k8s和deepflow部署与测试

环境详情：当您在上安装登录到主节点并使用在每个节点的/etc/hosts$(-cs部分配置手动修改设置crictl安装一个 Pod 网络插件，例如 Calico 或 Flannel。启动otel-collector和otel-agent需要程序集成API，发送到以DaemonSet运行在每个节点的otel-agent，otel-agent再将数据发送给otel-collector汇总，然后发往可以

大囚长

1479人浏览 · 2024-06-04 11:12:53

大囚长 · 2024-06-04 11:12:53 发布

Ubuntu-22-LTS部署k8s和deepflow

环境详情：
Static hostname: k8smaster.example.net
Icon name: computer-vm
Chassis: vm
Machine ID: 22349ac6f9ba406293d0541bcba7c05d
Boot ID: 605a74a509724a88940bbbb69cde77f2
Virtualization: vmware
Operating System: Ubuntu 22.04.4 LTS
Kernel: Linux 5.15.0-106-generic
Architecture: x86-64
Hardware Vendor: VMware, Inc.
Hardware Model: VMware Virtual Platform

当您在 Ubuntu 22.04 上安装 Kubernetes 集群时，您可以遵循以下步骤：

设置主机名并在 hosts 文件中添加条目：

登录到主节点并使用 hostnamectl 命令设置主机名：
```
hostnamectl set-hostname "k8smaster.example.net"
```

在工作节点上，运行以下命令设置主机名（分别对应第一个和第二个工作节点）：

hostnamectl set-hostname "k8sworker1.example.net"  # 第一个工作节点
hostnamectl set-hostname "k8sworker2.example.net"  # 第二个工作节点

在每个节点的 /etc/hosts 文件中添加以下条目：

10.1.1.70 k8smaster.example.net k8smaster
10.1.1.71 k8sworker1.example.net k8sworker1

禁用 swap 并添加内核设置：

在所有节点上执行以下命令以禁用交换功能：

swapoff -a
sed -i '/swap/ s/^\(.*\)$/#\1/g' /etc/fstab

加载以下内核模块：

tee /etc/modules-load.d/containerd.conf <<EOF
overlay
br_netfilter
EOF
modprobe overlay
modprobe br_netfilter

为 Kubernetes 设置以下内核参数：

tee /etc/sysctl.d/kubernetes.conf <<EOF
net.bridge.bridge-nf-call-ip6tables = 1
net.bridge.bridge-nf-call-iptables = 1
net.ipv4.ip_forward = 1
EOF
sysctl --system

安装 containerd 运行时：

首先安装 containerd 的依赖项：

apt install -y curl gnupg2 software-properties-common apt-transport-https ca-certificates

启用 Docker 存储库：

curl -fsSL https://download.docker.com/linux/ubuntu/gpg | apt-key add -
add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"

安装 containerd：

apt update
apt install -y containerd.io

配置 containerd 使用 systemd 作为 cgroup：

containerd config default | tee /etc/containerd/config.toml > /dev/null 2>&1
sed -i 's/SystemdCgroup\\=false/SystemdCgroup\\=true/g' /etc/containerd/config.toml

部分配置手动修改

disabled_plugins = []
imports = []
oom_score = 0
plugin_dir = ""
required_plugins = []
root = "/var/lib/containerd"
state = "/run/containerd"
temp = ""
version = 2

[cgroup]
path = ""

[debug]
address = ""
format = ""
gid = 0
level = ""
uid = 0

[grpc]
address = "/run/containerd/containerd.sock"
gid = 0
max_recv_message_size = 16777216
max_send_message_size = 16777216
tcp_address = ""
tcp_tls_ca = ""
tcp_tls_cert = ""
tcp_tls_key = ""
uid = 0

[metrics]
address = ""
grpc_histogram = false

[plugins]

[plugins."io.containerd.gc.v1.scheduler"]
    deletion_threshold = 0
    mutation_threshold = 100
    pause_threshold = 0.02
    schedule_delay = "0s"
    startup_delay = "100ms"

[plugins."io.containerd.grpc.v1.cri"]
    device_ownership_from_security_context = false
    disable_apparmor = false
    disable_cgroup = false
    disable_hugetlb_controller = true
    disable_proc_mount = false
    disable_tcp_service = true
    drain_exec_sync_io_timeout = "0s"
    enable_selinux = false
    enable_tls_streaming = false
    enable_unprivileged_icmp = false
    enable_unprivileged_ports = false
    ignore_deprecation_warnings = []
    ignore_image_defined_volumes = false
    max_concurrent_downloads = 3
    max_container_log_line_size = 16384
    netns_mounts_under_state_dir = false
    restrict_oom_score_adj = false
    # 修改以下这行
    sandbox_image = "registry.aliyuncs.com/google_containers/pause:3.8"
    selinux_category_range = 1024
    stats_collect_period = 10
    stream_idle_timeout = "4h0m0s"
    stream_server_address = "127.0.0.1"
    stream_server_port = "0"
    systemd_cgroup = false
    tolerate_missing_hugetlb_controller = true
    unset_seccomp_profile = ""

    [plugins."io.containerd.grpc.v1.cri".cni]
    bin_dir = "/opt/cni/bin"
    conf_dir = "/etc/cni/net.d"
    conf_template = ""
    ip_pref = ""
    max_conf_num = 1

    [plugins."io.containerd.grpc.v1.cri".containerd]
    default_runtime_name = "runc"
    disable_snapshot_annotations = true
    discard_unpacked_layers = false
    ignore_rdt_not_enabled_errors = false
    no_pivot = false
    snapshotter = "overlayfs"

    [plugins."io.containerd.grpc.v1.cri".containerd.default_runtime]
        base_runtime_spec = ""
        cni_conf_dir = ""
        cni_max_conf_num = 0
        container_annotations = []
        pod_annotations = []
        privileged_without_host_devices = false
        runtime_engine = ""
        runtime_path = ""
        runtime_root = ""
        runtime_type = ""

        [plugins."io.containerd.grpc.v1.cri".containerd.default_runtime.options]

    [plugins."io.containerd.grpc.v1.cri".containerd.runtimes]

        [plugins."io.containerd.grpc.v1.cri".containerd.runtimes.runc]
        base_runtime_spec = ""
        cni_conf_dir = ""
        cni_max_conf_num = 0
        container_annotations = []
        pod_annotations = []
        privileged_without_host_devices = false
        runtime_engine = ""
        runtime_path = ""
        runtime_root = ""
        runtime_type = "io.containerd.runc.v2"

        [plugins."io.containerd.grpc.v1.cri".containerd.runtimes.runc.options]
            BinaryName = ""
            CriuImagePath = ""
            CriuPath = ""
            CriuWorkPath = ""
            IoGid = 0
            IoUid = 0
            NoNewKeyring = false
            NoPivotRoot = false
            Root = ""
            ShimCgroup = ""
            SystemdCgroup = true

    [plugins."io.containerd.grpc.v1.cri".containerd.untrusted_workload_runtime]
        base_runtime_spec = ""
        cni_conf_dir = ""
        cni_max_conf_num = 0
        container_annotations = []
        pod_annotations = []
        privileged_without_host_devices = false
        runtime_engine = ""
        runtime_path = ""
        runtime_root = ""
        runtime_type = ""

        [plugins."io.containerd.grpc.v1.cri".containerd.untrusted_workload_runtime.options]

    [plugins."io.containerd.grpc.v1.cri".image_decryption]
    key_model = "node"

    [plugins."io.containerd.grpc.v1.cri".registry]
    config_path = ""

    [plugins."io.containerd.grpc.v1.cri".registry.auths]

    [plugins."io.containerd.grpc.v1.cri".registry.configs]

    [plugins."io.containerd.grpc.v1.cri".registry.headers]

    [plugins."io.containerd.grpc.v1.cri".registry.mirrors]
        # 添加如下4行
        [plugins."io.containerd.grpc.v1.cri".registry.mirrors."docker.io"]
        endpoint = ["https://docker.mirrors.ustc.edu.cn"]
        [plugins."io.containerd.grpc.v1.cri".registry.mirrors."k8s.gcr.io"]
        endpoint = ["https://registry.aliyuncs.com/google_containers"]

    [plugins."io.containerd.grpc.v1.cri".x509_key_pair_streaming]
    tls_cert_file = ""
    tls_key_file = ""

[plugins."io.containerd.internal.v1.opt"]
    path = "/opt/containerd"

[plugins."io.containerd.internal.v1.restart"]
    interval = "10s"

[plugins."io.containerd.internal.v1.tracing"]
    sampling_ratio = 1.0
    service_name = "containerd"

[plugins."io.containerd.metadata.v1.bolt"]
    content_sharing_policy = "shared"

[plugins."io.containerd.monitor.v1.cgroups"]
    no_prometheus = false

[plugins."io.containerd.runtime.v1.linux"]
    no_shim = false
    runtime = "runc"
    runtime_root = ""
    shim = "containerd-shim"
    shim_debug = false

[plugins."io.containerd.runtime.v2.task"]
    platforms = ["linux/amd64"]
    sched_core = false

[plugins."io.containerd.service.v1.diff-service"]
    default = ["walking"]

[plugins."io.containerd.service.v1.tasks-service"]
    rdt_config_file = ""

[plugins."io.containerd.snapshotter.v1.aufs"]
    root_path = ""

[plugins."io.containerd.snapshotter.v1.btrfs"]
    root_path = ""

[plugins."io.containerd.snapshotter.v1.devmapper"]
    async_remove = false
    base_image_size = ""
    discard_blocks = false
    fs_options = ""
    fs_type = ""
    pool_name = ""
    root_path = ""

[plugins."io.containerd.snapshotter.v1.native"]
    root_path = ""

[plugins."io.containerd.snapshotter.v1.overlayfs"]
    mount_options = []
    root_path = ""
    sync_remove = false
    upperdir_label = false

[plugins."io.containerd.snapshotter.v1.zfs"]
    root_path = ""

[plugins."io.containerd.tracing.processor.v1.otlp"]
    endpoint = ""
    insecure = false
    protocol = ""

[proxy_plugins]

[stream_processors]

[stream_processors."io.containerd.ocicrypt.decoder.v1.tar"]
    accepts = ["application/vnd.oci.image.layer.v1.tar+encrypted"]
    args = ["--decryption-keys-path", "/etc/containerd/ocicrypt/keys"]
    env = ["OCICRYPT_KEYPROVIDER_CONFIG=/etc/containerd/ocicrypt/ocicrypt_keyprovider.conf"]
    path = "ctd-decoder"
    returns = "application/vnd.oci.image.layer.v1.tar"

[stream_processors."io.containerd.ocicrypt.decoder.v1.tar.gzip"]
    accepts = ["application/vnd.oci.image.layer.v1.tar+gzip+encrypted"]
    args = ["--decryption-keys-path", "/etc/containerd/ocicrypt/keys"]
    env = ["OCICRYPT_KEYPROVIDER_CONFIG=/etc/containerd/ocicrypt/ocicrypt_keyprovider.conf"]
    path = "ctd-decoder"
    returns = "application/vnd.oci.image.layer.v1.tar+gzip"

[timeouts]
"io.containerd.timeout.bolt.open" = "0s"
"io.containerd.timeout.shim.cleanup" = "5s"
"io.containerd.timeout.shim.load" = "5s"
"io.containerd.timeout.shim.shutdown" = "3s"
"io.containerd.timeout.task.state" = "2s"

[ttrpc]
address = ""
gid = 0
uid = 0

重启并启用容器服务：

systemctl restart containerd
systemctl enable containerd

设置crictl

cat > /etc/crictl.yaml <<EOF
runtime-endpoint: unix:///var/run/containerd/containerd.sock
image-endpoint: unix:///var/run/containerd/containerd.sock
timeout: 10
debug: false
pull-image-on-create: false
EOF

添加阿里云的 Kubernetes 源：

首先，导入阿里云的 GPG 密钥：

curl -fsSL https://mirrors.aliyun.com/kubernetes/apt/doc/apt-key.gpg | apt-key add -

然后，添加阿里云的 Kubernetes 源：

tee /etc/apt/sources.list.d/kubernetes.list <<EOF
deb https://mirrors.aliyun.com/kubernetes/apt/ kubernetes-xenial main
EOF

安装 Kubernetes 组件：

更新软件包索引并安装 kubelet、kubeadm 和 kubectl：

apt-get update
apt-get install -y kubelet kubeadm kubectl

设置 kubelet 使用 systemd 作为 cgroup 驱动：

# 可忽略
# sed -i 's/cgroup-driver=systemd/cgroup-driver=cgroupfs/g' /var/lib/kubelet/kubeadm-flags.env
# systemctl daemon-reload
# systemctl restart kubelet

