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The 5 Recent AWS Innovations We Are Excited About

Keeping in line with its commitment to offer nothing but the best to its customers,, Inc. rolled out various developments to its Amazon Web Services or AWS cloud computing offering. As it stands, these developments have been explicitly designed to boost the utility for many customers.

While fostering agility, speed, and innovation at a reduced cost, AWS works to enable numerous organizations such as government agencies, startups, and large enterprises to better leverage the cloud. That said, the following are the top five AWS developments that we are most excited about.

Top Five AWS Innovations Creating Buzz

To keep in line with this aim, Swami Sivasubramanian, VP of data, analytics, and ML services at AWS, recently announced several new products along with some associated details.

At the AWS Summit held on 21st April 2022 in San Francisco, Sivasubramanian publicized innovations across several service categories like machine learning, databases, application development, and the Internet of Things.

Let’s now have a look at some of the most important AWS developments across categories.

Aurora Serverless v2

Aurora Serverless v2 can scale the database to hundreds of thousands of transactions per second. This results in up to 90% cost savings compared to the earlier versions.

Version 2 also encloses high availability, resilience, performance, low latency, and quick querying capabilities. Apart from this, there are no extra costs or upfront commitments to use Amazon Aurora Serverless v2, and organizations only pay for the database capacity.

Customers usually face the most common dilemma while managing database capacity: they tend to overspend and provision too much. At times, the capacity needs are underestimated, which results in application downtime risk.

With Aurora Serverless v2, database activity is monitored continuously, thus adjusting capacity in fine-grained increments to offer the correct amount of database resources that an application needs.

AWS IoT TwinMaker

Another innovation announced during the summit was AWS IoT TwinMaker. With AWS IoT TwinMaker, developers can create digital twins of real-world systems like factories, industrial equipment, buildings, and production lines.

AWS IoT TwinMaker offers the tools one would need to build digital twins. Organizations can increase production output, optimize building operations, and enhance equipment performance with these digital twins.

That said, AWS IoT TwinMaker facilitates better field operations in manufacturing plants, increased uptime in remote facilities equipment, and boosted tenant experience in commercial buildings.

AWS Amplify Studio

AWS Amplify Studio – a visual development environment – offers new features to frontend developers. With these, developers can accelerate UI development with minimum coding by integrating Amplify’s power-packed management capabilities and backend configuration.

Moreover, with Amplify Studio, the designs made in Figma automatically translate into human-readable React UI component code.

AWS Glue Autoscaling

AWS Glue Autoscaling discards the need to plan Glue Spark cluster capacity, as it sets the maximum capacity of workers and runs jobs.

AWS Glue will monitor the execution of the Spark application and will allocate more worker nodes to the cluster in close to real-time. It will further help in automatically adding or removing workers from the cluster.

Besides, with AWS Glue Autoscaling, one doesn’t need to experiment and decide on the number of workers assigned to AWS Glue ETL jobs. In simple words: AWS Glue Autoscaling facilitates the right size for the ETL job, and the business pays for the resources they need.

AWS Glue Sensitive Data Detection

With Glue Sensitive Data Detection, enterprises can identify sensitive data while it is still in the data pipeline. As a result, sensitive data doesn’t land in the data lake. With AWS, Glue identifies various personal Identifiable Information (PII) and other sensitive data such as credit card numbers. Customers can track the information for auditing or redact the sensitive information before the records are written into a data lake.

AWS Glue Sensitive Data Detection uses machine learning and pattern matching to automatically detect PII and other sensitive data. It does so at the column and cell levels when AWS Glue Job runs.

Each of these innovations announced aims to offer organizations the required agility, speed, and ways to cut costs and save time.

Wrapping Up

With these innovations, AWS looks to create a more flexible computing environment that customers can make effective use of. As such, organizations can focus on things that are most important to them rather than worrying about the infrastructure and other technical intricacies.

In a way, AWS innovations generally partake in the overall intention of incorporating the best of the available technologies. They are geared towards significantly impacting customers, developers, businesses, and other organizational units alike.

Indeed, the AWS advancements are going strong. What are your thoughts about these most recent innovations announced by AWS? Do you think it will make the managing of data and other aspects of your IT infrastructure more efficient? Can you relate to our excitement about these developments?

Drop us a line, and let’s discuss.

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