Concepts
AWS imposes default service quotas for different services to ensure fair usage and to protect the infrastructure from overuse. These quotas can be related to the number of instances, volume storage, number of buckets, etc., depending on the particular AWS service. For example, there may be a limit on how many EC2 instances you can launch within a region or how many IOPS you can provision for an EBS volume.
When configuring service quotas for a workload in a standby environment, it’s essential to strike the right balance between cost and availability. Standby environments are often used for disaster recovery (DR) purposes and may not require the full capacity of the production environment.
Configuring Service Quotas in a Standby Environment:
1. Assess Your Requirements:
Evaluate the necessary capacity for your standby environment. If it’s solely for DR, you might configure it at a fraction of your production environment’s capacity, keeping scalability in mind for when you need to ramp up.
2. Request Quota Increases:
If the default service quotas don’t meet the requirements of your standby workload, you can request quota increases through the AWS Service Quotas console or AWS CLI. For example, you might need more EC2 instances than the default limit.
AWS CLI to request quota increase example:
aws service-quotas request-service-quota-increase \
–service-code ec2 \
–quota-code L-1216C47A \
–desired-value 50
3. Monitor Quotas:
Regularly monitor your service quotas using AWS CloudWatch. This helps ensure that your standby environment is always within the desired quotas and can function effectively in case of a failover event.
4. Automate Adjustments:
Automation is key in a standby environment. Consider setting up AWS Lambda functions to adjust and monitor EC2 instances or other resource counts based on demand or a scheduled DR drill.
Handling Throttling:
In AWS, once the rate of API requests exceeds the service’s baseline limit, throttling may occur. This prevents any further API calls until the request rate is below the acceptable threshold.
Reducing Throttling Risks in a Standby Environment:
1. Exponential Backoff:
Implement exponential backoff in your application logic. This is an algorithm that progressively increases the wait time between retries after a failed API request due to throttling. AWS SDKs have built-in support for exponential backoff.
2. Caching:
Reduce the number of API calls by implementing caching mechanisms. Storing frequently accessed data can minimize the need to repeatedly call the same APIs, thereby reducing the risk of throttling.
3. Spread API Calls:
Rather than issuing a burst of API calls in a short period, distribute them evenly over time to stay within the request limit.
4. Using SQS:
Integrate Amazon Simple Queue Service (SQS) to help manage API call bursts. Requests can be queued and then processed at a controlled pace to match the service limits.
In summary, effectively managing service quotas and handling throttling are crucial for maintaining a robust standby environment in AWS. By assessing requirements, requesting increases appropriately, monitoring quotas, and reducing the risk of throttling through strategies like exponential backoff and effective API call distribution, architects can ensure that standby environments are cost-efficient and prepared for failover when necessary.
Answer the Questions in Comment Section
True or False: Service quotas in AWS are fixed and cannot be increased upon request.
- ( ) True
- ( ) False
False
Service quotas, also known as service limits, are the maximum number of resources you can create in an AWS account; many of these limits can be increased by submitting a request to AWS through the Service Quotas console or the AWS Support Center.
When approaching service quotas while scaling your workloads, what is the best practice?
- (A) Keep the default quotas and throttle your application to stay within limits.
- (B) Continuously monitor your usage and request quota increases in anticipation of growth.
- (C) Do not monitor quotas and handle limit errors as they happen.
- (D) Design your workload to use resources from multiple AWS regions to avoid service quotas.
(B) Continuously monitor your usage and request quota increases in anticipation of growth.
Best practices involve proactive monitoring of utilization and making requests for service quota increases in advance of reaching the limits to ensure uninterrupted service.
True or False: Throttling in AWS is a method that automatically scales your resource usage based on demand.
- ( ) True
- ( ) False
False
Throttling in AWS often refers to the deliberate slowing of service requests when the request rate exceeds the service quota or predefined throughput limits. It is not a scaling mechanism; AWS Auto Scaling is used for automatic scaling based on demand.
In a standby environment, how can one prevent service throttling?
- (A) By not using standby environments.
- (B) By setting appropriate alarms to monitor usage against service quotas.
- (C) By requesting an increase in service quotas well before they are reached.
- (D) By caching frequent requests.
(C) By requesting an increase in service quotas well before they are reached.
To prevent service throttling in a standby environment, it is advisable to request service quota increases in advance based on estimated growth and projected usage, ensuring resources are available when needed.
What AWS service enables you to manage and view service quotas?
- (A) AWS Identity and Access Management (IAM)
- (B) AWS Cost Explorer
- (C) AWS Service Quotas
- (D) AWS CloudFormation
(C) AWS Service Quotas
AWS Service Quotas is the AWS service that allows you to manage and view quotas for the different AWS services from a central location.
True or False: AWS throttles services at the account level, not the resource or user level.
- ( ) True
- ( ) False
False
AWS throttles service requests based on a variety of factors, including account level, resource level, and user level, depending on the particular service and usage pattern.
Which AWS service can help you in preventing and responding to service throttling events?
- (A) AWS CloudTrail
- (B) AWS CloudWatch
- (C) AWS Config
- (D) Amazon S3
(B) AWS CloudWatch
AWS CloudWatch can monitor your usage and Service Quotas to create alarms that help you take action or automate responses to service throttling events.
What should you do when you receive an error indicating that a service quota has been exceeded?
- (A) Immediately request a quota increase for the affected service.
- (B) Throttle back your application’s usage to stay within the quota.
- (C) Load balance the application’s traffic to another AWS region.
- (D) Review your application’s architecture for inefficiencies.
(A) Immediately request a quota increase for the affected service.
When a service quota is exceeded and an error is received, requesting a quota increase is essential to restore service, though it is also wise to check the application’s resource utilization patterns for efficiency improvements.
True or False: It is possible to automate the monitoring of service quotas and alert notifications with AWS services.
- ( ) True
- ( ) False
True
It is possible to automate service quota monitoring and alert notifications using AWS CloudWatch along with Amazon Simple Notification Service (SNS) for sending alerts.
What is the purpose of AWS Service Quotas’ Request Quota Increase feature?
- (A) To lower the existing service quotas for cost saving.
- (B) To temporarily extend quotas for one-time large-scale operations.
- (C) To permanently increase service quotas to accommodate growth.
- (D) To configure autoscaling for AWS resources.
(C) To permanently increase service quotas to accommodate growth.
The Request Quota Increase feature of AWS Service Quotas is used to permanently raise the service quotas for your resources in an AWS account to support higher usage and growth.
True or False: Setting a CloudWatch alarm for 80% usage of a key service quota can help avoid service disruption due to throttling.
- ( ) True
- ( ) False
True
Setting CloudWatch alarms at a certain threshold of quota consumption allows for the proactive management of service quotas to avoid service disruptions.
When an AWS service is throttled, what HTTP status code is commonly returned by the AWS API?
- (A) 400 Bad Request
- (B) 403 Forbidden
- (C) 429 Too Many Requests
- (D) 503 Service Unavailable
(C) 429 Too Many Requests
When AWS service throttling occurs due to reaching a service rate limit, the AWS API typically returns the HTTP 429 Too Many Requests error code.
Great blog post! Helped me understand service quotas better.
How exactly do you configure service quotas for a workload in a standby environment?
Can anyone explain the difference between service quotas and throttling?
Thanks for this detailed guide!
This post was very informative. I’ve been struggling with service quotas for a while.
Excellent explanation. Could someone please give an example of setting up service quotas for RDS?
What happens if we exceed a service quota?
Nice article!