Author:

Running a Flask API on an AWS Ubuntu instance is a common setup for web applications, but encountering issues like the API not responding from external sources can be frustrating. If your Flask app was working perfectly with curl requests, but suddenly stops responding from outside AWS, there are several potential causes to explore. This guide will walk you through the steps to identify and resolve the connection issue, whether it’s related to security group configurations, port access, or Flask settings.

Troubleshooting Flask API Accessibility in AWS

If your Flask API is not accessible from outside your AWS instance, but it works locally (e.g., with curl on localhost), there are a few things you can check. Below are steps to troubleshoot and fix the issue:

1. Check Flask Binding

By default, Flask binds to 127.0.0.1, which means it only accepts requests from localhost. To allow external access, you need to bind it to 0.0.0.0.

In your Flask app, modify the run method:

app.run(host='0.0.0.0', port=5000)

This will allow the app to accept connections from any IP address.

2. Check Security Group

Ensure that your AWS EC2 security group allows inbound traffic on port 5000.

• Go to your EC2 console.
• Select your instance.
• Check the Inbound rules of your security group.
• Ensure there is an inbound rule for TCP on port 5000 from any IP (0.0.0.0/0), or specify the IP range you need to allow.

3. Check Network ACLs

Verify that the network ACLs associated with your subnet are not blocking **inbound or outbound **traffic on port 5000. Ensure that both inbound and outbound rules allow traffic on port 5000.

4. Check EC2 Instance Firewall

If your **EC2 instance **is running a firewall like ufw (Uncomplicated Firewall), ensure that it’s configured to allow traffic on port 5000. Run the following command to allow traffic:

sudo ufw allow 5000/tcp

5. Check CloudWatch Logs

Review your CloudWatch logs to check for any errors related to network connectivity or your Flask app. This can provide insights into whether your app is running properly or if there are issues preventing access.

6. Test with Curl from Outside AWS

After making the above changes, test the Flask API from an external machine by running the following command:

curl http://<your_aws_public_ip>:5000

If everything is set up correctly, you should get a response from your Flask API.

By following the troubleshooting steps and reviewing your security group settings, you should be able to identify why your Flask API is no longer responding to external requests. Don’t forget to also check your Flask application’s configuration and the machine’s network settings. With a little persistence, you’ll have your Flask API up and running on AWS again. If the issue persists, consider reviewing your firewall rules or AWS instance configuration for any overlooked factors.

When integrating Azure Front Door with an AWS-hosted Single Page Application (SPA) on S3 + CloudFront, developers often encounter MIME type errors. A common issue is that scripts and stylesheets fail to load due to incorrect MIME types, leading to errors such as:

“Expected a JavaScript module script but the server responded with a MIME type of ‘text/html’.”

This typically happens due to misconfigurations in CloudFront, S3 bucket settings, or response headers. In this post, we’ll explore the root cause of these errors and how to properly configure your setup to ensure smooth redirection and loading of static assets.

The error is occuring is due to Azure Front Door incorrectly serving your AWS S3/CloudFront-hosted Single Page Application (SPA). The MIME type mismatch suggests that the frontend resources (JS, CSS) are being served as text/html instead of their correct content types. This is often caused by misconfigurations in Azure Front Door, S3, or CloudFront.

---

✅ Solutions

1. Ensure Proper MIME Types in S3

Your AWS S3 bucket must serve files with the correct MIME types.

• Open AWS S3 Console → Select your Bucket → Properties → Scroll to “Static website hosting.”
• Check the metadata of the files:
  • JavaScript files should have Content-Type: application/javascript
  • CSS files should have Content-Type: text/css
• If incorrect, update them:
  • Go to Objects → Select a file → Properties → Under “Metadata,” add the correct Content-Type.

Command to Fix for All Files

If you want to correct MIME types for all files at once, run this command:

When solving the popular “Two Sum” problem, different programming languages and techniques offer varying levels of efficiency. Let’s compare Python and Java implementations using both nested loops and optimized data structures.

The Problem Statement

Given an array of integers and a target sum, return the indices of two numbers that add up to the target. For example:

Example Input

array = [2, 7, 11, 15]
target = 9

Expected Output

[0, 1]

This output indicates that the numbers at indices 0 and 1 (2 and 7) add up to 9.

Python Solutions

1. Python with Nested Loops

This straightforward solution uses two nested loops to check every possible pair of numbers.

