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Hritik Raj
Hritik Raj

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🚀 AWS 131: Scalable Data - Provisioning Private RDS with Storage Autoscaling

#aws #rds #mysql #100daysofcloud

AWS

🗄️ Managed Databases: Setting Up a Secure MySQL Sandbox

Hey Cloud Builders 👋

Welcome to Day 31 of the #100DaysOfCloud Challenge!
Today, we are supporting the Nautilus Development Team by provisioning a robust, private database backend. We are moving away from manually installed databases on EC2 and embracing Amazon RDS. Our goal is to set up a MySQL instance that is secure (private-facing only) and scalable (storage autoscaling).

This task is part of my hands-on practice on the KodeKloud Engineer platform, which I highly recommend for anyone looking to master real-world DevOps scenarios.

🎯 Objective

  • Provision a private RDS instance named devops-rds.
  • Use the MySQL 8.4.x engine on a db.t3.micro (Free Tier eligible) instance.
  • Configure the instance with a Sandbox/Free Tier template to minimize costs.
  • Enable Storage Autoscaling with a maximum threshold of 50GB.
  • Ensure the instance reaches the Available state.

💡 Why Amazon RDS is a DevOps Favorite

Manually managing a database involves patching, backups, and scaling hardware. RDS automates these tasks, giving you high availability with minimal effort.

🔹 Key Concepts

  • Private RDS: By setting "Public Access" to No, we ensure the database can only be reached by resources inside our VPC (like our web servers), keeping it safe from the public internet.

  • Storage Autoscaling: This feature allows RDS to automatically increase your storage capacity when it detects you are running out of space. This prevents "Database Full" errors that could crash your app.

  • Instance Classes (db.t3.micro): These are burstable performance instances. They provide a baseline level of CPU performance with the ability to burst higher when your database workload increases.

🛠️ Step-by-Step: The RDS Provisioning Workflow

We’ll move from Engine Configuration → Instance Sizing → Scalability Settings.

🔹 Phase A: Database Engine & Templates

  • Engine: Select MySQL.
  • Version: Choose the latest 8.4.x version available.
  • Template: Select the Free Tier (or Sandbox) template to ensure we stay within the cost-effective limits.

🔹 Phase B: Settings & Sizing

  • Identifier: Set the DB instance identifier to devops-rds.
  • Credentials: Set your master username (e.g., admin) and a secure master password.
  • Instance Type: Specifically select db.t3.micro under burstable classes.

🔹 Phase C: Connectivity & Storage Scaling

  • Public Access: Set this to No to keep the instance private.
  • Storage Autoscaling: ✓ Enable storage autoscaling.
    • Threshold: Set the "Maximum storage threshold" to 50GB.

✅ Verify Success

  • Status Monitoring: Navigate to the RDS Databases list.
  • Wait for Available: The status will transition from Creating → Backing up → Available.

  • Confirm: 🎉 Once the status is green and says Available, your database is ready to accept connections from your application servers!

📝 Key Takeaways

  • 🚀 Automatic Growth: Storage autoscaling eliminates the need to manually "resize" disks as your data grows.
  • 🛡️ Security by Default: Keeping RDS instances private is an industry best practice for protecting sensitive data.
  • 🕒 Provisioning Time: RDS instances usually take 5–10 minutes to provision because AWS is setting up the underlying hardware, OS, and software for you.

🚫 Common Mistakes

  • Publicly Accessible: Accidentally setting public access to "Yes" exposes your database port to the internet a major security risk!
  • Wrong Instance Class: Selecting a db.m5 or db.r5 instance by mistake can lead to unexpected costs outside the Free Tier.
  • Autoscaling Cap: Setting the maximum threshold too low. Ensure your threshold (50GB) leaves enough room for expected growth.

🌟 Final Thoughts

You’ve just provisioned a production-ready database backbone! Mastering RDS is essential for any DevOps Engineer, as it is the most common way to handle persistent data in the AWS cloud. Next, we can look at setting up Read Replicas for even better performance!

🌟 Practice Like a Pro

If you want to try these tasks yourself in a real AWS environment, check out:
👉 KodeKloud Engineer - Practice Labs

It’s where I’ve been sharpening my skills daily!

🔗 Let’s Connect

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