初始化 Kubernetes 集群：

使用 kubeadm 初始化集群，并指定阿里云的镜像仓库：

# kubeadm init --image-repository registry.aliyuncs.com/google_containers
I0513 14:16:59.740096   17563 version.go:256] remote version is much newer: v1.30.0; falling back to: stable-1.28
[init] Using Kubernetes version: v1.28.9
[preflight] Running pre-flight checks
[preflight] Pulling images required for setting up a Kubernetes cluster
[preflight] This might take a minute or two, depending on the speed of your internet connection
[preflight] You can also perform this action in beforehand using 'kubeadm config images pull'
W0513 14:17:01.440936   17563 checks.go:835] detected that the sandbox image "registry.aliyuncs.com/google_containers/pause:3.8" of the container runtime         is inconsistent with that used by kubeadm. It is recommended that using "registry.aliyuncs.com/google_containers/pause:3.9" as the CRI sandbox image.
[certs] Using certificateDir folder "/etc/kubernetes/pki"
[certs] Generating "ca" certificate and key
[certs] Generating "apiserver" certificate and key
[certs] apiserver serving cert is signed for DNS names [k8smaster.example.net kubernetes kubernetes.default kubernetes.default.svc kubernetes.default.svc.        cluster.local] and IPs [10.96.0.1 10.1.1.70]
[certs] Generating "apiserver-kubelet-client" certificate and key
[certs] Generating "front-proxy-ca" certificate and key
[certs] Generating "front-proxy-client" certificate and key
[certs] Generating "etcd/ca" certificate and key
[certs] Generating "etcd/server" certificate and key
[certs] etcd/server serving cert is signed for DNS names [k8smaster.example.net localhost] and IPs [10.1.1.70 127.0.0.1 ::1]
[certs] Generating "etcd/peer" certificate and key
[certs] etcd/peer serving cert is signed for DNS names [k8smaster.example.net localhost] and IPs [10.1.1.70 127.0.0.1 ::1]
[certs] Generating "etcd/healthcheck-client" certificate and key
[certs] Generating "apiserver-etcd-client" certificate and key
[certs] Generating "sa" key and public key
[kubeconfig] Using kubeconfig folder "/etc/kubernetes"
[kubeconfig] Writing "admin.conf" kubeconfig file
[kubeconfig] Writing "kubelet.conf" kubeconfig file
[kubeconfig] Writing "controller-manager.conf" kubeconfig file
[kubeconfig] Writing "scheduler.conf" kubeconfig file
[etcd] Creating static Pod manifest for local etcd in "/etc/kubernetes/manifests"
[control-plane] Using manifest folder "/etc/kubernetes/manifests"
[control-plane] Creating static Pod manifest for "kube-apiserver"
[control-plane] Creating static Pod manifest for "kube-controller-manager"
[control-plane] Creating static Pod manifest for "kube-scheduler"
[kubelet-start] Writing kubelet environment file with flags to file "/var/lib/kubelet/kubeadm-flags.env"
[kubelet-start] Writing kubelet configuration to file "/var/lib/kubelet/config.yaml"
[kubelet-start] Starting the kubelet
[wait-control-plane] Waiting for the kubelet to boot up the control plane as static Pods from directory "/etc/kubernetes/manifests". This can take up to         4m0s
[apiclient] All control plane components are healthy after 4.002079 seconds
[upload-config] Storing the configuration used in ConfigMap "kubeadm-config" in the "kube-system" Namespace
[kubelet] Creating a ConfigMap "kubelet-config" in namespace kube-system with the configuration for the kubelets in the cluster
[upload-certs] Skipping phase. Please see --upload-certs
[mark-control-plane] Marking the node k8smaster.example.net as control-plane by adding the labels: [node-role.kubernetes.io/control-plane node.kubernetes.        io/exclude-from-external-load-balancers]
[mark-control-plane] Marking the node k8smaster.example.net as control-plane by adding the taints [node-role.kubernetes.io/control-plane:NoSchedule]
[bootstrap-token] Using token: m9z4yq.dok89ro6yt23wykr
[bootstrap-token] Configuring bootstrap tokens, cluster-info ConfigMap, RBAC Roles
[bootstrap-token] Configured RBAC rules to allow Node Bootstrap tokens to get nodes
[bootstrap-token] Configured RBAC rules to allow Node Bootstrap tokens to post CSRs in order for nodes to get long term certificate credentials
[bootstrap-token] Configured RBAC rules to allow the csrapprover controller automatically approve CSRs from a Node Bootstrap Token
[bootstrap-token] Configured RBAC rules to allow certificate rotation for all node client certificates in the cluster
[bootstrap-token] Creating the "cluster-info" ConfigMap in the "kube-public" namespace
[kubelet-finalize] Updating "/etc/kubernetes/kubelet.conf" to point to a rotatable kubelet client certificate and key
[addons] Applied essential addon: CoreDNS
[addons] Applied essential addon: kube-proxy

Your Kubernetes control-plane has initialized successfully!

To start using your cluster, you need to run the following as a regular user:

  mkdir -p $HOME/.kube
  sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
  sudo chown $(id -u):$(id -g) $HOME/.kube/config

Alternatively, if you are the root user, you can run:

  export KUBECONFIG=/etc/kubernetes/admin.conf

You should now deploy a pod network to the cluster.
Run "kubectl apply -f [podnetwork].yaml" with one of the options listed at:
  https://kubernetes.io/docs/concepts/cluster-administration/addons/

Then you can join any number of worker nodes by running the following on each as root:

kubeadm join 10.1.1.70:6443 --token m9z4yq.dok89ro6yt23wykr \
        --discovery-token-ca-cert-hash sha256:17c3f29bd276592e668e9e6a7a187140a887254b4555cf7d293c3313d7c8a178

配置 kubectl：

为当前用户设置 kubectl 访问：

mkdir -p $HOME/.kube
cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
chown $(id -u):$(id -g) $HOME/.kube/config

安装网络插件：

安装一个 Pod 网络插件，例如 Calico 或 Flannel。例如，使用 Calico：

kubectl apply -f https://docs.projectcalico.org/manifests/calico.yaml
# 网络插件初始化完毕之后，coredns容器就正常了
kubectl logs -n kube-system -l k8s-app=kube-dns

验证集群：

启动一个nginx pod：

# vim nginx_pod.yml
apiVersion: v1
kind: Pod
metadata:
  name: test-nginx-pod
  namespace: test
  labels:
    app: nginx
spec:
  containers:
  - name: test-nginx-container
    image: nginx:latest
    ports:
    - containerPort: 80
  tolerations:
    - key: "node-role.kubernetes.io/control-plane"
      operator: "Exists"
      effect: "NoSchedule"
---

apiVersion: v1
kind: Service
# service和pod必须位于同一个namespace
metadata:
  name: nginx-service
  namespace: test
spec:
  type: NodePort
  # selector应该匹配pod的labels
  selector:
    app: nginx
  ports:
  - protocol: TCP
    port: 80
    nodePort: 30007
    targetPort: 80

启动

kubectl apply -f nginx_pod.yml

部署opentelemetry-collector测试

otel-collector和otel-agent需要程序集成API，发送到以DaemonSet运行在每个节点的otel-agent，otel-agent再将数据发送给otel-collector汇总，然后发往可以处理otlp trace数据的后端，如zipkin、jaeger等。

自定义测试yaml文件

apiVersion: v1
kind: ConfigMap
metadata:
  name: otel-collector-conf
  namespace: default
data:
  # 你的配置数据
  config.yaml: |
    receivers:
      otlp:
        protocols:
          grpc:
          http:
    processors:
      batch:
    exporters:
      logging:
        loglevel: debug
    service:
      pipelines:
        traces:
          receivers: [otlp]
          processors: [batch]
          exporters: [logging]

---
apiVersion: v1
kind: Service
metadata:
  name: otel-collector
  labels:
    app: opentelemetry
spec:
  type: NodePort
  ports:
    - port: 4317
      targetPort: 4317
      nodePort: 30080
      name: otlp-grpc
    - port: 8888
      targetPort: 8888
      name: metrics
  selector:
    component: otel-collector

---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: otel-collector
  labels:
    app: opentelemetry
spec:
  replicas: 1
  selector:
    matchLabels:
      component: otel-collector
  template:
    metadata:
      labels:
        component: otel-collector
    spec:
      tolerations:
      - key: node-role.kubernetes.io/control-plane
        operator: Exists
        effect: NoSchedule
      containers:
      - name: otel-collector
        image: otel/opentelemetry-collector:latest
        ports:
        - containerPort: 4317
        - containerPort: 8888
        env:
        - name: MY_POD_IP
          valueFrom:
            fieldRef:
              fieldPath: status.podIP
        volumeMounts:
        - name: otel-collector-config-vol
          mountPath: /conf
      volumes:
      - configMap:
          name: otel-collector-conf
        name: otel-collector-config-vol

启动

mkdir /conf
kubectl apply -f otel-collector.yaml
kubectl get -f otel-collector.yaml

删除

kubectl delete -f otel-collector.yaml

使用官方提供示例

kubectl apply -f https://raw.githubusercontent.com/open-telemetry/opentelemetry-collector/main/examples/k8s/otel-config.yaml

根据需要修改文件

otel-config.yaml

---
apiVersion: v1
kind: ConfigMap
metadata:
  name: otel-agent-conf
  labels:
    app: opentelemetry
    component: otel-agent-conf
data:
  otel-agent-config: |
    receivers:
      otlp:
        protocols:
          grpc:
            endpoint: ${env:MY_POD_IP}:4317
          http:
            endpoint: ${env:MY_POD_IP}:4318
    exporters:
      otlp:
        endpoint: "otel-collector.default:4317"
        tls:
          insecure: true
        sending_queue:
          num_consumers: 4
          queue_size: 100
        retry_on_failure:
          enabled: true
    processors:
      batch:
      memory_limiter:
        # 80% of maximum memory up to 2G
        limit_mib: 400
        # 25% of limit up to 2G
        spike_limit_mib: 100
        check_interval: 5s
    extensions:
      zpages: {}
    service:
      extensions: [zpages]
      pipelines:
        traces:
          receivers: [otlp]
          processors: [memory_limiter, batch]
          exporters: [otlp]
---
apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: otel-agent
  labels:
    app: opentelemetry
    component: otel-agent
spec:
  selector:
    matchLabels:
      app: opentelemetry
      component: otel-agent
  template:
    metadata:
      labels:
        app: opentelemetry
        component: otel-agent
    spec:
      tolerations:
      - key: node-role.kubernetes.io/control-plane
        operator: Exists
        effect: NoSchedule
      containers:
      - command:
          - "/otelcol"
          - "--config=/conf/otel-agent-config.yaml"
        image: otel/opentelemetry-collector:0.94.0
        name: otel-agent
        resources:
          limits:
            cpu: 500m
            memory: 500Mi
          requests:
            cpu: 100m
            memory: 100Mi
        ports:
        - containerPort: 55679 # ZPages endpoint.
        - containerPort: 4317 # Default OpenTelemetry receiver port.
        - containerPort: 8888  # Metrics.
        env:
          - name: MY_POD_IP
            valueFrom:
              fieldRef:
                apiVersion: v1
                fieldPath: status.podIP
          - name: GOMEMLIMIT
            value: 400MiB
        volumeMounts:
        - name: otel-agent-config-vol
          mountPath: /conf
      volumes:
        - configMap:
            name: otel-agent-conf
            items:
              - key: otel-agent-config
                path: otel-agent-config.yaml
          name: otel-agent-config-vol
---
apiVersion: v1
kind: ConfigMap
metadata:
  name: otel-collector-conf
  labels:
    app: opentelemetry
    component: otel-collector-conf
data:
  otel-collector-config: |
    receivers:
      otlp:
        protocols:
          grpc:
            endpoint: ${env:MY_POD_IP}:4317
          http:
            endpoint: ${env:MY_POD_IP}:4318
    processors:
      batch:
      memory_limiter:
        # 80% of maximum memory up to 2G
        limit_mib: 1500
        # 25% of limit up to 2G
        spike_limit_mib: 512
        check_interval: 5s
    extensions:
      zpages: {}
    exporters:
      otlp:
        endpoint: "http://someotlp.target.com:4317" # Replace with a real endpoint.
        tls:
          insecure: true
      zipkin:
        endpoint: "http://10.1.1.10:9411/api/v2/spans"
        format: "proto"
    service:
      extensions: [zpages]
      pipelines:
        traces/1:
          receivers: [otlp]
          processors: [memory_limiter, batch]
          exporters: [zipkin]
---
apiVersion: v1
kind: Service
metadata:
  name: otel-collector
  labels:
    app: opentelemetry
    component: otel-collector
spec:
  ports:
  - name: otlp-grpc # Default endpoint for OpenTelemetry gRPC receiver.
    port: 4317
    protocol: TCP
    targetPort: 4317
  - name: otlp-http # Default endpoint for OpenTelemetry HTTP receiver.
    port: 4318
    protocol: TCP
    targetPort: 4318
  - name: metrics # Default endpoint for querying metrics.
    port: 8888
  selector:
    component: otel-collector
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: otel-collector
  labels:
    app: opentelemetry
    component: otel-collector
spec:
  selector:
    matchLabels:
      app: opentelemetry
      component: otel-collector
  minReadySeconds: 5
  progressDeadlineSeconds: 120
  replicas: 1 #TODO - adjust this to your own requirements
  template:
    metadata:
      labels:
        app: opentelemetry
        component: otel-collector
    spec:
      tolerations:
      - key: node-role.kubernetes.io/control-plane
        operator: Exists
        effect: NoSchedule
      containers:
      - command:
          - "/otelcol"
          - "--config=/conf/otel-collector-config.yaml"
        image: otel/opentelemetry-collector:0.94.0
        name: otel-collector
        resources:
          limits:
            cpu: 1
            memory: 2Gi
          requests:
            cpu: 200m
            memory: 400Mi
        ports:
        - containerPort: 55679 # Default endpoint for ZPages.
        - containerPort: 4317 # Default endpoint for OpenTelemetry receiver.
        - containerPort: 14250 # Default endpoint for Jaeger gRPC receiver.
        - containerPort: 14268 # Default endpoint for Jaeger HTTP receiver.
        - containerPort: 9411 # Default endpoint for Zipkin receiver.
        - containerPort: 8888  # Default endpoint for querying metrics.
        env:
          - name: MY_POD_IP
            valueFrom:
              fieldRef:
                apiVersion: v1
                fieldPath: status.podIP
          - name: GOMEMLIMIT
            value: 1600MiB
        volumeMounts:
        - name: otel-collector-config-vol
          mountPath: /conf
#        - name: otel-collector-secrets
#          mountPath: /secrets
      volumes:
        - configMap:
            name: otel-collector-conf
            items:
              - key: otel-collector-config
                path: otel-collector-config.yaml
          name: otel-collector-config-vol
#        - secret:
#            name: otel-collector-secrets
#            items:
#              - key: cert.pem
#                path: cert.pem
#              - key: key.pem
#                path: key.pem

