tencent cloud

Overview

This document describes how to host a Spring Cloud application to TKE.

Hosting Spring Cloud applications to TKE has the following advantages:

• Improve the resource utilization.
• Kubernetes is a natural fit for microservice architectures.
• Improve the Ops efficiency and facilitate DevOps implementation.
• Highly scalable Kubernetes makes it easy to dynamically scale applications.
• TKE provides Kubernetes master management to ease Kubernetes cluster Ops and management.
• TKE is integrated with other cloud-native products of Tencent Cloud to help you better use Tencent Cloud products.

Best Practices

PiggyMetrics overview

This document describes how to host a Spring Cloud application to TKE by forking the open-source PiggyMetrics on GitHub and adapting it to Tencent Cloud products.

Note：

The modified PiggyMetrics deployment project is hosted on GitHub. After creating the basic service cluster, you can download the deployment project and deploy it in TKE.

The PiggyMetrics homepage is as shown below:

PiggyMetrics is a microservice-architecture application for personal finances developed by using the Spring Cloud framework.

PiggyMetrics consists of the following microservices:

PiggyMetrics deployment architecture and add-ons

In the following best practice, applications deployed in CVM are containerized and hosted to TKE. In this use case, one VPC is used and divided into two subnets:

• Subnet-Basic is deployed with stateful basic services, including Dubbo's service registry Nacos, MySQL, and Redis.
• Subnet-K8S is deployed with PiggyMetrics application services, all of which are containerized and run in TKE.

The VPC is divided as shown below:

The network planning for the PiggyMetrics instance is as shown below:

The add-ons used in the PiggyMetrics instance are as shown below:

Overview

TCR

Tencent Cloud Tencent Container Registry (TCR) are available in Personal Edition and Enterprise Edition as differentiated below:

• TCR Personal Edition is only deployed in Guangzhou, while TCR Enterprise Edition is deployed in every region.
• TCR Personal Edition doesn't offer SLA guarantee.

PiggyMetrics is a Dubbo containerized demo project, so TCR Personal Edition perfectly meets its needs. However, for enterprise users, TCR Enterprise Edition is recommended. To use an image repository, see Basic Image Repository Operations.

TSW

Tencent Service Watcher (TSW) provides cloud-native service observability solutions that can trace upstream and downstream dependencies in distributed architectures, draw topologies, and provide multidimensional call observation by service, API, instance, and middleware.

TSW is architecturally divided into four modules:

The architecture is as shown below:

Directions

Creating basic service cluster

• In the TencentDB for MongoDB console, create an instance and run the following command to initialize it:

  # Download the MongoDB client, decompress it, and enter the `bin` directory.
  
  wget https://fastdl.mongodb.org/linux/mongodb-linux-x86_64-3.6.18.tgz
  tar -zxvf mongodb-linux-x86_64-3.6.18.tgz
  cd mongodb-linux-x86_64-3.6.18/bin
  
  # Run the following command to initialize MongoDB, where `mongouser` is the admin account created when the MongoDB instance is created.
  
  ./mongo -u mongouser -p --authenticationDatabase "admin" [mongodb IP]/piggymetrics mongo-init.js

  A guest user of the piggymetrics library is created in the MongoDB initialization script mongo-init.js by default, which can be modified as needed.

• In the CLB console, create a private network CLB instance for Subnet-K8S (the ID of this CLB instance will be used later).

• TSW is currently in beta test and supports both Java and Go.

Building Docker image

Writing Dockerfile

The following uses account-service as an example to describe how to write a Dockerfile. The project directory structure of account-service is displayed, Dockerfile is in the root directory of the project, and account-service.jar is the packaged file that needs to be added to the image.

➜  account-service tree
├── Dockerfile
├── skywalking
│   ├── account.config
│   └── skywalking-agent.zip
├── pom.xml
├── src
│    ....
├── target
│    .....
│   └── account-service.jar
└── account-service.iml

Note：

Here, SkyWalking Agent is used as the TSW access client that reports call chain information to the TSW backend. For more information on how to download SkyWalking Agent, see PiggyMetrics deployment architecture and add-ons.

