Whether you are building an application or planning to migrate your existing infrastructure to the cloud, if you are planning for AWS, you should go for the right component. There are more than 100 services with some advantages and disadvantages. Therefore you should go with the right service.
All companies cannot cover all the services of AWS. Some services take time before they are launched in a specific region.
You need to make sure the services your business needs are available in the chosen area.
Based on the AWS service and productivity of the particular area, the price dimension is different.
The primary reason for having an Amazon web service is to increase performance and scalability. With scalability and performance, the application will grow, which is the main objective of the investment, isn’t it?
In a few cases, AWS appears similar to the infinite source of the computing system. However, there are some limitations. These limitations may reflect in various dimensions.
• Provisioned resources like EC2 instances, IAM Roles, VPCs, S3 buckets, etc.
• Timeline of data retention, for example, SQS message retention, CloudWatch metrics.
• Throughput (i.e. concurrent Lambda executions, CloudWatch List/Describe/Put requests, SNS messages per second, Dynamo DB capacity units, EFS throughput in Gb/s)
• Payload size (i.e. SQS messages, Dynamo DB items, Kinesis records, IoT messages, IAM policy size)
• Storage size (i.e. EBS volume size)
Who does the scaling for that AWS service, and how?
When you distinguish the AWS resources and configurations that drive scale, you need to recognize who does the scaling and how it is done so you can have a strong system setup. I’ve distinguished the accompanying categories:
• Customer does the scaling. There are mechanisms to expand scale; however, they must be set off by you.
• Examples: DynamoDB limit units (if not utilizing DynamoDB Auto Scaling), Kinesis number of shards, EC2 occurrence types, RDS read copies, RDS storage increment, AWS Elasticsearch node count.
• AWS does the scaling. So you don’t need to stress over overseeing scale by any stretch of the imagination.
• Examples: Lambda work executions, S3 bucket size and number of articles, Dynamo DB table size, SQS messages each second
• Shared obligation. AWS offers automated mechanisms, yet you need to design them.
• Examples: EC2/ECS Auto Scaling, Elastic Load Balancer (arrangement and pre-warming), Dynamo DB Auto Scaling, RDS Aurora Read Replica Auto Scaling.
AWS web service has many amazingly skilled specialists prepared to forestall and resolve a wide range of disappointment scenarios. Nonetheless, disappointments in the AWS service under survey will happen now and then. If you need to limit the danger of lost revenue for your business, you need to consider the alternatives a specific AWS service provides to deal with disappointment. It’s additionally worth thinking about the fact that it is so hard to set up those mechanisms.