July’s Best Bits – AWS Blog Round-up

Within the blink of an eye, July is almost over!

Rather than taking a closer look at one of the many exciting advancements within AWS specific solutions, we thought we’d do an end of the month round-up of some of our favourite articles released by AWS this month.

We’ve included a healthy blend of event posts, new automation tools, well-architected approaches and more.

Choosing a Well-Architected CI/CD approach: Open Source on AWS

This post explores evaluating the criteria for selecting the right tool with a focus on the balance between meeting functional and non-functional requirements whilst maximizing value. Great for those with a head for well architected source code management, continuous integration engines and container registry.

Automating Amazon CloudWatch dashboards and alarms for Amazon Managed Workflows for Apache Airflow

Try saying that title 10 times fast! It’s a bit of a mouthful but it makes for great reading. In the post, Mark Richman, Senior Solutions Architect at AWS, details the fully managed service that makes it easier to run open-source versions of Apache airflow on AWS.

Implementing Multi-Region Disaster Recovery Using Event-Driven Architecture

In this AWS blog post, they share a reference architecture that uses a multi-Region active/passive strategy to implement a hot standby strategy for disaster recovery (DR).

DR Strategies – Active/Passive to Multi-site

Announcing specialized support for extracting data from invoices and receipts using Amazon Textract

Find out how Amazon Textract’s new Analyze Expense API helps to extract line item details in addition to key-value pairs from invoices and receipts (a frequent request AWS hear from customers and partners). Amazon Textract uses machine learning (ML) to understand the context of invoices and receipts (we’ve loved using this tool in our own client success projects).

Brand Tracking with Bayesian Statistics and AWS Batch

How can mathematical models and probability theory, specifically Bayesian methods, address some of the big problems in brand marketing? And how can AWS Batch, together with Metaflow, solve many of the technical issues that used to be major obstacles when using Bayesian methods at scale? A detailed and insightful read from Corrie Bartelheimer, Senior Data Scientist at Latana.

Governance, Risk and Compliance track at AWS re:Inforce 2021

The AWS re:Inforce 2021 event takes place in Houston, Texas this August 24th-25th. If your stateside and able to visit, this post has a thorough breakdown of what to expect within both the breakout and builders’ sessions.

Bring your own container to project model accuracy drift with Amazon SageMaker Model Monitor

Vinay Hanumaiah, Senior Deep Learning Architect at Amazon ML Solutions Lab, walks through some useful techniques to detect a particular kind of data drift known as covariate drift. He then demonstrates how to incorporate your own drift detection algorithms and visual tools with Model Monitor. This post is one of our favourites for July, detailing the setup with Amazon S3, the training of datasets and how to create a monitor schedule (the visualisation of data drift is particularly interesting).

Projected Drift Scores Over Time

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