Code:

def two_sum(array, target):
    for i in range(len(array)):
        for j in range(i + 1, len(array)):
            if array[i] + array[j] == target:
                return [i, j]
    return []

array = [2, 7, 8, 11]
target = 9
print(two_sum(array, target))  # Output: [0, 1]

Performance:

• Memory Usage: 13.5 MB
• Runtime: 2093 ms

Explanation:

Python checks every pair of numbers in the array, making it accurate but slow. Its time complexity is O(n²) due to the double loop.

2. Python with Dictionary (Optimized)

This optimized solution leverages a dictionary to store numbers and their indices for faster lookups.

Code:

class Solution(object):
    def twoSum(self, nums, target):
        num_to_index = {}
        for i, num in enumerate(nums):
            complement = target - num
            if complement in num_to_index:
                return [num_to_index[complement], i]
            num_to_index[num] = i
        return []

nums = [2, 7, 11, 15]
target = 9
solution = Solution()
print(solution.twoSum(nums, target))  # Output: [0, 1]

Performance:

• Memory Usage: 13.1 MB
• Runtime: 0 ms

Explanation:

By storing the numbers in a dictionary, we reduce the time complexity to O(n). The dictionary enables instant lookups for the complement of the current number.

Java Solutions

1. Java with Nested Loops

Similar to Python’s nested loops, this solution iterates through every pair of numbers to find the correct indices.

Code:

class Solution {
    public int[] twoSum(int[] nums, int target) {
        for (int i = 0; i < nums.length; i++) {
            for (int j = i + 1; j < nums.length; j++) {
                if (nums[i] + nums[j] == target) {
                    return new int[] {i, j};
                }
            }
        }
        return new int[] {};
    }
}

int[] nums = {2, 7, 11, 15};
int target = 9;
Solution sol = new Solution();
int[] result = sol.twoSum(nums, target);
// Output: [0, 1]

Performance:

• Memory Usage: 45 MB
• Runtime: 78 ms

Explanation:

While Java runs nested loops more efficiently than Python due to its compiled nature, the time complexity remains O(n²).

2. Java with HashMap (Optimized)

This implementation mirrors Python’s dictionary-based approach but uses Java’s HashMap for efficient lookups.

Code:

import java.util.HashMap;

class Solution {
    public int[] twoSum(int[] nums, int target) {
        HashMap<Integer, Integer> numToIndex = new HashMap<>();
        for (int i = 0; i < nums.length; i++) {
            int complement = target - nums[i];
            if (numToIndex.containsKey(complement)) {
                return new int[] {numToIndex.get(complement), i};
            }
            numToIndex.put(nums[i], i);
        }
        return new int[] {};
    }
}

int[] nums = {2, 7, 11, 15};
int target = 9;
Solution sol = new Solution();
int[] result = sol.twoSum(nums, target);
// Output: [0, 1]

Performance:

• Memory Usage: 44.9 MB
• Runtime: 2 ms

Explanation:

Using a HashMap significantly reduces the runtime to O(n), as lookups and insertions in a HashMap are extremely fast.

Comparing the Solutions

Solution	Language	Time Complexity	Runtime	Memory Usage
Nested Loops	Python	O(n²)	2093 ms	13.5 MB
Dictionary (Optimized)	Python	O(n)	0 ms	13.1 MB
Nested Loops	Java	O(n²)	78 ms	45 MB
HashMap (Optimized)	Java	O(n)	2 ms	44.9 MB

Key Takeaways:

1. Optimized solutions outperform nested loops: Leveraging data structures like dictionaries (Python) or HashMaps (Java) can drastically reduce runtime.
2. Language differences matter: Python’s nested loops are significantly slower than Java’s, but its dictionary implementation is faster due to Python’s efficient data handling.
3. Memory usage varies: Java generally consumes more memory due to its internal processing overhead.

Conclusion

When solving problems like Two Sum, choosing the right data structure can drastically improve performance. For optimal efficiency, avoid nested loops in favor of dictionaries or HashMaps. While Python is often faster for smaller datasets due to its interpreted nature, Java’s compiled approach ensures consistent performance across larger datasets.

In this guide, we will walk through the step-by-step process of importing an SQL dump into a MySQL database running inside a Docker container. Whether you’re setting up a database for a development environment or restoring data for a production system, Docker simplifies the process by providing an isolated, consistent environment.

