Automating software development has been a key concept. Automating infrastructure reduces configuration changes and eliminates human error risk. It also provides transparency for all project teams.
Launching a new product or improving an existing infrastructure can be difficult without automation. However, there are many automation tools that can make your project’s lifecycle easier.
This article will focus on two of the most popular automation tools, Terraform and Kubernetes, and their key differences.
Terraform is an open-source software program that allows us safely and predictably manage large-scale infrastructure using infrastructure as code and cloud-agnostic principles. This powerful tool was developed by Hashicorp and allows infrastructure provisioning on-premises or in the cloud.
Terraform is written using a declarative configuration language called Hashicorp Configuration Language (HCL). This allows for the automation of infrastructure management in any environment. In addition, it enables IT professionals to work together and safely make changes to cloud environments and scale them according to business requirements.
Modules offer great reusability and code-sharing opportunities to increase collaboration and productivity in teams that work on the cloud. Providers are plugins that allow for interaction and integration with various APIs. They are one of the most important ways to expand Terraform’s functionality.
Terraform maintains an internal state of managed infrastructure. This includes resources, configuration, metadata, and their relationships. Terraform actively maintains the state and uses it to plan, track changes and modify infrastructure environments. To facilitate teamwork and collaboration, the state should be kept remote.
Three concrete steps make up the core Terraform workflow. The first is generating the infrastructure code configuration files representing our desired environment. Then, we verify that the plan generated is consistent with our manifests. After reviewing all changes carefully, we apply the plan for provisioning infrastructure resources.
Kubernetes (K8s), an open-source platform for container orchestration, automating deployments, and managing containerized applications, is available. The powerful orchestration system allows applications to scale easily and attain high availability. Google developed it based on its extensive experience working with critical production workloads.
Kubernetes is cloud-agnostic, allowing great flexibility when running workloads in both cloud and on-premises environments. It is also extensible, allowing you to easily add features or custom tooling to your clusters.
Its self-healing capabilities are one of its greatest benefits. Failures in containers are automatically restarted and rescheduled. Nodes can be set to replace nodes automatically, and traffic is only served by healthy components that have passed health checks.
Rollouts can be handled in stages, and Kubernetes has smart mechanisms that monitor the health of applications during deployments. If the application health does not report a healthy state after a deployment, rolling back any problematic changes is done automatically.
Over the years, Kubernetes has seen a lot of discussion about how to keep the application running while releasing new software versions. There are many deployment options.
Kubernetes manages service discovery and load-balancing traffic between pods that are similar. It does not require complex external solutions.
You can extend the built-in mechanisms it provides to manage configurations and secrets for your apps. In addition, it makes scaling your applications easy with its autoscaling options and command-based scaling.
Multi-cloud deployments are possible with multiple resources
Helps avoid downtime
Facilitates the recording, tracking, management, and reporting of changes
Feature declarative syntax
Comprehensive and easily readable documentation
Cons of Terraform 👎
It doesn’t fully support GKE (Google Kubernetes Engine)
It doesn’t have error handling
There is no rollback. If the need arises, users must destroy the managed object and then re-apply it
Bugs are common in new releases
Pros and Cons of Kubernetes
Pros of Kubernetes 👍
Resource-friendly – allows horizontal scaling of infrastructure
It prevents infrastructure lock-ins
Feature declarative syntax
Automates healing by monitoring replicas and making certain that the system is always healthy
Google-backed, leading container management tool with extensive documentation
Cons of Kubernetes 👎
It is difficult to master
Only infrastructure orchestration is possible
It may be necessary to adjust workflows to introduce K8s into an organization
Terraform vs. Kubernetes
Both these modern technologies share many similarities, but they also have fundamental differences. Let’s take a closer look at some of them.
Terraform and Kubernetes is different in that they have different goals and solve different problems. Terraform is focused on provisioning infrastructure components and targets infrastructure as code. Kubernetes is designed to allow us to run container workloads and target the container orchestration area.
Terraform defines declarative objects using Hashicorp Configuration Language (or HCL). You can create resources that run on multiple cloud platforms by using an HCL file.
