1
00:00:00,240 --> 00:00:02,900
‫Now, let's talk about AWS Compute Optimizer

2
00:00:02,900 --> 00:00:05,720
‫which is used to reduce costs and improve performance

3
00:00:05,720 --> 00:00:09,370
‫by recommending optimal AWS resources for your workloads.

4
00:00:09,370 --> 00:00:11,350
‫So it's going to do an analysis

5
00:00:11,350 --> 00:00:14,340
‫of your EC2 instances, your auto scaling groups,

6
00:00:14,340 --> 00:00:15,620
‫and tell you, for example,

7
00:00:15,620 --> 00:00:18,350
‫which one are over-provisioned or under provisioned

8
00:00:18,350 --> 00:00:20,610
‫and then you can build your optimizations

9
00:00:20,610 --> 00:00:22,430
‫and then you can have a better cost perspective

10
00:00:22,430 --> 00:00:23,980
‫and also a better performance.

11
00:00:23,980 --> 00:00:25,960
‫This way it does it is that it will use machine learning

12
00:00:25,960 --> 00:00:28,650
‫under the hood to analyze your resource configuration

13
00:00:28,650 --> 00:00:30,780
‫as well as track their CloudWatch metrics

14
00:00:30,780 --> 00:00:32,800
‫to understand their utilization.

15
00:00:32,800 --> 00:00:34,840
‫So supported resources by Compute Optimizer

16
00:00:34,840 --> 00:00:37,530
‫are EC2 instances, auto scaling groups,

17
00:00:37,530 --> 00:00:39,870
‫EBS volumes, Lambda functions.

18
00:00:39,870 --> 00:00:43,070
‫And this allows you to lower your costs by up to 25%

19
00:00:43,070 --> 00:00:44,280
‫without doing much

20
00:00:44,280 --> 00:00:45,560
‫and the recommendations themselves

21
00:00:45,560 --> 00:00:47,930
‫can be exported into Amazon S3.

22
00:00:47,930 --> 00:00:49,300
‫So that's it, I hope you liked it

23
00:00:49,300 --> 00:00:51,250
‫and I will see you in the next lecture.