---

Why Use Docker for MySQL?

Docker is an ideal tool for developers who want to run MySQL without the hassle of local installation. Here’s why:

1. Consistency: Docker ensures the same MySQL version and configuration across environments.
2. Isolation: Run MySQL independently without interfering with your local environment.
3. Portability: Share your Docker setup with team members for quick replication.
4. Ease of Cleanup: When done, remove the container without leaving residues on your system.

---

Prerequisites

Before we start, ensure you have the following installed on your system:

1. Docker: Download and install Docker from docker.com.
2. SQL Dump File: The SQL dump file you want to import (e.g., backup.sql).
3. Basic Command Line Knowledge: Familiarity with terminal or command prompt commands.

---

Step 1: Pull the MySQL Docker Image

First, download the official MySQL Docker image from Docker Hub. This image contains the MySQL server and is regularly updated by the MySQL team.

By default, this command fetches the latest MySQL version. If you need a specific version, specify it like this:

---

Step 2: Run the MySQL Container

To create and run a MySQL container, use the docker run command. Replace the placeholder values as needed:

• --name mysql-container: Assigns a name to the container.
• -e MYSQL_ROOT_PASSWORD=rootpassword: Sets the root password for MySQL.
• -d: Runs the container in detached mode.
• -p 3306:3306: Maps port 3306 of the container to port 3306 on your host.

You can verify the container is running by using:

---

Step 3: Create a Volume for Persistent Data (Optional)

If you want the database data to persist even after the container is removed, create a Docker volume:

Run the MySQL container with the volume attached:

This ensures your data is saved in the mysql-data volume.

---

Step 4: Copy the SQL Dump File into the Container

To import an SQL dump, you need the file to be accessible inside the container. Use the docker cp command to copy the dump file:

Here:

• backup.sql is your SQL dump file.
• mysql-container is the name of your running MySQL container.

---

Step 5: Import the SQL Dump into MySQL

Once the dump file is inside the container, connect to the MySQL shell to execute the import. Follow these steps:

a. Access the Container

Start an interactive session inside the running container:

This gives you a shell prompt inside the container.

b. Log in to MySQL

Log in as the root user using the password you set earlier:

When prompted, enter the root password (rootpassword in this case).

c. Create a New Database

Before importing the dump, create a database to hold the data:

Replace my_database with your preferred database name.

d. Import the SQL Dump

Run the following command to import the dump into the newly created database:

---

Step 6: Verify the Import

After the import process is complete, verify the database content:

This will list all the tables imported from the dump file.

---

Step 7: Connect to the MySQL Database

You can now connect to the MySQL database from your local machine using any MySQL client, such as MySQL Workbench or DBeaver. Use the following connection details:

• Host: localhost
• Port: 3306
• Username: root
• Password: rootpassword
• Database: my_database

---

Step 8: Cleanup (Optional)

When you no longer need the MySQL container, you can stop and remove it:

If you used a Docker volume for persistent storage, it remains intact. To remove the volume, run:

---

Troubleshooting Tips

• Error: “Access Denied” When Importing SQL Dump
  Ensure that the database exists, and you’re using the correct username and password.
• Error: “File Not Found” for Dump File
  Check if the file was copied correctly into the container. Use docker exec -it mysql-container ls / to verify.
• SQL Syntax Errors
  Confirm that the dump file is compatible with the MySQL version running in the container.

---

Conclusion

Importing an SQL dump into a Dockerized MySQL database is a straightforward process that ensures your database setup is clean, consistent, and portable. Docker’s ability to isolate environments makes it an excellent choice for database management in development and testing scenarios.

By following the steps outlined above, you can quickly set up a MySQL container, import your data, and get started with minimal effort. If you encounter issues, refer to the troubleshooting section or leave a comment below for assistance.

Happy Dockerizing!

SAA-C03 exam practice questions with detailed answers Question 4

The company that you are working for has a highly available architecture consisting of an elastic load balancer and several EC2 instances configured with auto-scaling in three Availability Zones. You want to monitor your EC2 instances based on a particular metric, which is not readily available in CloudWatch.

Which of the following is a custom metric in CloudWatch which you have to manually set up?

