Now Europe (Frankfurt) region can use Amazon Aurora Serverless with PostgreSQL compatibility

Amazon Aurora is a completely organized relational database which unites the performance and availability of high-end commercial databases with the ease and cost-efficiency of open source databases. Aurora Serverless is an on-demand, auto-scaling configuration for Amazon Aurora (MySQL-compatible and PostgreSQL-compatible editions), where the database will automatically start up, shut down, and scale capacity up or down based on your application's needs. It's an easy, cost-efficient alternative for unusual, irregular, or uncertain workloads. Further, you do not have to provide or handle database capacity while using Amazon Aurora Serverless. Only you have to create an endpoint using the Amazon RDS Management Console, and Aurora Serverless manages the remaining. Only you have to pay for the database resources you utilize, on a per-second basis and you don't charge for the database instance except if it's really ongoing. Amazon Aurora Serverless with PostgreSQL compatibility feature is now accessible in Europe (Frankfurt) region. With this feature expansion, it is currently available in the US East (N. Virginia), US East (Ohio), US West (Oregon), EU (Ireland), EU (Frankfurt) and Asia Pacific (Tokyo) regions. To know more information on Aurora Serverless, read AWS Blog, the Aurora Serverless product page, and in the Aurora documentation.

AWS PrivateLink now assisted by Amazon RDS Data API

Now AWS PrivateLink can utilise Amazon RDS Data API secretly for Aurora Serverless from your Amazon VPC excluding public IPs, and traffic to travel through the Internet. Amazon RDS Data API allows you to concentrate on creating your applications keeping out all trouble of handling database connections or connection pools. HTTPS is use to transmit with your Aurora cluster by Amazon RDS Data API and is sheltered through SSL and IAM authentication. AWS PrivateLink offers individual connectivity between VPCs, AWS services, and on-premises applications, safely on the Amazon network. Now Amazon RDS Data API users can utilise private IP connectivity and security groups to fulfil their particular compliance needs. By utilising AWS PrivateLink you can run SQL statements with the help of Data API, during clarifying your internal network architecture. Now you don’t require to utilise an Internet Gateway, Network Address Translation (NAT) devices, or firewall proxies to join to RDS Data API. Create an interface VPC endpoint for Data API for Aurora Serverless in your VPC with the Amazon VPC console, SDK, or CLI to use AWS PrivateLink. Additionally, you can access the VPC endpoint from on-premises environments or from other VPCs using AWS VPN, AWS Direct Connect, or VPC Peering. This Amazon RDS Data API is accessible in US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), and Asia Pacific (Tokyo) Regions. To get further details, read documentation, or get started in the AWS Console.

Launching AWS Amplify for iOS and Android

AWS Amplify is an easy open-source development platform for creating secure, scalable, cloud-enabled mobile and web applications covering of libraries, UI components, and a CLI toolchain. It makes simple for you to verify users, securely save data and user metadata, approved selective access to data, integrate machine learning, analyse application metrics, and run server-side code. The Amplify libraries and CLI, part of the Amplify Framework, are open source and provide a pluggable interface which allows you to modify and design your personalised plugins. AWS Amplify includes an entire mobile application development workflow from version control, code testing, to production deployment, and it smoothly scales with your business from thousands of users to tens of millions. At AWS re:Invent 2019, AWS launching a preview of Amplify iOS and Amplify Android open source libraries that allow mobile developers to create scalable and secure cloud powered serverless applications. Adding competencies like Analytics, AI/ML, API (GraphQL and REST), DataStore, and Storage to their mobile applications using these Amplify libraries can be seamless for developers. The Amplify iOS and Android libraries are use case-centric, in contrast to the AWS service-centric Mobile SDKs, and offer a declarative interface which allows mobile developers to programmatically implement best practices with concepts occurring in a quick development cycle and shorter lines of codes. Also this release adds assistance for the Predictions category in Amplify iOS which enables developers to simply add and configure AI/ML related use cases in their iOS applications with less lines of code. Developers can fulfil use cases like text translation, speech to text generation, image recognition, text to speech, and insights from text using the Predictions category in the new Amplify iOS library and the Amplify CLI. No machine learning expertise needed. The supported use cases leverage services like Amazon Rekognition, Amazon Translate, Amazon Polly, Amazon Transcribe, Amazon Comprehend, and Amazon Textract. To know more about how to use the Amplify iOS and Amplify Android, read aws blog post.

