Hey there,

As cloud professionals, we are always looking for ways to improve our skills and build solutions that are scalable, secure, and efficient. While regular news and updates keep us informed, sometimes it's good to take a deep dive into topics that matter.

That’s why we’re bringing you this special issue of CloudPro, where we explore two carefully selected books that provide practical, hands-on learning experiences.

The first book, AWS Cloud Projects, takes a step-by-step approach to building real-world cloud solutions. We’ll walk through a key project—Deploying a Serverless Application on AWS Lambda with Terraform—to help you understand infrastructure as code (IaC) in action.

The second book, Solutions Architect’s Handbook, goes beyond the basics to teach cloud-native architecture best practices. We’ve included an in-depth section on Designing Scalable Microservices with Kubernetes to help you optimize your deployments for performance and efficiency.

If you’re serious about learning by doing, this issue is for you. Dive in and explore!

AWS Cloud Projects

Lately, I've been thinking a lot about the value of hands-on learning. There's something about actually building projects that sticks with you far longer than just reading concepts. That’s why when I came across AWS Cloud Projects, I knew it was worth sharing with you.

This book doesn’t just explain AWS concepts—it walks you through real-world implementations, step by step. Whether you’re spinning up cloud infrastructure, deploying AI-powered applications, or optimizing security, the projects in this book serve as practical blueprints.

One particular chapter stood out: Deploying a Serverless Application on AWS Lambda with Terraform. Here’s a detailed excerpt to give you a strong foundation:

"In this project, we’ll set up a serverless API using AWS Lambda and API Gateway, all provisioned through Terraform. Infrastructure as Code (IaC) allows us to automate deployments, ensuring repeatability and reducing manual effort.

Step 1: Define the Lambda Function

We start by defining our Lambda function using Terraform. Below is a basic Terraform configuration to deploy a function:

resource "aws_lambda_function" "my_lambda" {
function_name = "serverless_api"
handler = "index.handler"
runtime = "nodejs14.x"
role = aws_iam_role.lambda_exec.arn
filename = "lambda.zip"
}

Step 2: Configure API Gateway

API Gateway allows our Lambda function to be exposed as an HTTP endpoint:

resource "aws_api_gateway_rest_api" "api" {
name = "serverless_api"
description = "API Gateway for our Lambda function"
}

Step 3: Deploying the Infrastructure

To apply these changes, we use:

terraform init
terraform apply -auto-approve

By following these steps, you’ll have a fully operational serverless API deployed on AWS using Terraform.

If you're someone who learns best by building, AWS Cloud Projects is a must-read. It’s the kind of book that makes learning AWS both practical and engaging.

Solutions Architect's Handbook

Cloud-Native Architecture: Scaling Beyond Limits

Another book I recently found valuable is Solutions Architect’s Handbook. It goes beyond the basics of cloud architecture and explores scalability, security, and generative AI in real-world applications. If you’re serious about designing scalable cloud systems, this book is a gem.

Here’s a deep dive into Designing Scalable Microservices with Kubernetes:

"When designing microservices at scale, Kubernetes provides a resilient, self-healing platform. But to truly optimize performance, we must consider three key factors: resource allocation, observability, and network efficiency.

Resource Optimization with Horizontal Pod Autoscaler (HPA)

Using HPA ensures workloads dynamically adjust to demand:

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: my-app-hpa
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: my-app
minReplicas: 2
maxReplicas: 10
metrics:
- type: Resource
resource:
name: cpu
targetAverageUtilization: 50

Observability with Prometheus & Grafana

Monitoring plays a crucial role in scaling applications. The book explains how to integrate Prometheus and Grafana for real-time insights into resource consumption and request rates.

apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
name: my-app-monitor
spec:
selector:
matchLabels:
app: my-app
endpoints:
- port: metrics

Network Optimization using Istio

Istio allows fine-grained traffic control, helping balance workloads efficiently.

apiVersion: networking.istio.io/v1alpha3
kind: VirtualService
metadata:
name: my-app
spec:
hosts:
- "my-app.example.com"
http:
- route:
- destination:
host: my-app
subset: v1

With these techniques in place, you can scale workloads efficiently without unnecessary costs. Solutions Architect’s Handbook provides a deeper look into how enterprises design cloud-native applications for high availability and scalability.

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Thanks for reading and have a great day!