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SkyDNS vs etcd: What are the differences?
### Introduction
In this Markdown code, we will highlight the key differences between SkyDNS and etcd.
1. **Functionality**: SkyDNS is a lightweight DNS server for Kubernetes that allows for service discovery within the cluster. It maps DNS names to Kubernetes services, making it easier for applications to locate and communicate with each other. On the other hand, etcd is a distributed key-value store used for shared configuration and service discovery across distributed systems. It provides a reliable way to store and manage critical data used by applications.
2. **Use Case**: SkyDNS is primarily used for DNS-based service discovery within Kubernetes clusters. It helps services locate each other by providing a DNS interface for easy communication. In contrast, etcd is more versatile and can be used for a wide range of use cases, including distributed coordination, leader election, and storing configuration data. It is not limited to a specific environment like SkyDNS.
3. **Consistency Model**: SkyDNS uses eventually consistent DNS records, which may introduce some latency in service discovery as changes propagate through the system. On the other hand, etcd provides strong consistency guarantees using the Raft consensus algorithm, ensuring that all nodes in the cluster have a consistent view of the data at all times. This makes etcd more suitable for critical data that requires strong consistency.
4. **Scalability**: SkyDNS is designed to scale horizontally by adding more instances to handle increased query loads and service discovery requests. However, it may not scale as seamlessly as etcd, which is built to be distributed and scalable out of the box. Etcd can handle large amounts of data and traffic efficiently across multiple nodes in a cluster.
5. **Data Model**: SkyDNS uses a simple key-value data model with DNS names mapped to Kubernetes services and endpoints. It is optimized for service discovery within Kubernetes clusters. In contrast, etcd supports complex data structures like directories, leasing, and watch capabilities, making it more flexible for various data storage and coordination tasks beyond just service discovery.
6. **Consensus Algorithm**: SkyDNS does not have its built-in consensus algorithm since its primary goal is to serve as a DNS server for service discovery. On the other hand, etcd uses the Raft consensus algorithm to ensure data consistency and fault tolerance in distributed systems. This makes etcd more suitable for critical data storage where consistency and fault tolerance are paramount.
In Summary, the key differences between SkyDNS and etcd lie in their functionality, use cases, consistency models, scalability, data models, and consensus algorithms.
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Learn MorePros of etcd
Pros of SkyDNS
Pros of etcd
- Service discovery11
- Fault tolerant key value store6
- Secure2
- Bundled with coreos2
- Consol integration1
- Privilege Access Management1
- Open Source1
Pros of SkyDNS
- Srv discovery for etcd2
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What is etcd?
etcd is a distributed key value store that provides a reliable way to store data across a cluster of machines. It’s open-source and available on GitHub. etcd gracefully handles master elections during network partitions and will tolerate machine failure, including the master.
What is SkyDNS?
SkyDNS is a distributed service for announcement and discovery of services. It leverages Raft for high-availability and consensus, and utilizes DNS queries to discover available services. This is done by leveraging SRV records in DNS, with special meaning given to subdomains, priorities and weights (more info here: http://blog.gopheracademy.com/skydns).
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What companies use etcd?
What companies use SkyDNS?
What companies use SkyDNS?
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What tools integrate with SkyDNS?
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What are some alternatives to etcd and SkyDNS?
Consul
Consul is a tool for service discovery and configuration. Consul is distributed, highly available, and extremely scalable.
Zookeeper
A centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services. All of these kinds of services are used in some form or another by distributed applications.
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Cassandra
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.