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  1. Stackups
  2. Utilities
  3. API Tools
  4. Service Discovery
  5. Baker Street vs SkyDNS

Baker Street vs SkyDNS

OverviewComparisonAlternatives

Overview

SkyDNS
SkyDNS
Stacks8
Followers23
Votes2
GitHub Stars2.2K
Forks304
Baker Street
Baker Street
Stacks0
Followers12
Votes0
GitHub Stars226
Forks18

Baker Street vs SkyDNS: What are the differences?

What is Baker Street? A simple client-side load balancer for microservices. Baker Street is an HAProxy-based client side load balancer that simplifies scaling, testing, and upgrading microservices.

What is SkyDNS? Distributed service for announcement and discovery of services. 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).

Baker Street and SkyDNS can be primarily classified as "Open Source Service Discovery" tools.

Some of the features offered by Baker Street are:

  • automatically splitting traffic among all healthy services sharing the same name in the system
  • making load balancing more efficient and robust by using local load balancers
  • removing problematic instances from the rotation more quickly by using local health checkers

On the other hand, SkyDNS provides the following key features:

  • You announce your service by submitting JSON over HTTP to SkyDNS with information about your service. This information will then be available for queries either via DNS or HTTP.
  • SkyDNS requires that services submit an HTTP request to update their TTL within the TTL they last supplied. If the service fails to do so within this timeframe SkyDNS will expire the service automatically. This will allow for nodes to fail and DNS to reflect this quickly.
  • You can find services by querying SkyDNS via any DNS client or utility. It uses a known domain syntax with wildcards to find matching services.

Baker Street and SkyDNS are both open source tools. It seems that SkyDNS with 1.97K GitHub stars and 301 forks on GitHub has more adoption than Baker Street with 222 GitHub stars and 16 GitHub forks.

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Detailed Comparison

SkyDNS
SkyDNS
Baker Street
Baker Street

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).

Baker Street is an HAProxy-based client side load balancer that simplifies scaling, testing, and upgrading microservices.

You announce your service by submitting JSON over HTTP to SkyDNS with information about your service. This information will then be available for queries either via DNS or HTTP.;SkyDNS requires that services submit an HTTP request to update their TTL within the TTL they last supplied. If the service fails to do so within this timeframe SkyDNS will expire the service automatically. This will allow for nodes to fail and DNS to reflect this quickly.;You can find services by querying SkyDNS via any DNS client or utility. It uses a known domain syntax with wildcards to find matching services.
automatically splitting traffic among all healthy services sharing the same name in the system;making load balancing more efficient and robust by using local load balancers;removing problematic instances from the rotation more quickly by using local health checkers
Statistics
GitHub Stars
2.2K
GitHub Stars
226
GitHub Forks
304
GitHub Forks
18
Stacks
8
Stacks
0
Followers
23
Followers
12
Votes
2
Votes
0
Pros & Cons
Pros
  • 2
    Srv discovery for etcd
No community feedback yet

What are some alternatives to SkyDNS, Baker Street?

Consul

Consul

Consul is a tool for service discovery and configuration. Consul is distributed, highly available, and extremely scalable.

Eureka

Eureka

Eureka is a REST (Representational State Transfer) based service that is primarily used in the AWS cloud for locating services for the purpose of load balancing and failover of middle-tier servers.

Zookeeper

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.

etcd

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.

Keepalived

Keepalived

The main goal of this project is to provide simple and robust facilities for loadbalancing and high-availability to Linux system and Linux based infrastructures.

SmartStack

SmartStack

Scaling a web infrastructure requires services, and building a service-oriented infrastructure is hard. Make it EASY, with SmartStack’s automated, transparent service discovery and registration: cruise control for your distributed infrastructure.

Serf

Serf

Serf is a service discovery and orchestration tool that is decentralized, highly available, and fault tolerant. Serf runs on every major platform: Linux, Mac OS X, and Windows. It is extremely lightweight: it uses 5 to 10 MB of resident memory and primarily communicates using infrequent UDP messages.

Nacos

Nacos

It is an easy-to-use dynamic service discovery, configuration and service management platform for building cloud native applications.

Libraries.io

Libraries.io

It is an open source web service that lists software development project dependencies and alerts developers to new versions of the software libraries they are using.

ODD Platform

ODD Platform

It is a next-generation data discovery and observability tool for enterprises and startups that help to efficiently democratize data, powers collaboration of data science and data engineering teams, significantly reduces time to data discovery, cuts on data downtime and offers a modern, easy-to-use environment with quick time-to-value. It makes all your data entities reliable, observable, and easily discoverable.

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