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Kubernetes vs Terraform: What are the differences?

Introduction

Kubernetes and Terraform are two popular tools used in the field of infrastructure management and deployment. While both serve different purposes, they have some key differences that set them apart from each other. In this article, we will explore the main differences between Kubernetes and Terraform.

  1. Architecture and Purpose: Kubernetes is an open-source container orchestration platform that is used for automating, scaling, and managing containerized applications. It provides a framework for deploying and managing containerized applications across a cluster of nodes. On the other hand, Terraform is an open-source infrastructure as code tool that is used for provisioning and managing infrastructure resources (such as virtual machines, networks, and storage) in a declarative manner.

  2. Abstraction Level: Kubernetes operates at a higher level of abstraction compared to Terraform. Kubernetes focuses on managing and orchestrating containers in a cluster, abstracting away the underlying infrastructure details. Terraform, on the other hand, provides a more low-level control over infrastructure resources, allowing users to define their infrastructure in detail.

  3. Focus on Scalability: Kubernetes is designed specifically for managing applications at scale. It provides features such as automatic scaling, load balancing, and service discovery, which are essential for running large-scale applications. Terraform, while it can be used for managing infrastructure at scale, does not have the same level of built-in scalability features as Kubernetes.

  4. Support for Multi-Cloud and Hybrid Environments: Kubernetes is cloud-agnostic and can be deployed across various cloud providers or in on-premises environments. It provides the ability to create hybrid or multi-cloud setups, where applications can be run across different cloud providers or a combination of cloud and on-premises infrastructure. Terraform also supports multi-cloud and hybrid environments, allowing users to define their infrastructure using a single configuration syntax that can be applied to different cloud providers.

  5. Granularity of Control: Terraform provides fine-grained control over infrastructure resources, allowing users to define and manage individual resources and their dependencies. Users can define complex resource relationships and specify resource attributes in detail. Kubernetes, on the other hand, focuses on managing applications as a whole and provides a higher level of abstraction, abstracting away the individual resources that make up an application.

  6. Community and Ecosystem: Kubernetes has a large and vibrant community with a rich ecosystem of tools and extensions. It has become the de facto standard for container orchestration and has a wide range of community-supported tools and integrations. Terraform also has a strong community and ecosystem, with a wide range of providers and modules available for different infrastructure resources.

In summary, Kubernetes is a container orchestration platform designed for managing containerized applications at scale, while Terraform is an infrastructure as code tool focused on provisioning and managing infrastructure resources. Kubernetes provides a higher level of abstraction and scalability features, while Terraform offers fine-grained control and supports multi-cloud and hybrid environments. Both tools have strong communities and ecosystems supporting them.

Decisions about Kubernetes and Terraform

Because Pulumi uses real programming languages, you can actually write abstractions for your infrastructure code, which is incredibly empowering. You still 'describe' your desired state, but by having a programming language at your fingers, you can factor out patterns, and package it up for easier consumption.

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Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 11M views

Our whole DevOps stack consists of the following tools:

  • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
  • Respectively Git as revision control system
  • SourceTree as Git GUI
  • Visual Studio Code as IDE
  • CircleCI for continuous integration (automatize development process)
  • Prettier / TSLint / ESLint as code linter
  • SonarQube as quality gate
  • Docker as container management (incl. Docker Compose for multi-container application management)
  • VirtualBox for operating system simulation tests
  • Kubernetes as cluster management for docker containers
  • Heroku for deploying in test environments
  • nginx as web server (preferably used as facade server in production environment)
  • SSLMate (using OpenSSL) for certificate management
  • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
  • PostgreSQL as preferred database system
  • Redis 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.
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Sergey Ivanov
Overview

We use Terraform to manage AWS cloud environment for the project. It is pretty complex, largely static, security-focused, and constantly evolving.

Terraform provides descriptive (declarative) way of defining the target configuration, where it can work out the dependencies between configuration elements and apply differences without re-provisioning the entire cloud stack.

Advantages

Terraform is vendor-neutral in a way that it is using a common configuration language (HCL) with plugins (providers) for multiple cloud and service providers.

Terraform keeps track of the previous state of the deployment and applies incremental changes, resulting in faster deployment times.

