devops infrastructure is the base for modern software development and operations. it helps teams to work together, scale up easily, and automate tasks. the main idea is to mix tools, methods, and practices to handle infrastructure in a better way throughout the software process.

when development and operations teams work together, manual work is reduced. it also makes the process faster and more reliable. this way, we can deliver better-quality applications.

what is infrastructure in devops?

in devops, infrastructure means the resources we need to create, deploy, and run applications. these resources can be physical, virtual, or cloud-based. they include −

servers − machines (physical or virtual) or containers where applications run.
networking − setups for data transfer, balancing the load, and connecting services.
storage − systems like file storage, databases, and data handling tools.
tools and services − platforms for automating tasks, monitoring systems, managing ci/cd pipelines, and setting configurations.

devops looks at infrastructure as code. this means we can manage it just like we manage application code using infrastructure as code (iac). iac makes sure everything is consistent and easy to repeat or scale.

key principles of devops infrastructure

the following table highlights the key principles of devops infrastructure −

principle	description
automation	we automate tasks like setting up, configuring, and scaling resources. this saves time and reduces mistakes. tools like terraform or ansible help us create the same setups every time.
scalability and elasticity	we design systems that handle changes in workload automatically. using cloud platforms, we can easily add or remove resources based on needs.
immutability	instead of changing existing infrastructure, we replace parts like containers during updates. this keeps things consistent and predictable.
version control	we track infrastructure changes with tools like git. this makes it easier to manage and roll back changes when needed.
monitoring and observability	tools like prometheus and grafana help us keep an eye on the system's health and performance all the time.
security by design	security is built into our workflows from the start. we use things like secrets management and automated compliance checks to keep the system safe.

infrastructure as code (iac): end-to-end example

infrastructure as code (iac) helps us manage and set up infrastructure using code. it replaces manual work with automation. this makes things consistent, easy to scale, and repeatable. tools like terraform, aws cloudformation, or ansible are commonly used for iac.

iac works well with devops pipelines. it supports continuous delivery and lets us track changes in the infrastructure like we do with code.

step-by-step example: provisioning a web server with terraform

prerequisites

first of all, install terraform on your machine. next, set up an aws account and configure aws-cli with credentials.

directory structure

arrange project files like this −

/iac-example
   main.tf
   variables.tf
   outputs.tf

define variables (variables.tf)

this file helps us make the setup flexible −

variable "region" {
   description = "aws region"
   default     = "us-east-1"
}
variable "instance_type" {
   description = "ec2 instance type"
   default     = "t2.micro"
}

configure resources (main.tf)

we define the infrastructure here −

provider "aws" {
   region = var.region
}
resource "aws_instance" "web" {
   ami           = "ami-0c02fb55956c7d316" # amazon linux 2 ami
   instance_type = var.instance_type
   tags = {
      name = "terraformexamplewebserver"
   }
   provisioner "remote-exec" {
      inline = [
         "sudo yum update -y",
         "sudo yum install -y httpd",
         "sudo systemctl start httpd",
         "sudo systemctl enable httpd"
      ]
   }
}
resource "aws_security_group" "web_sg" {
   name_prefix = "web-sg-"
   ingress {
      from_port   = 80
      to_port     = 80
      protocol    = "tcp"
      cidr_blocks = ["0.0.0.0/0"]
   }
   egress {
      from_port   = 0
      to_port     = 0
      protocol    = "-1"
      cidr_blocks = ["0.0.0.0/0"]
   }
}

output information (outputs.tf)

show important details after the setup −

output "instance_public_ip" {
   value = aws_instance.web.public_ip
}

execute the terraform workflow

run these commands to create the infrastructure −

terraform init        # initialize the terraform environment
terraform plan        # see the execution plan
terraform apply       # apply the changes

verify the setup

after running terraform apply, terraform will give you the ec2 instance's public ip. open the ip in a browser to check if the web server is working.

this example shows how to set up a simple web server on aws using terraform. iac simplifies modern infrastructure management. it helps us work faster and better with devops practices.

cloud infrastructure

cloud infrastructure is the combination of hardware and software needed to provide computing resources like storage, networking, and computing power over the internet.

cloud service providers like aws, microsoft azure, and google cloud platform (gcp) manage this infrastructure. with cloud infrastructure, we can access resources anytime without needing physical hardware. it's scalable, flexible, and works on demand.

public vs. private vs. hybrid clouds

public cloud − a public cloud is managed by third-party companies like aws, azure, or gcp. they provide resources over the internet. in a public cloud, many organizations use the same infrastructure. this makes it cheap, scalable, and easy to use with a pay-as-you-go model. examples include amazon ec2 and microsoft azure virtual machines.

