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Kubernetes (k8s) is a container orchestration platform that allows applications and services to be run in containers. Learn about etcd today.
I hope this article will not only give you some gains, but also enjoy learning. If you have any suggestions, you can leave a message and communicate with me.
Column introduction
This is the column where this article is located, welcome to subscribe: [In-depth analysis of k8s] column
Briefly introduce what this column will do:
It is mainly to deeply analyze each knowledge point and help everyone fully master k8s. The following are the updated chapters
| serial number | article |
| first lecture | In-depth analysis of k8s: getting started guide (1) |
| second lecture | In-depth analysis of k8s: getting started guide (2) |
| third lecture | In-depth analysis of Pod objects (1) |
| fourth lecture | In-depth analysis of Pod objects (2) |
| fifth lecture | In-depth analysis of stateless services |
| Lecture Six | In-depth analysis of stateful services |
| Seventh lecture | In-depth analysis of the controller |
| eighth lecture |
In-depth analysis of ReplicaSet |
| Lecture 9 | In-depth analysis of rolling upgrade |
| tenth lecture | In-depth analysis of StatefulSet (1) |
| Eleventh lecture | In-depth analysis of StatefulSet (2) |
| Lecture 12 | In-depth analysis of DaemonSet |
| Lecture Thirteen | In-depth analysis of Job |
1 Basic introduction
1.1 Concept introduction
Kubernetes (K8s for short) is an open source container orchestration platform for automating the deployment, scaling, and management of containerized applications . In Kubernetes, etcd is a key component used to store all configuration data and state information in the Kubernetes cluster.
This article will introduce the concept, advantages, principles and usage of etcd.
etcd
etcd is a distributed, high-availability key-value storage system developed by CoreOS and open-sourced. It uses the Raft algorithm to guarantee its high availability and consistency, and can be deployed on multiple nodes in the cluster. Each etcd node contains a complete copy of the data and is replicated and synchronized with other nodes to ensure data consistency and availability.
In Kubernetes, etcd stores all Kubernetes objects (such as Pod, Service, Deployment, etc.) and cluster status information. Various components of Kubernetes (such as API Server, Controller Manager, Scheduler, etc.) communicate and coordinate through etcd.
1.2 Introduction of advantages
etcd has the following advantages:
High availability : etcd uses the Raft algorithm to implement distributed, high-availability storage, which can be deployed on multiple nodes in the cluster to ensure data availability and consistency.
Reliability : etcd can store data persistently and use multi-version control to ensure data consistency and reliability.
Ease of use : etcd provides a simple REST API and command line tools, making data reading, writing and management very simple and easy to use.
1.3 Principle Introduction
Some key principles of etcd include:
Data model : The data model in etcd is based on key-value pairs . Each key-value pair consists of a unique key and a corresponding value . In Kubernetes, etcd stores all Kubernetes objects (such as Pod, Service, Deployment, etc.) and cluster status information.
Distributed storage : etcd uses the Raft algorithm to implement distributed, high-availability storage , which can be deployed on multiple nodes in the cluster to ensure data availability and consistency. Each etcd node contains a complete copy of the data and is replicated and synchronized with other nodes to ensure data consistency and availability. When a node in the cluster fails, etcd can automatically re-elect a new master node to ensure data availability and consistency.
Consistency protocol : etcd uses the Raft algorithm to ensure data consistency and availability . The Raft algorithm is a distributed consensus algorithm for achieving consistency and availability in distributed systems. The Raft algorithm divides the etcd cluster into multiple nodes, one of which acts as a leader (leader) , responsible for processing all client requests, and replicating write operations to other replica nodes. When the leader node fails, other nodes will re-elect a new leader node.
Snapshots and recovery : etcd uses a snapshot mechanism to periodically back up data and uses snapshots to speed up the recovery process. When an etcd node starts up, it restores data from snapshots stored on local disk to quickly re-establish the cluster state.
Extended-Raft algorithm:
The Raft algorithm is a distributed consensus algorithm used to ensure that the data of all nodes in a distributed system remains consistent . It was proposed by distributed system researchers Ongaro and Ousterhout in 2014 to replace the Paxos algorithm.
The Raft algorithm mainly includes three steps:
- election
- log replication
- vote
election
The Raft algorithm uses a process called "election" to select a leader who maintains data consistency.
During the election process, each node sends a vote request, and other nodes receive and reply with votes .
If a node receives votes from a majority of nodes, that node becomes the leader.
log replication
After the election process is over, the leader will start the log replication process , i.e. sync new data to all nodes.
During log replication, the leader will send new data to other nodes, and the other nodes will receive and add the new data to their own log.
vote
After the log replication process is over, the Raft algorithm will use voting to determine which node is the leader.
Each node sends a vote request, and other nodes receive and reply with votes. If a node receives votes from a majority of nodes, that node becomes the leader.
2 Introduction
To use etcd, you need to understand the following aspects:
Install etcd : You can download the etcd binary from the official website and install it, or you can run etcd through a Docker container.
Start the etcd cluster : You can start the etcd cluster through the etcdctl command line tool or API.
Data reading and writing : You can use the etcdctl command line tool or API to read and write data in etcd. For example, you can use the etcdctl get command to get a value stored in etcd, and use the etcdctl put command to store a value in etcd.
Cluster management : You can use etcdctl command line tool or API to manage etcd cluster. For example, you can use the etcdctl member command to list the member nodes in the cluster.
3 Role in Kubernetes
It can be used to store all configuration data in a Kubernetes cluster , including:
- service discovery
- distributed locking
- cluster scheduling
- high availability
- Store resource state : facilitate communication between components in the Kubernetes cluster, and achieve high availability to ensure the availability of the Kubernetes cluster
- Tracking Cluster Status : Facilitates detecting errors and failures, and tracking user requests so that the Kubernetes cluster can respond correctly.
All the metadata required for functions such as , thus ensuring the availability of Kubernetes clusters.
4 Summary
In Kubernetes, etcd is a key component , so there are some usage considerations to be aware of.
For example, instead of directly modifying Kubernetes objects stored in etcd, you should do so through the Kubernetes API Server.
Additionally, to ensure high availability and consistency of etcd, multiple etcd nodes should be used in a Kubernetes cluster and properly configured and managed.
In short, etcd is a very important component in Kubernetes, which is responsible for storing all configuration data and status information of the Kubernetes cluster .
Understanding the concepts, advantages, principles and usage of etcd is very important for learning and using Kubernetes.
Summarize etcd in one sentence:
etcd is a persistent distributed key-value store that can be used to store all configuration data in a Kubernetes cluster.
etcd will stop here today, see you next time
