Right-sizing resources in AWS - Step-by-Step Execution

Process Flow - Right-sizing resources

Start: Assess current resource usage

↓

Collect metrics: CPU, Memory, Network

↓

Analyze usage vs capacity

↓

Decision: Over-provisioned?

↓

Downsize resource

↓

Apply changes

→Monitor continuously

↓

End

This flow shows how to check resource usage, decide if resizing is needed, then adjust resources accordingly.

Execution Sample

AWS

1. Check CPU and memory usage of EC2 instance
2. If usage < 30%, consider smaller instance type
3. Change instance type to smaller size
4. Monitor performance after change

This example shows how to decide and apply right-sizing for an AWS EC2 instance.

Process Table

Step	CPU Usage (%)	Memory Usage (%)	Decision	Action Taken
1	45	50	No resizing needed	Keep current instance type
2	25	20	Over-provisioned	Plan to downsize
3	25	20	Downsize to t3.medium	Change instance type
4	30	35	Performance acceptable	Continue monitoring
5	55	60	Usage increased	Consider resizing again
6	N/A	N/A	End of evaluation cycle	Stop

💡 Evaluation cycle ends after monitoring confirms stable performance or triggers new resizing.

Status Tracker

Variable	Start	After Step 2	After Step 3	After Step 4	Final
CPU Usage (%)	45	25	25	30	55
Memory Usage (%)	50	20	20	35	60
Instance Type	t3.large	t3.large	t3.medium	t3.medium	t3.medium
Decision	None	Downsize	Downsize applied	Monitor	Review needed

Key Moments - 2 Insights

Why do we check both CPU and memory usage before resizing?

Because resizing based on only one metric might cause performance issues if the other resource is still heavily used. See execution_table steps 1 and 2 where both metrics guide the decision.

What happens if usage increases after downsizing?

We monitor continuously and may need to resize again to a larger instance, as shown in execution_table step 5.

Visual Quiz - 3 Questions

Look at the execution table, what was the CPU usage when the decision to downsize was made?

A 25%

B 45%

C 30%

D 55%

💡 Hint

Check the 'CPU Usage (%)' and 'Decision' columns at step 2 in the execution_table.

At which step was the instance type changed to a smaller size?

A Step 1

B Step 3

C Step 2

D Step 4

💡 Hint

Look at the 'Action Taken' column in the execution_table for the step where the instance type changes.

If memory usage stayed high but CPU was low, what would be the best action?

A Downsize instance

B Keep current instance

C Upsize instance

D Stop monitoring

💡 Hint

Refer to the key_moments about checking both CPU and memory before resizing.

Concept Snapshot

Right-sizing resources means adjusting cloud resources to match actual usage.
Check CPU and memory metrics regularly.
If usage is low, downsize to save cost.
If usage is high, upsize to maintain performance.
Always monitor after changes to ensure stability.

Full Transcript

Right-sizing resources in cloud means checking how much CPU and memory your server uses. If the usage is low, you can choose a smaller server to save money. If usage is high, pick a bigger server to keep things running smoothly. You start by collecting usage data, then decide if resizing is needed. After changing the server size, keep watching the usage to make sure performance stays good. This process repeats regularly to keep costs low and performance high.

Practice

1. What does right-sizing mean in cloud resource management?

easy

A. Always picking the largest resource available

B. Choosing the best resource size to match your actual needs

C. Using resources without monitoring their usage

D. Ignoring cost and focusing only on performance

Solution

1. Step 1: Understand the meaning of right-sizing

   Right-sizing means selecting resources that fit your workload requirements without waste.

2. Step 2: Compare options to definition

   Only Choosing the best resource size to match your actual needs matches the idea of matching resource size to actual needs.

3. Final Answer:

   Choosing the best resource size to match your actual needs -> Option B

4. Quick Check:

   Right-sizing = best fit resource size [OK]

Hint: Right-sizing means matching size to need, not max or ignore usage [OK]

Common Mistakes:

• Thinking right-sizing means always picking the biggest resource
• Ignoring usage data when choosing resources
• Confusing right-sizing with ignoring costs

2. Which AWS service helps you analyze resource usage to right-size your EC2 instances?

easy

A. AWS CloudTrail

B. AWS Cost Explorer

C. AWS Trusted Advisor

D. AWS Lambda

Solution

1. Step 1: Identify AWS services for resource optimization

   AWS Trusted Advisor provides recommendations including right-sizing EC2 instances.

2. Step 2: Eliminate unrelated services

   CloudTrail logs API calls, Cost Explorer shows costs, Lambda runs code; only Trusted Advisor analyzes usage for right-sizing.

3. Final Answer:

   AWS Trusted Advisor -> Option C

4. Quick Check:

   Trusted Advisor = right-sizing help [OK]

Hint: Trusted Advisor gives right-sizing tips for EC2 [OK]

Common Mistakes:

• Confusing CloudTrail with usage analysis
• Thinking Cost Explorer directly suggests right-sizing
• Selecting Lambda which is unrelated to resource sizing

3. You have an EC2 instance running at 10% CPU most of the time. What is the likely output of a right-sizing recommendation script?

medium

A. Recommend upgrading to a larger instance type

B. Recommend no change to instance size

C. Recommend terminating the instance

D. Recommend downgrading to a smaller instance type

Solution

1. Step 1: Analyze CPU usage data

   10% CPU usage means the instance is underutilized and likely oversized.

2. Step 2: Determine right-sizing action

   Underutilization suggests downgrading to a smaller instance to save cost.

3. Final Answer:

   Recommend downgrading to a smaller instance type -> Option D

4. Quick Check:

   Low CPU usage = downsize instance [OK]

Hint: Low CPU means smaller instance recommended [OK]

Common Mistakes:

• Choosing to upgrade when usage is low
• Thinking no change is needed despite low usage
• Confusing termination with right-sizing

4. A user tries to right-size an EC2 instance but gets an error: "Instance type not supported in this AZ." What is the best fix?

medium

A. Change the instance type to one supported in the availability zone

B. Ignore the error and try again

C. Terminate the instance immediately

D. Switch to a different AWS region without checking

Solution

1. Step 1: Understand the error context

   The error means the chosen instance type is not available in the current availability zone.

2. Step 2: Apply correct fix

   Selecting an instance type supported in the same availability zone resolves the error.

3. Final Answer:

   Change the instance type to one supported in the availability zone -> Option A

4. Quick Check:

   Unsupported instance type in AZ = pick supported type [OK]

Hint: Pick instance types supported in your AZ [OK]

Common Mistakes:

• Ignoring the error and retrying
• Terminating instance without fixing
• Switching regions without checking availability

5. You manage a fleet of EC2 instances with varying CPU usage. Which approach best applies right-sizing to reduce costs without hurting performance?

hard

A. Start with smallest instance types, monitor usage, then scale up as needed

B. Always pick the largest instance type to avoid performance issues

C. Randomly change instance types monthly without monitoring

D. Terminate all instances and switch to on-demand only

Solution

1. Step 1: Understand right-sizing best practice

   Right-sizing means starting small and adjusting based on real usage data to avoid waste.

2. Step 2: Evaluate options for cost and performance balance

   Start with smallest instance types, monitor usage, then scale up as needed follows best practice by starting small, monitoring, and scaling up only if needed.

3. Final Answer:

   Start with smallest instance types, monitor usage, then scale up as needed -> Option A

4. Quick Check:

   Start small + monitor + scale = right-sizing [OK]

Hint: Start small, watch usage, then adjust size [OK]

Common Mistakes:

• Always picking largest instance wastes money
• Changing types randomly causes instability
• Terminating all instances ignores workload needs