AWS wellarchitected documentation change
Summary
Updated documentation to consistently use 'Amazon EC2 Auto Scaling' terminology instead of generic 'Auto Scaling' references. Clarified service-specific capabilities and limitations.
Security assessment
Changes focus on terminology standardization and service-specific accuracy (EC2 Auto Scaling vs generic Auto Scaling). No security vulnerabilities, mitigations, or security features are mentioned or addressed in the diff. Updates are purely documentation clarifications for service boundaries and capabilities.
Diff
diff --git a/wellarchitected/2024-06-27/framework/cost_manage_demand_resources_dynamic.md b/wellarchitected/2024-06-27/framework/cost_manage_demand_resources_dynamic.md index 57649c136..de718b3d9 100644 --- a//wellarchitected/2024-06-27/framework/cost_manage_demand_resources_dynamic.md +++ b//wellarchitected/2024-06-27/framework/cost_manage_demand_resources_dynamic.md @@ -23 +23 @@ _Cost optimization with AWS Instance Scheduler._ -You can also easily configure schedules for your Amazon EC2 instances across your accounts and Regions with a simple user interface (UI) using AWS Systems Manager Quick Setup. You can schedule Amazon EC2 or Amazon RDS instances with AWS Instance Scheduler and you can stop and start existing instances. However, you cannot stop and start instances which are part of your Auto Scaling group (ASG) or that manage services such as Amazon Redshift or Amazon OpenSearch Service. Auto Scaling groups have their own scheduling for the instances in the group and these instances are created. +You can also easily configure schedules for your Amazon EC2 instances across your accounts and Regions with a simple user interface (UI) using AWS Systems Manager Quick Setup. You can schedule Amazon EC2 or Amazon RDS instances with AWS Instance Scheduler and you can stop and start existing instances. However, you cannot stop and start instances which are part of your Amazon EC2 Auto Scaling group (ASG) or that manage services such as Amazon Redshift or Amazon OpenSearch Service. Amazon EC2 Auto Scaling groups have their own scheduling for the instances in the group and these instances are created. @@ -25 +25 @@ You can also easily configure schedules for your Amazon EC2 instances across you -[AWS Auto Scaling](https://aws.amazon.com/autoscaling/) helps you adjust your capacity to maintain steady, predictable performance at the lowest possible cost to meet changing demand. It is a fully managed and free service to scale the capacity of your application that integrates with Amazon EC2 instances and Spot Fleets, Amazon ECS, Amazon DynamoDB, and Amazon Aurora. Auto Scaling provides automatic resource discovery to help find resources in your workload that can be configured, it has built-in scaling strategies to optimize performance, costs, or a balance between the two, and provides predictive scaling to assist with regularly occurring spikes. +[AWS Auto Scaling](https://aws.amazon.com/autoscaling/) helps you adjust your capacity to maintain steady, predictable performance at the lowest possible cost to meet changing demand. It is a fully managed and free service to scale the capacity of your application that integrates with Amazon EC2 instances and Spot Fleets, Amazon ECS, Amazon DynamoDB, and Amazon Aurora. Amazon EC2 Auto Scaling provides automatic resource discovery to help find resources in your workload that can be configured, it has built-in scaling strategies to optimize performance, costs, or a balance between the two, and provides predictive scaling to assist with regularly occurring spikes. @@ -27 +27 @@ You can also easily configure schedules for your Amazon EC2 instances across you -There are multiple scaling options available to scale your Auto Scaling group: +There are multiple scaling options available to scale your Amazon EC2 Auto Scaling group: @@ -42 +42 @@ There are multiple scaling options available to scale your Auto Scaling group: -Auto Scaling policies differ and can be categorized as dynamic and scheduled scaling policies. Dynamic policies are manual or dynamic scaling which, scheduled or predictive scaling. You can use scaling policies for dynamic, scheduled, and predictive scaling. You can also use metrics and alarms from [Amazon CloudWatch](https://aws.amazon.com/cloudwatch/) to trigger scaling events for your workload. We recommend you use [launch templates](https://docs.aws.amazon.com/autoscaling/ec2/userguide/launch-templates.html), which allow you to access the latest features and improvements. Not all Auto Scaling features are available when you use launch configurations. For example, you cannot create an Auto Scaling group that launches both Spot and On-Demand Instances or that specifies multiple instance types. You must use a launch template to configure these features. When using launch templates, we recommended you version each one. With versioning of launch templates, you can create a subset of the full set of parameters. Then, you can reuse it to create other versions of the same launch template. +Amazon EC2 Auto Scaling policies differ and can be categorized as dynamic and scheduled scaling policies. Dynamic policies are manual or dynamic scaling which, scheduled or predictive scaling. You can use