部署deepflow监控单个k8s集群

官方文档
 官方demo

安装helm

snap install helm --classic

设置pv

kubectl apply -f https://openebs.github.io/charts/openebs-operator.yaml
## config default storage class
kubectl patch storageclass openebs-hostpath  -p '{"metadata": {"annotations":{"storageclass.kubernetes.io/is-default-class":"true"}}}'

部署deepflow

helm repo add deepflow https://deepflowio.github.io/deepflow
helm repo update deepflow # use `helm repo update` when helm < 3.7.0
helm install deepflow -n deepflow deepflow/deepflow --create-namespace
# 显示如下
NAME: deepflow
LAST DEPLOYED: Tue May 14 14:13:50 2024
NAMESPACE: deepflow
STATUS: deployed
REVISION: 1
NOTES:
██████╗ ███████╗███████╗██████╗ ███████╗██╗      ██████╗ ██╗    ██╗
██╔══██╗██╔════╝██╔════╝██╔══██╗██╔════╝██║     ██╔═══██╗██║    ██║
██║  ██║█████╗  █████╗  ██████╔╝█████╗  ██║     ██║   ██║██║ █╗ ██║
██║  ██║██╔══╝  ██╔══╝  ██╔═══╝ ██╔══╝  ██║     ██║   ██║██║███╗██║
██████╔╝███████╗███████╗██║     ██║     ███████╗╚██████╔╝╚███╔███╔╝
╚═════╝ ╚══════╝╚══════╝╚═╝     ╚═╝     ╚══════╝ ╚═════╝  ╚══╝╚══╝ 

An automated observability platform for cloud-native developers.

# deepflow-agent Port for receiving trace, metrics, and log

deepflow-agent service: deepflow-agent.deepflow
deepflow-agent Host listening port: 38086

# Get the Grafana URL to visit by running these commands in the same shell

NODE_PORT=$(kubectl get --namespace deepflow -o jsonpath="{.spec.ports[0].nodePort}" services deepflow-grafana)
NODE_IP=$(kubectl get nodes -o jsonpath="{.items[0].status.addresses[0].address}")
echo -e "Grafana URL: http://$NODE_IP:$NODE_PORT  \nGrafana auth: admin:deepflow"

节点安装deepflow-ctl

curl -o /usr/bin/deepflow-ctl https://deepflow-ce.oss-cn-beijing.aliyuncs.com/bin/ctl/stable/linux/$(arch | sed 's|x86_64|amd64|' | sed 's|aarch64|arm64|')/deepflow-ctl
chmod a+x /usr/bin/deepflow-ctl

访问grafana页面

NODE_PORT=$(kubectl get --namespace deepflow -o jsonpath="{.spec.ports[0].nodePort}" services deepflow-grafana)
NODE_IP=$(kubectl get nodes -o jsonpath="{.items[0].status.addresses[0].address}")
echo -e "Grafana URL: http://$NODE_IP:$NODE_PORT  \nGrafana auth: admin:deepflow"

Ubuntu-22-LTS部署k8s和deepflow

当您在 Ubuntu 22.04 上安装 Kubernetes 集群时，您可以遵循以下步骤：

设置主机名并在 hosts 文件中添加条目：

登录到主节点并使用 hostnamectl 命令设置主机名：
```
hostnamectl set-hostname "k8smaster.example.net"
```

在工作节点上，运行以下命令设置主机名（分别对应第一个和第二个工作节点）：

hostnamectl set-hostname "k8sworker1.example.net"  # 第一个工作节点
hostnamectl set-hostname "k8sworker2.example.net"  # 第二个工作节点

在每个节点的 /etc/hosts 文件中添加以下条目：

10.1.1.70 k8smaster.example.net k8smaster
10.1.1.71 k8sworker1.example.net k8sworker1

禁用 swap 并添加内核设置：

在所有节点上执行以下命令以禁用交换功能：

swapoff -a
sed -i '/swap/ s/^\(.*\)$/#\1/g' /etc/fstab

加载以下内核模块：

tee /etc/modules-load.d/containerd.conf <<EOF
overlay
br_netfilter
EOF
modprobe overlay
modprobe br_netfilter

为 Kubernetes 设置以下内核参数：

tee /etc/sysctl.d/kubernetes.conf <<EOF
net.bridge.bridge-nf-call-ip6tables = 1
net.bridge.bridge-nf-call-iptables = 1
net.ipv4.ip_forward = 1
EOF
sysctl --system

安装 containerd 运行时：

首先安装 containerd 的依赖项：

apt install -y curl gnupg2 software-properties-common apt-transport-https ca-certificates

启用 Docker 存储库：

curl -fsSL https://download.docker.com/linux/ubuntu/gpg | apt-key add -
add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"

安装 containerd：

apt update
apt install -y containerd.io

配置 containerd 使用 systemd 作为 cgroup：

containerd config default | tee /etc/containerd/config.toml > /dev/null 2>&1
sed -i 's/SystemdCgroup\\=false/SystemdCgroup\\=true/g' /etc/containerd/config.toml

部分配置手动修改

disabled_plugins = []
imports = []
oom_score = 0
plugin_dir = ""
required_plugins = []
root = "/var/lib/containerd"
state = "/run/containerd"
temp = ""
version = 2

[cgroup]
path = ""

[debug]
address = ""
format = ""
gid = 0
level = ""
uid = 0

[grpc]
address = "/run/containerd/containerd.sock"
gid = 0
max_recv_message_size = 16777216
max_send_message_size = 16777216
tcp_address = ""
tcp_tls_ca = ""
tcp_tls_cert = ""
tcp_tls_key = ""
uid = 0

[metrics]
address = ""
grpc_histogram = false

[plugins]

[plugins."io.containerd.gc.v1.scheduler"]
    deletion_threshold = 0
    mutation_threshold = 100
    pause_threshold = 0.02
    schedule_delay = "0s"
    startup_delay = "100ms"

[plugins."io.containerd.grpc.v1.cri"]
    device_ownership_from_security_context = false
    disable_apparmor = false
    disable_cgroup = false
    disable_hugetlb_controller = true
    disable_proc_mount = false
    disable_tcp_service = true
    drain_exec_sync_io_timeout = "0s"
    enable_selinux = false
    enable_tls_streaming = false
    enable_unprivileged_icmp = false
    enable_unprivileged_ports = false
    ignore_deprecation_warnings = []
    ignore_image_defined_volumes = false
    max_concurrent_downloads = 3
    max_container_log_line_size = 16384
    netns_mounts_under_state_dir = false
    restrict_oom_score_adj = false
    # 修改以下这行
    sandbox_image = "registry.aliyuncs.com/google_containers/pause:3.8"
    selinux_category_range = 1024
    stats_collect_period = 10
    stream_idle_timeout = "4h0m0s"
    stream_server_address = "127.0.0.1"
    stream_server_port = "0"
    systemd_cgroup = false
    tolerate_missing_hugetlb_controller = true
    unset_seccomp_profile = ""

    [plugins."io.containerd.grpc.v1.cri".cni]
    bin_dir = "/opt/cni/bin"
    conf_dir = "/etc/cni/net.d"
    conf_template = ""
    ip_pref = ""
    max_conf_num = 1

    [plugins."io.containerd.grpc.v1.cri".containerd]
    default_runtime_name = "runc"
    disable_snapshot_annotations = true
    discard_unpacked_layers = false
    ignore_rdt_not_enabled_errors = false
    no_pivot = false
    snapshotter = "overlayfs"

    [plugins."io.containerd.grpc.v1.cri".containerd.default_runtime]
        base_runtime_spec = ""
        cni_conf_dir = ""
        cni_max_conf_num = 0
        container_annotations = []
        pod_annotations = []
        privileged_without_host_devices = false
        runtime_engine = ""
        runtime_path = ""
        runtime_root = ""
        runtime_type = ""

        [plugins."io.containerd.grpc.v1.cri".containerd.default_runtime.options]

    [plugins."io.containerd.grpc.v1.cri".containerd.runtimes]

        [plugins."io.containerd.grpc.v1.cri".containerd.runtimes.runc]
        base_runtime_spec = ""
        cni_conf_dir = ""
        cni_max_conf_num = 0
        container_annotations = []
        pod_annotations = []
        privileged_without_host_devices = false
        runtime_engine = ""
        runtime_path = ""
        runtime_root = ""
        runtime_type = "io.containerd.runc.v2"

        [plugins."io.containerd.grpc.v1.cri".containerd.runtimes.runc.options]
            BinaryName = ""
            CriuImagePath = ""
            CriuPath = ""
            CriuWorkPath = ""
            IoGid = 0
            IoUid = 0
            NoNewKeyring = false
            NoPivotRoot = false
            Root = ""
            ShimCgroup = ""
            SystemdCgroup = true

    [plugins."io.containerd.grpc.v1.cri".containerd.untrusted_workload_runtime]
        base_runtime_spec = ""
        cni_conf_dir = ""
        cni_max_conf_num = 0
        container_annotations = []
        pod_annotations = []
        privileged_without_host_devices = false
        runtime_engine = ""
        runtime_path = ""
        runtime_root = ""
        runtime_type = ""

        [plugins."io.containerd.grpc.v1.cri".containerd.untrusted_workload_runtime.options]

    [plugins."io.containerd.grpc.v1.cri".image_decryption]
    key_model = "node"

    [plugins."io.containerd.grpc.v1.cri".registry]
    config_path = ""

    [plugins."io.containerd.grpc.v1.cri".registry.auths]

    [plugins."io.containerd.grpc.v1.cri".registry.configs]

    [plugins."io.containerd.grpc.v1.cri".registry.headers]

    [plugins."io.containerd.grpc.v1.cri".registry.mirrors]
        # 添加如下4行
        [plugins."io.containerd.grpc.v1.cri".registry.mirrors."docker.io"]
        endpoint = ["https://docker.mirrors.ustc.edu.cn"]
        [plugins."io.containerd.grpc.v1.cri".registry.mirrors."k8s.gcr.io"]
        endpoint = ["https://registry.aliyuncs.com/google_containers"]

    [plugins."io.containerd.grpc.v1.cri".x509_key_pair_streaming]
    tls_cert_file = ""
    tls_key_file = ""

[plugins."io.containerd.internal.v1.opt"]
    path = "/opt/containerd"

[plugins."io.containerd.internal.v1.restart"]
    interval = "10s"

[plugins."io.containerd.internal.v1.tracing"]
    sampling_ratio = 1.0
    service_name = "containerd"