private cloud − a private cloud is dedicated to just one organization. it can be hosted either on-premises or by a third-party provider. this type of cloud offers better security, more control, and customization compared to public clouds. however, it can be more expensive. private clouds are great for industries that need high data privacy.

hybrid cloud − a hybrid cloud combines public and private clouds. this allows data and applications to move between both. the hybrid model is flexible. it lets businesses use the public cloud’s scalability while keeping sensitive data in the private cloud. this helps with managing workloads, security, and compliance

using aws / gcp / azure for infrastructure management

each of the following cloud platform has its own strengths. the best choice depends on what we need, our current setup, and business requirements.

aws (amazon web services)

aws has many services, like compute (ec2), storage (s3), and databases (rds, dynamodb). it also offers tools like cloudformation and aws opsworks to automate things. aws has managed services such as aws elastic beanstalk for web apps and aws lambda for serverless computing.

gcp (google cloud platform)

gcp is good for machine learning, analytics, and ai. key tools are google compute engine for virtual machines, google kubernetes engine (gke) for containers, and google cloud storage. gcp is especially useful for data analytics with tools like bigquery.

microsoft azure

azure is the cloud platform by microsoft. it offers compute (azure virtual machines), storage (azure blob storage), and networking (azure virtual network). azure works well with microsoft software. it also supports hybrid cloud setups with azure arc. many businesses using microsoft tools prefer azure.

advanced concepts of cloud infrastructure

the following table highlights some advanced concepts of cloud infrastructure −

concept	key points	explanation
ci/cd pipeline infrastructure	building ci/cd pipelines with jenkins, gitlab ci, or argocd	jenkins helps automate builds and deployment with plugins. gitlab ci connects version control and ci/cd. argocd is used for kubernetes-native continuous deployment using gitops.
	automating infrastructure deployment in pipelines	with iac tools like terraform and cloudformation, we can automatically deploy infrastructure, ensuring its consistent and repeatable in ci/cd pipelines.
networking in devops infrastructure	managing virtual networks and subnets	virtual networks (vnets) create isolated cloud environments. subnets split these networks into smaller parts to manage traffic and improve security.
	load balancers and traffic routing	load balancers share traffic across servers, ensuring availability. routing helps improve app performance by directing traffic in a smart way.
	implementing service mesh (istio, linkerd)	service meshes like istio and linkerd manage communication between microservices, offering traffic management, security, and observability without changing app code.
security in infrastructure	securing infrastructure as code	we validate iac scripts with tools like checkov or sentinel. this helps enforce security rules and avoids mistakes before deployment.
	using vault for secrets management	vault securely stores sensitive data, like api keys and passwords. it encrypts and dynamically manages secrets, fitting into ci/cd workflows for safe credential management.
	devsecops: integrating security into pipelines	we add security practices early in the ci/cd pipeline with tools like snyk and aqua security. these scan code for vulnerabilities during build or deployment.
scaling infrastructure	horizontal vs. vertical scaling	horizontal scaling adds more instances to share the load. vertical scaling adds more resources (cpu/ram) to existing machines. horizontal scaling gives better flexibility and redundancy.
	auto-scaling infrastructure with kubernetes and cloud tools	kubernetes and cloud services (aws, gcp, azure) automatically scale resources based on demand, helping with performance and resource use.
	cost optimization while scaling	to optimize costs, we can choose the right-sized instances, use spot instances, and enable auto-scaling. this helps balance cost and performance.
disaster recovery and backup	backup solutions for devops infrastructure	backup tools like aws backup and azure backup save data and configurations. these backups ensure we can recover data during failures.
	automating recovery in failover scenarios	tools like route 53 and cloud dns help with auto-recovery during failures. they minimize downtime, making sure the system keeps running smoothly.
infrastructure testing and validation	unit testing iac scripts	unit tests help verify the correctness of iac scripts before deployment. tools like terraform check and plan scripts to make sure they work as expected.
	using tools like test kitchen and terratest	test kitchen and terratest automate the testing of iac by deploying infrastructure, running tests, and checking if it works correctly.
	chaos engineering to test resilience	chaos engineering introduces controlled failures using tools like chaos monkey to check how resilient the infrastructure is and ensure it recovers from disruptions.

conclusion

in this chapter, we looked at the key parts of modern infrastructure management. we covered setting up ci/cd pipelines, networking, security, scaling, disaster recovery, and infrastructure testing. tools like jenkins, gitlab ci, and argocd help us automate pipelines easily. we also talked about how load balancing, service meshes, and cloud scaling improve performance and keep things available.

we also discussed securing infrastructure with practices like devsecops and vault. to make sure everything stays resilient, we talked about using chaos engineering and automated recovery. by understanding and using these ideas, we can build strong, scalable, and secure infrastructures that support continuous delivery, security, and smooth operations.

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