1 00:00:00,690 --> 00:00:05,250 In this video, we are going to see how to recruit our lambda functions. 2 00:00:05,280 --> 00:00:09,150 That means you will see a Lambda Invocation types. 3 00:00:09,750 --> 00:00:15,180 After that, we will map these Lambda Invocation types with our course one developing serverless e-commerce 4 00:00:15,180 --> 00:00:15,960 application. 5 00:00:16,200 --> 00:00:22,860 So this Lambda Invocation types will be our serverless journey when developing our service ecommerce 6 00:00:22,860 --> 00:00:23,610 application. 7 00:00:25,330 --> 00:00:29,900 So Islam, the function is using a river for various use cases. 8 00:00:29,920 --> 00:00:37,990 Sometimes we want to invoke lambda function over HTTP and other times trigger a function based on different 9 00:00:37,990 --> 00:00:38,710 events. 10 00:00:39,570 --> 00:00:45,420 It is extremely useful to understand the different ways that we can invoke lambda function. 11 00:00:46,140 --> 00:00:50,040 Here are three different ways we can invoke lambda functions. 12 00:00:50,700 --> 00:00:54,600 You can see in here a place Lambda has three invocation types. 13 00:00:55,050 --> 00:00:57,150 Lambda Synchronous Invocation. 14 00:00:57,150 --> 00:00:59,430 Lambda Asynchronous Invocation. 15 00:00:59,490 --> 00:01:03,240 Lambda Event Source Mapping with Pulling Invocation. 16 00:01:05,000 --> 00:01:08,630 So you can all see in location types in one image. 17 00:01:08,780 --> 00:01:14,960 Synchronous invocation is triggered by push model and execute immediately and wait response. 18 00:01:14,990 --> 00:01:17,600 We can say request response model. 19 00:01:18,510 --> 00:01:23,080 Asynchronous invocation is triggered by event model and executes. 20 00:01:23,100 --> 00:01:23,990 Asynchronous. 21 00:01:24,000 --> 00:01:24,810 Don't wait. 22 00:01:24,810 --> 00:01:26,130 Immediate response. 23 00:01:26,760 --> 00:01:30,270 Event source mapping invocation is triggered by pol based. 24 00:01:30,300 --> 00:01:33,900 That means lambda function receive multiple items. 25 00:01:35,520 --> 00:01:39,810 So let's see one by one and explain these types. 26 00:01:40,470 --> 00:01:42,780 Lambda Synchronous invocation. 27 00:01:42,930 --> 00:01:47,490 This is one of the simple Lambda Invocation model in this communication type. 28 00:01:47,520 --> 00:01:53,610 Lambda functions execute immediately when you perform the Lambda Invoke by API call. 29 00:01:53,820 --> 00:02:00,990 So when we perform a Lambda Invoke an API call, we wait for the function to process the function and 30 00:02:00,990 --> 00:02:02,640 return back to the response. 31 00:02:03,060 --> 00:02:08,580 The response data includes the function response and additional data which can be retrieved from the 32 00:02:08,580 --> 00:02:11,540 Dynamo DB or some other resources. 33 00:02:11,700 --> 00:02:13,920 But the idea is we should wait. 34 00:02:13,920 --> 00:02:16,470 A response from the Synchronous Invocation. 35 00:02:18,060 --> 00:02:25,160 A common scenario for synchronous invocation is the API Gateway, Lambda and Dynamo DB integration. 36 00:02:25,170 --> 00:02:31,590 You can see in the Image API Gateway Lambda and Dynamo DB that we can perform CRUD operation for a particular 37 00:02:31,590 --> 00:02:35,910 Dynamo DB table with exposing APIs from the API gateway. 38 00:02:36,880 --> 00:02:42,760 The important thing is in here, the invocation type flag should be request response. 39 00:02:43,480 --> 00:02:50,020 This instructs a place to execute our lambda function and wait for the response or function to complete. 40 00:02:50,650 --> 00:02:57,580 When we perform the synchronous invocation, we are responsible for inspecting the response and determining 41 00:02:57,580 --> 00:03:02,410 if there was an error like time or execution and decide to retry invocation. 