[plugins."io.containerd.metadata.v1.bolt"]
    content_sharing_policy = "shared"

[plugins."io.containerd.monitor.v1.cgroups"]
    no_prometheus = false

[plugins."io.containerd.runtime.v1.linux"]
    no_shim = false
    runtime = "runc"
    runtime_root = ""
    shim = "containerd-shim"
    shim_debug = false

[plugins."io.containerd.runtime.v2.task"]
    platforms = ["linux/amd64"]
    sched_core = false

[plugins."io.containerd.service.v1.diff-service"]
    default = ["walking"]

[plugins."io.containerd.service.v1.tasks-service"]
    rdt_config_file = ""

[plugins."io.containerd.snapshotter.v1.aufs"]
    root_path = ""

[plugins."io.containerd.snapshotter.v1.btrfs"]
    root_path = ""

[plugins."io.containerd.snapshotter.v1.devmapper"]
    async_remove = false
    base_image_size = ""
    discard_blocks = false
    fs_options = ""
    fs_type = ""
    pool_name = ""
    root_path = ""

[plugins."io.containerd.snapshotter.v1.native"]
    root_path = ""

[plugins."io.containerd.snapshotter.v1.overlayfs"]
    mount_options = []
    root_path = ""
    sync_remove = false
    upperdir_label = false

[plugins."io.containerd.snapshotter.v1.zfs"]
    root_path = ""

[plugins."io.containerd.tracing.processor.v1.otlp"]
    endpoint = ""
    insecure = false
    protocol = ""

[proxy_plugins]

[stream_processors]

[stream_processors."io.containerd.ocicrypt.decoder.v1.tar"]
    accepts = ["application/vnd.oci.image.layer.v1.tar+encrypted"]
    args = ["--decryption-keys-path", "/etc/containerd/ocicrypt/keys"]
    env = ["OCICRYPT_KEYPROVIDER_CONFIG=/etc/containerd/ocicrypt/ocicrypt_keyprovider.conf"]
    path = "ctd-decoder"
    returns = "application/vnd.oci.image.layer.v1.tar"

[stream_processors."io.containerd.ocicrypt.decoder.v1.tar.gzip"]
    accepts = ["application/vnd.oci.image.layer.v1.tar+gzip+encrypted"]
    args = ["--decryption-keys-path", "/etc/containerd/ocicrypt/keys"]
    env = ["OCICRYPT_KEYPROVIDER_CONFIG=/etc/containerd/ocicrypt/ocicrypt_keyprovider.conf"]
    path = "ctd-decoder"
    returns = "application/vnd.oci.image.layer.v1.tar+gzip"

[timeouts]
"io.containerd.timeout.bolt.open" = "0s"
"io.containerd.timeout.shim.cleanup" = "5s"
"io.containerd.timeout.shim.load" = "5s"
"io.containerd.timeout.shim.shutdown" = "3s"
"io.containerd.timeout.task.state" = "2s"

[ttrpc]
address = ""
gid = 0
uid = 0

重启并启用容器服务：

systemctl restart containerd
systemctl enable containerd

设置crictl

cat > /etc/crictl.yaml <<EOF
runtime-endpoint: unix:///var/run/containerd/containerd.sock
image-endpoint: unix:///var/run/containerd/containerd.sock
timeout: 10
debug: false
pull-image-on-create: false
EOF

添加阿里云的 Kubernetes 源：

首先，导入阿里云的 GPG 密钥：

curl -fsSL https://mirrors.aliyun.com/kubernetes/apt/doc/apt-key.gpg | apt-key add -

然后，添加阿里云的 Kubernetes 源：

tee /etc/apt/sources.list.d/kubernetes.list <<EOF
deb https://mirrors.aliyun.com/kubernetes/apt/ kubernetes-xenial main
EOF

安装 Kubernetes 组件：

更新软件包索引并安装 kubelet、kubeadm 和 kubectl：

apt-get update
apt-get install -y kubelet kubeadm kubectl

设置 kubelet 使用 systemd 作为 cgroup 驱动：

# 可忽略
# sed -i 's/cgroup-driver=systemd/cgroup-driver=cgroupfs/g' /var/lib/kubelet/kubeadm-flags.env
# systemctl daemon-reload
# systemctl restart kubelet

初始化 Kubernetes 集群：

使用 kubeadm 初始化集群，并指定阿里云的镜像仓库：

# kubeadm init --image-repository registry.aliyuncs.com/google_containers
I0513 14:16:59.740096   17563 version.go:256] remote version is much newer: v1.30.0; falling back to: stable-1.28
[init] Using Kubernetes version: v1.28.9
[preflight] Running pre-flight checks
[preflight] Pulling images required for setting up a Kubernetes cluster
[preflight] This might take a minute or two, depending on the speed of your internet connection
[preflight] You can also perform this action in beforehand using 'kubeadm config images pull'
W0513 14:17:01.440936   17563 checks.go:835] detected that the sandbox image "registry.aliyuncs.com/google_containers/pause:3.8" of the container runtime         is inconsistent with that used by kubeadm. It is recommended that using "registry.aliyuncs.com/google_containers/pause:3.9" as the CRI sandbox image.
[certs] Using certificateDir folder "/etc/kubernetes/pki"
[certs] Generating "ca" certificate and key
[certs] Generating "apiserver" certificate and key
[certs] apiserver serving cert is signed for DNS names [k8smaster.example.net kubernetes kubernetes.default kubernetes.default.svc kubernetes.default.svc.        cluster.local] and IPs [10.96.0.1 10.1.1.70]
[certs] Generating "apiserver-kubelet-client" certificate and key
[certs] Generating "front-proxy-ca" certificate and key
[certs] Generating "front-proxy-client" certificate and key
[certs] Generating "etcd/ca" certificate and key
[certs] Generating "etcd/server" certificate and key
[certs] etcd/server serving cert is signed for DNS names [k8smaster.example.net localhost] and IPs [10.1.1.70 127.0.0.1 ::1]
[certs] Generating "etcd/peer" certificate and key
[certs] etcd/peer serving cert is signed for DNS names [k8smaster.example.net localhost] and IPs [10.1.1.70 127.0.0.1 ::1]
[certs] Generating "etcd/healthcheck-client" certificate and key
[certs] Generating "apiserver-etcd-client" certificate and key
[certs] Generating "sa" key and public key
[kubeconfig] Using kubeconfig folder "/etc/kubernetes"
[kubeconfig] Writing "admin.conf" kubeconfig file
[kubeconfig] Writing "kubelet.conf" kubeconfig file
[kubeconfig] Writing "controller-manager.conf" kubeconfig file
[kubeconfig] Writing "scheduler.conf" kubeconfig file
[etcd] Creating static Pod manifest for local etcd in "/etc/kubernetes/manifests"
[control-plane] Using manifest folder "/etc/kubernetes/manifests"
[control-plane] Creating static Pod manifest for "kube-apiserver"
[control-plane] Creating static Pod manifest for "kube-controller-manager"
[control-plane] Creating static Pod manifest for "kube-scheduler"
[kubelet-start] Writing kubelet environment file with flags to file "/var/lib/kubelet/kubeadm-flags.env"
[kubelet-start] Writing kubelet configuration to file "/var/lib/kubelet/config.yaml"
[kubelet-start] Starting the kubelet
[wait-control-plane] Waiting for the kubelet to boot up the control plane as static Pods from directory "/etc/kubernetes/manifests". This can take up to         4m0s
[apiclient] All control plane components are healthy after 4.002079 seconds
[upload-config] Storing the configuration used in ConfigMap "kubeadm-config" in the "kube-system" Namespace
[kubelet] Creating a ConfigMap "kubelet-config" in namespace kube-system with the configuration for the kubelets in the cluster
[upload-certs] Skipping phase. Please see --upload-certs
[mark-control-plane] Marking the node k8smaster.example.net as control-plane by adding the labels: [node-role.kubernetes.io/control-plane node.kubernetes.        io/exclude-from-external-load-balancers]
[mark-control-plane] Marking the node k8smaster.example.net as control-plane by adding the taints [node-role.kubernetes.io/control-plane:NoSchedule]
[bootstrap-token] Using token: m9z4yq.dok89ro6yt23wykr
[bootstrap-token] Configuring bootstrap tokens, cluster-info ConfigMap, RBAC Roles
[bootstrap-token] Configured RBAC rules to allow Node Bootstrap tokens to get nodes
[bootstrap-token] Configured RBAC rules to allow Node Bootstrap tokens to post CSRs in order for nodes to get long term certificate credentials
[bootstrap-token] Configured RBAC rules to allow the csrapprover controller automatically approve CSRs from a Node Bootstrap Token
[bootstrap-token] Configured RBAC rules to allow certificate rotation for all node client certificates in the cluster
[bootstrap-token] Creating the "cluster-info" ConfigMap in the "kube-public" namespace
[kubelet-finalize] Updating "/etc/kubernetes/kubelet.conf" to point to a rotatable kubelet client certificate and key
[addons] Applied essential addon: CoreDNS
[addons] Applied essential addon: kube-proxy

Your Kubernetes control-plane has initialized successfully!

To start using your cluster, you need to run the following as a regular user:

  mkdir -p $HOME/.kube
  sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
  sudo chown $(id -u):$(id -g) $HOME/.kube/config

Alternatively, if you are the root user, you can run:

  export KUBECONFIG=/etc/kubernetes/admin.conf

You should now deploy a pod network to the cluster.
Run "kubectl apply -f [podnetwork].yaml" with one of the options listed at:
  https://kubernetes.io/docs/concepts/cluster-administration/addons/

Then you can join any number of worker nodes by running the following on each as root:

kubeadm join 10.1.1.70:6443 --token m9z4yq.dok89ro6yt23wykr \
        --discovery-token-ca-cert-hash sha256:17c3f29bd276592e668e9e6a7a187140a887254b4555cf7d293c3313d7c8a178

配置 kubectl：

为当前用户设置 kubectl 访问：

mkdir -p $HOME/.kube
cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
chown $(id -u):$(id -g) $HOME/.kube/config

安装网络插件：

安装一个 Pod 网络插件，例如 Calico 或 Flannel。例如，使用 Calico：

kubectl apply -f https://docs.projectcalico.org/manifests/calico.yaml
# 网络插件初始化完毕之后，coredns容器就正常了
kubectl logs -n kube-system -l k8s-app=kube-dns

验证集群：

启动一个nginx pod：

# vim nginx_pod.yml
apiVersion: v1
kind: Pod
metadata:
  name: test-nginx-pod
  namespace: test
  labels:
    app: nginx
spec:
  containers:
  - name: test-nginx-container
    image: nginx:latest
    ports:
    - containerPort: 80
  tolerations:
    - key: "node-role.kubernetes.io/control-plane"
      operator: "Exists"
      effect: "NoSchedule"
---

apiVersion: v1
kind: Service
# service和pod必须位于同一个namespace
metadata:
  name: nginx-service
  namespace: test
spec:
  type: NodePort
  # selector应该匹配pod的labels
  selector:
    app: nginx
  ports:
  - protocol: TCP
    port: 80
    nodePort: 30007
    targetPort: 80

启动

kubectl apply -f nginx_pod.yml

部署opentelemetry-collector测试

自定义测试yaml文件

apiVersion: v1
kind: ConfigMap
metadata:
  name: otel-collector-conf
  namespace: default
data:
  # 你的配置数据
  config.yaml: |
    receivers:
      otlp:
        protocols:
          grpc:
          http:
    processors:
      batch:
    exporters:
      logging:
        loglevel: debug
    service:
      pipelines:
        traces:
          receivers: [otlp]
          processors: [batch]
          exporters: [logging]

---
apiVersion: v1
kind: Service
metadata:
  name: otel-collector
  labels:
    app: opentelemetry
spec:
  type: NodePort
  ports:
    - port: 4317
      targetPort: 4317
      nodePort: 30080
      name: otlp-grpc
    - port: 8888
      targetPort: 8888
      name: metrics
  selector:
    component: otel-collector

---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: otel-collector
  labels:
    app: opentelemetry
spec:
  replicas: 1
  selector:
    matchLabels:
      component: otel-collector
  template:
    metadata:
      labels:
        component: otel-collector
    spec:
      tolerations:
      - key: node-role.kubernetes.io/control-plane
        operator: Exists
        effect: NoSchedule
      containers:
      - name: otel-collector
        image: otel/opentelemetry-collector:latest
        ports:
        - containerPort: 4317
        - containerPort: 8888
        env:
        - name: MY_POD_IP
          valueFrom:
            fieldRef:
              fieldPath: status.podIP
        volumeMounts:
        - name: otel-collector-config-vol
          mountPath: /conf
      volumes:
      - configMap:
          name: otel-collector-conf
        name: otel-collector-config-vol

