Amazon AutoScaling Implementation
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Amazon AutoScaling Implementation

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Questions and Answers

What is the primary purpose of Amazon AutoScaling?

  • To automatically scale EC2 capacity based on user-defined conditions (correct)
  • To manually increase server capacity during peak times
  • To provide fixed pricing for EC2 instances
  • To create static EC2 instances regardless of workload
  • What is the role of the launch configuration in the AutoScaling process?

  • It sets the pricing plan for EC2 instances
  • It contains instructions on how to launch new instances (correct)
  • It allocates storage for the EC2 instances
  • It determines the maximum number of instances in an AutoScaling group
  • How is the scale up policy defined in AutoScaling?

  • By configuring a fixed number of instances to be added each time
  • By setting a threshold for network bandwidth usage
  • By setting adjustment type to IncreaseInstances and adjustment amount of 1
  • By using adjustment type ChangeInCapacity with a scaling adjustment of 1 (correct)
  • What metric is used to define the scale up alarm in the AutoScaling example?

    <p>CPUUtilization</p> Signup and view all the answers

    What threshold must be met for the scale down alarm to trigger?

    <p>Average CPU utilization must be less than 50%</p> Signup and view all the answers

    In the AutoScaling process, which AWS service is primarily used to trigger scaling policies?

    <p>Amazon CloudWatch</p> Signup and view all the answers

    What function is used to create a connection to the AutoScaling service?

    <p>boto.ec2.autoscale.connect_to_region</p> Signup and view all the answers

    Which of the following parameters is NOT included in the settings for an AutoScaling group?

    <p>Network speed limit</p> Signup and view all the answers

    Study Notes

    Amazon AutoScaling

    • Amazon AutoScaling allows users to automatically scale Amazon EC2 capacity up or down based on predefined conditions.
    • AutoScaling helps manage application performance by increasing the number of EC2 instances during workload spikes and reducing instances during low workloads to save costs.
    • AutoScaling can be used for IoT applications and platforms deployed on Amazon EC2.

    AutoScaling Implementation Example

    • The text provides a Python code example for creating an AutoScaling group.
    • The code establishes a connection to the AutoScaling service using boto.ec2.autoscale.connect_to_region.
    • A launch configuration is created with details like AMI-ID, instance type, and security groups.
    • An AutoScaling group is created with settings including maximum and minimum instances, launch configuration, availability zones, and an optional load balancer.
    • Scaling policies are defined for both up and down scaling, using a ChangeInCapacity adjustment type and a scaling adjustment value.
    • Amazon CloudWatch alarms trigger the scaling policies.
    • The up-scaling alarm uses CPUUtilization metric with an average statistic and threshold of 70% for 60 seconds.
    • The down-scaling alarm uses a similar structure, with a threshold of 50%.

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    Description

    The third step in the IoT design methodology is to define the Domain Model. The domain model describes the main concepts, entities and objects in the domain of lot system to be designed. Domain model defines the attributes of the objects and relationships between objects. Domain model provides an abstract representation of the concepts, objects and entities in the IoT domain, independent of any specific technology or platform. With the domain model, the IoT system designers can get an understanding of the IoT domain for which the system is to be designed. Figure 5.3 shows the domain model for the home automation system example. The entities, objects and concepts defined in the domain model include:

    Physical Entity: Physical Entity is a discrete and identifiable entity in the physical environment (e.g. a room, a light, an appliance, a car, etc.). The IoT system provides information about the Physical Entity (using sensors) or performs actuation upon the Physical Entity (e.g., switching on a light). In the home automation example, there are two Physical Entities involved - one is the room in the home (of which the lighting conditions are to be monitored) and the other is the light appliance to be controlled.

    Virtual Entity: Virtual Entity is a representation of the Physical Entity in the digital world. For each Physical Entity, there is a Virtual Entity in the domain model. In the home automation example, there is one Virtual Entity for the room to be monitored, another for the appliance to be controlled.

    • Device: Device provides a medium for interactions between Physical Entities and Virtual Entities. Devices are either attached to Physical Entities or placed near Physical Entities. Devices are used to gather information about Physical Entities (e.g., from sensors), perform actuation upon Physical Entities (e.g. using actuators) or used to identify Physical Entities (e.g., using tags). In the home automation example, the device is a single-board mini computer which has light sensor and actuator (relay switch) attached to it.

    Resource Resources are software components which can be either "on-device" or "network-resources". On-device resources are hosted on the device and include software components that either provide information on or enable actuation upon the Physical Entity to which the device is attached. Network resources include the software components that are available in network (such as a database). In the home automation example, the on-device resource is the operating system that runs on the single-board mini computer.

    Service: Services provide an interface for interacting with the Physical Entity. Services access the resources hosted on the device or the network resources to obtain information about the Physical Entity or perform actuation upon the Physical Entity.

    wernet of Things A Hands-On Approach

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