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  1. Stackups
  2. Application & Data
  3. Container Registry
  4. Container Tools
  5. AWS CodeDeploy vs Kubernetes

AWS CodeDeploy vs Kubernetes

OverviewDecisionsComparisonAlternatives

Overview

Kubernetes
Kubernetes
Stacks61.2K
Followers52.8K
Votes685
AWS CodeDeploy
AWS CodeDeploy
Stacks380
Followers624
Votes38

AWS CodeDeploy vs Kubernetes: What are the differences?

Introduction:

When comparing AWS CodeDeploy and Kubernetes, it is important to understand the key differences between these two popular deployment and management tools for containerized applications.

1. Scalability and Flexibility: AWS CodeDeploy is mainly focused on deploying applications to Amazon EC2 instances and on-premises servers, providing a simple and scalable solution for application deployment. On the other hand, Kubernetes offers greater flexibility and scalability by allowing developers to deploy containerized applications across a cluster of machines, automatically scaling resources based on the workload.

2. Orchestration Capabilities: Kubernetes excels in container orchestration, providing advanced features such as automated scheduling, scaling, and self-healing of containers. AWS CodeDeploy, while capable of managing deployments, does not offer the same level of orchestration capabilities as Kubernetes, making it more suitable for simpler deployment scenarios.

3. Resource Monitoring and Management: Kubernetes provides extensive resource monitoring and management tools, allowing users to track the performance of containers and adjust resource allocations accordingly. AWS CodeDeploy, on the other hand, focuses more on the deployment process itself and lacks the robust monitoring capabilities offered by Kubernetes.

4. Service Discovery and Load Balancing: Kubernetes includes built-in service discovery and load balancing features, making it easier for applications to communicate with each other and distribute incoming traffic across different pods. AWS CodeDeploy does not offer similar native capabilities for service discovery and load balancing, requiring additional configurations to achieve similar functionality.

5. Container Networking: Kubernetes provides a rich set of networking features, including container-to-container communication, service networking, and network policies for fine-grained control over traffic flow. In contrast, AWS CodeDeploy does not have built-in networking capabilities tailored for containerized environments, requiring users to rely on external solutions for networking configurations.

6. Vendor Lock-in: Using AWS CodeDeploy may lead to vendor lock-in as it is tightly integrated with the AWS ecosystem, making it challenging to migrate to a different cloud provider. Kubernetes, being open-source and cloud-agnostic, offers more flexibility in terms of deployment across various cloud platforms, reducing the risk of vendor lock-in.

Summary: In summary, Kubernetes provides advanced orchestration capabilities, extensive resource monitoring, and networking features, making it a preferred choice for managing containerized applications in complex environments. On the other hand, AWS CodeDeploy is more focused on simplified application deployment scenarios, offering scalability and ease of use within the AWS ecosystem.

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Advice on Kubernetes, AWS CodeDeploy

Simon
Simon

Senior Fullstack Developer at QUANTUSflow Software GmbH

Apr 27, 2020

DecidedonGitHubGitHubGitHub PagesGitHub PagesMarkdownMarkdown

Our whole DevOps stack consists of the following tools:

  • @{GitHub}|tool:27| (incl. @{GitHub Pages}|tool:683|/@{Markdown}|tool:1147| for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
  • Respectively @{Git}|tool:1046| as revision control system
  • @{SourceTree}|tool:1599| as @{Git}|tool:1046| GUI
  • @{Visual Studio Code}|tool:4202| as IDE
  • @{CircleCI}|tool:190| for continuous integration (automatize development process)
  • @{Prettier}|tool:7035| / @{TSLint}|tool:5561| / @{ESLint}|tool:3337| as code linter
  • @{SonarQube}|tool:2638| as quality gate
  • @{Docker}|tool:586| as container management (incl. @{Docker Compose}|tool:3136| for multi-container application management)
  • @{VirtualBox}|tool:774| for operating system simulation tests
  • @{Kubernetes}|tool:1885| as cluster management for docker containers
  • @{Heroku}|tool:133| for deploying in test environments
  • @{nginx}|tool:1052| as web server (preferably used as facade server in production environment)
  • @{SSLMate}|tool:2752| (using @{OpenSSL}|tool:3091|) for certificate management
  • @{Amazon EC2}|tool:18| (incl. @{Amazon S3}|tool:25|) for deploying in stage (production-like) and production environments
  • @{PostgreSQL}|tool:1028| as preferred database system
  • @{Redis}|tool:1031| as preferred in-memory database/store (great for caching)

The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

  • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
  • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
  • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
  • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
  • Scalability: All-in-one framework for distributed systems.
  • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
12.8M views12.8M
Comments
Anis
Anis

Founder at Odix

Nov 7, 2020

Review

I recommend this : -Spring reactive for back end : the fact it's reactive (async) it consumes half of the resources that a sync platform needs (so less CPU -> less money). -Angular : Web Front end ; it's gives you the possibility to use PWA which is a cheap replacement for a mobile app (but more less popular). -Docker images. -Kubernetes to orchestrate all the containers. -I Use Jenkins / blueocean, ansible for my CI/CD (with Github of course) -AWS of course : u can run a K8S cluster there, make it multi AZ (availability zones) to be highly available, use a load balancer and an auto scaler and ur good to go. -You can store data by taking any managed DB or u can deploy ur own (cheap but risky).