The Dockerfile of account-service is as shown below:

FROM java:8-jre

# Working directory in the container 

/appWORKDIR /app

# Add the locally packaged application to the image.

ADD ./target/account-service.jar

# Copy SkyWalking Agent to the image.

COPY ./skywalking/skywalking-agent.zip 

# Decompress SkyWalking Agent and delete the original compressed file.

RUN unzip skywalking-agent.zip && rm -f skywalking-agent.zip

# Add the SkyWalking configuration file.

COPY ./skywalking/account.config ./skywalking-agent/config/agent.config

# Start the application.

CMD ["java", "-Xmx256m", "-javaagent:/app/skywalking-agent/skywalking-agent.jar", "-jar", "/app/account-service.jar"]

# Port description of the application

EXPOSE 6000

Note：

As each Run command in the Dockerfile will generate an image layer, we recommend you combine these commands into one.

Image build

TCR provides both automatic and manual methods to build an image. To demonstrate the build process, the manual method is used.

The image name needs to be in line with the convention of ccr.ccs.tencentyun.com/[namespace]/[ImageName]:[image tag]:

• Here, namespace can be the project name to facilitate image management and use. In this document, piggymetrics represents all the images under the PiggyMetrics project.
• ImageName can contain the subpath, generally used for multi-project use cases of enterprise users. In addition, if a local image is already built, you can run the docker tag command to rename the image in line with the naming convention.

1. Run the following command to build an image as shown below:

   # Recommended build method, which eliminates the need for secondary tagging operations
   
   sudo docker build -t ccr.ccs.tencentyun.com/[namespace]/[ImageName]:[image tag]
   
   # Build a local `account-service` image. The last `.` indicates that the Dockerfile is stored in the current directory (`account-service`).
   
   ➜  account-service docker build -t ccr.ccs.tencentyun.com/piggymetrics/account-service:1.0.0 .
   
   # Rename existing images in line with the naming convention
   
   sudo docker tag [ImageId] ccr.ccs.tencentyun.com/[namespace]/[ImageName]:[image tag]

2. After the build is complete, you can run the following command to view all the images in your local repository.

   docker images | grep piggymetrics
   

   A sample is as shown below:
   

Uploading image to TCR

Creating namespace

The PiggyMetrics project uses TCR Personal Edition (TCR Enterprise Edition is recommended for enterprise users).

1. Log in to the TKE console.
2. Click TCR > Personal > Namespace to enter the Namespace page.
3. Click Create and create the piggymetrics namespace in the pop-up window. All the images of the PiggyMetrics project are stored under this namespace as shown below:
   

Uploading image

Log in to TCR and upload an image.

1. Run the following command to log in to TCR.

   docker login --username=[Tencent Cloud account ID] ccr.ccs.tencentyun.com
   

   • You can get your Tencent Cloud account ID on the Account Info page.
   • If you forget your TCR login password, you can reset it in My Images of TCR Personal Edition.
     
   • If you are prompted that you have no permission to run the command, add sudo before the command and run it as shown below. In this case, you need to enter two passwords, the server admin password required for sudo and the TCR login password.
     

     sudo docker login --username=[Tencent Cloud account ID] ccr.ccs.tencentyun.com
     

     As shown below:
     

2. Run the following command to push the locally generated image to TCR.

   docker push ccr.ccs.tencentyun.com/[namespace]/[ImageName]:[image tag]
   

   As shown below:
   

3. In My Images, you can view all the uploaded images.

   The default image type is Private. If you want to let others use the image, you can set it to Public in Image Info as shown below:
   

Deploying service in TKE

Creating K8s cluster PiggyMetrics

1. Before the deployment, you need to create a K8s cluster as instructed in Quickly Creating a Standard Cluster.

   Note：

   When a cluster is created, we recommend you enable Placement Group on the Select Model page. It helps distribute CVM instances across different hosts to increase the system reliability.