A. Memory Utilization of an EC2 instance

B. CPU Utilization of an EC2 instance

C. Disk Reads activity of an EC2 instance

D. Network packets out of an EC2 instance

 

Answer:

---

Detailed Explanation:

Option A: Memory Utilization of an EC2 instance

• Explanation:
  Memory utilization is not provided by default in CloudWatch because it is an OS-level metric, not a hypervisor-level metric. To monitor this, you need to:
  1. Install the CloudWatch Agent on your EC2 instance.
  2. Configure the agent to collect memory usage data from the operating system.
  3. Send this data as a custom metric to CloudWatch.
• Why it’s a Custom Metric:
  CloudWatch does not have visibility into the operating system by default. Metrics like memory usage require an interaction with the OS, which necessitates a custom setup.
• Key Takeaway:
  Memory utilization is a custom metric in CloudWatch and needs to be manually configured and sent.

---

Option B: CPU Utilization of an EC2 instance

• Explanation:
  CPU Utilization is a standard metric provided by CloudWatch. It measures the percentage of allocated EC2 compute resources being used.
• Why it’s Not Custom:
  This metric is available by default without any additional configuration or setup. CloudWatch collects and displays this metric as part of the basic EC2 monitoring.
• Key Takeaway:
  CPU Utilization is a standard CloudWatch metric, not a custom one.

---

Option C: Disk Reads activity of an EC2 instance

• Explanation:
  Disk Read Activity is another standard metric provided by CloudWatch. It measures the number of read operations performed on the instance’s disks.
• Why it’s Not Custom:
  This metric is collected and displayed by CloudWatch without requiring any manual setup or additional configuration.
• Key Takeaway:
  Disk Reads is a standard CloudWatch metric, not a custom one.

---

Option D: Network packets out of an EC2 instance

• Explanation:
  Network Packets Out is a standard metric available in CloudWatch. It tracks the number of network packets sent out by the instance.
• Why it’s Not Custom:
  CloudWatch provides this metric by default as part of EC2’s basic monitoring.
• Key Takeaway:
  Network Packets Out is a standard CloudWatch metric, not a custom one.

---

Conclusion

Option	Metric	Custom or Standard?	Why?
A	Memory Utilization	Custom Metric	Requires CloudWatch Agent for OS-level data collection.
B	CPU Utilization	Standard Metric	Automatically provided by CloudWatch.
C	Disk Reads Activity	Standard Metric	Automatically provided by CloudWatch.
D	Network Packets Out	Standard Metric	Automatically provided by CloudWatch.

Correct Answer: A. Memory Utilization of an EC2 instance

Stephane Maarek is a highly respected online educator and entrepreneur, specializing in AWS (Amazon Web Services), Apache Kafka, and other cloud-related topics. Known for his engaging and practical teaching style, he has empowered over 1.5 million students globally to succeed in the field of cloud computing. His courses are hosted primarily on Udemy and cater to a wide range of certifications, including AWS Cloud Practitioner, Solutions Architect, DevOps, SysOps, and advanced AI/ML tracks.

---

Foundational AWS Courses

1. AWS Certified Cloud Practitioner (CLF-C02)
   • Overview: Introduces AWS cloud fundamentals, core services, security, billing, and pricing models.
   • Highlights: Designed for non-technical professionals and beginners. Includes six practice exams to simulate real exam conditions.
   • Ideal For: Anyone new to AWS or cloud computing (aws ccp stephane maarek)​
2. AWS Certified Solutions Architect – Associate (SAA-C03)
   • Overview: Focuses on building scalable, fault-tolerant, and cost-efficient architectures.
   • Highlights: Hands-on labs with practical use cases, mock exams, and a detailed breakdown of core services like EC2, S3, and RDS.
   • Ideal For: Aspiring architects looking to design and deploy AWS applications.
   • Course Link: Stephane Maarek AWS Solutions Architect Associate

---

Advanced AWS Certifications

3. AWS Certified Solutions Architect – Professional (SAP-C02)
   • Overview: Covers advanced architectural concepts such as multi-region deployments, disaster recovery, and cost optimization.
   • Highlights: Deep dives into AWS services, case studies, and scenario-based practice exams.
   • Ideal For: Experienced architects aiming to tackle complex cloud solutions​
4. AWS Certified DevOps Engineer – Professional (DOP-C02)
   • Overview: Centers on automation, CI/CD pipelines, infrastructure as code, and monitoring solutions.
   • Highlights: Practical labs, detailed walkthroughs of tools like CloudFormation and CodePipeline.
   • Ideal For: DevOps professionals seeking automation expertise​.