scaling policies for dynamic, scheduled, and predictive scaling. You can also use metrics and alarms from [Amazon CloudWatch](https://aws.amazon.com/cloudwatch/) to trigger scaling events for your workload. We recommend you use [launch templates](https://docs.aws.amazon.com/autoscaling/ec2/userguide/launch-templates.html), which allow you to access the latest features and improvements. Not all Amazon EC2 Auto Scaling features are available when you use launch configurations. For example, you cannot create an Amazon EC2 Auto Scaling group that launches both Spot and On-Demand Instances or that specifies multiple instance types. You must use a launch template to configure these features. When using launch templates, we recommended you version each one. With versioning of launch templates, you can create a subset of the full set of parameters. Then, you can reuse it to create other versions of the same launch template. @@ -46 +46 @@ You can use AWS Auto Scaling or incorporate scaling in your code with [AWS APIs -[Elastic Load Balancing (Elastic Load Balancing)](https://aws.amazon.com/elasticloadbalancing/) helps you scale by distributing demand across multiple resources. With using ASG and Elastic Load Balancing, you can manage incoming requests by optimally routing traffic so that no one instance is overwhelmed in an Auto Scaling group. The requests would be distributed among all the targets of a target group in a round-robin fashion without consideration for capacity or utilization. +[Elastic Load Balancing (ELB)](https://aws.amazon.com/elasticloadbalancing/) helps you scale by distributing demand across multiple resources. With using ASG and ELB, you can manage incoming requests by optimally routing traffic so that no one instance is overwhelmed in an Amazon EC2 Auto Scaling group. The requests would be distributed among all the targets of a target group in a round-robin fashion without consideration for capacity or utilization. @@ -48 +48 @@ You can use AWS Auto Scaling or incorporate scaling in your code with [AWS APIs -Typical metrics can be standard Amazon EC2 metrics, such as CPU utilization, network throughput, and Elastic Load Balancing observed request and response latency. When possible, you should use a metric that is indicative of customer experience, typically a custom metric that might originate from application code within your workload. To elaborate how to meet the demand dynamically in this document, we will group Auto Scaling into two categories as demand-based and time-based supply models and deep dive into each. +Typical metrics can be standard Amazon EC2 metrics, such as CPU utilization, network throughput, and ELB observed request and response latency. When possible, you should use a metric that is indicative of customer experience, typically a custom metric that might originate from application code within your workload. To elaborate how to meet the demand dynamically in this document, we will group Amazon EC2 Auto Scaling into two categories as demand-based and time-based supply models and deep dive into each. @@ -71 +71 @@ _Time-based scaling policies_ -You can use scheduled or predictive auto scaling to implement a time-based approach. Workloads can be scheduled to scale out or in at defined times (for example, the start of business hours), making resources available when users arrive or demand increases. Predictive scaling uses patterns to scale out while scheduled scaling uses pre-defined times to scale out. You can also use [attribute-based instance type selection (ABS) strategy](https://docs.aws.amazon.com/autoscaling/ec2/userguide/create-asg-instance-type-requirements.html) in Auto Scaling groups, which lets you express your instance requirements as a set of attributes, such as vCPU, memory, and storage. This also allows you to automatically use newer generation instance types when they are released and access a broader range of capacity with Amazon EC2 Spot Instances. Amazon EC2 Fleet and Amazon EC2 Auto Scaling select and launch instances that fit the specified attributes, removing the need to manually pick instance types. +You can use scheduled or predictive auto scaling to implement a time-based approach. Workloads can be scheduled to scale out or in at defined times (for example, the start of business hours), making resources available when users arrive or demand increases. Predictive scaling uses patterns to scale out while scheduled scaling uses pre-defined times to scale out. You can also use [attribute-based instance type selection (ABS) strategy](https://docs.aws.amazon.com/autoscaling/ec2/userguide/create-asg-instance-type-requirements.html) in Amazon EC2 Auto Scaling groups, which lets you express your instance requirements as a set of attributes, such as vCPU, memory, and storage. This also allows you to automatically use newer generation instance types when they are released and access a broader range of capacity with Amazon EC2 Spot Instances. Amazon EC2 Fleet and Amazon EC2 Auto Scaling select and launch instances that fit the specified attributes, removing the need to manually pick instance types. @@ -79 +79 @@ When architecting with a time-based approach keep in mind two key considerations - * **Configure scheduled scaling:** For predictable