Performance efficiency pillar in AWS - Commands & Configuration

Introduction

Performance efficiency pillar helps you build cloud systems that run fast and use resources well. It solves problems like slow apps or wasted computing power by guiding how to choose and adjust resources.

When your website slows down during busy times and you want it to stay fast.

When you want to save money by using just the right amount of cloud resources.

When you need your app to handle more users without crashing or lagging.

When you want to test different cloud setups to find the fastest one.

When you want to monitor and improve your system’s speed over time.

Commands

This command creates an alarm that watches CPU use on an EC2 server. It alerts you if CPU use stays above 70% for 10 minutes, helping you spot when the server is busy and might need more power.

Terminal

aws cloudwatch put-metric-alarm --alarm-name HighCPUUtilization --metric-name CPUUtilization --namespace AWS/EC2 --statistic Average --period 300 --threshold 70 --comparison-operator GreaterThanThreshold --dimensions Name=InstanceId,Value=i-0123456789abcdef0 --evaluation-periods 2 --alarm-actions arn:aws:sns:us-east-1:123456789012:MyTopic --unit Percent

Expected Output

No output (command runs silently)

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--alarm-name - Names the alarm for easy identification

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--threshold - Sets the CPU usage level that triggers the alarm

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--alarm-actions - Defines what happens when the alarm triggers, like sending a message

This command sets up automatic scaling for your servers. It keeps at least one server running and can add up to three when demand grows, so your app stays fast without wasting resources.

Terminal

aws autoscaling create-auto-scaling-group --auto-scaling-group-name my-asg --launch-configuration-name my-launch-config --min-size 1 --max-size 3 --desired-capacity 1 --vpc-zone-identifier subnet-12345678

Expected Output

No output (command runs silently)

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--min-size - Minimum number of servers to keep running

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--max-size - Maximum number of servers to add when needed

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--desired-capacity - Number of servers to start with

This command links a scaling policy to your auto-scaling group. The policy tells AWS when to add more servers, for example, when CPU use is high, so your app can handle more users smoothly.

Terminal

aws autoscaling attach-scaling-policy --auto-scaling-group-name my-asg --policy-name cpu-scale-out --policy-arn arn:aws:autoscaling:us-east-1:123456789012:scalingPolicy:abcdef12-3456-7890-abcd-ef1234567890:autoScalingGroupName/my-asg:policyName/cpu-scale-out

Expected Output

No output (command runs silently)

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--policy-name - Names the scaling policy

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--policy-arn - Identifies the exact policy to attach

This command fetches CPU usage data for your server over one hour. It helps you see how busy your server was and decide if you need to change resources for better performance.

Terminal

aws cloudwatch get-metric-statistics --namespace AWS/EC2 --metric-name CPUUtilization --dimensions Name=InstanceId,Value=i-0123456789abcdef0 --start-time 2024-06-01T00:00:00Z --end-time 2024-06-01T01:00:00Z --period 300 --statistics Average

Expected Output

{"Label":"CPUUtilization","Datapoints":[{"Timestamp":"2024-06-01T00:05:00Z","Average":45.0},{"Timestamp":"2024-06-01T00:10:00Z","Average":55.0}],"ResponseMetadata":{"RequestId":"abcd1234-5678-90ef-ghij-klmnopqrstuv"}}

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--start-time - Sets the beginning of the time range for data

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--end-time - Sets the end of the time range for data

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--statistics - Chooses the type of data summary, here average CPU use

Key Concept

If you remember nothing else from this pattern, remember: monitor your system’s performance and adjust resources automatically to keep your app fast and efficient.

Common Mistakes

Setting the CPU threshold too high for alarms

You might miss early signs of overload and your app could slow down before you react.

Set a reasonable threshold like 70% so you get alerts before performance drops.

Not configuring auto-scaling limits properly

Your app might not scale up enough or could scale too much, wasting money or causing slowdowns.

Set min, max, and desired capacity based on expected traffic and budget.

Ignoring monitoring data after setup

You miss opportunities to improve performance or reduce costs by adjusting resources.

Regularly check CloudWatch metrics and adjust alarms and scaling policies as needed.

Summary

Create CloudWatch alarms to watch key performance metrics like CPU usage.

Set up auto-scaling groups to add or remove servers based on demand.

Attach scaling policies to automate resource changes when performance thresholds are met.

Use CloudWatch commands to review performance data and make informed adjustments.

