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  1. Stackups
  2. DevOps
  3. Version Control
  4. Version Control System
  5. AWS Elastic Load Balancing (ELB) vs Git

AWS Elastic Load Balancing (ELB) vs Git

OverviewComparisonAlternatives

Overview

Git
Git
Stacks343.7K
Followers184.2K
Votes6.6K
GitHub Stars57.1K
Forks26.9K
AWS Elastic Load Balancing (ELB)
AWS Elastic Load Balancing (ELB)
Stacks12.8K
Followers8.8K
Votes59

AWS Elastic Load Balancing (ELB) vs Git: What are the differences?

Developers describe AWS Elastic Load Balancing (ELB) as "Automatically distribute your incoming application traffic across multiple Amazon EC2 instances". With Elastic Load Balancing, you can add and remove EC2 instances as your needs change without disrupting the overall flow of information. If one EC2 instance fails, Elastic Load Balancing automatically reroutes the traffic to the remaining running EC2 instances. If the failed EC2 instance is restored, Elastic Load Balancing restores the traffic to that instance. Elastic Load Balancing offers clients a single point of contact, and it can also serve as the first line of defense against attacks on your network. You can offload the work of encryption and decryption to Elastic Load Balancing, so your servers can focus on their main task. On the other hand, Git is detailed as "Fast, scalable, distributed revision control system". Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency.

AWS Elastic Load Balancing (ELB) belongs to "Load Balancer / Reverse Proxy" category of the tech stack, while Git can be primarily classified under "Version Control System".

"Easy" is the primary reason why developers consider AWS Elastic Load Balancing (ELB) over the competitors, whereas "Distributed version control system" was stated as the key factor in picking Git.

Git is an open source tool with 28.2K GitHub stars and 16.3K GitHub forks. Here's a link to Git's open source repository on GitHub.

According to the StackShare community, Git has a broader approval, being mentioned in 3932 company stacks & 4778 developers stacks; compared to AWS Elastic Load Balancing (ELB), which is listed in 723 company stacks and 314 developer stacks.

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Detailed Comparison

Git
Git
AWS Elastic Load Balancing (ELB)
AWS Elastic Load Balancing (ELB)

Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency.

With Elastic Load Balancing, you can add and remove EC2 instances as your needs change without disrupting the overall flow of information. If one EC2 instance fails, Elastic Load Balancing automatically reroutes the traffic to the remaining running EC2 instances. If the failed EC2 instance is restored, Elastic Load Balancing restores the traffic to that instance. Elastic Load Balancing offers clients a single point of contact, and it can also serve as the first line of defense against attacks on your network. You can offload the work of encryption and decryption to Elastic Load Balancing, so your servers can focus on their main task.

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Distribution of requests to Amazon EC2 instances (servers) in multiple Availability Zones so that the risk of overloading one single instance is minimized. And if an entire Availability Zone goes offline, Elastic Load Balancing routes traffic to instances in other Availability Zones.;Continuous monitoring of the health of Amazon EC2 instances registered with the load balancer so that requests are sent only to the healthy instances. If an instance becomes unhealthy, Elastic Load Balancing stops sending traffic to that instance and spreads the load across the remaining healthy instances.;Support for end-to-end traffic encryption on those networks that use secure (HTTPS/SSL) connections.;The ability to take over the encryption and decryption work from the Amazon EC2 instances, and manage it centrally on the load balancer.;Support for the sticky session feature, which is the ability to "stick" user sessions to specific Amazon EC2 instances.;Association of the load balancer with your domain name. Because the load balancer is the only computer that is exposed to the Internet, you don’t have to create and manage public domain names for the instances that the load balancer manages. You can point the instance's domain records at the load balancer instead and scale as needed (either adding or removing capacity) without having to update the records with each scaling activity.;When used in an Amazon Virtual Private Cloud (Amazon VPC), support for creation and management of security groups associated with your load balancer to provide additional networking and security options.;Supports use of both the Internet Protocol version 4 (IPv4) and Internet Protocol version 6 (IPv6).
Statistics
GitHub Stars
57.1K
GitHub Stars
-
GitHub Forks
26.9K
GitHub Forks
-
Stacks
343.7K
Stacks
12.8K
Followers
184.2K
Followers
8.8K
Votes
6.6K
Votes
59
Pros & Cons
Pros
  • 1429
    Distributed version control system
  • 1053
    Efficient branching and merging
  • 959
    Fast
  • 843
    Open source
  • 726
    Better than svn
Cons
  • 16
    Hard to learn
  • 11
    Inconsistent command line interface
  • 9
    Easy to lose uncommitted work
  • 8
    Worst documentation ever possibly made
  • 5
    Awful merge handling
Pros
  • 48
    Easy
  • 8
    ASG integration
  • 2
    Reliability
  • 1
    Coding
  • 0
    SSL offloading
Integrations
No integrations available
Amazon EC2
Amazon EC2

What are some alternatives to Git, AWS Elastic Load Balancing (ELB)?

HAProxy

HAProxy

HAProxy (High Availability Proxy) is a free, very fast and reliable solution offering high availability, load balancing, and proxying for TCP and HTTP-based applications.

Mercurial

Mercurial

Mercurial is dedicated to speed and efficiency with a sane user interface. It is written in Python. Mercurial's implementation and data structures are designed to be fast. You can generate diffs between revisions, or jump back in time within seconds.

Traefik

Traefik

A modern HTTP reverse proxy and load balancer that makes deploying microservices easy. Traefik integrates with your existing infrastructure components and configures itself automatically and dynamically.

SVN (Subversion)

SVN (Subversion)

Subversion exists to be universally recognized and adopted as an open-source, centralized version control system characterized by its reliability as a safe haven for valuable data; the simplicity of its model and usage; and its ability to support the needs of a wide variety of users and projects, from individuals to large-scale enterprise operations.

Plastic SCM

Plastic SCM

Plastic SCM is a distributed version control designed for big projects. It excels on branching and merging, graphical user interfaces, and can also deal with large files and even file-locking (great for game devs). It includes "semantic" features like refactor detection to ease diffing complex refactors.

Fly

Fly

Deploy apps through our global load balancer with minimal shenanigans. All Fly-enabled applications get free SSL certificates, accept traffic through our global network of datacenters, and encrypt all traffic from visitors through to application servers.

Pijul

Pijul

Pijul is a free and open source (AGPL 3) distributed version control system. Its distinctive feature is to be based on a sound theory of patches, which makes it easy to learn and use, and really distributed.

Envoy

Envoy

Originally built at Lyft, Envoy is a high performance C++ distributed proxy designed for single services and applications, as well as a communication bus and “universal data plane” designed for large microservice “service mesh” architectures.

Hipache

Hipache

Hipache is a distributed proxy designed to route high volumes of http and websocket traffic to unusually large numbers of virtual hosts, in a highly dynamic topology where backends are added and removed several times per second. It is particularly well-suited for PaaS (platform-as-a-service) and other environments that are both business-critical and multi-tenant.

DVC

DVC

It is an open-source Version Control System for data science and machine learning projects. It is designed to handle large files, data sets, machine learning models, and metrics as well as code.

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