Amazon Athena provides assistance for User Defined Functions (UDF)

Amazon Athena is an interactive query service which makes simple to study data straight in Amazon S3 with the help of standard SQL. You do not need to handle any infrastructure as Amazon Athena is serverless. Athena is simple to utilize. Simply point to your data in Amazon S3, specify the schema, and begin querying using standard SQL to execute ad-hoc queries and you will get results within seconds with few clicks in AWS management console. There is no necessity for complex ETL jobs to make your data for analysis with Amazon Athena. This makes it simple to SQL expertise to faster explore large-scale datasets. Now Amazon Athena offers new feature i.e. user-defined functions (UDFs), a feature which allows users to write custom scalar functions and call them in SQL queries. While Amazon Athena presents built-in functions, UDFs allow users to execute custom processing like compressing and decompressing data, redacting sensitive data, or applying customized decryption. Using Athena Query Federation SDK users can write their UDFs in Java. When a UDF is used in a SQL query submitted to Athena, it is called and performed on AWS Lambda. UDFs can be utilized in both SELECT and FILTER clauses of a SQL query. Users can call several UDFs in the same query. This new Athena UDF feature is accessible in Preview mode in the us-east-1 (N. Virginia) region. You can follow these steps to start your Preview. To know more on User Define Functions (UDF), read documentation. You can get UDF example implementations here. And to know further how to write your functions with Athena Query Federation SDK, go through this link.

AWS Glue gives power to apply custom certificates for JDBC Connections

AWS Glue is an entirely organized extract, transform, and load service (ETL Service) which helps to make it easier and cost-effective to classify your data, clean it, enrich it, and transfer it securely between different data stores. AWS Glue contains a central metadata repository known as the AWS Glue Data Catalog. This Glue Data Catalog is an ETL engine which automatically produces Python or Scala code, and a flexible scheduler that takes care of dependency resolution, job monitoring, and retries. There is no infrastructure required to setup or manage as AWS Glue is serverless. Now custom certificates can be used in AWS Glue during JDBC connections to join to your data sources from Glue ETL jobs and crawlers. You may choose to apply custom certificates because you got a certificate from a third party supplier, or since the default certificates supported by AWS Glue do not fulfil your needs. Earlier, you were solely allowed to implement the default certificates offered by AWS Glue. Now this feature is accessible in every region where AWS Glue is available. Read the documentation to know further.

Interface VPC endpoint offered by Amazon Athena

Amazon Athena is easy to use interactive query service which is simple to scan data with the help of standard SQL in Amazon S3. Athena is serverless, so there is no infrastructure to run, and you charge for the queries that you execute. Amazon Athena lets you to join to Athena through an interface VPC endpoint in your Virtual Private Cloud (VPC). You can submit your queries to Athena certainly excluding the need of Internet Gateway in your VPC using this new feature. You can get started with AWS Command Line Interface (AWS CLI) or AWS Management console to create an interface VPC endpoint to join to Amazon Athena. You must join from an instance to utilise Amazon Athena which is inside the VPC or join your private network to your VPC with the help of Amazon VPN (Virtual Private Network) or AWS Direct Connect. To know further about this feature, refer Creating an Interface Endpoint. This feature is accessible in every AWS Regions where Amazon Athena is obtainable excluding EU (Stockholm) and US (GovCloud). There are no extra charges for Amazon Athena to utilize this feature. Interface VPC endpoint charges apply. To read more on this feature, go through the documentation.