---

Specialty Certifications

5. AWS Certified Security – Specialty
   • Overview: Focuses on securing workloads in AWS, covering encryption, IAM, incident response, and compliance.
   • Highlights: Labs on implementing security best practices, managing vulnerabilities, and securing APIs.
   • Ideal For: Security professionals or architects​
6. AWS Certified Data Analytics – Specialty
   • Overview: Comprehensive coverage of data lakes, big data processing, and visualization.
   • Highlights: Training on tools like Redshift, Kinesis, Glue, and QuickSight.
   • Ideal For: Data engineers and analysts​
7. AWS Certified Networking – Specialty
   • Overview: In-depth exploration of AWS network design, including hybrid architectures and VPC peering.
   • Highlights: Scenarios on Direct Connect, Route 53, and advanced networking solutions.
   • Ideal For: Professionals managing complex networking tasks​
8. AWS Certified AI Practitioner (AIF-C01)
   • Overview: Introduces machine learning concepts and generative AI capabilities on AWS.
   • Highlights: Teaches the use of AI responsibly, understanding AI models, and leveraging SageMaker.
   • Ideal For: AI enthusiasts and professionals new to machine learning​

---

Specialized AWS Topics

9. Apache Kafka Series
   • Overview: While not strictly AWS-focused, this course dives into Kafka fundamentals and its integration with AWS.
   • Highlights: Hands-on labs covering Kafka Streams, connectors, and real-time processing.
   • Ideal For: Developers building event-driven applications.

---

10. Practice Exams and Supporting Materials

Stephane’s courses are well-known for their extensive practice exams and supplementary resources. These exams simulate real-world scenarios and include detailed explanations for every question. They help students:

• Understand exam patterns and concepts.
• Learn to manage time effectively during exams.
• Strengthen weak areas through focused revisions.

Additionally, students have access to downloadable PDFs, interactive quizzes, and hands-on labs, ensuring they are thoroughly prepared for certification.

---

Why Choose Stephane Maarek?

1. Engaging Teaching Style: His courses are designed with a logical flow, making complex concepts easy to grasp.
2. Regular Updates: All courses are regularly updated to reflect the latest AWS changes.
3. Real-World Experience: Stephane integrates his real-world expertise into his teaching, making it practical and relatable.
4. Global Recognition: His courses are some of the highest-rated on platforms like Udemy, consistently achieving ratings above 4.7/5.
5. Comprehensive Content: Each course offers a blend of theoretical knowledge and practical exercises.

---

Student Success Stories

With over 220,000 reviews and millions of enrolled students, Stephane Maarek’s courses have helped countless individuals achieve their AWS certification goals. Many learners attribute their career advancements and deeper understanding of cloud computing to his expert guidance.

---

Conclusion

Whether you’re a beginner aiming for the AWS Cloud Practitioner certification or a professional seeking advanced credentials like DevOps or AI/ML, Stephane Maarek’s courses are an invaluable resource. His detailed practice exams, hands-on labs, and engaging teaching make learning both enjoyable and effective.

For more information and course enrollments, visit his Udemy profile​ Stephanemaarek

AWS SAA-C03 Exam Practice Questions and Answers – Question 3

A company needs the ability to analyze the log files of its proprietary application. The logs are stored in JSON format in an Amazon S3 bucket. Queries will be simple and will run on-demand. A solutions architect needs to perform the analysis with minimal changes to the existing architecture. What should the solutions architect do to meet these requirements with the LEAST amount of operational overhead?

A. Use Amazon Redshift to load all the content into one place and run the SQL queries as needed.

B. Use Amazon CloudWatch Logs to store the logs. Run SQL queries as needed from the Amazon CloudWatch console.

C. Use Amazon Athena directly with Amazon S3 to run the queries as needed.

D. Use AWS Glue to catalog the logs. Use a transient Apache Spark cluster on Amazon EMR to run the SQL queries as needed.

---

Correct Answer: C. Use Amazon Athena directly with Amazon S3 to run the queries as needed.

---

Explanation:

Option A: Use Amazon Redshift to load all the content into one place and run the SQL queries as needed.

