Etcd: Difference between revisions
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a | {{Infobox software | ||
| name = etcd | |||
{{ | | logo = <!-- No image available --> | ||
{{ | | developer = [[CoreOS]], [[Red Hat]], [[IBM]] | ||
| released = {{Start date and age|2013|07|24}} | |||
| latest release version = 3.5.0 | |||
| programming language = [[Go (programming language)|Go]] | |||
| operating system = [[Linux]], [[macOS]], [[Windows]] | |||
| platform = [[Cross-platform]] | |||
| genre = [[Distributed computing]], [[Key-value store]] | |||
| license = [[Apache License 2.0]] | |||
}} | |||
'''etcd''' is a distributed, reliable key-value store that is used to store data across a cluster of machines. It is designed to be a highly available and consistent store for configuration data, service discovery, and coordination of distributed systems. | |||
==Overview== | |||
Etcd is an open-source project originally developed by [[CoreOS]] and is now maintained by the [[Cloud Native Computing Foundation]]. It is written in the [[Go (programming language)|Go programming language]] and is designed to be simple, secure, and fast. Etcd is often used in [[container orchestration]] systems such as [[Kubernetes]] to store configuration data and manage service discovery. | |||
==Architecture== | |||
Etcd uses the [[Raft (algorithm)|Raft consensus algorithm]] to manage a highly available replicated log. This ensures that the data stored in etcd is consistent across all nodes in the cluster. The architecture of etcd is designed to handle network partitions and machine failures gracefully, ensuring that the system remains available and consistent. | |||
===Cluster=== | |||
An etcd cluster consists of multiple nodes, each of which can serve read and write requests. The cluster elects a leader node using the Raft algorithm, and all write requests are handled by this leader. The leader then replicates the changes to the follower nodes, ensuring consistency across the cluster. | |||
===Data Model=== | |||
Etcd uses a simple key-value data model. Keys are organized in a directory-like structure, allowing for hierarchical data organization. Each key can have a value, which is a byte array, and can be associated with metadata such as version and lease information. | |||
==Features== | |||
Etcd provides several features that make it suitable for use in distributed systems: | |||
* '''Consistency''': Etcd provides strong consistency guarantees using the Raft algorithm. | |||
* '''High Availability''': The system is designed to remain available even in the presence of node failures. | |||
* '''Watch''': Clients can watch for changes to keys and directories, allowing for real-time updates. | |||
* '''Transactions''': Etcd supports atomic transactions, allowing multiple operations to be executed as a single unit. | |||
* '''Authentication and Authorization''': Etcd includes mechanisms for securing access to data through authentication and role-based access control. | |||
==Use Cases== | |||
Etcd is commonly used in scenarios where distributed coordination and configuration management are required. Some common use cases include: | |||
* '''Service Discovery''': Etcd can be used to register and discover services in a distributed system. | |||
* '''Configuration Management''': Etcd can store configuration data that needs to be shared across multiple nodes. | |||
* '''Leader Election''': Etcd can be used to elect a leader in a distributed system, ensuring that only one node performs a critical task at a time. | |||
==Security== | |||
Etcd provides several security features to protect data and ensure secure communication between nodes: | |||
* '''Transport Layer Security (TLS)''': Etcd supports TLS for encrypting communication between clients and servers. | |||
* '''Role-Based Access Control (RBAC)''': Etcd allows administrators to define roles and permissions for accessing data. | |||
* '''Authentication''': Etcd supports basic authentication to verify the identity of clients. | |||
==Performance== | |||
Etcd is designed to be fast and efficient, with optimizations for both read and write operations. The performance of etcd can be affected by factors such as network latency, disk I/O, and the size of the data set. | |||
==Conclusion== | |||
Etcd is a critical component in many modern distributed systems, providing a reliable and consistent store for configuration data and service discovery. Its use of the Raft consensus algorithm ensures strong consistency and high availability, making it a popular choice for cloud-native applications. | |||
==See Also== | |||
* [[Kubernetes]] | |||
* [[Consul (software)]] | |||
* [[ZooKeeper]] | |||
==External Links== | |||
* [https://etcd.io/ Official etcd website] | |||
* [https://github.com/etcd-io/etcd etcd GitHub repository] | |||
{{Cloud computing}} | |||
{{Distributed computing}} | |||
[[Category:Distributed data stores]] | |||
[[Category:Free software]] | |||
[[Category:Cloud computing]] | |||
[[Category:Software using the Apache license]] | |||
Latest revision as of 21:27, 1 January 2025
etcd is a distributed, reliable key-value store that is used to store data across a cluster of machines. It is designed to be a highly available and consistent store for configuration data, service discovery, and coordination of distributed systems.
Overview[edit]
Etcd is an open-source project originally developed by CoreOS and is now maintained by the Cloud Native Computing Foundation. It is written in the Go programming language and is designed to be simple, secure, and fast. Etcd is often used in container orchestration systems such as Kubernetes to store configuration data and manage service discovery.
Architecture[edit]
Etcd uses the Raft consensus algorithm to manage a highly available replicated log. This ensures that the data stored in etcd is consistent across all nodes in the cluster. The architecture of etcd is designed to handle network partitions and machine failures gracefully, ensuring that the system remains available and consistent.
Cluster[edit]
An etcd cluster consists of multiple nodes, each of which can serve read and write requests. The cluster elects a leader node using the Raft algorithm, and all write requests are handled by this leader. The leader then replicates the changes to the follower nodes, ensuring consistency across the cluster.
Data Model[edit]
Etcd uses a simple key-value data model. Keys are organized in a directory-like structure, allowing for hierarchical data organization. Each key can have a value, which is a byte array, and can be associated with metadata such as version and lease information.
Features[edit]
Etcd provides several features that make it suitable for use in distributed systems:
- Consistency: Etcd provides strong consistency guarantees using the Raft algorithm.
- High Availability: The system is designed to remain available even in the presence of node failures.
- Watch: Clients can watch for changes to keys and directories, allowing for real-time updates.
- Transactions: Etcd supports atomic transactions, allowing multiple operations to be executed as a single unit.
- Authentication and Authorization: Etcd includes mechanisms for securing access to data through authentication and role-based access control.
Use Cases[edit]
Etcd is commonly used in scenarios where distributed coordination and configuration management are required. Some common use cases include:
- Service Discovery: Etcd can be used to register and discover services in a distributed system.
- Configuration Management: Etcd can store configuration data that needs to be shared across multiple nodes.
- Leader Election: Etcd can be used to elect a leader in a distributed system, ensuring that only one node performs a critical task at a time.
Security[edit]
Etcd provides several security features to protect data and ensure secure communication between nodes:
- Transport Layer Security (TLS): Etcd supports TLS for encrypting communication between clients and servers.
- Role-Based Access Control (RBAC): Etcd allows administrators to define roles and permissions for accessing data.
- Authentication: Etcd supports basic authentication to verify the identity of clients.
Performance[edit]
Etcd is designed to be fast and efficient, with optimizations for both read and write operations. The performance of etcd can be affected by factors such as network latency, disk I/O, and the size of the data set.
Conclusion[edit]
Etcd is a critical component in many modern distributed systems, providing a reliable and consistent store for configuration data and service discovery. Its use of the Raft consensus algorithm ensures strong consistency and high availability, making it a popular choice for cloud-native applications.
See Also[edit]
External Links[edit]
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