High Availability and Scaling Flashcards

1
Q

Scaling by adding more

A

Vertical Scaling

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2
Q

Scaling by creating more

A

Horizontal Scaling

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3
Q

Advantage of horizontal scaling

A

More Availability

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4
Q

Specifies all the needed settings that go into building out an EC2 instances

A

Launch Template

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5
Q

Collection of settings you can configure so you don’t have to walk through the EC2 wizard over and over

A

Launch Template

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6
Q

Capable of leveraging all EC2 auto-scaling features

A

Launch templates

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7
Q

Does Launch Templates support versioning?

A

Yes

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8
Q

A collection of EC2 instances that are treated as a collective group for purposes of scaling and management

A

Auto Scaling Groups

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9
Q

Lowest number of Ec2 instances you’ll ever have. Number of instances will not dip below this number

A

Minimum

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10
Q

Highest number of EC2 instances you’ll ever provision. Number of instances will not get above this.

A

Maximum

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11
Q

How many instances are launched when creating an auto-scaling group

A

Desired

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12
Q

Perform custom actions on instances when corresponding lifecycle events occur

A

Lifecycle Hook

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13
Q

Used for storing application logs on shutdown

A

Scaling in hooks

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14
Q

Used for installing/configuring software before instance goes online

A

Scaling out hooks

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15
Q

Vital to creating a highly available application due to spreading resources out over multiple availability zones

A

Auto Scaling Groups

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16
Q

Scaling adjustments to vary the scaling depending on the size of the alarm breach

A

Step Scaling

17
Q

Scaling which relies on metrics for scaling needs

A

Simple Scaling

18
Q

Scaling that uses a scaling metric and value that your ASG should maintain at all times

A

Target Tracking

19
Q

Stops instances from being placed behind the load balancer, failing the health check, and being terminated prematurely

A

Instance Warm-up

20
Q

Pauses auto scaling for a set amount of time

A

Instance Cooldown

21
Q

Reactive scaling, Once the load is there you measure it and determine if you need to create more instances

A

Reactive Scaling

22
Q

Scaling predictable workloads, which creates a scaling event to get resources ready before they are actually needed

A

Scheduled scaling

23
Q

Scaling using AWS machine learning algorithms to determine when to scale

A

Predictive scaling

24
Q

Resizing the database from one size to another can create greater performance

A

Vertical Scaling

25
Q

Storage can be resized but it’s only able to go up not down

A

Scaling Storage

26
Q

Creating read-only copies of our data can help spread out the workload

A

Read Replicas

27
Q

Offload scaling to AWS, excels with unpredictable workloads

A

Aurora Serverless

28
Q

Storage only scales up - it won’t scale back down.

A

RDS

29
Q

Deploy highly available Reader instance which can be used for read operations

A

Multi-AZ Cluster DB Deployments

30
Q

Cannot be used for reads or writes

A

Standby Instances

31
Q

Used when possible if the situation calls for a relational database

A

Aurora

32
Q

AWS does all the scaling when using non-relational databases

A

DynamoDB

33
Q

DynamoDB scaling is used for generally predictable workload and is the most cost-effective model

A

Provisioned

34
Q

DynamoDB scaling used for sporadic workloads, less cost-effective pay per read/write

A

On-Demand

35
Q

DynamoDB unit of measurement for reads per second for an item up to 4KB in size

A

Read Capacity Unit (RCU)

36
Q

DynamoDB unit of measurement for writes per second for an item up to 1KB in size

A

Write Capacity Unit (WCU)

37
Q
A