• Explanation:
  • Amazon Redshift is a fully managed data warehouse solution designed for complex, large-scale analytical queries. However, using Redshift for on-demand and simple queries introduces unnecessary overhead.
  • It requires the creation of a data warehouse, loading data into it, and managing resources, which contradicts the requirement for minimal operational overhead.
• Suitability:
  • Not ideal. It adds significant operational complexity and cost for a use case that can be handled more efficiently with serverless solutions.

---

Option B: Use Amazon CloudWatch Logs to store the logs. Run SQL queries as needed from the Amazon CloudWatch console.

• Explanation:
  • CloudWatch Logs is a service for monitoring and analyzing log data in real-time, but it is not designed for querying JSON logs directly in S3.
  • Transferring logs from S3 to CloudWatch Logs adds operational steps and complexity, making this approach less suitable.
• Suitability:
  • Not suitable. This approach involves additional steps and complexity that do not align with the requirements.

---

Option C: Use Amazon Athena directly with Amazon S3 to run the queries as needed.

• Explanation:
  • Amazon Athena is a serverless, interactive query service designed to analyze data directly in Amazon S3 using SQL.
  • Athena supports JSON, Parquet, and other formats, making it a perfect fit for querying log files in JSON format.
  • It requires no infrastructure setup or data movement, minimizing operational overhead.
  • By creating a schema for the JSON data, queries can be executed directly on the data stored in S3.
• Suitability:
  • Best option. Athena provides a low-overhead, cost-effective solution for on-demand querying of JSON logs in S3.

---

Option D: Use AWS Glue to catalog the logs. Use a transient Apache Spark cluster on Amazon EMR to run the SQL queries as needed.

• Explanation:
  • AWS Glue can catalog the logs, and Amazon EMR with Apache Spark can process the data. However, this approach requires setting up and managing Glue crawlers, Spark clusters, and job execution, introducing significant operational overhead.
  • While suitable for complex processing tasks, it is overly complex for simple, on-demand queries.
• Suitability:
  • Not ideal. This solution adds unnecessary complexity and is more appropriate for large-scale data processing, not simple queries.

---

Recommended Solution:

Correct Answer: C. Use Amazon Athena directly with Amazon S3 to run the queries as needed.

• Why?
  • Athena meets all the requirements with minimal operational overhead.
  • It provides a serverless and cost-effective way to query JSON log files stored in S3 on-demand using SQL.

SAA-C03 exam practice questions with detailed answers Question 2

A company is working on a file-sharing application that will utilize an amazon s3 bucket for storage. The company intends to make all the files accessible through an amazon cloudfront distribution, and not directly through 53. What should be the solution architect’s course of action to meet this requirement?

A. Create specific policies for each s3 bucket, assigning read authorization exclusively to cloudfront access.

B. Establish an iam user with read access to 53 bucket objects and link the user to cloudfront.

C. Create an s3 bucket policy that identifies the cloudfront distribution id as the principal and the target s3 bucket as the amazon resource name (arn).

D. Generate an origin access identity (OAI), associating the OAI with the cloudfront distribution and adjust s3 bucket permissions to restrict access to only OAI for reading.

---

Let’s think and analyze the question options. What will be the correct answer?

Explanation:

1. Scenario Analysis:
   • The company wants files in the S3 bucket to only be accessible via CloudFront and not directly from S3.
   • To achieve this, access to the S3 bucket must be restricted, and only the CloudFront distribution should have read access.
2. Why Option D is Correct:
   • Origin Access Identity (OAI) is a special CloudFront feature that ensures secure access between CloudFront and the S3 bucket.
   • By associating the OAI with the CloudFront distribution, you grant CloudFront exclusive read access to the S3 bucket while preventing direct access to the bucket from the public.
   • The bucket policy is updated to allow the OAI to read objects while denying public access.
3. Why Other Options are Incorrect:
   • A: Creating specific policies for the bucket does not address restricting access only to CloudFront or use OAI for secure access.
   • B: IAM users are not required for this use case. IAM is used for programmatic access or human users, not CloudFront.
   • C: You cannot directly assign a CloudFront distribution ID as a principal in an S3 bucket policy. This is not how CloudFront integrates with S3.

---

Solution:

1. Create an OAI in CloudFront.
2. Update the S3 bucket policy to allow read access only for the OAI.
3. Deny all public access to the S3 bucket.

This ensures secure file access only through the CloudFront distribution.

