1 00:00:00,270 --> 00:00:01,550 ‫Okay, so we've seen CloudWatch 2 00:00:01,550 --> 00:00:02,383 ‫throughout the course, 3 00:00:02,383 --> 00:00:03,960 ‫but let's just go and do a quick summary on it. 4 00:00:03,960 --> 00:00:05,410 ‫So first CloudWatch metrics, 5 00:00:05,410 --> 00:00:08,120 ‫it's going to provide metrics for every service in AWS, 6 00:00:08,120 --> 00:00:10,141 ‫and you need to understand what the metric means. 7 00:00:10,141 --> 00:00:12,350 ‫So usually the name of the metric gives you 8 00:00:12,350 --> 00:00:13,730 ‫a pretty good indication of what it is. 9 00:00:13,730 --> 00:00:16,100 ‫For example, CPU Utilization, NetworkIn, 10 00:00:16,100 --> 00:00:18,709 ‫and then based on how the metric is behaving, 11 00:00:18,709 --> 00:00:21,820 ‫it gives you an idea of how the service is behaving, 12 00:00:21,820 --> 00:00:23,887 ‫and you can do some troubleshooting based on this. 13 00:00:23,887 --> 00:00:25,910 ‫So metrics belong to namespaces, 14 00:00:25,910 --> 00:00:27,388 ‫and then you have a dimension, 15 00:00:27,388 --> 00:00:29,390 ‫which is an attribute of a metric, 16 00:00:29,390 --> 00:00:31,870 ‫for example, instance id, environments, 17 00:00:31,870 --> 00:00:32,703 ‫et cetera, et cetera, 18 00:00:32,703 --> 00:00:35,476 ‫and you can choose up to 30 dimensions per metric. 19 00:00:35,476 --> 00:00:37,040 ‫Metrics will have timestamps, 20 00:00:37,040 --> 00:00:40,470 ‫and you can create CloudWatch dashboards of metrics. 21 00:00:40,470 --> 00:00:43,150 ‫So in this course we've seen EC2 metrics for example, 22 00:00:43,150 --> 00:00:46,170 ‫and we also seen the EC2 detailed monitoring. 23 00:00:46,170 --> 00:00:49,270 ‫So we know that by default EC2 instances will have 24 00:00:49,270 --> 00:00:50,800 ‫metrics every five minutes, 25 00:00:50,800 --> 00:00:54,270 ‫but if you enable detailed monitoring for a cost, 26 00:00:54,270 --> 00:00:55,250 ‫it's additional, 27 00:00:55,250 --> 00:00:58,564 ‫then you're going to get data of metrics every one minute. 28 00:00:58,564 --> 00:01:00,890 ‫And if you enable this, then for example, 29 00:01:00,890 --> 00:01:03,670 ‫you're going to be able to react faster to changing metrics 30 00:01:03,670 --> 00:01:06,200 ‫for your EC2 instances and it gives you some benefits for 31 00:01:06,200 --> 00:01:09,175 ‫your ASG, if you want to scale out and in faster. 32 00:01:09,175 --> 00:01:11,290 ‫Now, the feature allows you to get 10 33 00:01:11,290 --> 00:01:12,616 ‫detailed monitoring metrics. 34 00:01:12,616 --> 00:01:16,220 ‫And the thing to note is that the Institute memory usage, 35 00:01:16,220 --> 00:01:18,750 ‫so your Ram, is not pushed by default and needs to be pushed 36 00:01:18,750 --> 00:01:20,880 ‫from the instance as a custom metric. 37 00:01:20,880 --> 00:01:22,910 ‫And we'll have a look at how to push custom metrics 38 00:01:22,910 --> 00:01:23,743 ‫very, very soon. 39 00:01:24,670 --> 00:01:27,110 ‫So when you are in the CloudWatch dashboard 40 00:01:27,110 --> 00:01:27,943 ‫on the left hand side, 41 00:01:27,943 --> 00:01:30,320 ‫there is metrics and you can find all the metrics. 42 00:01:30,320 --> 00:01:31,153 ‫And as you can see, 43 00:01:31,153 --> 00:01:33,400 ‫we see all the namespaces in here for our metrics. 44 00:01:33,400 --> 00:01:36,210 ‫If we have a look, we have based on services, for example, 45 00:01:36,210 --> 00:01:39,430 ‫ELB auto-scaling EBS, EC2, EFS and so on. 46 00:01:39,430 --> 00:01:43,530 ‫So a lot of information given you given to you here, 47 00:01:43,530 --> 00:01:44,696 ‫so we can click on EC2, 48 00:01:44,696 --> 00:01:46,950 ‫And we can have a per instance metric, 49 00:01:46,950 --> 00:01:49,880 ‫just to see one metric and I'm going to type credits 50 00:01:49,880 --> 00:01:52,220 ‫to see the CPU credit balance. 51 00:01:52,220 --> 00:01:53,900 ‫For example, I will take this instance, 52 00:01:53,900 --> 00:01:56,010 ‫which was created a long time ago. 53 00:01:56,010 --> 00:01:58,070 ‫And then what I'm going to do is I'm going to choose a 54 00:01:58,070 --> 00:01:59,510 ‫custom range, 55 00:01:59,510 --> 00:02:03,850 ‫which is going to be a one month to find some data in here. 56 00:02:03,850 --> 00:02:05,240 ‫Okay, so we have the data here. 57 00:02:05,240 --> 00:02:06,810 ‫And so the cool thing in CloudWatch metrics 58 00:02:06,810 --> 00:02:08,174 ‫is that you can just click 59 00:02:08,174 --> 00:02:10,770 ‫and select the time span you want. 60 00:02:10,770 --> 00:02:11,627 ‫And here we go, 61 00:02:11,627 --> 00:02:13,740 ‫we're getting some information around our metrics. 62 00:02:13,740 --> 00:02:16,750 ‫As you can see, we get metrics every five minutes here. 63 00:02:16,750 --> 00:02:19,380 ‫So every data point is every five minutes because detailed 64 00:02:19,380 --> 00:02:22,120 ‫monitoring was not enabled for this instance, okay. 65 00:02:22,120 --> 00:02:23,580 ‫But if I did enable detailed monitoring, 66 00:02:23,580 --> 00:02:25,181 ‫I would get data every one minutes. 67 00:02:25,181 --> 00:02:28,037 ‫So this is just the basics of quality metrics and nothing 68 00:02:28,037 --> 00:02:31,140 ‫too fancy, but we can definitely filter by time. 69 00:02:31,140 --> 00:02:34,680 ‫We can view it as a different lines or stacked area or line 70 00:02:34,680 --> 00:02:37,960 ‫or number or a pie chart. You can add it to a dashboard. 71 00:02:37,960 --> 00:02:39,700 ‫You can download as a CSV, you can share it. 72 00:02:39,700 --> 00:02:41,950 ‫Okay, So cloud metric is very, very handy. 73 00:02:41,950 --> 00:02:44,231 ‫And you can have a look at all the metrics, you know, 74 00:02:44,231 --> 00:02:46,070 ‫based on the region you want, 75 00:02:46,070 --> 00:02:47,900 ‫based on the dimension you want, 76 00:02:47,900 --> 00:02:49,984 ‫the resource you want, so you can filter everything. 77 00:02:49,984 --> 00:02:51,380 ‫So that's it for closure metrics. 78 00:02:51,380 --> 00:02:54,380 ‫I hope you liked it. And I will see you in the next lecture.