计师工作日常」&#xff0c;今天分享的是一个好看有质感的水波纹按钮。 最新文章通过公众号「设计师工作日常」发布。 目录 整体效果核心代码html 代码css 部分代码 完整代码如下html 页面css 样式页面渲染效果 整体效果 &a…
阅读更多...
【Spring Cloud】远程调用

【Spring Cloud】远程调用

目录 Spring Cloud Netflix Feign简介前言Feign是什么OpenFeign组件和Spring Cloud OpenFeignOpenFeign组件Spring Cloud OpenFeign OpenFeign-微服务接口调用需求说明1. 启动Eureka Server服务2.创建两个项目&#xff0c;将其注册到Eureka Server3.在服务提供者中添加业务处理…
阅读更多...
【UE Websocket】“WebSocket Server”插件使用记录

【UE Websocket】“WebSocket Server”插件使用记录

1. 在商城中下载“WebSocket Server”插件 该插件具有如下节点&#xff0c;基本可以满足WebSocket服务端的所有需求 2. 如果想创建一个基本的服务端&#xff0c;我们可以新建一个actor蓝图&#xff0c;添加如下节点 3. UE运行后&#xff0c;我们可以使用在线的websocket测试助手…
阅读更多...
RuntimeError: CUDA out of memory. Tried to allocate 1.77 GiB？如何解决

RuntimeError: CUDA out of memory. Tried to allocate 1.77 GiB？如何解决

&#x1f3c6;本文收录于「Bug调优」专栏&#xff0c;主要记录项目实战过程中的Bug之前因后果及提供真实有效的解决方案&#xff0c;希望能够助你一臂之力&#xff0c;帮你早日登顶实现财富自由&#x1f680;&#xff1b;同时&#xff0c;欢迎大家关注&&收藏&&…
阅读更多...
开源与闭源AI模型的对决：数据隐私、商业应用与社区参与

开源与闭源AI模型的对决：数据隐私、商业应用与社区参与

引言 在人工智能&#xff08;AI&#xff09;领域&#xff0c;模型的发展路径主要分为“开源”和“闭源”两条。这两种模型在数据隐私保护、商业应用以及社区参与与合作方面各有优劣&#xff0c;是创业公司、技术巨头和开发者们必须仔细权衡的重要选择。那么&#xff0c;面对这些…
阅读更多...
7、PyCharm的基础使用

7、PyCharm的基础使用

阅读更多...
6、python开发环境-PyCharm

6、python开发环境-PyCharm

下载完成之后双击进行安装 找到安装好的解释器程序
阅读更多...
ZeroTier+Nomachine远程

ZeroTier+Nomachine远程

目录 前述&#xff1a;一、Zero二、Nomachine 前述&#xff1a; 需要远程控制时&#xff0c;服务端与客户端都必须下载这两个软件&#xff01;远程主机&#xff08;被控制的主机&#xff09;和远程客户端&#xff08;控制主机的用户&#xff09;都必须具有网络连接&#xff0c;…
阅读更多...
11.Redis之zset类型

11.Redis之zset类型

1.zset类型基本介绍 有序描述的是&#xff1a;升序/降序 Set 集合 1.唯一 2. 无序 孙行者,行者孙, 者行孙 >同一只猴~~ List有序的 孙行者,行者孙, 者行孙 >不同的猴~~ zset 中的 member 仍然要求是唯一的!!(score 则可以重复) 排序的规则是啥? 给 zset 中的 member 同…
阅读更多...
快速排序算法备考

快速排序算法备考

快排模板 快速排序(快排) (C语言实现)_c语言快速排序_Brant_zero2022的博客-CSDN博客 快排使用递归来实现 关键思想:划分 //划分 int partion(int A[],int L,int R){int midA[L];while(L<R){//每一次划分:左边元素<枢轴元素<右边元素//R往前找&#xff0c;直到找到一…
阅读更多...
SQL 语言：基本概述和数据定义

SQL 语言：基本概述和数据定义

文章目录 1. 数据库语言2. SQL 概述2.1 SQL 的特点2.2 SQL 语言支持三级模式结构2.3 SQL 的基本组成 3. 数据定义3.1 数据类型3.2 创建表3.3 修改和删除表3.4 创建和删除索引3.5 创建和删除视图 1. 数据库语言 数据结构化语言 (Structured Query Language&#xff0c;SQL)&…
阅读更多...
【机器学习】——线性模型

