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- Product Overview
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- Quick Start
- Operation Guide
- Fault Action Library
- Compute
- JVM Process CPU at Full Load
- Cross-AZ Experiment in CVM
- CVM DNS Unavailability Experiment
- CVM Domain Name Parsing Tampering Experiment
- CVM System Time Skew
- CVM Disk IO Hang Fault Experiment
- CVM Memory OOM and Disk IO Load
- Experiments on CVM Intra-host Network Disorder
- CVM Kernel Faults
- Experiments on CVM Intra-host Network Latency
- High Utilization of CVM Resources (CPU, Memory, and Disk)
- Experiments on CVM Intra-host Network Corruption
- Experiments on CVM Intra-host Network Duplication
- Experiments on CVM Intra-host Network Occupation
- CVM Network Interruption
- CVM Ping Unreachable
- Cloud API Ban in CVM
- Database
- Primary-secondary Switch in TencentDB for PostgreSQL
- MySQL Instance Overall Unavailable
- Primary-secondary Switch in MySQL
- Setting Maximum Number of Connections in MySQL
- Primary Node Fault Experiment on TencentDB for MySQL
- TencentDB for MySQL Read-only Instance Group Unavailable
- Primary-secondary Switch in TDSQL for MySQM
- Primary-secondary Switch in MariaDB
- Primary-secondary Switch in TDSQL-C
- Practice of TencentDB for Redis Proxy Node Faults
- TencentDB for Redis Primary Node Fault
- Primary-secondary Nodes in TencentDB for Redis Instance Unavailable
- Simulating Primary-secondary Switch in Redis
- Simulating MongoDB Storage Node Fault
- Simulating Self-Built MySQL Crash Through Network Blocking
- Restarting TencentDB for MySQL
- Primary-secondary Switch in SQL Server
- Network
- Container
- Simulating Container Resource Network Faults
- Experiment on Container Resource Pod Operation Faults
- Experiment on Container Resource Node Faults
- Experiment on Container Resource Application Process Faults
- Standard Cluster and Serverless Cluster Super Node Faults
- Serverless Pod Fault Experiment Case
- Cluster Node Resource (CPU, Memory, Disk) Stress Test Faults
- Serverless Pod Virtual Node Shutdown Faults
- Simulating Serverless Cluster Pod Network Faults
- High Cluster Pod Resource (CPU, Memory, and Disk) Utilization Rate
- Cluster Pod TencentCloud API Ban
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- Cloud Load Balancer
- Message Queue
- Direct Connect
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Experiment on Container Resource Node Faults
Last updated: 2024-09-26 15:47:38
Background
Container nodes (such as worker nodes in a Kubernetes cluster) host container resources and are responsible for running and managing container instances. However, container nodes may encounter hardware faults, resource shortages, network faults, etc., which could lead to container instances not operating correctly.
To enhance the reliability and stability of container services, node fault experiments are needed. Through these experiments, you can verify whether the system can operate normally in the event of container node faults, and uncover potential issues in advance for system architecture optimization and emergency planning.
Experiment Execution
Step 1: Experiment Preparation
Create a container node, add instances, and deploy the test service. If there is already a container node available for the experiment, proceed directly to create the experiment.
Enter Agent Management page and install the agents.
Step 2: Create an Experiment
1. Log in Tencent Smart Advisor > Chaotic Fault Generator, go to Experiment Management page, and click Create a New Experiment.
2. Click Skip and create a blank experiment, and fill in the experiment details.
3. Select Container as the instance type, and select Standard Cluster Node as the instance object, then click Add Instance.
4. Click Add Now to add fault action.
5. Select the fault action Node Operation - Node Shutdown.
6. Set action parameters and click Confirm.
7. After action parameter configuration, click Next. Configure Guardrail Policy and Monitoring Metrics considering actual situations, click Submit to complete experiment creation.
Step 3: Execute the Experiment
1. View the node status before executing the fault.
2. Go to experiment details, click Go to the action group for execution.
3. Click Execute to start an experiment.
4. Click the Action Card, and check details of action execution.
5. View the execution logs to confirm it has been executed successfully.
6. View the node status after the fault execution. You can see that the node is in an abnormal status now. It indicates that the fault injection was successful, and the Pods under the cluster node are also running abnormally.
7. Execute the recovery actions, view the execution logs, and confirm that the recovery actions were successful.
8. After successful execution of the fault recovery action, view the status of the cluster node. You can see that the node is operating normally, and the Pods under the cluster node are also functioning properly, indicating that the fault has been successfully resolved.
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