启动

mkdir /conf
kubectl apply -f otel-collector.yaml
kubectl get -f otel-collector.yaml

删除

kubectl delete -f otel-collector.yaml

使用官方提供示例

kubectl apply -f https://raw.githubusercontent.com/open-telemetry/opentelemetry-collector/main/examples/k8s/otel-config.yaml

根据需要修改文件

otel-config.yaml

---
apiVersion: v1
kind: ConfigMap
metadata:
  name: otel-agent-conf
  labels:
    app: opentelemetry
    component: otel-agent-conf
data:
  otel-agent-config: |
    receivers:
      otlp:
        protocols:
          grpc:
            endpoint: ${env:MY_POD_IP}:4317
          http:
            endpoint: ${env:MY_POD_IP}:4318
    exporters:
      otlp:
        endpoint: "otel-collector.default:4317"
        tls:
          insecure: true
        sending_queue:
          num_consumers: 4
          queue_size: 100
        retry_on_failure:
          enabled: true
    processors:
      batch:
      memory_limiter:
        # 80% of maximum memory up to 2G
        limit_mib: 400
        # 25% of limit up to 2G
        spike_limit_mib: 100
        check_interval: 5s
    extensions:
      zpages: {}
    service:
      extensions: [zpages]
      pipelines:
        traces:
          receivers: [otlp]
          processors: [memory_limiter, batch]
          exporters: [otlp]
---
apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: otel-agent
  labels:
    app: opentelemetry
    component: otel-agent
spec:
  selector:
    matchLabels:
      app: opentelemetry
      component: otel-agent
  template:
    metadata:
      labels:
        app: opentelemetry
        component: otel-agent
    spec:
      tolerations:
      - key: node-role.kubernetes.io/control-plane
        operator: Exists
        effect: NoSchedule
      containers:
      - command:
          - "/otelcol"
          - "--config=/conf/otel-agent-config.yaml"
        image: otel/opentelemetry-collector:0.94.0
        name: otel-agent
        resources:
          limits:
            cpu: 500m
            memory: 500Mi
          requests:
            cpu: 100m
            memory: 100Mi
        ports:
        - containerPort: 55679 # ZPages endpoint.
        - containerPort: 4317 # Default OpenTelemetry receiver port.
        - containerPort: 8888  # Metrics.
        env:
          - name: MY_POD_IP
            valueFrom:
              fieldRef:
                apiVersion: v1
                fieldPath: status.podIP
          - name: GOMEMLIMIT
            value: 400MiB
        volumeMounts:
        - name: otel-agent-config-vol
          mountPath: /conf
      volumes:
        - configMap:
            name: otel-agent-conf
            items:
              - key: otel-agent-config
                path: otel-agent-config.yaml
          name: otel-agent-config-vol
---
apiVersion: v1
kind: ConfigMap
metadata:
  name: otel-collector-conf
  labels:
    app: opentelemetry
    component: otel-collector-conf
data:
  otel-collector-config: |
    receivers:
      otlp:
        protocols:
          grpc:
            endpoint: ${env:MY_POD_IP}:4317
          http:
            endpoint: ${env:MY_POD_IP}:4318
    processors:
      batch:
      memory_limiter:
        # 80% of maximum memory up to 2G
        limit_mib: 1500
        # 25% of limit up to 2G
        spike_limit_mib: 512
        check_interval: 5s
    extensions:
      zpages: {}
    exporters:
      otlp:
        endpoint: "http://someotlp.target.com:4317" # Replace with a real endpoint.
        tls:
          insecure: true
      zipkin:
        endpoint: "http://10.1.1.10:9411/api/v2/spans"
        format: "proto"
    service:
      extensions: [zpages]
      pipelines:
        traces/1:
          receivers: [otlp]
          processors: [memory_limiter, batch]
          exporters: [zipkin]
---
apiVersion: v1
kind: Service
metadata:
  name: otel-collector
  labels:
    app: opentelemetry
    component: otel-collector
spec:
  ports:
  - name: otlp-grpc # Default endpoint for OpenTelemetry gRPC receiver.
    port: 4317
    protocol: TCP
    targetPort: 4317
  - name: otlp-http # Default endpoint for OpenTelemetry HTTP receiver.
    port: 4318
    protocol: TCP
    targetPort: 4318
  - name: metrics # Default endpoint for querying metrics.
    port: 8888
  selector:
    component: otel-collector
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: otel-collector
  labels:
    app: opentelemetry
    component: otel-collector
spec:
  selector:
    matchLabels:
      app: opentelemetry
      component: otel-collector
  minReadySeconds: 5
  progressDeadlineSeconds: 120
  replicas: 1 #TODO - adjust this to your own requirements
  template:
    metadata:
      labels:
        app: opentelemetry
        component: otel-collector
    spec:
      tolerations:
      - key: node-role.kubernetes.io/control-plane
        operator: Exists
        effect: NoSchedule
      containers:
      - command:
          - "/otelcol"
          - "--config=/conf/otel-collector-config.yaml"
        image: otel/opentelemetry-collector:0.94.0
        name: otel-collector
        resources:
          limits:
            cpu: 1
            memory: 2Gi
          requests:
            cpu: 200m
            memory: 400Mi
        ports:
        - containerPort: 55679 # Default endpoint for ZPages.
        - containerPort: 4317 # Default endpoint for OpenTelemetry receiver.
        - containerPort: 14250 # Default endpoint for Jaeger gRPC receiver.
        - containerPort: 14268 # Default endpoint for Jaeger HTTP receiver.
        - containerPort: 9411 # Default endpoint for Zipkin receiver.
        - containerPort: 8888  # Default endpoint for querying metrics.
        env:
          - name: MY_POD_IP
            valueFrom:
              fieldRef:
                apiVersion: v1
                fieldPath: status.podIP
          - name: GOMEMLIMIT
            value: 1600MiB
        volumeMounts:
        - name: otel-collector-config-vol
          mountPath: /conf
#        - name: otel-collector-secrets
#          mountPath: /secrets
      volumes:
        - configMap:
            name: otel-collector-conf
            items:
              - key: otel-collector-config
                path: otel-collector-config.yaml
          name: otel-collector-config-vol
#        - secret:
#            name: otel-collector-secrets
#            items:
#              - key: cert.pem
#                path: cert.pem
#              - key: key.pem
#                path: key.pem

部署deepflow监控单个k8s集群

官方文档
 官方demo

安装helm

snap install helm --classic

设置pv

kubectl apply -f https://openebs.github.io/charts/openebs-operator.yaml
## config default storage class
kubectl patch storageclass openebs-hostpath  -p '{"metadata": {"annotations":{"storageclass.kubernetes.io/is-default-class":"true"}}}'

部署deepflow

helm repo add deepflow https://deepflowio.github.io/deepflow
helm repo update deepflow # use `helm repo update` when helm < 3.7.0
helm install deepflow -n deepflow deepflow/deepflow --create-namespace
# 显示如下
NAME: deepflow
LAST DEPLOYED: Tue May 14 14:13:50 2024
NAMESPACE: deepflow
STATUS: deployed
REVISION: 1
NOTES:
██████╗ ███████╗███████╗██████╗ ███████╗██╗      ██████╗ ██╗    ██╗
██╔══██╗██╔════╝██╔════╝██╔══██╗██╔════╝██║     ██╔═══██╗██║    ██║
██║  ██║█████╗  █████╗  ██████╔╝█████╗  ██║     ██║   ██║██║ █╗ ██║
██║  ██║██╔══╝  ██╔══╝  ██╔═══╝ ██╔══╝  ██║     ██║   ██║██║███╗██║
██████╔╝███████╗███████╗██║     ██║     ███████╗╚██████╔╝╚███╔███╔╝
╚═════╝ ╚══════╝╚══════╝╚═╝     ╚═╝     ╚══════╝ ╚═════╝  ╚══╝╚══╝ 

An automated observability platform for cloud-native developers.

# deepflow-agent Port for receiving trace, metrics, and log

deepflow-agent service: deepflow-agent.deepflow
deepflow-agent Host listening port: 38086

# Get the Grafana URL to visit by running these commands in the same shell

NODE_PORT=$(kubectl get --namespace deepflow -o jsonpath="{.spec.ports[0].nodePort}" services deepflow-grafana)
NODE_IP=$(kubectl get nodes -o jsonpath="{.items[0].status.addresses[0].address}")
echo -e "Grafana URL: http://$NODE_IP:$NODE_PORT  \nGrafana auth: admin:deepflow"

节点安装deepflow-ctl

curl -o /usr/bin/deepflow-ctl https://deepflow-ce.oss-cn-beijing.aliyuncs.com/bin/ctl/stable/linux/$(arch | sed 's|x86_64|amd64|' | sed 's|aarch64|arm64|')/deepflow-ctl
chmod a+x /usr/bin/deepflow-ctl

访问grafana页面

NODE_PORT=$(kubectl get --namespace deepflow -o jsonpath="{.spec.ports[0].nodePort}" services deepflow-grafana)
NODE_IP=$(kubectl get nodes -o jsonpath="{.items[0].status.addresses[0].address}")
echo -e "Grafana URL: http://$NODE_IP:$NODE_PORT  \nGrafana auth: admin:deepflow"

Ubuntu-22-LTS部署k8s和deepflow

当您在 Ubuntu 22.04 上安装 Kubernetes 集群时，您可以遵循以下步骤：

设置主机名并在 hosts 文件中添加条目：

登录到主节点并使用 hostnamectl 命令设置主机名：
```
hostnamectl set-hostname "k8smaster.example.net"
```

在工作节点上，运行以下命令设置主机名（分别对应第一个和第二个工作节点）：

hostnamectl set-hostname "k8sworker1.example.net"  # 第一个工作节点
hostnamectl set-hostname "k8sworker2.example.net"  # 第二个工作节点

在每个节点的 /etc/hosts 文件中添加以下条目：

10.1.1.70 k8smaster.example.net k8smaster
10.1.1.71 k8sworker1.example.net k8sworker1

禁用 swap 并添加内核设置：

在所有节点上执行以下命令以禁用交换功能：

swapoff -a
sed -i '/swap/ s/^\(.*\)$/#\1/g' /etc/fstab

加载以下内核模块：

tee /etc/modules-load.d/containerd.conf <<EOF
overlay
br_netfilter
EOF
modprobe overlay
modprobe br_netfilter

为 Kubernetes 设置以下内核参数：

tee /etc/sysctl.d/kubernetes.conf <<EOF
net.bridge.bridge-nf-call-ip6tables = 1
net.bridge.bridge-nf-call-iptables = 1
net.ipv4.ip_forward = 1
EOF
sysctl --system

安装 containerd 运行时：

首先安装 containerd 的依赖项：

apt install -y curl gnupg2 software-properties-common apt-transport-https ca-certificates

启用 Docker 存储库：

curl -fsSL https://download.docker.com/linux/ubuntu/gpg | apt-key add -
add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"

安装 containerd：

apt update
apt install -y containerd.io

配置 containerd 使用 systemd 作为 cgroup：

containerd config default | tee /etc/containerd/config.toml > /dev/null 2>&1
sed -i 's/SystemdCgroup\\=false/SystemdCgroup\\=true/g' /etc/containerd/config.toml

部分配置手动修改

disabled_plugins = []
imports = []
oom_score = 0
plugin_dir = ""
required_plugins = []
root = "/var/lib/containerd"
state = "/run/containerd"
temp = ""
version = 2

[cgroup]
path = ""

[debug]
address = ""
format = ""
gid = 0
level = ""
uid = 0

[grpc]
address = "/run/containerd/containerd.sock"
gid = 0
max_recv_message_size = 16777216
max_send_message_size = 16777216
tcp_address = ""
tcp_tls_ca = ""
tcp_tls_cert = ""
tcp_tls_key = ""
uid = 0

[metrics]
address = ""
grpc_histogram = false

[plugins]

[plugins."io.containerd.gc.v1.scheduler"]
    deletion_threshold = 0
    mutation_threshold = 100
    pause_threshold = 0.02
    schedule_delay = "0s"
    startup_delay = "100ms"

[plugins."io.containerd.grpc.v1.cri"]
    device_ownership_from_security_context = false
    disable_apparmor = false
    disable_cgroup = false
    disable_hugetlb_controller = true
    disable_proc_mount = false
    disable_tcp_service = true
    drain_exec_sync_io_timeout = "0s"
    enable_selinux = false
    enable_tls_streaming = false
    enable_unprivileged_icmp = false
    enable_unprivileged_ports = false
    ignore_deprecation_warnings = []
    ignore_image_defined_volumes = false
    max_concurrent_downloads = 3
    max_container_log_line_size = 16384
    netns_mounts_under_state_dir = false
    restrict_oom_score_adj = false
    # 修改以下这行
    sandbox_image = "registry.aliyuncs.com/google_containers/pause:3.8"
    selinux_category_range = 1024
    stats_collect_period = 10
    stream_idle_timeout = "4h0m0s"
    stream_server_address = "127.0.0.1"
    stream_server_port = "0"
    systemd_cgroup = false
    tolerate_missing_hugetlb_controller = true
    unset_seccomp_profile = ""

