From the course: AWS for DevOps: High Availability and Elasticity
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Scaling DynamoDB: The database tier - Amazon Web Services (AWS) Tutorial
From the course: AWS for DevOps: High Availability and Elasticity
Scaling DynamoDB: The database tier
- [Narrator] As we're continuing to look at persistence or data options and high availability and elasticity. Let's look now at Amazon's no sequel manage offering or DynamoDB, so the idea here is that if you need the persistence in your application, you can work with a fully managed set of no sequel services. In Dynamo as you'll see, there is no concept of a machine or a server or even a database. What you create are scalable tables and these tables are implemented as no sequel. What that means is you can pretty much put almost anything into the table and when you go to read it out, you then impose a schema on read, so that you can get the information out in a format that you need. Now, although the fully managed aspect can be very, very useful in your application architecture, what I found in the real world is if your developers have no experience with no sequel, it can be quite daunting to switch from a relational model to a no sequel model, so if you are going to go down this path,…
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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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