Terraform allows us to share reusable modules between projects. We have built an impressive library of modules internally, which makes it very easy to assemble a new project from pre-fabricated building blocks.

Disadvantages

Software is imperfect, and Terraform is no exception. Occasionally we hit annoying bugs that we have to work around. The interaction with any underlying APIs is encapsulated inside 3rd party Terraform providers, and any bug fixes or new features require a provider release. Some providers have very poor coverage of the underlying APIs.

Terraform is not great for managing highly dynamic parts of cloud environments. That part is better delegated to other tools or scripts.

Terraform state may go out of sync with the target environment or with the source configuration, which often results in painful reconciliation.

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I personally am not a huge fan of vendor lock in for multiple reasons:

  • I've seen cost saving moves to the cloud end up costing a fortune and trapping companies due to over utilization of cloud specific features.
  • I've seen S3 failures nearly take down half the internet.
  • I've seen companies get stuck in the cloud because they aren't built cloud agnostic.

I choose to use terraform for my cloud provisioning for these reasons:

  • It's cloud agnostic so I can use it no matter where I am.
  • It isn't difficult to use and uses a relatively easy to read language.
  • It tests infrastructure before running it, and enables me to see and keep changes up to date.
  • It runs from the same CLI I do most of my CM work from.
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Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.

Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!

Check Out My Architecture: CLICK ME

Check out the GitHub repo attached

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Pros of Kubernetes
Pros of Terraform
  • 166
    Leading docker container management solution
  • 129
    Simple and powerful
  • 107
    Open source
  • 76
    Backed by google
  • 58
    The right abstractions
  • 25
    Scale services
  • 20
    Replication controller
  • 11
    Permission managment
  • 9
    Supports autoscaling
  • 8
    Simple
  • 8
    Cheap
  • 6
    Self-healing
  • 5
    Open, powerful, stable
  • 5
    Reliable
  • 5
    No cloud platform lock-in
  • 5
    Promotes modern/good infrascture practice
  • 4
    Scalable
  • 4
    Quick cloud setup
  • 3
    Custom and extensibility
  • 3
    Captain of Container Ship
  • 3
    Cloud Agnostic
  • 3
    Backed by Red Hat
  • 3
    Runs on azure
  • 3
    A self healing environment with rich metadata
  • 2
    Everything of CaaS
  • 2
    Gke
  • 2
    Golang
  • 2
    Easy setup
  • 2
    Expandable
  • 2
    Sfg
  • 121
    Infrastructure as code
  • 73
    Declarative syntax
  • 45
    Planning
  • 28
    Simple
  • 24
    Parallelism
  • 8
    Well-documented
  • 8
    Cloud agnostic
  • 6
    It's like coding your infrastructure in simple English
  • 6
    Immutable infrastructure
  • 5
    Platform agnostic
  • 4
    Extendable
  • 4
    Automation
  • 4
    Automates infrastructure deployments
  • 4
    Portability
  • 2
    Lightweight
  • 2
    Scales to hundreds of hosts

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Cons of Kubernetes
Cons of Terraform
  • 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
  • 1
    Additional vendor lock-in (Docker)
  • 1
    More moving parts to secure
  • 1
    Additional Technology Overhead
  • 1
    Doesn't have full support to GKE

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What is Kubernetes?

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.

What is Terraform?

With Terraform, you describe your complete infrastructure as code, even as it spans multiple service providers. Your servers may come from AWS, your DNS may come from CloudFlare, and your database may come from Heroku. Terraform will build all these resources across all these providers in parallel.

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What companies use Kubernetes?
What companies use Terraform?
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What are some alternatives to Kubernetes and Terraform?
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.
Nomad
Nomad is a cluster manager, designed for both long lived services and short lived batch processing workloads. Developers use a declarative job specification to submit work, and Nomad ensures constraints are satisfied and resource utilization is optimized by efficient task packing. Nomad supports all major operating systems and virtualized, containerized, or standalone applications.
OpenStack
OpenStack is a cloud operating system that controls large pools of compute, storage, and networking resources throughout a datacenter, all managed through a dashboard that gives administrators control while empowering their users to provision resources through a web interface.
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
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.
See all alternatives