    [plugins."io.containerd.grpc.v1.cri".cni]
    bin_dir = "/opt/cni/bin"
    conf_dir = "/etc/cni/net.d"
    conf_template = ""
    ip_pref = ""
    max_conf_num = 1

    [plugins."io.containerd.grpc.v1.cri".containerd]
    default_runtime_name = "runc"
    disable_snapshot_annotations = true
    discard_unpacked_layers = false
    ignore_rdt_not_enabled_errors = false
    no_pivot = false
    snapshotter = "overlayfs"

    [plugins."io.containerd.grpc.v1.cri".containerd.default_runtime]
        base_runtime_spec = ""
        cni_conf_dir = ""
        cni_max_conf_num = 0
        container_annotations = []
        pod_annotations = []
        privileged_without_host_devices = false
        runtime_engine = ""
        runtime_path = ""
        runtime_root = ""
        runtime_type = ""

        [plugins."io.containerd.grpc.v1.cri".containerd.default_runtime.options]

    [plugins."io.containerd.grpc.v1.cri".containerd.runtimes]

        [plugins."io.containerd.grpc.v1.cri".containerd.runtimes.runc]
        base_runtime_spec = ""
        cni_conf_dir = ""
        cni_max_conf_num = 0
        container_annotations = []
        pod_annotations = []
        privileged_without_host_devices = false
        runtime_engine = ""
        runtime_path = ""
        runtime_root = ""
        runtime_type = "io.containerd.runc.v2"

        [plugins."io.containerd.grpc.v1.cri".containerd.runtimes.runc.options]
            BinaryName = ""
            CriuImagePath = ""
            CriuPath = ""
            CriuWorkPath = ""
            IoGid = 0
            IoUid = 0
            NoNewKeyring = false
            NoPivotRoot = false
            Root = ""
            ShimCgroup = ""
            SystemdCgroup = true

    [plugins."io.containerd.grpc.v1.cri".containerd.untrusted_workload_runtime]
        base_runtime_spec = ""
        cni_conf_dir = ""
        cni_max_conf_num = 0
        container_annotations = []
        pod_annotations = []
        privileged_without_host_devices = false
        runtime_engine = ""
        runtime_path = ""
        runtime_root = ""
        runtime_type = ""

        [plugins."io.containerd.grpc.v1.cri".containerd.untrusted_workload_runtime.options]

    [plugins."io.containerd.grpc.v1.cri".image_decryption]
    key_model = "node"

    [plugins."io.containerd.grpc.v1.cri".registry]
    config_path = ""

    [plugins."io.containerd.grpc.v1.cri".registry.auths]

    [plugins."io.containerd.grpc.v1.cri".registry.configs]

    [plugins."io.containerd.grpc.v1.cri".registry.headers]

    [plugins."io.containerd.grpc.v1.cri".registry.mirrors]
        # 添加如下4行
        [plugins."io.containerd.grpc.v1.cri".registry.mirrors."docker.io"]
        endpoint = ["https://docker.mirrors.ustc.edu.cn"]
        [plugins."io.containerd.grpc.v1.cri".registry.mirrors."k8s.gcr.io"]
        endpoint = ["https://registry.aliyuncs.com/google_containers"]

    [plugins."io.containerd.grpc.v1.cri".x509_key_pair_streaming]
    tls_cert_file = ""
    tls_key_file = ""

[plugins."io.containerd.internal.v1.opt"]
    path = "/opt/containerd"

[plugins."io.containerd.internal.v1.restart"]
    interval = "10s"

[plugins."io.containerd.internal.v1.tracing"]
    sampling_ratio = 1.0
    service_name = "containerd"

[plugins."io.containerd.metadata.v1.bolt"]
    content_sharing_policy = "shared"

[plugins."io.containerd.monitor.v1.cgroups"]
    no_prometheus = false

[plugins."io.containerd.runtime.v1.linux"]
    no_shim = false
    runtime = "runc"
    runtime_root = ""
    shim = "containerd-shim"
    shim_debug = false

[plugins."io.containerd.runtime.v2.task"]
    platforms = ["linux/amd64"]
    sched_core = false

[plugins."io.containerd.service.v1.diff-service"]
    default = ["walking"]

[plugins."io.containerd.service.v1.tasks-service"]
    rdt_config_file = ""

[plugins."io.containerd.snapshotter.v1.aufs"]
    root_path = ""

[plugins."io.containerd.snapshotter.v1.btrfs"]
    root_path = ""

[plugins."io.containerd.snapshotter.v1.devmapper"]
    async_remove = false
    base_image_size = ""
    discard_blocks = false
    fs_options = ""
    fs_type = ""
    pool_name = ""
    root_path = ""

[plugins."io.containerd.snapshotter.v1.native"]
    root_path = ""

[plugins."io.containerd.snapshotter.v1.overlayfs"]
    mount_options = []
    root_path = ""
    sync_remove = false
    upperdir_label = false

[plugins."io.containerd.snapshotter.v1.zfs"]
    root_path = ""

[plugins."io.containerd.tracing.processor.v1.otlp"]
    endpoint = ""
    insecure = false
    protocol = ""

[proxy_plugins]

[stream_processors]

[stream_processors."io.containerd.ocicrypt.decoder.v1.tar"]
    accepts = ["application/vnd.oci.image.layer.v1.tar+encrypted"]
    args = ["--decryption-keys-path", "/etc/containerd/ocicrypt/keys"]
    env = ["OCICRYPT_KEYPROVIDER_CONFIG=/etc/containerd/ocicrypt/ocicrypt_keyprovider.conf"]
    path = "ctd-decoder"
    returns = "application/vnd.oci.image.layer.v1.tar"

[stream_processors."io.containerd.ocicrypt.decoder.v1.tar.gzip"]
    accepts = ["application/vnd.oci.image.layer.v1.tar+gzip+encrypted"]
    args = ["--decryption-keys-path", "/etc/containerd/ocicrypt/keys"]
    env = ["OCICRYPT_KEYPROVIDER_CONFIG=/etc/containerd/ocicrypt/ocicrypt_keyprovider.conf"]
    path = "ctd-decoder"
    returns = "application/vnd.oci.image.layer.v1.tar+gzip"

[timeouts]
"io.containerd.timeout.bolt.open" = "0s"
"io.containerd.timeout.shim.cleanup" = "5s"
"io.containerd.timeout.shim.load" = "5s"
"io.containerd.timeout.shim.shutdown" = "3s"
"io.containerd.timeout.task.state" = "2s"

[ttrpc]
address = ""
gid = 0
uid = 0

重启并启用容器服务：

systemctl restart containerd
systemctl enable containerd

设置crictl

cat > /etc/crictl.yaml <<EOF
runtime-endpoint: unix:///var/run/containerd/containerd.sock
image-endpoint: unix:///var/run/containerd/containerd.sock
timeout: 10
debug: false
pull-image-on-create: false
EOF

添加阿里云的 Kubernetes 源：

首先，导入阿里云的 GPG 密钥：

curl -fsSL https://mirrors.aliyun.com/kubernetes/apt/doc/apt-key.gpg | apt-key add -

然后，添加阿里云的 Kubernetes 源：

tee /etc/apt/sources.list.d/kubernetes.list <<EOF
deb https://mirrors.aliyun.com/kubernetes/apt/ kubernetes-xenial main
EOF

安装 Kubernetes 组件：

更新软件包索引并安装 kubelet、kubeadm 和 kubectl：

apt-get update
apt-get install -y kubelet kubeadm kubectl

设置 kubelet 使用 systemd 作为 cgroup 驱动：

# 可忽略
# sed -i 's/cgroup-driver=systemd/cgroup-driver=cgroupfs/g' /var/lib/kubelet/kubeadm-flags.env
# systemctl daemon-reload
# systemctl restart kubelet

初始化 Kubernetes 集群：

使用 kubeadm 初始化集群，并指定阿里云的镜像仓库：

# kubeadm init --image-repository registry.aliyuncs.com/google_containers
I0513 14:16:59.740096   17563 version.go:256] remote version is much newer: v1.30.0; falling back to: stable-1.28
[init] Using Kubernetes version: v1.28.9
[preflight] Running pre-flight checks
[preflight] Pulling images required for setting up a Kubernetes cluster
[preflight] This might take a minute or two, depending on the speed of your internet connection
[preflight] You can also perform this action in beforehand using 'kubeadm config images pull'
W0513 14:17:01.440936   17563 checks.go:835] detected that the sandbox image "registry.aliyuncs.com/google_containers/pause:3.8" of the container runtime         is inconsistent with that used by kubeadm. It is recommended that using "registry.aliyuncs.com/google_containers/pause:3.9" as the CRI sandbox image.
[certs] Using certificateDir folder "/etc/kubernetes/pki"
[certs] Generating "ca" certificate and key
[certs] Generating "apiserver" certificate and key
[certs] apiserver serving cert is signed for DNS names [k8smaster.example.net kubernetes kubernetes.default kubernetes.default.svc kubernetes.default.svc.        cluster.local] and IPs [10.96.0.1 10.1.1.70]
[certs] Generating "apiserver-kubelet-client" certificate and key
[certs] Generating "front-proxy-ca" certificate and key
[certs] Generating "front-proxy-client" certificate and key
[certs] Generating "etcd/ca" certificate and key
[certs] Generating "etcd/server" certificate and key
[certs] etcd/server serving cert is signed for DNS names [k8smaster.example.net localhost] and IPs [10.1.1.70 127.0.0.1 ::1]
[certs] Generating "etcd/peer" certificate and key
[certs] etcd/peer serving cert is signed for DNS names [k8smaster.example.net localhost] and IPs [10.1.1.70 127.0.0.1 ::1]
[certs] Generating "etcd/healthcheck-client" certificate and key
[certs] Generating "apiserver-etcd-client" certificate and key
[certs] Generating "sa" key and public key
[kubeconfig] Using kubeconfig folder "/etc/kubernetes"
[kubeconfig] Writing "admin.conf" kubeconfig file
[kubeconfig] Writing "kubelet.conf" kubeconfig file
[kubeconfig] Writing "controller-manager.conf" kubeconfig file
[kubeconfig] Writing "scheduler.conf" kubeconfig file
[etcd] Creating static Pod manifest for local etcd in "/etc/kubernetes/manifests"
[control-plane] Using manifest folder "/etc/kubernetes/manifests"
[control-plane] Creating static Pod manifest for "kube-apiserver"
[control-plane] Creating static Pod manifest for "kube-controller-manager"
[control-plane] Creating static Pod manifest for "kube-scheduler"
[kubelet-start] Writing kubelet environment file with flags to file "/var/lib/kubelet/kubeadm-flags.env"
[kubelet-start] Writing kubelet configuration to file "/var/lib/kubelet/config.yaml"
[kubelet-start] Starting the kubelet
[wait-control-plane] Waiting for the kubelet to boot up the control plane as static Pods from directory "/etc/kubernetes/manifests". This can take up to         4m0s
[apiclient] All control plane components are healthy after 4.002079 seconds
[upload-config] Storing the configuration used in ConfigMap "kubeadm-config" in the "kube-system" Namespace
[kubelet] Creating a ConfigMap "kubelet-config" in namespace kube-system with the configuration for the kubelets in the cluster
[upload-certs] Skipping phase. Please see --upload-certs
[mark-control-plane] Marking the node k8smaster.example.net as control-plane by adding the labels: [node-role.kubernetes.io/control-plane node.kubernetes.        io/exclude-from-external-load-balancers]
[mark-control-plane] Marking the node k8smaster.example.net as control-plane by adding the taints [node-role.kubernetes.io/control-plane:NoSchedule]
[bootstrap-token] Using token: m9z4yq.dok89ro6yt23wykr
[bootstrap-token] Configuring bootstrap tokens, cluster-info ConfigMap, RBAC Roles
[bootstrap-token] Configured RBAC rules to allow Node Bootstrap tokens to get nodes
[bootstrap-token] Configured RBAC rules to allow Node Bootstrap tokens to post CSRs in order for nodes to get long term certificate credentials
[bootstrap-token] Configured RBAC rules to allow the csrapprover controller automatically approve CSRs from a Node Bootstrap Token
[bootstrap-token] Configured RBAC rules to allow certificate rotation for all node client certificates in the cluster
[bootstrap-token] Creating the "cluster-info" ConfigMap in the "kube-public" namespace
[kubelet-finalize] Updating "/etc/kubernetes/kubelet.conf" to point to a rotatable kubelet client certificate and key
[addons] Applied essential addon: CoreDNS
[addons] Applied essential addon: kube-proxy

Your Kubernetes control-plane has initialized successfully!

