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myTectra AWS Lambda Training: Learn how to Compute Code Serverless using Lamda, continuous scaling, triggers, orchestration, aws setup functions. Expertise in amazon s3 to trigger AWS lambda in order to process the data instantly after uploading, streaming data, data cleansing, how to build serverless, mobile, IoT backends., etc. Enroll & Become Certified!
After completion of the course, the following are the topics you will learn about:
Here, instead of giving a general overview, we should include specific users, who should really benefit from learning this technology.
The following are the prerequisites required for learning this course:
You can also go through our self paced videos on
Here, we should include core skills that the user gains upon completion of the training course.
This course will help the individuals to understand the concepts of Lambda:
Introduction to computer services and their benefits:
The current generation always focuses on getting the information in a quick and the easiest way.
To do so, the current generation is completely dependant on using computer systems wherever it is possible to automate their daily tasks. In real-time scenarios the use of computers or computer services are utilized in the following areas:
The word Serverless completely describes Lambda style paradigm. This is the future and most organizations are already started utilizing this. All the big companies like Google, Microsoft, and IBM who are into cloud infrastructure have started building their own version of Lambda to the market space.
So what is the fuss about Serverless computing and why it is classified as paramount in the technology world?
Serverless Computing:
Serverless computing can be defined as a process where the code execution and management are completely done by the system supervision and no manual intervention is needed. The code can be executed and when there is an external event is triggered and the code version and the resources needed to execute the same are all managed by the computer system itself and code execution happens. This eliminates the organizations to have 24/7 cloud computing platforms where it results in extra bills because they have been monitored and managed all the time to support the application that is executed in the instance.
Benefits of Serverless Computing:
One can completely focus on application functionality and the code. All the execution and management are taken care of by the Lambda environment.
With the use of Lambda, platform one doesn’t need to maintain the cloud infrastructure 24/7 and no one needs to have a close eye on the execution environment. It only runs when the code is executed and the execution happens only when there is an external event triggered.
These are best suitable for short-duration and single event transactions types. They are a terrible match for traditional virtual machines
The use of AWS services enables you to add custom logic to the AWS resources ( like Amazon S3 bucket, Amazon DynamoDB, etc). Thus making it easy to apply and compile the data so that it goes into the cloud itself.
The use of custom back-end services are definitely needed and avails the following benefits:
These custom events can be triggered on the client-side
Battery drains and enables easier updates
All this can happen with the use of custom back-end services.
If you are a first-time user then we recommend you to follow all the introductory videos of this service so that you will get used to it. A lot of use cases are available to cater to this.
One should understand the programming model and deployment options that are available within Lambda functions. Without any proper knowledge, it will be difficult for the teams to effectively utilize this.
Understand the console-based lambda functions. This is vital for overall execution.
Make sure you are under the code storage limit.
Please do take measures to control the dependencies in the functional deployment package.
Make sure to use environment variables to execute operational parameters
Understanding and executing the runtime necessities under minimum deploying package size.
Minimize the use of complex frameworks like Spring Framework and incorporate simpler frameworks like Java dependency injection like Dagger and Guice.
One has to understand the limitations that are associated while using AWS Lambda
|
Resource |
Limitations |
|
Memory Allocation |
Minimum is 128 MB, Maximum is 1536 MB |
|
Ephemeral disk capacity should be |
512 MB |
|
Number of file descriptors |
1024 |
|
Maximum execution duration per request |
1024 |
An event model or event in an AWS service is a developer who created an application that is used to trigger a function to execute and run.
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