From the course: AWS for DevOps: High Availability and Elasticity
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Scaling EC2 with auto-scaling groups - Amazon Web Services (AWS) Tutorial
From the course: AWS for DevOps: High Availability and Elasticity
Scaling EC2 with auto-scaling groups
- [Instructor] Next let's look at scaling EC2 Instances. You want to consider using the most appropriate or best instance size, the amount of CPU, RAM, etc; type: whether it's compute optimized, memory optimized, GPU enabled or any of the other ever-growing, various options and cost: on-demand, spot or reserved. This might seem obvious but again in the most common mistakes that I see around AWS architectures it is very frequently when servers are being used around using too many or the wrong type or some combination of not-thoughtful implementation of EC2 which has resulted in some of my customers in having tens of thousands of dollars in wasted service fees, so I can not skip this. Now, that being said, once you cover the basics well then you can use sophisticated tools like the Auto Scaling tools to set event-based scaling for EC2. Now, I've included this graphic from Amazon's resources around the Auto Scaling lifecycle because I've found, in production, that it can be confusing…
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Contents
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Defining application areas and AWS services3m 59s
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(Locked)
Scaling S3: The data (file) tier6m 9s
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(Locked)
HA for EC2 via AMI, EIP, and alarms7m 17s
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(Locked)
HA for EC2 with load balancers6m 1s
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(Locked)
Scaling EC2 with auto-scaling groups6m 51s
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(Locked)
Scaling containers with ECS8m 25s
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(Locked)
Scaling Lambda: The middle tier4m 48s
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(Locked)
Scaling CloudFront: The front end5m 35s
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(Locked)
Scaling ElastiCache: The front end4m 47s
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(Locked)
Scaling Kinesis: The middle tier6m 10s
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(Locked)
Scaling DynamoDB: The database tier6m 27s
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(Locked)
Scaling RDS: The database tier5m 2s
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