- Product Overview
- Purchase Guide
- 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
- Big Data
- Cloud Load Balancer
- Message Queue
- Direct Connect
- Custom Actions
- Cloud Streaming Services (CSS)
- Compute
- Permission Management Guide
- API Documentation
- FAQs
- Related Protocol
- Contact Us
- Product Overview
- Purchase Guide
- 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
- Big Data
- Cloud Load Balancer
- Message Queue
- Direct Connect
- Custom Actions
- Cloud Streaming Services (CSS)
- Compute
- Permission Management Guide
- API Documentation
- FAQs
- Related Protocol
- Contact Us
Overview
Last updated: 2024-09-26 15:34:19
Tencent Smart Advisor-Chaotic Fault Generator (CFG) provides efficient, convenient, safe, and reliable fault injection services. In addition, it also provides industry templates, monitoring guardrails, and other core functions, and is committed to helping users promptly discover business disaster recovery risks and verify the effectiveness of high-availability plans, thereby improving system availability and resilience.
Basic Concepts
Before use of the CFG, understanding the relevant concepts will help you get started with product operations faster.
Concept | Description | Example |
Chaos engineering | Chaos engineering is a discipline that conducts experiments on distributed systems. It updates the understanding of the system through practice, thereby understanding and discovering the unknown weaknesses of the system. The purpose is to build the ability and confidence of the system to resist out-of-control conditions in the production environment. | - |
Experiment | The process of verifying and improving system availability by injecting specified faults into specified locations of the system and observing the experimental results. | - |
Action | It refers to the atomic fault actions injected into the system during the experiment, including various fault injection scenes of IaaS, PaaS, and SaaS. In an experiment, users can freely combine and orchestrate multiple experiment actions. An action group is a collection of actions. | High CPU usage, CVM shutdown, and database primary/secondary switch |
Object | The instance object that the action acts on. | CVM and MySQL |
Template | Save valuable and frequently used experiments and scenes as experiment templates for quick reuse later. The templates include basic experiment information and action orchestration solution, and you only need to determine the experiment object for subsequent use. | Cross-AZ disaster recovery experiment template and network fault template |
Monitoring metrics | To determine whether the system is running stably and whether the fault injection is successful, the system steady-state metrics can be configured in advance to observe changes in steady-state metrics during experiments, perceiving system changes in real time. | Disk usage (%) |
Guardrail policy | Configure alarm metrics and trigger policies. When the alarm metrics reach the trigger threshold, the system can automatically stop the experiment and roll back the action to control the impact scope of the experiment. | If the disk usage (%) reaches 90%, the experiment will automatically stop. |
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