【机器学习】——线性模型

&#x1f4bb;博主现有专栏&#xff1a; C51单片机&#xff08;STC89C516&#xff09;&#xff0c;c语言&#xff0c;c&#xff0c;离散数学&#xff0c;算法设计与分析&#xff0c;数据结构&#xff0c;Python&#xff0c;Java基础&#xff0c;MySQL&#xff0c;linux&#xf…
阅读更多...
面试被问到不懂的东西，是直接说不懂还是坚持狡辩一下？

面试被问到不懂的东西，是直接说不懂还是坚持狡辩一下？

大家好&#xff0c;我是瑶琴呀。 面试被问到不懂的东西&#xff0c;是直接说不懂还是坚持狡辩一下&#xff1f;这个问题可以转变一下&#xff0c;如果你顺利拿到 offer&#xff0c;公司安排的工作跟你之前的技术和经验不匹配&#xff0c;你还愿意干下去吗&#xff1f; 转变一…
阅读更多...
太速科技-FMC125-两路125Msps AD，两路160Msps DA FMC子卡

太速科技-FMC125-两路125Msps AD，两路160Msps DA FMC子卡

FMC125-两路125Msps AD&#xff0c;两路160Msps DA FMC子卡 一、板卡概述 板卡可实现2路14bit 125Msps AD 和2路16bit 160MspsDA功能&#xff0c;FMC LPC连接器用于扩展到xilinx用于模拟信号、中频信号采集&#xff0c;信号发出等应用。 二、性能指标 板卡功能 参…
阅读更多...
幻影成像制作中，哪些技术细节不可忽视？

幻影成像制作中，哪些技术细节不可忽视？

在当今多媒体展厅设计的潮流中&#xff0c;幻影成像技术以其立体的数字影像和卓越的视觉效果&#xff0c;脱颖而出&#xff0c;成为备受瞩目的焦点。它不仅吸引了众多参观者的目光&#xff0c;更在社交媒体上掀起了热烈的讨论。然而&#xff0c;要想在多媒体展厅中精心打造一场…
阅读更多...
2024可信赖的企业级生成式 AI 白皮书

2024可信赖的企业级生成式 AI 白皮书

来源&#xff1a;COPU&IBM&#xff1a; 近期历史回顾&#xff1a;
阅读更多...
k8s devops实战教程+生产实践+可就业

k8s devops实战教程+生产实践+可就业

k8s devops实战教程 简介教程涉及到内容教程获取学习教程后的收货助学群 简介 越来越多的企业应用云原生化&#xff0c;催生很多应用的部署方式也发生了很多变化。 从物理机部署应用过度到虚机部署应用再到应用容器化&#xff0c;从单应用再到服务拆分为微服务&#xff0c;靠人…
阅读更多...
是他将计算机从“一屋子”变成“一柜子”——量子前哨缅怀小型机之父 戈登·贝尔

是他将计算机从“一屋子”变成“一柜子”——量子前哨缅怀小型机之父 戈登·贝尔

内容来源&#xff1a;量子前哨&#xff08;ID&#xff1a;Qforepost&#xff09; 文丨浪味仙 排版丨沛贤 深度好文&#xff1a;6000字丨15分钟阅读 5 月 21 日&#xff0c; 美国贝尔实验室资深人士 John Mashey 发布消息称&#xff0c;计算机先驱戈登贝尔&#xff08;Gordon…
阅读更多...
机器人系统ros2-开发学习实践15-模拟用 URDF 建模 步行机器人行走示例

机器人系统ros2-开发学习实践15-模拟用 URDF 建模 步行机器人行走示例

目标&#xff1a; 本教程将向您展示如何建模行走机器人、将状态发布为tf2消息并在 Rviz 中查看模拟。首先&#xff0c;我们创建描述机器人组件的 URDF 模型。接下来&#xff0c;我们编写一个节点来模拟运动并发布 JointState 和变换。然后我们使用robot_state_publisher将整个…
阅读更多...
推荐文章
最新文章

Copyright @ 2022~2023