August brought with it many new service enhancements, launches of features in new AWS Regions, as well as some services in preview entering general availability. In this blog, we’ve curated a list of items from the August announcements that should be on the radar of any enterprise seeking to drive efficiency and effectiveness in the cloud. Let’s look at keeping Amazon DynamoDB under accounts limits with new account metrics, AWS Lake Formation, using AWS Certificate Manager (ACM) with site-to-site VPNs, using machine learning as a service for forecasting time-series data, and a new Amazon Redshift Quick Start!
Amazon DynamoDB Account Metrics
Sometimes, it’s the little things that help enterprises stay on track! Amazon DynamoDB has become the go-to NoSQL database solution for serverless and traditional workloads alike. To date, monitoring the limits for Amazon DynamoDB could prove to be tricky. August brought the announcement that Amazon DynamoDB now publishes account metrics to Amazon CloudWatch. To have a look, navigate to the Amazon CloudWatch console and select Metrics → DynamoDB → Account Metrics. You can also access these newly published metrics via the API. This will allow you to configure alerts for Amazon DynamoDB for conditions that will potentially cause your tables to be unavailable due to account level limits being reached.
Check out DynamoDB Metrics and Dimensions in the Amazon DynamoDB Developer Guide to learn more.
AWS Lake Formation
AWS Lake Formation was announced in general availability in August. AWS Lake Formation is a very effective data lake accelerator from AWS, allowing enterprises to “dip their toe in the water” with data lakes. Historically, setting up and configuring a data lake was not a trivial task. It required complex definitions for diverse data sources, data loading and ingestion pipelines, securing and partitioning data once in the data lake, cataloging, data cleaning and the list goes on. For enterprises needing more complex solutions, there may still need to be some customization, but AWS Lake Formation greatly reduces the lift to get a foundation in place.
All it takes is defining where the data lives now and what accesses you want to be available for the data. AWS Lake Formation will then ingest the data from databases and object storage, clean and classify the data using machine learning algorithms, and secure access. These data catalogs can then be published to users who can use the data with services like Amazon EMR for Apache Spark, Amazon Redshift Spectrum, and Amazon Athena.
Dive deeper with AWS Lake Formation by visiting the AWS Lake Formation console.
AWS Site-to-Site VPN now Supports Certificate Authentication
AWS Site-to-Site Virtual Private Network (VPN) now supports digital certificates for Internet Key Exchange (IKE) authentication. This means that you can now use AWS Certificate Manager (ACM) instead of pre-shared keys for these types of connections! This will help to offload the management of these types of keys to the ACM service rather than placing their rotation or renewal on a calendar.
First you need to create a private Certificate Authority (CA) in the ACM service. You can then create a digital certificate from this CA for use on the non-AWS side. There is no need to specify an IP address for your customer gateway, which means updating that IP won’t cause future connectivity issues or reconfiguration worries. In this configuration, all new tunnels created with the gateway that employs the digital certificate will create additional certificates from the same private CA.
Check out the product page to learn more: AWS VPN.
Amazon Forecast is Generally Available
Forecasting time series data historically has required a team of data engineers and data scientists to get the job done. Not only does this require expensive expertise to accomplish, but it also can take time. August brought the announcement of the general availability of Amazon Forecast for forecasting time series data as a managed service with no machine learning experience required! Amazon Forecast is based on the same technology that serves Amazon.com and was announced in preview at re:Invent 2018. The feature set has been expanding ever since to combine time series data with additional variables to build forecasts.
All you need to get started is the historical data, and any data that you feel may influence the forecast. The machine learning happens under the hood, making predictions that are up to 50% more accurate than looking at time series data alone. No servers, no models to write, no algorithms to train. Best of all you only pay for what you use!
Check it out at the product page to learn more: Amazon Forecast.
Amazon Redshift Quick Start
Amazon Redshift is a fully managed data warehouse that makes queries lightning fast due to its internal ecosystem and columnar data storage architecture. It provides for a simple and cost-effective way to query your data using SQL or existing business intelligence tools. The August announcement of the Amazon Redshift Quick Start will make getting up and running with Amazon Redshift much simpler, deploying a modular, highly available environment for Amazon Redshift.
To get started:
- View the architecture and details
- View the deployment guide for instructions
- Download the AWS CloudFormation templates that automate the deployment
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