Kubernetes defines declarative objects in YAML and JSON files. These files are used to demonstrate how to manage Kubernetes objects. YAML is preferable to JSON when writing configuration files, but they can be used interchangeably.
Terraform’s workflow is easy to use and offers a welcoming experience for new users. However, to run applications in Kubernetes efficiently, one must understand many of the cluster’s internal components and mechanics. It is usually more difficult for new users to get to grips with Kubernetes.
Planning Phase & Configuration Drift
Terraform is a tool that allows you to identify and notify about configuration drift. It does this by using the planning phase of the standard workflow. Kubernetes, on the other hand, doesn’t provide this functionality.
Terraform CLI provides a command-line interface to Terraform. It supports switches and subcommands such as terraform plan and terraform application. Terraform uses the CLI for commands to execute and manage declarative configurations to create any resources.
Kubernetes comes with its command line tool to manage Kubernetes resource clusters. Kubectl can create resources, such as allocating memory and CPU to containers and creating nodes. It also allows you the ability to deploy applications.
Here is a comparison between Kubernetes vs. Terraform:
Open-source container orchestration system
Open-source, infrastructure as code, software tool
Initial release date: 9 September 2014
Initial release date: 28 July 2014
Developer: Google, Rancher Labs, Cloud Native Computing Foundation
It uses YAML/JSON
It uses Hashicorp Configuration Language (or HCL)
Uses kubectl to run Kubernetes commands
Uses Terraform CLI to run commands
Requires a lot of cluster internal components and mechanics
Easy to understand
Kubernetes Common Use Cases
Orchestrating Containers across Several Hosts
Kubernetes is platform-independent, so that you can host your containers on multiple machines or in the cloud. To ensure high availability, it also has a failover layer.
Managing Compute Resources
It is often cheaper to host a dedicated Kubernetes cluster than to run multiple servers. It’s also easier to manage a Kubernetes cluster than multiple hosts with different servers.
Running CI/CD Platforms
Kubernetes is a key component of CI/CD methodologies and the preferred choice for running CI/CD platforms like Jenkins, Spinnaker, and Drone. Kubernetes will run CI/CD platforms as long as they can be packed in a container.
Kubernetes supports dynamic storage volume provisioning. Storage systems can be attached to any platform you choose, including network and cloud storage.
Service Discovery and Load Balancing
Kubernetes exposes the container cluster service to other platforms via a cluster’s DNS point. Kubernetes can distribute traffic and load balance traffic to ensure that deployed instances are available and stable when there is a lot of network traffic.
Terraform Common Use Cases
Terraform tracks your resources and uses a state file to keep track. This serves as a reference point for when resources are changed. Terraform uses a state file to determine which changes are required to your infrastructure to achieve any desired end-state.
Terraform is a platform that can be used in any cloud. To manage infrastructure resources hosted by multiple cloud providers, you can use an HCL configuration file. It can also handle cross-cloud dependencies. Multi-cloud deployments increase robustness and fault tolerance.
Managing Multi-Tier Applications
Multi-tier applications can be separated by defining a single logic for each tier. Terraform automatically manages the dependencies between each tier by defining each tier as a collection. Dependencies and plug-ins are required to ensure consistency among the tiers. These can be difficult to install manually.
Terraform provisioning ensures these dependencies are correctly installed and implemented every time. Terraform, for example, confirms that the database tier is available before provisioning web servers or load balancers.
Terraform can communicate with Software-Defined Networks to configure the network to meet the requirements of its applications. This allows you to move from a ticket-based workflow and automate the deployment process, which reduces deployment time.
We explored the key differences between Terraform and Kubernetes, two of the most popular modern DevOps tools. We found out what each tool offers to developers and IT operators and what they are best at. Terraform is a single framework that automates resources declaratively on multiple cloud platforms. Kubernetes manages resource management, deployments, and load balancing in your container environments.
These tools will make it easier to automate infrastructure, deployments of applications, monitoring, and other tasks.
Avi is a tech enthusiast with expertise in trending technologies such as DevOps, Cloud Computing, Big Data and many more. He is passionate about learning cutting-edge technologies and sharing his knowledge with others through… read more