2. After the cluster is created, you can view its information on the Cluster Management page in the TKE console. Here, the new cluster is named piggyMetrics.
3. Click the PiggyMetrics-k8s-demo cluster to enter the Basic Info page to view the cluster configuration information.
4. (Optional) If you want to use K8s management tools such as kubectl and Lens, you need to follow two steps:
   1. Enable public network access.
   2. Store the API authentication token in the local config file under user home/.kube (choose another if the config file has content) to ensure that the default cluster can be accessed each time. If you choose not to store the token in the config file under .kube, see the Instructions on Connecting to Kubernetes Cluster via kubectl under Cluster API Server Info in the console as shown below:
      

Creating namespace

A namespace is a logical environment in a Kubernetes cluster, allowing you to divide teams or projects. You can create a namespace in the following three methods, and method 1 is recommended.

kubectl create namespace piggymetrics

kubctl create –f namespace.yaml

# Create the piggymetrics namespace.
apiVersion: v1
kind: Namespace
metadata: 
  name: piggymetrics
spec: 
  finalizers:
  - kubernetes

Using ConfigMap to store configuration information

ConfigMap allows you to decouple the configuration from the running image, making the application more portable. The PiggyMetrics backend service needs to get the MongoDB host and port information from the environment variables and store them by using the ConfigMap.
You can use ConfigMap to store configuration information in the following two methods:

# Create a ConfigMap.
apiVersion: v1
kind: ConfigMap
metadata: 
  name: piggymetrics-env
  namespace: piggymetrics
data: 
  # MongoDB IP address
  MONGODB_HOST: 10.0.1.13 
  # TSW access address as described below
  SW_AGENT_COLLECTOR_BACKEND_SERVICES: ap-shanghai.tencentservicewatcher.com:11800

Using Secret to store sensitive information

A Secret can be used to store sensitive information such as passwords, tokens, and keys to reduce exposure risks. PiggyMetrics uses it to store account and password information.
You can use a Secret to store sensitive information in the following two methods:

# Create a Secret.
apiVersion: v1
kind: Secret
metadata: 
  name: piggymetrics-keys
  namespace: piggymetrics
  labels: 
    qcloud-app: piggymetrics-keys
data: 
  # Replace XXX below with the actual value.
  MONGODB_USER: XXX
  MONGODB_PASSWORD: XXX
  SW_AGENT_AUTHENTICATION: XXX
type: Opaque

Deploying stateful service with StatefulSet

A StatefulSet is used to manage stateful applications. A Pod created accordingly has a persistent identifier in line with the specifications, which will be retained after the Pod is migrated, terminated, or restarted. When using persistent storage, you can map storage volumes to identifiers.
The basic add-ons and services under the PiggyMetrics project such as configuration services, registry, and RabbitMQ have their own data stored and are therefore suitable for deployment through StatefulSet.

Below is a sample deployment YAML for config-server:

---
kind: Service
apiVersion: v1
metadata: 
  name: config-server
  namespace: piggymetrics
spec: 
  clusterIP: None
  ports: 
    - name: http
      port: 8888
      targetPort: 8888
      protocol: TCP
  selector: 
    app: config
    version: v1

---
apiVersion: apps/v1
kind: StatefulSet
metadata: 
  name: config
  namespace: piggymetrics
  labels: 
    app: config
    version: v1
spec: 
  serviceName: "config-server"
  replicas: 1
  selector: 
    matchLabels: 
      app: config
      version: v1
  template: 
    metadata: 
      labels: 
        app: config
        version: v1
    spec: 
      terminationGracePeriodSeconds: 10
      containers: 
        - name: config
          image: ccr.ccs.tencentyun.com/piggymetrics/config-server:2.0.03
          ports: 
            - containerPort: 8888
              protocol: TCP

Deploying Deployment

A Deployment declares the Pod template and controls the Pod running policy, which is suitable for deploying stateless applications. PiggyMetrics backend services such as Account are stateless and can use the Deployment.