Practice

1. What is the main goal of the AWS Performance Efficiency pillar?

easy

A. To make sure your system runs fast and adapts to changes

B. To secure your data from unauthorized access

C. To reduce the cost of your cloud resources

D. To organize your cloud resources in a neat way

Solution

1. Step 1: Understand the purpose of the Performance Efficiency pillar

   This pillar focuses on how well your system performs and adapts to changes in demand. Only To make sure your system runs fast and adapts to changes talks about running fast and adapting, which matches the pillar's goal.

2. Final Answer:

   To make sure your system runs fast and adapts to changes -> Option A

3. Quick Check:

   Performance Efficiency = Fast and adaptable system [OK]

Hint: Performance means speed and adaptability [OK]

Common Mistakes:

• Confusing performance with security
• Thinking cost reduction is the main goal
• Mixing organization with performance

2. Which AWS service helps automatically adjust the number of servers to meet demand?

easy

A. Amazon S3

B. Amazon RDS

C. AWS IAM

D. AWS Auto Scaling

Solution

1. Step 1: Identify the service that adjusts server count automatically

   AWS Auto Scaling changes the number of servers based on demand. Eliminate unrelated services: Amazon S3 stores files, Amazon RDS manages databases, and AWS IAM controls access, so they don't adjust server numbers.

2. Final Answer:

   AWS Auto Scaling -> Option D

3. Quick Check:

   Auto Scaling = Adjust servers automatically [OK]

Hint: Auto Scaling means automatic server adjustment [OK]

Common Mistakes:

• Choosing storage or database services instead
• Confusing IAM with scaling
• Not knowing what Auto Scaling does

3. Given this AWS setup: An application uses an Elastic Load Balancer (ELB) with Auto Scaling enabled. What happens when user traffic suddenly doubles?

medium

A. The application crashes due to overload

B. The ELB rejects extra traffic to keep servers stable

C. Auto Scaling adds more servers and ELB distributes traffic evenly

D. Auto Scaling removes servers to save costs

Solution

1. Step 1: Understand ELB and Auto Scaling roles

   ELB spreads traffic across servers; Auto Scaling adds servers when demand rises. Auto Scaling will add servers to handle more users, and ELB will balance the load.

2. Final Answer:

   Auto Scaling adds more servers and ELB distributes traffic evenly -> Option C

3. Quick Check:

   More traffic = More servers + balanced load [OK]

Hint: More traffic triggers Auto Scaling and ELB balances load [OK]

Common Mistakes:

• Thinking ELB rejects traffic
• Assuming the app crashes immediately
• Believing Auto Scaling removes servers on high load

4. You set up Auto Scaling but notice your application still slows down under heavy load. What is a likely cause?

medium

A. Auto Scaling is not configured with proper scaling policies

B. You used an Elastic Load Balancer correctly

C. Your database is too fast

D. You enabled monitoring and alerts

Solution

1. Step 1: Check Auto Scaling configuration

   If scaling policies are missing or incorrect, Auto Scaling won't add servers when needed. Using ELB correctly helps performance, a fast database is good, and monitoring helps detect issues, so they are not causes.

2. Final Answer:

   Auto Scaling is not configured with proper scaling policies -> Option A

3. Quick Check:

   Wrong scaling policies cause slow response [OK]

Hint: Check scaling policies if Auto Scaling fails [OK]

Common Mistakes:

• Blaming ELB when it's set up right
• Thinking a fast database causes slowdowns
• Ignoring the importance of scaling policies

5. You want to improve performance for a web app with unpredictable traffic spikes. Which combination best follows the Performance Efficiency pillar?

hard

A. Use fixed-size servers and manual traffic routing

B. Use Auto Scaling with Elastic Load Balancer and fast SSD storage

C. Use a single large server and no monitoring

D. Use slow storage but increase server size manually

Solution

1. Step 1: Identify best practices for unpredictable traffic

   Auto Scaling adjusts servers automatically, ELB balances traffic, and fast SSD storage speeds data access. Use Auto Scaling with Elastic Load Balancer and fast SSD storage uses all these features, while others rely on manual or slow methods.

2. Final Answer:

   Use Auto Scaling with Elastic Load Balancer and fast SSD storage -> Option B

3. Quick Check:

   Auto Scaling + ELB + fast storage = best performance [OK]

Hint: Combine Auto Scaling, ELB, and fast storage for spikes [OK]

Common Mistakes:

• Choosing fixed or manual scaling
• Ignoring load balancing
• Using slow storage for performance