The AWS Solutions Architect Associate (SAA-C03) exam is one of the most sought-after certifications for cloud professionals. This guide consolidates the best resources, strategies, and tips to help you ace the exam on your first attempt.

---

1. Understand the Exam Format

Before diving into preparation, familiarize yourself with the exam details:

• Exam Type: Multiple choice and multiple responses
• Domains Covered:
  1. Design Secure Architectures (30%)
  2. Design Resilient Architectures (26%)
  3. Design High-Performing Architectures (24%)
  4. Design Cost-Optimized Architectures (20%)
• Duration: 130 minutes
• Passing Score: ~720/1000
• Cost: $150 (plus applicable taxes)

---

2. Core Resources for Preparation

a) Best Courses for AWS SAA C03

Invest in high-quality video courses to build your foundational knowledge and learn key AWS services in depth.

1. Stephen Marek’s SAA-C03 Course
   • Available on Udemy, this is one of the best-rated courses. Stephen’s teaching style is highly engaging, and he focuses on both theoretical and practical aspects of AWS services.
   • Includes hands-on labs and quizzes to solidify your learning.
   • Link: Stephen Marek AWS SAA-C03
2. Adrian Cantrill’s AWS Solutions Architect Associate Course
   • A deep dive into AWS concepts with high-quality diagrams and real-world scenarios.
   • Comprehensive coverage of all exam domains.
   • Link: 20% Discount Link Adrian Cantrill AWS Course

---

b) AWS Solutions Architect mock exams and Practice Tests

1. Tutorials Dojo Question Bank: Tutorials Dojo AWS practice
   • Created by Jon Bonso, these are some of the most reliable and well-explained practice questions for AWS certifications.
   • Includes detailed explanations for every answer, helping you understand concepts thoroughly.
   • Link: Tutorials Dojo AWS Practice Exams
2. ExamTopics
   • A free resource offering a vast collection of community-sourced SAA-C03 questions.
   • While the accuracy of some answers may vary, it’s excellent for exposure to different question formats.
   • Link: ExamTopics AWS Questions
3. Peace of Code YouTube Videos
   • A fantastic YouTube channel offering AWS exam tips and walkthroughs of mock questions.
   • Focuses on real-world scenarios and provides in-depth explanations.
   • Link: Peace of Code AWS Playlist
4. ItsAws.com
   • You can find all the questions and answers on my website. Link [Link coming soon]

---

c) AWS exam whitepapers and Documentation

Whitepapers are an official resource from AWS and are highly recommended for exam preparation.

1. AWS Well-Architected Framework
   • Covers best practices for building secure, high-performing, and cost-optimized architectures.
   • Link: AWS Well-Architected Framework
2. AWS Security Documentation
   • Essential for understanding IAM, encryption, and security practices.
   • Link: AWS Security Whitepapers
3. AWS FAQs
   • Read FAQs for services like EC2, S3, RDS, Lambda, and VPC for detailed insights.

---

3. Study Plan and Strategy

a) Study Timeline

Allocate at least 4–6 weeks to prepare thoroughly.

1. Week 1–2: Learn Core Concepts
   • Watch Stephen Marek’s or Adrian Cantrill’s videos and take notes.
   • Start hands-on practice in the AWS Management Console.
2. Week 3–4: Reinforce Learning
   • Solve questions from Tutorials Dojo and ExamTopics.
   • Refer to AWS whitepapers for deeper insights.
3. Week 5–6: Focus on Weak Areas
   • Revise notes and rewatch video lectures on weak topics.
   • Take full-length mock tests to simulate exam conditions.

b) Practice Hands-On Labs

AWS is practical, so gaining hands-on experience is crucial. Work on these areas:

• Setting up EC2 instances, security groups, and VPCs.
• Configuring S3 buckets with lifecycle policies and permissions.
• Deploying serverless applications with AWS Lambda.

c) Simulate the Exam

• Take at least 3 full-length practice tests in exam-like conditions.
• Aim to consistently score 80% or higher before scheduling your exam.

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4. Exam Day Tips

1. Time Management:
   • 130 minutes for 65 questions gives ~2 minutes per question. Don’t get stuck on a single question; flag it and move on.
2. Elimination Technique:
   • Use the process of elimination to narrow down options, especially for scenario-based questions.
3. Review Your Answers:
   • Use any remaining time to review flagged questions.

