NAVIJO ON CLOUD

 In this blog, I will look at some of the ways to schedule and/or run job/batch-jobs in AWS using AWS native services. In Part 2 of the post, I will talk about how to extend your current on premise job schedule to AWS.  1)       Using AWS Lambda –               An AWS Lambda can be triggered via several ways. The most common way will be to trigger by a file upload to S3. Create your  AWS  Lambda function and set the trigger. Your trigger can be a file upload to S3. The moment a file is uploaded it executes the  AWS  Lambda which contains your execution code.                   Considerations for using  AWS  Lam bda – a.     When processing large files use AWS Lambda as a trigger rather than a file processor. For example - lets say your requirement is to load fact and dimension files into Amazon Redshift, and you are using Amazon QuickSight to reports on Amazon Redshift. Considering the time and payload limits of AWS Lambda, a suggested architecture in this scenario would be to us

AWS lists over 100 services today. The speed at which AWS has released these services and the number of enhancements to each of these services overtime is remarkable.  However, in my opinion, of all the service announcements and enhancements, three of them deserve special credit. These three played a pivotal role in popularizing Cloud and AWS, and helped catapult AWS to the top. 1)       Public launch of Amazon S3 in early 2006 2)       Public launch of Amazon EC2 in mid 2006 (Remember EC2-Classic) 3)        Amazon   EC2- Classic to  Amazon  EC2-VPC in 2013 (Many people I have spoken to think of AWS and Cloud, as the future; the new shiny object. I get a surprised look almost every time I tell people  Amazon  S3 and  Amazon  EC2 were introduced back in 2006; so AWS is not new). Compute and/or Storage are the backbone of software applications.  Amazon  S3 being scalable, durable and most primarily low cost, redefined storage.  Spinning up a server when you want, not having to wa