Kendra Crawler

 

Amazon Kendra is an intelligent search service powered by machine learning, enabling organizations to provide relevant information to customers and employees, when they need it.

Amazon Kendra recently introduce the web crawler to index and search webpages.

Critical information can be scattered across multiple data sources in an enterprise, including internal and external websites. Kendra web crawler helps to index documents made available on websites (HTML, PDF, MS Word, MS PowerPoint, and Plain Text) and search for information across this content using Kendra Intelligent Search.

The Kendra web crawler honors access rules in robots.txt, and customers using the Kendra web crawler will need to ensure they are authorized to index those webpages in order to return search results for end users.

Ref: https://aws.amazon.com/kendra/

Cloud Architect

 

Today, got my second cloud certification in AWS (Amazon Web Service) as 2021 self learning goal.  

It's follow-up of last year cloud work at https://ganesansenthilvel.blogspot.com/2020/06/cloud-practitioner.html

AWS Certified Solutions Architect exam is a testimony of the snatched role opportunity as Cloud Architect.  

This certification is an acid test to me by Amazon for the below abilities

• Design and deploy dynamically scalable, highly available, fault-tolerant, and reliable applications
• Select appropriate AWS services to design and deploy an application based on given requirements
• Migrate complex, multi-tier applications on AWS
• Design and deploy enterprise-wide scalable operations on AWS
• Implement cost-control strategies

Since 2008, it's my 13th certification year in the relevant career opportunities like .NET, Big Data, IoT, SAFe, Blockchain, Cloud, etc.

Continuous Learning is the minimum requirement for success in any field.

Athena Parameterized Query

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

Recently, AWS worked on architecture improvements.  As the result, Amazon Athena leverages the re-usability, simplification, and security benefits of parameterized queries.

Last Thursday, analysts can save time and eliminate errors by converting queries that have frequently modified criteria, such as date filters or aggregation periods, into a parameterized query that serves multiple use cases. Application developers can use them to safeguard against SQL injection risks and simplify application integrations that generate SQL based on a user’s selections.

As an example, there is a query for retail sales metrics where the filters for product category, region, and date can vary from one execution to the next. Instead of manually modifying the logic in your SQL code each time you run the query, you can use variables for product category, region, and date whose values are provided when executing the query.

Parameterized query is available in SELECT and INSERT INTO queries through the Athena console, API, and SQL clients using Athena’s ODBC or JDBC drivers. Ref: https://docs.aws.amazon.com/athena/latest/ug/querying-with-prepared-statements.html

Cloud Watch design

 

AWS CloudWatch is a vital instrumentation service for all resources of AWS.  By design, it has two core components

1. Metric
2. Alarm

In AWS Metric model, a dimension is metrics metadata in the form of a name/value pair. Metrics can have up to ten dimensions. When you set dimensions, AWS services send both data and metadata to CloudWatch. Dimensions can be useful for filtering data and aggregating statistics.

CloudWatch Alarms feature allows you to watch CloudWatch metrics and to receive notifications when the metrics fall outside of the levels (high or low thresholds) that you configure. You can attach multiple Alarms to each metric and each one can have multiple actions.

Workflow Studio

 

AWS Step Functions allow you to build scalable, distributed applications using state machines. As of now, building workflows on Step Functions required you to learn and understand Amazon State Language (ASL).

Now, AWS provides a low-code visual tool namely Workflow Studio. It helps you learn Step Functions through a guided interactive interface and allows you to prototype and build workflows faster.

Workflow Studio is great for developers who are new to Step Functions, because it reduces the time to build their first workflow and provides an accelerated learning path where developers learn by doing. It helps developers who are experienced in building workflows, because they can now develop them faster using a visual tool. For example, you can use Workflow Studio to do prototypes of the workflows and share them with your stakeholders quickly.

The attached screeshot shows how easy is to create a state machine using Workflow Studio.