Amazon Glue AWS is a fully managed ETL service providing an underlying engine to process the data, making it easy for clients to manage data. Amazon Glue: Seamless Solution to Serverless Computing
AWS Glue is a Serverless ETL (Extract, Transform, Load) service which makes it effortless for clients to construct and load their data for analytics. ETL service makes our data movable between various data sources. AWS Management Console is used to create and run ETL job script with just a few clicks. AWS Glue points to the data stored on AWS, finds the data, and stores metadata in the AWS Glue Data Catalog. Once the metadata is cataloged, your data can be searchable and available for ETL. Know more about Continuous ETL here.
AWS provides the capability to focus more on code than to think about where my code will run. All the infrastructure set up is handled by third party services on the cloud. Data is stored on Amazon S3 data stores and resides in the cloud from where we can store or retrieve data anytime and anywhere. It doesn’t mean that you don’t have servers. Indeed, you don’t have to set up the infrastructure of servers or buy them.
It acts as data storage that stores data on the cloud. Data can be located in the AWS Data Lake with the help of AWS Glue, which helps to maintain the catalog of the data.
The architecture of Amazon Glue AWS comprises of below mentioned bulleted points that are needed to take note of:
Businesses need to understand serverless application with major pros and cons of serverless architecture, before deciding about serverless computing.
Bypass the complex middleware and consider a lightweight node.js implementation to deploy serverless functions from your mainframe CICS applications.
Happy Serverless September 2020! We at Coding Sans love working with serverless technology. This is why we decided to publish a report with the latest serverless trends this year. We partnered up with nine other companies who share our love to make it happen.
In this post, I will go through the process of predicting key performance characteristics and the cost of scale-per-request serverless platforms (like AWS Lambda, IBM Cloud Functions, Azure Functions, and Google Cloud Functions) with different workload intensities (in terms of requests per second) using a performance model.
Serverless computing promises greater scalability, faster development, more efficient deployment, and lower cost.