YAML parameters for the account-service Deployment are as follows:

Below is a complete sample YAML file for the account-service Deployment:

# account-service Deployment
apiVersion: apps/v1
kind: Deployment
metadata: 
  name: account-service
  namespace: piggymetrics
  labels: 
    app: account-service
    version: v1
spec: 
  replicas: 1
  selector: 
    matchLabels: 
      app: account-service
      version: v1
  template: 
    metadata: 
      labels: 
        app: account-service
        version: v1
    spec: 
      containers: 
        - name: account-service
          image: ccr.ccs.tencentyun.com/piggymetrics/account-service:1.0.1
          env: 
            # MongoDB IP address
            - name: MONGODB_HOST
              valueFrom: 
                configMapKeyRef: 
                  key: MONGODB_HOST
                  name: piggymetrics-env
                  optional: false
            # MongoDB username
            - name: MONGODB_USER
              valueFrom: 
                secretKeyRef: 
                  key: MONGODB_USER
                  name: piggymetrics-keys
                  optional: false
            # MongoDB password
            - name: MONGODB_PASSWORD
              valueFrom: 
                secretKeyRef: 
                  key: MONGODB_PASSWORD
                  name: piggymetrics-keys
                  optional: false
            # TSW access point
            - name: SW_AGENT_COLLECTOR_BACKEND_SERVICES
              valueFrom: 
                configMapKeyRef: 
                  key: SW_AGENT_COLLECTOR_BACKEND_SERVICES
                  name: piggymetrics-env
                  optional: false
            # TSW access token
            - name: SW_AGENT_AUTHENTICATION
              valueFrom: 
                secretKeyRef: 
                  key: SW_AGENT_AUTHENTICATION
                  name: piggymetrics-keys
                  optional: false
          ports: 
            # Container port
            - containerPort: 6000
              protocol: TCP
      imagePullSecrets: # Token to pull the image
        - name: qcloudregistrykey

Deploying Service

You can specify the Service type with Kubernetes ServiceType, which defaults to ClusterIP. Valid values of ServiceType include the following:

• LoadBalancer: Provides public network, VPC, and private network access.
• NodePort: : Accesses services through the CVM IP and host port.
• ClusterIP: Accesses services through the service name and port.

The frontend pages and the gateway of PiggyMetrics are packaged together and need to provide services, so ServiceType is set to LoadBalancer. TKE enriches the LoadBalancer mode by configuring the Service through annotations.

If you use the service.kubernetes.io/qcloud-loadbalancer-internal-subnetid annotations, a private network CLB instance will be created when the Service is deployed. In general, we recommend you create the CLB instance in advance and use the service.kubernetes.io/loadbalance-id annotations in the deployment YAML to improve the efficiency.

Below is the deployment YAML for gateway service:

# Deploy `gateway service`.
apiVersion: v1
kind: Service
metadata: 
  name: gateway
  namespace: piggymetrics
  annotations: 
    # Replace it with the ID of the CLB instance of `Subnet-K8S`.
    service.kubernetes.io/loadbalance-id: lb-hfyt76co
spec: 
  externalTrafficPolicy: Cluster
  ports: 
    - name: http
      port: 80
      targetPort: 4000
      protocol: TCP
  selector: # Map the backend `gateway` to the Service.
    app: gateway
    version: v1
  type: LoadBalancer

Viewing deployment result

At this point, you have completed the deployment of PiggyMetrics in TKE and can view the deployment result in the following steps:

1. Log in to the TKE console and click the Cluster ID/Name to enter the cluster details page.
2. Click Services and Routes > Service to enter the Service page, where you can see the created Service. You can access the PiggyMetrics page through the gateway service VIP.

Integrating CLS

Enabling container log collection

The container log collection feature is disabled by default and needs to be enabled as instructed below:

1. Log in to the TKE console and click Cluster Ops > Feature Management on the left sidebar.
2. At the top of the Feature Management page, select the region. On the right of the target cluster, click Set.
   