Now Amazon EventBridge is accessible in AWS Middle East (Bahrain) AWS Region

Amazon EventBridge is a serverless event bus service which is simple to join your applications with data from a multiple sources. Amazon EventBridge provides a stream of real-time data from your individual applications, Software-as-a-Service (SaaS) applications like Zendesk, Datadog, and Pagerduty, and AWS services and routes that data to targets like AWS Lambda. You can assign routing rules to find out where to transmit your data to create application architectures which proceed in real time to each of your data sources. Amazon EventBridge permits you to design event driven architectures, which are loosely coupled and distributed. Now you can utilize Amazon EventBridge to simply join applications together in the AWS Middle East (Bahrain) AWS Region. Amazon EventBridge makes it simple to create event-driven applications, as EventBridge handles event ingestion and delivery, security, authorization, and error handling. To get the complete list of AWS Region where Amazon EventBridge is accessible, refer AWS Region table. To begin with the EventBridge, you can use AWS Management Console, Command Line Interface (CLI), or SDK.

Now AWS Glue assists wheel files as dependencies for Glue Python Shell jobs

AWS Glue is an ETL service (extract, transform, and load) that is completely organized to make it easy to classify your data, polished it, enhance it, and transfer it accurately between different data stores. AWS Glue made up of a central metadata repository called as AWS Glue Data Catalog, an ETL engine that automatically creates Python or Scala code, and a flexible scheduler that handles dependency resolution, job monitoring, and retries. AWS Glue is serverless, so there’s no infrastructure to set up or manage. Earlier, you just allowed to add python dependencies with the help of egg files to AWS Glue Python Shell jobs. Now, with the help of wheel files, you can add python dependencies to AWS Glue Python Shell jobs, allowing you to get benefits of new potentials of the wheel packaging format. And now this feature is accessible in every AWS Region where AWS Glue is accessible. To get the complete list of AWS Region where AWS Glue is available, refer AWS Region page. To read more about this feature, read documentation.

Data API Assisted By Amazon Aurora Serverless PostgreSQL

You can access Amazon Aurora Serverless PostgreSQL with the help of built-in Data API, that allows you to access Aurora Serverless with web services-based applications. Specially, Amazon Aurora can be accessed seamlessly from AWS Lambda, AWS AppSync, and AWS Cloud9. The Data API lets you concentrate on creating your applications excluding all troubles of handling database connections or connection pools. Rather, you can use SQL commands against Amazon Aurora Serverless cluster by only calling HTTPS API endpoint offered by the Data API. The Data API handles database connections and returning data. As Data API holds database credentials saved in AWS Secrets Manager, you don’t require to give credentials in API calls. The users utilizing AWS Lambda, the Data API gives a certain method to access your database excluding the extra raised for Lambda functions to be initiated in Amazon VPC. Integration with the AWS SDK gives programmatic interface to run SQL statements with parameters, transaction execution, and batch updates. Data API is accessible US East (N.Virginia, Ohio), US West (Oregon), Asia Pacific(Tokyo) and Europe(Ireland) AWS Regions. And it supports PostgreSQL-compatible and MySQL-compatible Aurora Serverless databases. To get further information to start with Data API containing directions, refer documentation.

Now Amazon Athena helps querying data in Amazon S3 Requester Pays buckets

Amazon Athena is an interactive query service which makes it simple to examine data straight in Amazon Simple Storage Service (Amazon S3) with the help of standard SQL. You can point Athena at your data stored in Amazon S3 using few clicks in the AWS Management Console and start utilizing standard SQL to execute ad-hoc queries and obtain results within seconds. There is no infrastructure to set up or manage as Athena is serverless, so you just charge for the queries you execute. Athena scales automatically—running queries simultaneously —so results are fast, even with large datasets and complex queries. Now Amazon Athena helps querying data in Amazon S3 Requester Pays buckets. Using this new launched feature, Athena workgroup administrators can configure workgroup settings to permit members to reference S3 Requester Pays buckets in queries. Once configured, the requester, rather than the bucket owner, pays for the Amazon S3 request and data transfer charges related to the query. Refer Create a Workgroup from Amazon Athena User Guide to know how to configure this setting for your workgroup. And to read further on Requester Pays buckets, click Requester Pays Buckets in the Amazon Simple Storage Service Developer Guide.