42 00:03:03,330 --> 00:03:10,440 We can perform synchronous requests most in location using a double CLI SDK and many other options. 43 00:03:11,370 --> 00:03:19,170 You can see an example of synchronous invocation using a double c that we are running the lambda invoke 44 00:03:19,230 --> 00:03:21,390 comments on cli. 45 00:03:21,810 --> 00:03:28,230 As you can see that when we specify the invocation type like is request response, that means it will 46 00:03:28,470 --> 00:03:34,770 execute our function and wait for the function response in order to complete and return response. 47 00:03:35,190 --> 00:03:41,400 The important part is we are responsible for checking the request, checking the response and determining 48 00:03:41,400 --> 00:03:44,280 whether it is an error or we should try the invoke. 49 00:03:44,520 --> 00:03:50,430 So in this synchronous invocation, we are waiting response and according to this response, we are 50 00:03:50,430 --> 00:03:55,320 checking the response data and it is looking for it is getting error or not. 51 00:03:55,320 --> 00:03:59,310 If it is getting error, we are going to retry the invoke again. 52 00:04:01,020 --> 00:04:07,590 There are many services that can trigger lambda function synchronously here, some of them in here. 53 00:04:07,590 --> 00:04:14,010 You can see that application load will answer Amazon Incognito, Amazon, Lakes, Alexa API, Gateway 54 00:04:14,010 --> 00:04:17,910 Cloud, Front Kinesis Data streams and so on. 55 00:04:20,380 --> 00:04:25,240 So now the second invocation type is Lambda Asynchronous invocation. 56 00:04:25,780 --> 00:04:31,900 In this communication type, Lambda function works with the events and invoke by events and not respond 57 00:04:31,900 --> 00:04:32,860 immediately. 58 00:04:33,520 --> 00:04:37,300 Basically, we can invoke a lambda function asynchronously. 59 00:04:37,480 --> 00:04:45,370 After that, Lambda sends the event an internal queue and returns a success response without any additional 60 00:04:45,370 --> 00:04:46,240 information. 61 00:04:46,840 --> 00:04:53,530 After that, a separate process reads the events from the queue and runs our lambda function. 62 00:04:54,450 --> 00:05:01,920 So you can see a common scenario for asynchronous invocation is the S3 Lambda and dynamic DB. 63 00:05:02,160 --> 00:05:13,820 You can see in the Image S3 or Amazon sense a sense trigger an event and this will be triggered a number 64 00:05:13,830 --> 00:05:19,800 asynchronously and a double is lambda interact with the dynamo db in the diagram Amazon S3 will call 65 00:05:19,820 --> 00:05:25,320 the Lambda asynchronously when a new object is written into the bucket. 66 00:05:25,950 --> 00:05:30,270 Amazon S3 has several events that can trigger to a lambda. 67 00:05:30,390 --> 00:05:36,210 For example, we can set that a new object is uploading the into bucket. 68 00:05:36,210 --> 00:05:41,580 We can trigger an event today lambda that is executed lambda function asynchronously. 69 00:05:43,110 --> 00:05:48,630 In order to invoke a function asynchronously, we should set the invocation type parameter to event. 70 00:05:48,930 --> 00:05:56,530 So it is very important you can see an example of the asynchronous invokes using the SLA. 71 00:05:57,000 --> 00:06:02,640 We can see that we are running a double lambda invoke comment and the invocation type is event. 72 00:06:02,760 --> 00:06:07,140 When we specify the invocation type, parameter value is event. 73 00:06:07,380 --> 00:06:14,190 If the function failed a the will automatically retry the invoke device because in asynchronous communication 74 00:06:14,370 --> 00:06:23,790 the lambda is automatically triggered by the triggered invoke by twice when there is an error by default. 75 00:06:23,790 --> 00:06:27,570 A double is lambda sets a retry policy for asynchronous invocations. 