You pay less money, but u need some technical 2 - 3 guys to make that done.

Good luck

115k views115k
Comments
Michael
Michael

CEO at asencis Ltd

Jan 5, 2021

Needs advice

We develop rapidly with docker-compose orchestrated services, however, for production - we utilise the very best ideas that Kubernetes has to offer: SCALE! We can scale when needed, setting a maximum and minimum level of nodes for each application layer - scaling only when the load balancer needs it. This allowed us to reduce our devops costs by 40% whilst also maintaining an SLA of 99.87%.

272k views272k
Comments

Detailed Comparison

Kubernetes
Kubernetes
AWS CodeDeploy
AWS CodeDeploy

Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.

AWS CodeDeploy is a service that automates code deployments to Amazon EC2 instances. AWS CodeDeploy makes it easier for you to rapidly release new features, helps you avoid downtime during deployment, and handles the complexity of updating your applications.

Lightweight, simple and accessible;Built for a multi-cloud world, public, private or hybrid;Highly modular, designed so that all of its components are easily swappable
AWS CodeDeploy fully automates your code deployments, allowing you to deploy reliably and rapidly;AWS CodeDeploy helps maximize your application availability by performing rolling updates across your Amazon EC2 instances and tracking application health according to configurable rules;AWS CodeDeploy allows you to easily launch and track the status of your deployments through the AWS Management Console or the AWS CLI;AWS CodeDeploy is platform and language agnostic and works with any application. You can easily reuse your existing setup code
Statistics
Stacks
61.2K
Stacks
380
Followers
52.8K
Followers
624
Votes
685
Votes
38
Pros & Cons
Pros
  • 166
    Leading docker container management solution
  • 130
    Simple and powerful
  • 108
    Open source
  • 76
    Backed by google
  • 58
    The right abstractions
Cons
  • 16
    Steep learning curve
  • 15
    Poor workflow for development
  • 8
    Orchestrates only infrastructure
  • 4
    High resource requirements for on-prem clusters
  • 2
    Too heavy for simple systems
Pros
  • 17
    Automates code deployments
  • 9
    Backed by Amazon
  • 7
    Adds autoscaling lifecycle hooks
  • 5
    Git integration
Integrations
Vagrant
Vagrant
Docker
Docker
Rackspace Cloud Servers
Rackspace Cloud Servers
Microsoft Azure
Microsoft Azure
Google Compute Engine
Google Compute Engine
Ansible
Ansible
Google Kubernetes Engine
Google Kubernetes Engine
CircleCI
CircleCI
Codeship
Codeship
GitHub
GitHub
Jenkins
Jenkins
Solano CI
Solano CI
Travis CI
Travis CI
Amazon EC2
Amazon EC2
Ansible
Ansible
Chef
Chef
Puppet Labs
Puppet Labs

What are some alternatives to Kubernetes, AWS CodeDeploy?

Rancher

Rancher

Rancher is an open source container management platform that includes full distributions of Kubernetes, Apache Mesos and Docker Swarm, and makes it simple to operate container clusters on any cloud or infrastructure platform.

Docker Compose

Docker Compose

With Compose, you define a multi-container application in a single file, then spin your application up in a single command which does everything that needs to be done to get it running.

Docker Swarm

Docker Swarm

Swarm serves the standard Docker API, so any tool which already communicates with a Docker daemon can use Swarm to transparently scale to multiple hosts: Dokku, Compose, Krane, Deis, DockerUI, Shipyard, Drone, Jenkins... and, of course, the Docker client itself.

Tutum

Tutum

Tutum lets developers easily manage and run lightweight, portable, self-sufficient containers from any application. AWS-like control, Heroku-like ease. The same container that a developer builds and tests on a laptop can run at scale in Tutum.

Portainer

Portainer

It is a universal container management tool. It works with Kubernetes, Docker, Docker Swarm and Azure ACI. It allows you to manage containers without needing to know platform-specific code.

Octopus Deploy

Octopus Deploy

Octopus Deploy helps teams to manage releases, automate deployments, and operate applications with automated runbooks. It's free for small teams.

Codefresh

Codefresh

Automate and parallelize testing. Codefresh allows teams to spin up on-demand compositions to run unit and integration tests as part of the continuous integration process. Jenkins integration allows more complex pipelines.

Distelli

Distelli

Build, test, and deploy your code from GitHub and BitBucket (or no repository at all) to any server in the world regardless of provider. Distelli customers iterate and ship faster with complete transparency.

CAST.AI

CAST.AI

It is an AI-driven cloud optimization platform for Kubernetes. Instantly cut your cloud bill, prevent downtime, and 10X the power of DevOps.

k3s

k3s

Certified Kubernetes distribution designed for production workloads in unattended, resource-constrained, remote locations or inside IoT appliances. Supports something as small as a Raspberry Pi or as large as an AWS a1.4xlarge 32GiB server.

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