Nested Workflows Offered By AWS Step Functions

AWS Step Functions allows you collaborate several AWS services into serverless workflows so that you can create and update apps faster. You can build and execute workflows which frame jointly services with the help of AWS Step Functions like AWS Lambda and Amazon ECS into feature-rich applications. Workflows are consists of a sequence of steps, with the output of one step functioning as input into the next. Now AWS Step Functions permits you to organize intricate methods by composing modular, reusable workflows. As companies utilize workflows very largely, their workflows get complex to create, check, and modify. Frequent workflow methods are usually repeated in different locations. With nesting your Step Functions workflows, you can create greater, very tangle workflows out of smaller, simpler workflows. AWS Step Functions lets you to exchange and restructure workflow modules excluding customizing code. This permits you to build new workflows from your current workflows in minutes. You can start a nested workflow execution from just one workflow step. You can configure your workflow to launch a nested workflow with the help of code snippets in the console. No extra cost for initiating a nested workflow. Nested workflows are charged same as each Step Functions workflows, refer pricing. Nested workflows are accessible in every AWS public regions where Step Functions is obtainable, visit AWS Regions to get list.

Now AWS Glue Feature Is Obtainable In South America (Sao Paulo) AWS Region

AWS Glue is an entirely organized ETL Service (Extract, Transform, Load) which is easy and cost-effective to classify your data, polish it, improve it, and shift it accurately within different data stores. AWS Glue made up of a central metadata repository called as the AWS Glue Data Catalog, an ETL engine which automatically creates Python or Scala code, and a flexible scheduler that manages dependency resolution, job monitoring, and retries. AWS Glue is serverless, so there’s no infrastructure to set up or manage. Now this AWS Glue feature is offered in the AWS South America (Sao Paulo) Region. AWS Glue crawls your data sources, recognizes data formats, and recommends schemas and transformations. AWS Glue can be used to execute serverless queries against your Amazon S3 data lake. AWS Glue automatically produces the code to run your data transformations and loading processes. AWS Glue execute your ETL jobs on Apache Spark environment. To get the entire list of region where AWS Glue is accessible, refer Region Table. And to know further about AWS Glue, read documentation

Now AWS CloudFormation Assisted By AWS Amplify Console

A Git-based workflow for deploying and hosting fullstack serverless web applications is offered by AWS Amplify Console. The AWS Amplify Console is a constant delivery and hosting service for latest web applications. A fullstack serverless app includes a frontend built with one page application frameworks like React, Angular, Vue, or Gatsby and an elective backend built with cloud resources like GraphQL or REST APIs and file and data storage. Join to your code repository and your front end and backend are deployed in one workflow, on each code commit. This certifies that your web application is updated after the deployment is successfully finished, removing variabilities between your application front end and backend. AWS CloudFormation gives a prevalent language for you to define and provision all the infrastructure resources in your cloud environment and clarifies the roll out over several AWS accounts and/or regions with only few clicks. Now AWS CloudFormation template can use to provision Amplify Console resources, allowing repeatable and reliable web app deployments. To know further on how to provision an Amplify Console CloudFormation template read AWS blog.