changes in demand, time-based scaling can provide the correct number of resources in a timely manner. It is also useful if resource creation and configuration is not fast enough to respond to changes on demand. Using the workload analysis configure scheduled scaling using AWS Auto Scaling. To configure time-based scheduling, you can use predictive scaling of scheduled scaling to increase the number of Amazon EC2 instances in your Auto Scaling groups in advance according to expected or predictable load changes. + * **Configure scheduled scaling:** For predictable changes in demand, time-based scaling can provide the correct number of resources in a timely manner. It is also useful if resource creation and configuration is not fast enough to respond to changes on demand. Using the workload analysis configure scheduled scaling using AWS Auto Scaling. To configure time-based scheduling, you can use predictive scaling of scheduled scaling to increase the number of Amazon EC2 instances in your Amazon EC2 Auto Scaling groups in advance according to expected or predictable load changes. @@ -81 +81 @@ When architecting with a time-based approach keep in mind two key considerations - * **Configure predictive scaling:** Predictive scaling allows you to increase the number of Amazon EC2 instances in your Auto Scaling group in advance of daily and weekly patterns in traffic flows. If you have regular traffic spikes and applications that take a long time to start, you should consider using predictive scaling. Predictive scaling can help you scale faster by initializing capacity before projected load compared to dynamic scaling alone, which is reactive in nature. For example, if users start using your workload with the start of the business hours and don’t use after hours, then predictive scaling can add capacity before the business hours which eliminates delay of dynamic scaling to react to changing traffic. + * **Configure predictive scaling:** Predictive scaling allows you to increase the number of Amazon EC2 instances in your Amazon EC2 Auto Scaling group in advance of daily and weekly patterns in traffic flows. If you have regular traffic spikes and applications that take a long time to start, you should consider using predictive scaling. Predictive scaling can help you scale faster by initializing capacity before projected load compared to dynamic scaling alone, which is reactive in nature. For example, if users start using your workload with the start of the business hours and don’t use after hours, then predictive scaling can add capacity before the business hours which eliminates delay of dynamic scaling to react to changing traffic. @@ -83 +83 @@ When architecting with a time-based approach keep in mind two key considerations - * **Configure dynamic automatic scaling:** To configure scaling based on active workload metrics, use Auto Scaling. Use the analysis and configure Auto Scaling to launch on the correct resource levels, and verify that the workload scales in the required time. You can launch and automatically scale a fleet of On-Demand Instances and Spot Instances within a single Auto Scaling group. In addition to receiving discounts for using Spot Instances, you can use Reserved Instances or a Savings Plan to receive discounted rates of the regular On-Demand Instance pricing. All of these factors combined help you to optimize your cost savings for Amazon EC2 instances and help you get the desired scale and performance for your application. + * **Configure dynamic automatic scaling:** To configure scaling based on active workload metrics, use Amazon EC2 Auto Scaling. Use the analysis and configure Amazon EC2 Auto Scaling to launch on the correct resource levels, and verify that the workload scales in the required time. You can launch and automatically scale a fleet of On-Demand Instances and Spot Instances within a single Amazon EC2 Auto Scaling group. In addition to receiving discounts for using Spot Instances, you can use Reserved Instances or a Savings Plan to receive discounted rates of the regular On-Demand Instance pricing. All of these factors combined help you to optimize your cost savings for Amazon EC2 instances and help you get the desired scale and performance for your application. @@ -96 +96 @@ When architecting with a time-based approach keep in mind two key considerations - * Scale the size of your Auto Scaling group + * Scale the size of your Amazon EC2 Auto Scaling group @@ -111 +111 @@ When architecting with a time-based approach keep in mind two key considerations - * [ Target Tracking Scaling Policies for Auto Scaling ](https://www.youtube.com/watch?v=-RumeaoPB2M) + * [ Target Tracking Scaling Policies for Amazon EC2 Auto Scaling ](https://www.youtube.com/watch?v=-RumeaoPB2M) @@ -120 +120 @@ When architecting with a time-based approach keep in mind two key considerations - * [ Attribute based Instance Type Selection for Auto Scaling for Amazon EC2 Fleet ](https://aws.amazon.com/blogs/aws/new-attribute-based-instance-type-selection-for-ec2-auto-scaling-and-ec2-fleet/) + * [ Attribute based Instance Type Selection for Amazon EC2 Auto Scaling for Amazon EC2 Fleet ](https://aws.amazon.com/blogs/aws/new-attribute-based-instance-type-selection-for-ec2-auto-scaling-and-ec2-fleet/)