To start using your cluster, you need to run the following as a regular user:

  mkdir -p $HOME/.kube
  sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
  sudo chown $(id -u):$(id -g) $HOME/.kube/config

Alternatively, if you are the root user, you can run:

  export KUBECONFIG=/etc/kubernetes/admin.conf

You should now deploy a pod network to the cluster.
Run "kubectl apply -f [podnetwork].yaml" with one of the options listed at:
  https://kubernetes.io/docs/concepts/cluster-administration/addons/

Then you can join any number of worker nodes by running the following on each as root:

kubeadm join 10.1.1.70:6443 --token m9z4yq.dok89ro6yt23wykr \
        --discovery-token-ca-cert-hash sha256:17c3f29bd276592e668e9e6a7a187140a887254b4555cf7d293c3313d7c8a178

配置 kubectl：

为当前用户设置 kubectl 访问：

mkdir -p $HOME/.kube
cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
chown $(id -u):$(id -g) $HOME/.kube/config

安装网络插件：

安装一个 Pod 网络插件，例如 Calico 或 Flannel。例如，使用 Calico：

kubectl apply -f https://docs.projectcalico.org/manifests/calico.yaml
# 网络插件初始化完毕之后，coredns容器就正常了
kubectl logs -n kube-system -l k8s-app=kube-dns

验证集群：

启动一个nginx pod：

# vim nginx_pod.yml
apiVersion: v1
kind: Pod
metadata:
  name: test-nginx-pod
  namespace: test
  labels:
    app: nginx
spec:
  containers:
  - name: test-nginx-container
    image: nginx:latest
    ports:
    - containerPort: 80
  tolerations:
    - key: "node-role.kubernetes.io/control-plane"
      operator: "Exists"
      effect: "NoSchedule"
---

apiVersion: v1
kind: Service
# service和pod必须位于同一个namespace
metadata:
  name: nginx-service
  namespace: test
spec:
  type: NodePort
  # selector应该匹配pod的labels
  selector:
    app: nginx
  ports:
  - protocol: TCP
    port: 80
    nodePort: 30007
    targetPort: 80

启动

kubectl apply -f nginx_pod.yml

部署opentelemetry-collector测试

自定义测试yaml文件

apiVersion: v1
kind: ConfigMap
metadata:
  name: otel-collector-conf
  namespace: default
data:
  # 你的配置数据
  config.yaml: |
    receivers:
      otlp:
        protocols:
          grpc:
          http:
    processors:
      batch:
    exporters:
      logging:
        loglevel: debug
    service:
      pipelines:
        traces:
          receivers: [otlp]
          processors: [batch]
          exporters: [logging]

---
apiVersion: v1
kind: Service
metadata:
  name: otel-collector
  labels:
    app: opentelemetry
spec:
  type: NodePort
  ports:
    - port: 4317
      targetPort: 4317
      nodePort: 30080
      name: otlp-grpc
    - port: 8888
      targetPort: 8888
      name: metrics
  selector:
    component: otel-collector

---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: otel-collector
  labels:
    app: opentelemetry
spec:
  replicas: 1
  selector:
    matchLabels:
      component: otel-collector
  template:
    metadata:
      labels:
        component: otel-collector
    spec:
      tolerations:
      - key: node-role.kubernetes.io/control-plane
        operator: Exists
        effect: NoSchedule
      containers:
      - name: otel-collector
        image: otel/opentelemetry-collector:latest
        ports:
        - containerPort: 4317
        - containerPort: 8888
        env:
        - name: MY_POD_IP
          valueFrom:
            fieldRef:
              fieldPath: status.podIP
        volumeMounts:
        - name: otel-collector-config-vol
          mountPath: /conf
      volumes:
      - configMap:
          name: otel-collector-conf
        name: otel-collector-config-vol

启动

mkdir /conf
kubectl apply -f otel-collector.yaml
kubectl get -f otel-collector.yaml

删除

kubectl delete -f otel-collector.yaml

使用官方提供示例

kubectl apply -f https://raw.githubusercontent.com/open-telemetry/opentelemetry-collector/main/examples/k8s/otel-config.yaml

根据需要修改文件

otel-config.yaml

---
apiVersion: v1
kind: ConfigMap
metadata:
  name: otel-agent-conf
  labels:
    app: opentelemetry
    component: otel-agent-conf
data:
  otel-agent-config: |
    receivers:
      otlp:
        protocols:
          grpc:
            endpoint: ${env:MY_POD_IP}:4317
          http:
            endpoint: ${env:MY_POD_IP}:4318
    exporters:
      otlp:
        endpoint: "otel-collector.default:4317"
        tls:
          insecure: true
        sending_queue:
          num_consumers: 4
          queue_size: 100
        retry_on_failure:
          enabled: true
    processors:
      batch:
      memory_limiter:
        # 80% of maximum memory up to 2G
        limit_mib: 400
        # 25% of limit up to 2G
        spike_limit_mib: 100
        check_interval: 5s
    extensions:
      zpages: {}
    service:
      extensions: [zpages]
      pipelines:
        traces:
          receivers: [otlp]
          processors: [memory_limiter, batch]
          exporters: [otlp]
---
apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: otel-agent
  labels:
    app: opentelemetry
    component: otel-agent
spec:
  selector:
    matchLabels:
      app: opentelemetry
      component: otel-agent
  template:
    metadata:
      labels:
        app: opentelemetry
        component: otel-agent
    spec:
      tolerations:
      - key: node-role.kubernetes.io/control-plane
        operator: Exists
        effect: NoSchedule
      containers:
      - command:
          - "/otelcol"
          - "--config=/conf/otel-agent-config.yaml"
        image: otel/opentelemetry-collector:0.94.0
        name: otel-agent
        resources:
          limits:
            cpu: 500m
            memory: 500Mi
          requests:
            cpu: 100m
            memory: 100Mi
        ports:
        - containerPort: 55679 # ZPages endpoint.
        - containerPort: 4317 # Default OpenTelemetry receiver port.
        - containerPort: 8888  # Metrics.
        env:
          - name: MY_POD_IP
            valueFrom:
              fieldRef:
                apiVersion: v1
                fieldPath: status.podIP
          - name: GOMEMLIMIT
            value: 400MiB
        volumeMounts:
        - name: otel-agent-config-vol
          mountPath: /conf
      volumes:
        - configMap:
            name: otel-agent-conf
            items:
              - key: otel-agent-config
                path: otel-agent-config.yaml
          name: otel-agent-config-vol
---
apiVersion: v1
kind: ConfigMap
metadata:
  name: otel-collector-conf
  labels:
    app: opentelemetry
    component: otel-collector-conf
data:
  otel-collector-config: |
    receivers:
      otlp:
        protocols:
          grpc:
            endpoint: ${env:MY_POD_IP}:4317
          http:
            endpoint: ${env:MY_POD_IP}:4318
    processors:
      batch:
      memory_limiter:
        # 80% of maximum memory up to 2G
        limit_mib: 1500
        # 25% of limit up to 2G
        spike_limit_mib: 512
        check_interval: 5s
    extensions:
      zpages: {}
    exporters:
      otlp:
        endpoint: "http://someotlp.target.com:4317" # Replace with a real endpoint.
        tls:
          insecure: true
      zipkin:
        endpoint: "http://10.1.1.10:9411/api/v2/spans"
        format: "proto"
    service:
      extensions: [zpages]
      pipelines:
        traces/1:
          receivers: [otlp]
          processors: [memory_limiter, batch]
          exporters: [zipkin]
---
apiVersion: v1
kind: Service
metadata:
  name: otel-collector
  labels:
    app: opentelemetry
    component: otel-collector
spec:
  ports:
  - name: otlp-grpc # Default endpoint for OpenTelemetry gRPC receiver.
    port: 4317
    protocol: TCP
    targetPort: 4317
  - name: otlp-http # Default endpoint for OpenTelemetry HTTP receiver.
    port: 4318
    protocol: TCP
    targetPort: 4318
  - name: metrics # Default endpoint for querying metrics.
    port: 8888
  selector:
    component: otel-collector
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: otel-collector
  labels:
    app: opentelemetry
    component: otel-collector
spec:
  selector:
    matchLabels:
      app: opentelemetry
      component: otel-collector
  minReadySeconds: 5
  progressDeadlineSeconds: 120
  replicas: 1 #TODO - adjust this to your own requirements
  template:
    metadata:
      labels:
        app: opentelemetry
        component: otel-collector
    spec:
      tolerations:
      - key: node-role.kubernetes.io/control-plane
        operator: Exists
        effect: NoSchedule
      containers:
      - command:
          - "/otelcol"
          - "--config=/conf/otel-collector-config.yaml"
        image: otel/opentelemetry-collector:0.94.0
        name: otel-collector
        resources:
          limits:
            cpu: 1
            memory: 2Gi
          requests:
            cpu: 200m
            memory: 400Mi
        ports:
        - containerPort: 55679 # Default endpoint for ZPages.
        - containerPort: 4317 # Default endpoint for OpenTelemetry receiver.
        - containerPort: 14250 # Default endpoint for Jaeger gRPC receiver.
        - containerPort: 14268 # Default endpoint for Jaeger HTTP receiver.
        - containerPort: 9411 # Default endpoint for Zipkin receiver.
        - containerPort: 8888  # Default endpoint for querying metrics.
        env:
          - name: MY_POD_IP
            valueFrom:
              fieldRef:
                apiVersion: v1
                fieldPath: status.podIP
          - name: GOMEMLIMIT
            value: 1600MiB
        volumeMounts:
        - name: otel-collector-config-vol
          mountPath: /conf
#        - name: otel-collector-secrets
#          mountPath: /secrets
      volumes:
        - configMap:
            name: otel-collector-conf
            items:
              - key: otel-collector-config
                path: otel-collector-config.yaml
          name: otel-collector-config-vol
#        - secret:
#            name: otel-collector-secrets
#            items:
#              - key: cert.pem
#                path: cert.pem
#              - key: key.pem
#                path: key.pem

部署deepflow监控单个k8s集群

官方文档
 官方demo

安装helm

snap install helm --classic

设置pv

kubectl apply -f https://openebs.github.io/charts/openebs-operator.yaml
## config default storage class
kubectl patch storageclass openebs-hostpath  -p '{"metadata": {"annotations":{"storageclass.kubernetes.io/is-default-class":"true"}}}'

部署deepflow

helm repo add deepflow https://deepflowio.github.io/deepflow
helm repo update deepflow # use `helm repo update` when helm < 3.7.0
helm install deepflow -n deepflow deepflow/deepflow --create-namespace
# 显示如下
NAME: deepflow
LAST DEPLOYED: Tue May 14 14:13:50 2024
NAMESPACE: deepflow
STATUS: deployed
REVISION: 1
NOTES:
██████╗ ███████╗███████╗██████╗ ███████╗██╗      ██████╗ ██╗    ██╗
██╔══██╗██╔════╝██╔════╝██╔══██╗██╔════╝██║     ██╔═══██╗██║    ██║
██║  ██║█████╗  █████╗  ██████╔╝█████╗  ██║     ██║   ██║██║ █╗ ██║
██║  ██║██╔══╝  ██╔══╝  ██╔═══╝ ██╔══╝  ██║     ██║   ██║██║███╗██║
██████╔╝███████╗███████╗██║     ██║     ███████╗╚██████╔╝╚███╔███╔╝
╚═════╝ ╚══════╝╚══════╝╚═╝     ╚═╝     ╚══════╝ ╚═════╝  ╚══╝╚══╝ 

An automated observability platform for cloud-native developers.

