Elastic Load Balancing & Auto Scaling Groups Section

Question 1

Scalability

Answer 1

ability to accommodate a larger load by making the hardware stronger (scale up), or by adding nodes (scale out)

Question 2

Elasticity

Answer 2

once a system is scalable, elasticity means that there will be some “auto-scaling” so that the system can scale based on the load. This is “cloud-friendly”: pay-per-use, match demand, optimize costs

Question 3

Agility

Answer 3

(not related to scalability - distractor) new IT resources are only a click away, which means that you reduce the time to make those resources available to your developers from weeks to just minutes

Question 4

Why use a load balancer

Answer 4

• Spread load across multiple downstream instances
• Expose a single point of access (DNS) to your application
• Seamlessly handle failures of downstream instances
• Do regular health checks to your instances
• Provide SSL termination (HTTPS) for your websites
• High availability across zones

Question 5

ELB

Answer 5

is a managed load balancer
• AWS guarantees that it will be working
• AWS takes care of upgrades, maintenance, high availability
• AWS provides only a few configuration knobs

3 kinds of load balancers offered by AWS:
• Application Load Balancer (HTTP / HTTPS only) – Layer 7
• Network Load Balancer (ultra-high performance, allows for TCP) – Layer 4
• Classic Load Balancer (slowly retiring) – Layer 4 & 7

Question 6

ASG

Answer 6

• Scale out (add EC2 instances) to match an increased load
• Scale in (remove EC2 instances) to match a decreased load
• Ensure we have a minimum and a maximum number of machines running
• Automatically register new instances to a load balancer
• Replace unhealthy instances
• Cost Savings: only run at an optimal capacity (principle of the cloud)

Question 7

Auto Scaling Groups – Scaling Strategies

Answer 7

Manual Scaling: Update the size of an ASG manually

Dynamic Scaling: Respond to changing demand

Simple / Step Scaling
• When a CloudWatch alarm is triggered (example CPU > 70%), then add 2 units
• When a CloudWatch alarm is triggered (example CPU < 30%), then remove 1

Target Tracking Scaling
• Example: I want the average ASG CPU to stay at around 40%

Scheduled Scaling
• Anticipate a scaling based on known usage patterns
• Example: increase the min. capacity to 10 at 5 pm on Fridays

Predictive Scaling
• Uses Machine Learning to predict future traffic ahead of time
• Automatically provisions the right number of EC2 instances in advance