3. On the Configure Features page, click Edit for log collection, enable log collection, and confirm this operation as shown below:
   

Creating log topic and logset

CLS is region-specific. To reduce the network latency, we recommend you select a region closest to your business when creating log resources, which are mainly logsets and log topics. A logset represents a project, a log topic represents a class of services, and a single logset can contain multiple log topics.

PiggyMetrics is deployed in Nanjing region, so you need to select Nanjing region on the Log Topic page when creating logsets:

1. Log in to the CLS console and select Nanjing region on the Log Topic page.
2. Click Create Log Topic and enter the relevant information in the pop-up window as prompted as shown below:
   
   • Log Topic Name: Enter piggymetrics.
   • Logset Operation: Select Create Logset.
   • Logset Name: Enter piggymetrics-logs.
3. Click OK.

   Note：

   As PiggyMetrics has multiple backend microservices, you can create a log topic for each microservice to facilitate log categorization.

   • A log topic is created for each PiggyMetrics service.
   • You need the log topic ID when creating log rules for containers.

Configuring log collection rule

You can configure container log collection rules in the console or with CRD.

apiVersion: cls.cloud.tencent.com/v1
kind: LogConfig
metadata: 
    name: account-log-rule
spec: 
    clsDetail: 
    extractRule: {}
    # Single-line text
    logType: minimalist_log
    # Log topic ID
    topicId: 8438cc9b-888f-469f-9cff-9891270a0a13
    inputDetail: 
    # Standard container output
    containerStdout: 
      container: account-service
      includeLabels: 
        app: account-service
        version: v1
      namespace: piggymetrics
    type: container_stdout

Viewing log

1. Log in to the CLS console and enter the Search and Analysis page.
2. On the Search and Analysis page, Create Index for the logs first and then click Search and Analysis to view the logs.
   

   Note：

   You can't find logs if no indexes are created.

Integrating TSW

TSW is currently in beta test and can be deployed in Guangzhou and Shanghai. Here, deployment in Shanghai is used as an example (PiggyMetrics is deployed in Nanjing).

Accessing TSW - getting access point information

1. Log in to the TSW console and click Service Observation > Service List on the left sidebar.
2. Click Access Service and select Java and the SkyWalking data collection method. The access method provides the Access Point and Token information.

Accessing TSW - application and container configuration

Enter the Access Point and Token of the TSW obtained in the previous step in collector.backend_service and agent.authentication respectively in the agent.config of SkyWalking. agent.service_name is the service name, and agent.namespace can be used to group microservices under the same domain. account-service configuration is as shown below:

You can also configure SkyWalking Agent by using environment variables. PiggyMetrics uses the ConfigMap and Secret to configure environment variables:

• Use the ConfigMap to configure SW_AGENT_COLLECTOR_BACKEND_SERVICES.
• Use the Secret to configure SW_AGENT_AUTHENTICATION.

As shown below:

At this point, you have completed TSW access. After starting the container service, you can view the call chain, service topology, and SQL analysis in the TSW console.

Using TSW

Viewing call exception through service API or call chain

1. Log in to the TSW console and click Service Observation > API Observation on the left sidebar.
2. On the API Observation page, you can view the call status of all APIs under a service, including the number of requests, success rate, error rate, response time, and other metrics.
   The figure shows that the gateway and account-service responded too slowly and all statistic-service requests failed in the past hour.
3. Click the service name statistics-service to enter the information page. Click API Observation, and you can see that the API {PUT}/{accountName} throws a NestedServletException exception, which makes the API unavailable.
4. Click the Trace ID to view the call chain details.

Viewing service topology

1. Log in to the TSW console and click Chain Tracing > Distributed Dependency Topology on the left sidebar.
2. On the Distributed Dependency Topology page, you can view the completed service dependencies as well as information such as the number of calls and average latency.