# deepflow-agent Port for receiving trace, metrics, and log

deepflow-agent service: deepflow-agent.deepflow
deepflow-agent Host listening port: 38086

# Get the Grafana URL to visit by running these commands in the same shell

NODE_PORT=$(kubectl get --namespace deepflow -o jsonpath="{.spec.ports[0].nodePort}" services deepflow-grafana)
NODE_IP=$(kubectl get nodes -o jsonpath="{.items[0].status.addresses[0].address}")
echo -e "Grafana URL: http://$NODE_IP:$NODE_PORT  \nGrafana auth: admin:deepflow"

节点安装deepflow-ctl

curl -o /usr/bin/deepflow-ctl https://deepflow-ce.oss-cn-beijing.aliyuncs.com/bin/ctl/stable/linux/$(arch | sed 's|x86_64|amd64|' | sed 's|aarch64|arm64|')/deepflow-ctl
chmod a+x /usr/bin/deepflow-ctl

访问grafana页面

NODE_PORT=$(kubectl get --namespace deepflow -o jsonpath="{.spec.ports[0].nodePort}" services deepflow-grafana)
NODE_IP=$(kubectl get nodes -o jsonpath="{.items[0].status.addresses[0].address}")
echo -e "Grafana URL: http://$NODE_IP:$NODE_PORT  \nGrafana auth: admin:deepflow"

在这里插入图片描述

FAQ

如何将pod的端口暴露出来

在 Kubernetes 中，如果你想要将 Pod 的端口暴露给集群外部的用户或服务访问，你可以通过创建 Service 来实现。Service 提供了几种不同的类型来支持不同的用例和网络需求。以下是一些常见的方法：

NodePort：这种类型的 Service 会在集群的所有节点上开放一个指定的端口（通常在 30000-32767 范围内），任何发送到这个端口的流量都会被转发到对应的 Pod。这是最简单的方式，但它会占用节点上的端口。

示例 YAML 配置：
```
apiVersion: v1
kind: Service
metadata:
  name: my-service
spec:
  type: NodePort
  selector:
    app: MyApp
  ports:
    - protocol: TCP
      port: 80
      targetPort: 9376
      nodePort: 30007
```
LoadBalancer：这种类型的 Service 通常由云提供商支持，它会为 Service 分配一个外部 IP 地址，所有发送到这个 IP 地址的流量都会被转发到 Pod。这种方式适用于需要直接从互联网访问服务的场景。

示例 YAML 配置：
```
apiVersion: v1
kind: Service
metadata:
  name: my-service
spec:
  selector:
    app: MyApp
  ports:
    - protocol: TCP
      port: 80
      targetPort: 9376
  type: LoadBalancer
```

Ingress：Ingress 是一个 API 对象，它定义了外部访问到集群服务的规则。它可以提供负载均衡、SSL 终端和基于名称的虚拟托管。这是一个更高级的暴露方式，可以让你使用一个单一的入口点来管理多个服务的访问。

示例 YAML 配置：

apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: example-ingress
spec:
  rules:
  - host: www.example.com
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: my-service
            port:
              number: 80

Port Forwarding：如果你只是临时需要从本地机器访问 Pod，可以使用 kubectl port-forward 命令将本地端口转发到 Pod 中的端口。

示例命令：
```
kubectl port-forward pods/my-pod 8080:80
```

这些方法可以根据你的具体需求和环境来选择使用。

deepflow是一个可观测平台吗

是的，DeepFlow 是一个可观测性平台。它是由云杉网络开发的，旨在为复杂的云基础设施及云原生应用提供深度可观测性。DeepFlow 基于 eBPF 技术实现了应用性能指标、分布式追踪、持续性能剖析等观测信号的零侵扰采集，并结合智能标签技术实现了所有观测信号的全栈关联和高效存取¹。

DeepFlow 提供了以下核心特性：

全景图：利用 eBPF 技术零侵扰绘制生产环境的服务全景图。
分布式追踪：基于 eBPF 和 Wasm 技术零侵扰实现分布式追踪。
持续性能剖析：利用 eBPF 技术以低开销零侵扰采集生产环境进程的性能剖析数据。
存储性能优化：通过 SmartEncoding 机制大幅降低存储成本。
无缝集成：可以作为 Prometheus、OpenTelemetry、SkyWalking、Pyroscope 的存储后端，也提供 SQL、PromQL、OTLP 等数据接口¹。

DeepFlow 旨在解决传统 APM 方案中的侵扰性和观测盲点问题，提供一种更高效、自动化的可观测性解决方案。

deepflow会自动监控k8s中的pod应用吗

是的，DeepFlow 可以自动监控 Kubernetes 中的 Pod 应用。DeepFlow 是一个可观测性平台，它基于 eBPF 技术实现了应用性能指标、分布式追踪、持续性能剖析等观测信号的零侵扰采集，并结合智能标签技术实现了所有观测信号的全栈关联和高效存取。

以下是 DeepFlow 在 Kubernetes 中自动监控 Pod 应用的一些特性：

零侵扰采集:
DeepFlow 使用 eBPF 技术，无需修改应用程序代码，即可自动收集应用性能指标、分布式追踪数据和持续性能剖析信息。
全栈关联:
DeepFlow 通过智能标签技术，将所有观测信号（指标、日志、追踪）关联到全栈中的不同组件，帮助您更好地理解应用程序的整体性能。
自动标记 K8s 资源:
DeepFlow 自动标记 Kubernetes 资源（如 Pod、Service、Deployment 等），使您可以轻松地按照资源维度进行监控。
持续性能剖析:
DeepFlow 可以低开销地采集生产环境进程的性能剖析数据，帮助您深入分析应用程序的性能瓶颈。

总之，DeepFlow 是一个强大的可观测性工具，可以自动监控 Kubernetes 中的应用程序，帮助您更好地理解和优化应用性能。

FAQ

如何将pod的端口暴露出来

NodePort：这种类型的 Service 会在集群的所有节点上开放一个指定的端口（通常在 30000-32767 范围内），任何发送到这个端口的流量都会被转发到对应的 Pod。这是最简单的方式，但它会占用节点上的端口。

示例 YAML 配置：
```
apiVersion: v1
kind: Service
metadata:
  name: my-service
spec:
  type: NodePort
  selector:
    app: MyApp
  ports:
    - protocol: TCP
      port: 80
      targetPort: 9376
      nodePort: 30007
```
LoadBalancer：这种类型的 Service 通常由云提供商支持，它会为 Service 分配一个外部 IP 地址，所有发送到这个 IP 地址的流量都会被转发到 Pod。这种方式适用于需要直接从互联网访问服务的场景。

示例 YAML 配置：
```
apiVersion: v1
kind: Service
metadata:
  name: my-service
spec:
  selector:
    app: MyApp
  ports:
    - protocol: TCP
      port: 80
      targetPort: 9376
  type: LoadBalancer
```

示例 YAML 配置：

apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: example-ingress
spec:
  rules:
  - host: www.example.com
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: my-service
            port:
              number: 80

Port Forwarding：如果你只是临时需要从本地机器访问 Pod，可以使用 kubectl port-forward 命令将本地端口转发到 Pod 中的端口。

示例命令：
```
kubectl port-forward pods/my-pod 8080:80
```

这些方法可以根据你的具体需求和环境来选择使用。

deepflow是一个可观测平台吗

DeepFlow 提供了以下核心特性：

全景图：利用 eBPF 技术零侵扰绘制生产环境的服务全景图。
分布式追踪：基于 eBPF 和 Wasm 技术零侵扰实现分布式追踪。
持续性能剖析：利用 eBPF 技术以低开销零侵扰采集生产环境进程的性能剖析数据。
存储性能优化：通过 SmartEncoding 机制大幅降低存储成本。
无缝集成：可以作为 Prometheus、OpenTelemetry、SkyWalking、Pyroscope 的存储后端，也提供 SQL、PromQL、OTLP 等数据接口¹。

DeepFlow 旨在解决传统 APM 方案中的侵扰性和观测盲点问题，提供一种更高效、自动化的可观测性解决方案。

deepflow会自动监控k8s中的pod应用吗

以下是 DeepFlow 在 Kubernetes 中自动监控 Pod 应用的一些特性：

零侵扰采集:
DeepFlow 使用 eBPF 技术，无需修改应用程序代码，即可自动收集应用性能指标、分布式追踪数据和持续性能剖析信息。
全栈关联:
DeepFlow 通过智能标签技术，将所有观测信号（指标、日志、追踪）关联到全栈中的不同组件，帮助您更好地理解应用程序的整体性能。
自动标记 K8s 资源:
DeepFlow 自动标记 Kubernetes 资源（如 Pod、Service、Deployment 等），使您可以轻松地按照资源维度进行监控。
持续性能剖析:
DeepFlow 可以低开销地采集生产环境进程的性能剖析数据，帮助您深入分析应用程序的性能瓶颈。

总之，DeepFlow 是一个强大的可观测性工具，可以自动监控 Kubernetes 中的应用程序，帮助您更好地理解和优化应用性能。

FAQ

如何将pod的端口暴露出来

NodePort：这种类型的 Service 会在集群的所有节点上开放一个指定的端口（通常在 30000-32767 范围内），任何发送到这个端口的流量都会被转发到对应的 Pod。这是最简单的方式，但它会占用节点上的端口。

示例 YAML 配置：
```
apiVersion: v1
kind: Service
metadata:
  name: my-service
spec:
  type: NodePort
  selector:
    app: MyApp
  ports:
    - protocol: TCP
      port: 80
      targetPort: 9376
      nodePort: 30007
```
LoadBalancer：这种类型的 Service 通常由云提供商支持，它会为 Service 分配一个外部 IP 地址，所有发送到这个 IP 地址的流量都会被转发到 Pod。这种方式适用于需要直接从互联网访问服务的场景。

示例 YAML 配置：
```
apiVersion: v1
kind: Service
metadata:
  name: my-service
spec:
  selector:
    app: MyApp
  ports:
    - protocol: TCP
      port: 80
      targetPort: 9376
  type: LoadBalancer
```

示例 YAML 配置：

apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: example-ingress
spec:
  rules:
  - host: www.example.com
    http:
      paths:
      - path: /
        pathType: Prefix
        backend:
          service:
            name: my-service
            port:
              number: 80

Port Forwarding：如果你只是临时需要从本地机器访问 Pod，可以使用 kubectl port-forward 命令将本地端口转发到 Pod 中的端口。

示例命令：
```
kubectl port-forward pods/my-pod 8080:80
```

这些方法可以根据你的具体需求和环境来选择使用。

deepflow是一个可观测平台吗

DeepFlow 提供了以下核心特性：

全景图：利用 eBPF 技术零侵扰绘制生产环境的服务全景图。
分布式追踪：基于 eBPF 和 Wasm 技术零侵扰实现分布式追踪。
持续性能剖析：利用 eBPF 技术以低开销零侵扰采集生产环境进程的性能剖析数据。
存储性能优化：通过 SmartEncoding 机制大幅降低存储成本。
无缝集成：可以作为 Prometheus、OpenTelemetry、SkyWalking、Pyroscope 的存储后端，也提供 SQL、PromQL、OTLP 等数据接口¹。

DeepFlow 旨在解决传统 APM 方案中的侵扰性和观测盲点问题，提供一种更高效、自动化的可观测性解决方案。

deepflow会自动监控k8s中的pod应用吗

以下是 DeepFlow 在 Kubernetes 中自动监控 Pod 应用的一些特性：

零侵扰采集:
DeepFlow 使用 eBPF 技术，无需修改应用程序代码，即可自动收集应用性能指标、分布式追踪数据和持续性能剖析信息。
全栈关联:
DeepFlow 通过智能标签技术，将所有观测信号（指标、日志、追踪）关联到全栈中的不同组件，帮助您更好地理解应用程序的整体性能。
自动标记 K8s 资源:
DeepFlow 自动标记 Kubernetes 资源（如 Pod、Service、Deployment 等），使您可以轻松地按照资源维度进行监控。
持续性能剖析:
DeepFlow 可以低开销地采集生产环境进程的性能剖析数据，帮助您深入分析应用程序的性能瓶颈。

总之，DeepFlow 是一个强大的可观测性工具，可以自动监控 Kubernetes 中的应用程序，帮助您更好地理解和优化应用性能。

K8S/Kubernetes

K8S/Kubernetes社区为您提供最前沿的新闻资讯和知识内容

更多推荐

【深度】阿里巴巴万级规模 K8s 集群全局高可用体系之美

作者 | 韩堂、柘远、沉醉来源 | 阿里巴巴云原生公众号前言台湾作家林清玄在接受记者采访的时候，如此评价自己 30 多年写作生涯：“第一个十年我才华横溢，‘贼光闪现’，令周边黯然失色；第二个十年，我终于‘宝光现形’，不再去抢风头，反而与身边的美丽相得益彰；进入第三个十年，繁华落尽见真醇，我进入了‘醇光初现’的阶段，真正体味到了境界之美”。长夜有穷，真水无香。领略过了 K8s“身在江

K8S/Kubernetes

如何基于 K8s 构建下一代 DevOps 平台？

作者 | 孙健波（天元）导读：当前云原生 DevOps 体系现状如何？面临哪些挑战？如何通过 OAM 解决云原生 DevOps 场景下的诸多问题？云原生开发应用模型 OAM(Open Application Model) 社区核心成员孙健波将为大家一一解答，并分享如何基于 OAM 和 Kubernetes 打造无限能力的下一代 DevOps 平台。什么是 DevOps？为什么基于 Kub