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5. After the Exam

• If you pass, share your journey on LinkedIn to build credibility.
• If not, revisit your weak areas and reschedule the exam.

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Conclusion

The AWS SAA-C03 exam is challenging but achievable with the right strategy and resources. By leveraging video courses, practice questions, and AWS documentation, you can build a strong foundation and pass the exam with confidence.

Good luck on your journey to becoming an AWS Certified Solutions Architect!

If you want to PASS the SAA C03 exam within a short time frame, then you must read “How I Passed the AWS SAA C03 Solution Architect Associate Exam in 4 Weeks“

The AWS Solutions Architect Associate (SAA-C03) exam can be daunting, but with the right strategy and dedication, success is achievable. In this blog, I’ll share the exact steps I took to prepare for the exam, divided into a manageable 30-day timeline. Feel free to read my blog post on A Guide to AWS Solution Architect Associate SAA C03 Exam

Then come here for an AWS SAA-C03 4-week plan.

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Step 1: Complete a Video Course (15 Days)

I started my preparation with Stephen Marek’s AWS SAA-C03 Course on Udemy. The course is approximately 26 hours long, and I divided it into 15 days. That’s less than 2 hours of content daily.

As a beginner to the cloud, I found some concepts challenging. My approach was to:

• Watch the daily video module multiple times, especially sections I struggled with.
• Spend an additional 2–3 hours reading and practicing in the AWS Management Console to reinforce my understanding.
• Revise the slides from the previous day’s lecture to stay on track.

By the end of 15 days, I completed the course and felt confident about the foundational concepts.

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Step 2: Solve Questions (10 Days)

The next 10 days were dedicated to solving practice questions. My target was 60–70 questions daily, which increased to over 100 questions as I became faster. Here’s how I approached it:

1. ExamTopics

• ExamTopics offers 500+ community-contributed questions with explanations. It’s a great resource, but you need to validate answers carefully.
• To access specific questions, I used Google searches:
  "SAA C03 exam question 1 site:examtopics.com"
"SAA C03 exam question 44 site:examtopics.com"


  I repeated this process for as many questions as possible, reaching around 544.

• Tips While Solving Questions:
  • Identify service patterns and build shortcuts. For example:
    • SQL queries on S3 buckets? Likely AWS Athena.
    • HTTP/HTTPS traffic? Think ALB or CloudFront.
    • UDP traffic? Likely NLB.
  • These shortcuts helped me answer faster and more accurately.

2. Peace of Code

• Peace of Code’s YouTube Channel offers excellent walkthroughs for AWS practice questions.
• I focused on the videos with over 300 questions and analyzed the explanations in depth.

3. Daily Goal

By solving 60–70 questions daily, I covered 600–700 questions in 10 days. On some days, I exceeded 120 questions because my pace improved as I understood AWS services better.

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Step 3: Mock Exams (2–3 Days)

Once I was confident, I switched to full-length mock exams to simulate real test conditions. I used Tutorials Dojo’s question bank, which provides some of the best exam-like scenarios.

• Take 4–6 timed exams to build stamina and familiarity with the exam format.
• Target 70%+ in each mock test. If you fall short, review the explanations and revisit weak areas.

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Step 4: Revision (2–3 Days)

The last step is to revise critical AWS concepts. During this period, I focused on:

• AWS Whitepapers:
  • Disaster Recovery Strategies
  • AWS Well-Architected Framework (Six Pillars)
• Summarizing my notes and revisiting practice questions I had marked as challenging.

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Final Thoughts

By following this structured 30-day plan, I gained the knowledge and confidence needed to pass the AWS SAA-C03 exam. While I took 4 weeks in total as a beginner, this 30-day timeline can help streamline your preparation.

Here’s a quick recap:

1. 15 Days: Complete a video course (Stephen Marek’s or Adrian Cantrill’s).
2. 10 Days: Solve 600+ questions from ExamTopics, Peace of Code, and Tutorials Dojo.
3. 2–3 Days: Take full-length mock exams to solidify your readiness.
4. 2–3 Days: Revise whitepapers and challenging concepts.

This strategy worked for me, and I hope it helps you too. Let’s PASS the AWS SAA-C03 exam together!

Feel free to share your experiences or ask questions in the comments below. You can also send me any resources or notes at contact@itsaws.com—I’d appreciate your support.