Data API Now Assisted By Amazon Aurora Serverless MySQL 5.6

Amazon Aurora is a MySQL and PostgreSQL-compatible relational database designed for the cloud, which unites the performance and availability of traditional enterprise databases with the lucidity and cost-effectiveness of open source databases. Amazon Aurora Serverless is an on-demand, auto-scaling configuration for Amazon Aurora (MySQL-compatible edition), where the database will automatically start up, shut down, and scale capacity up or down related to your application's requirements. It allows you to execute your database in the cloud without handling any database instances. It's an easy, cost-effective choice for unusual, irregular, or uncertain workloads. Now Amazon Aurora Serverless MySQL 5.6 can be accessed with the help of the built-in Data API allowing you to access Aurora Serverless with web services-based applications, containing AWS Lambda, AWS AppSync, and AWS Cloud9. The Data API lets you to concentrate on creating your applications without bothering about handling database connections or connection pools. Rather, now you can use SQL commands against an Aurora Serverless cluster by only inducing an API endpoint offered by the Data API and the Data API handles the managing database connections and returning data. Further, the Data API leverages database credentials saved in AWS Secrets Manager, removing the requirement to proceed credentials in the API calls. Refer the documentation to know further on how to start with Data API. This feature Data API is accessible in US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), and Asia Pacific (Tokyo) Regions.

Node.js v10 Supported By AWS Lambda

AWS Lambda is a compute service that allows you to execute code excluding provisioning or managing servers. AWS Lambda runs your code only when required and scales automatically, from a few requests per day to thousands per second. Besides, you can execute code for virtually any type of application or backend service - all with zero administration. Now you can build your AWS Lambda functions with the Node.js v10. Also the to the leveraging new features in Node.js v10 like the performance enhancements in the V8 6.6 engine, Lambda functions written in Node.js 10 execute on the recent generation of Amazon Linux, Amazon Linux 2. You can directly upload your code as a ZIP via AWS CLI or AWS Lambda console and choose the Node.js 10.x runtime to start deploying your Node.js code as a Lambda function. Further you can utilize the AWS Serverless Application Model (SAM) to deploy and manage your serverless application authored in Node.js. You can read more about the Node.js programming model in the AWS Lambda documentation. The Node.js 10.x runtime is accessible in every regions where Lambda is available. AWS Lambda will automatically update the language minor versions to recent minor version, as defined by https://github.com/nodejs/Release.

AWS Glue Is Obtainable In AWS GovCloud (US-East) Region

AWS Glue is an entirely organized ETL service – Extract, Transform, and Load which performs it simpler for customers to arrange and load their data for analytics. You can build and execute an ETL job with a few clicks in the AWS Management Console. You directly point AWS Glue to your data saved on AWS. Besides, AWS Glue finds your data and saves the related metadata (e.g. table definition and schema) in the AWS Glue Data Catalog. Once recorded, your data is instantly searchable, queryable, and available for ETL. AWS Glue crawls your data sources, recognizes data formats, and proposes schemas and transformations. AWS Glue automatically creates the code to run your data transformations and loading processes. AWS Glue is serverless, so there is no infrastructure to provision or manage. AWS Glue executes your ETL jobs on a completely managed Apache Spark environment. Now, you can utilize AWS Glue in the AWS GovCloud (US-East) Region. To get the entire list where AWS Glue is accessible, click AWS Region Table

Amazon Aurora Serverless Provides Sharing and Cross-Region Copying of Snapshots

Amazon Aurora (Aurora) is an entirely organized relational database engine that's compatible with MySQL and PostgreSQL. MySQL and PostgreSQL unites the speed and reliability of high-end commercial databases with the lucidity and cost-efficiency of open-source databases. The code, tools, and applications you utilize with your current MySQL and PostgreSQL databases can be used with Aurora. Now sharing snapshots of Aurora Serverless DB clusters with other AWS accounts or publicly is possible. Besides, AWS providing the potential to replicate Aurora Serverless DB cluster snapshots over AWS regions. Authorized AWS accounts can restore a DB cluster straight from the shared DB cluster snapshot without replicating it. DB cluster snapshots could be divided for a diversity of scenarios, for example, when you use disparate AWS accounts for detachment of development and production environments, share data with partners, or associate publicly on research projects. Cloning DB cluster snapshots to other AWS region enables you to retain a replica of your data for disaster recovery or for database migration. To know how to share or copy your DB cluster snapshots, visit AWS management console or use AWS SDK or CLI. And to get more information about Amazon Aurora, refer documentation