76 00:06:27,570 --> 00:06:35,130 Your function will be invoked twice if there is an error in order to avoid event losses when using asynchronous 77 00:06:35,130 --> 00:06:42,150 lambda, always attach a dead letter Q on the function in order to save events that weren't successfully 78 00:06:42,150 --> 00:06:42,870 processed. 79 00:06:43,840 --> 00:06:50,680 Here you can list of the services that invoke Lambda function asynchronously as you set that Amazon 80 00:06:50,680 --> 00:06:51,790 S3 event. 81 00:06:52,360 --> 00:06:58,900 SNS S is cloud formation, cloud watch looks and Events Code Command, pull, based, invokes and so 82 00:06:58,900 --> 00:06:59,230 on. 83 00:07:01,440 --> 00:07:07,470 So if you come to the last location type, which is the event source mapping with polling location, 84 00:07:08,070 --> 00:07:14,670 this is the poll based location model allows us to integrate with the police streams and queue based 85 00:07:14,670 --> 00:07:15,570 services. 86 00:07:16,230 --> 00:07:20,190 These services don't invoke a lambda function directly. 87 00:07:20,820 --> 00:07:29,550 Lambda will pull from the available case or kinesis streams, retrieve records and invoke the functions. 88 00:07:30,520 --> 00:07:37,030 A.W. Islam the event source mapping manage the polar and performs the synchronous inverse of our function. 89 00:07:37,780 --> 00:07:41,470 Data streams or cues are read in the batch. 90 00:07:41,740 --> 00:07:48,280 The function receives multiple items when executing to function, so a batch size can configure according 91 00:07:48,280 --> 00:07:49,480 to the service type. 92 00:07:49,480 --> 00:07:54,070 And after that, the event source mapping will send data according to batch size. 93 00:07:54,550 --> 00:08:01,990 If the batch size is too large to send in one event, it has to be split up, resulting in events with 94 00:08:01,990 --> 00:08:04,870 smaller number of items than the batch size. 95 00:08:05,980 --> 00:08:12,100 So you can see in the image a common scenario for event source mapping with polling location is the 96 00:08:12,520 --> 00:08:21,910 case and a lambda you can see in the image Amazon case and lambda using the event source mapping, basically 97 00:08:21,910 --> 00:08:26,380 lambda function pulling events from the case. 98 00:08:26,410 --> 00:08:30,340 Let me explain more clearly in this diagram. 99 00:08:30,340 --> 00:08:33,070 Amazon case has some key records. 100 00:08:33,070 --> 00:08:38,620 These records can be added from other services like event, SMS and so on. 101 00:08:38,620 --> 00:08:44,500 So the idea is that we have some Q message in the Amazon queue. 102 00:08:45,130 --> 00:08:53,890 After that, a lambda function, pull the events from the Amazon case and receive Q records with event 103 00:08:53,890 --> 00:08:55,450 source mapping invocation. 104 00:08:55,780 --> 00:09:02,440 So Lambda function retrieve Q records according to the batch size property of polling configuration. 105 00:09:03,220 --> 00:09:09,280 Another common scenario for one source mapping with polling location is string based processing. 106 00:09:09,640 --> 00:09:16,480 These are the Kinesis and Dynamo DC streams that can learn the pole the stream records with event source 107 00:09:16,480 --> 00:09:17,890 mapping in locations. 108 00:09:18,880 --> 00:09:21,370 So the base size property is very important. 109 00:09:21,370 --> 00:09:28,180 We give the example of the x and lambda and we said that the stream based processing by A.B. streams 110 00:09:28,180 --> 00:09:33,430 and kindness streams using the event based event source mapping location. 111 00:09:33,640 --> 00:09:39,640 And here is the list of the services that invoke Lambda functions as an event source mapping. 112 00:09:39,670 --> 00:09:45,610 These are the Amazon Kinesis, Amazon Dynamo DB and Amazon Simple Q Services. 113 00:09:47,540 --> 00:09:52,100 As you can see that we have seen several a number in location types.