As of the third quarter of 2022, Amazon Web Services was the leading cloud vendor, accounting for 32% of the total consumer spend after growing 27% year on year, according to a report by Canalys. The demand for long-term enterprise digitalization continues to rise, and migrating to the cloud is the best way for modern businesses to go digital and do more with less.
To meet the growing demand for cloud computing, AWS continues to innovate its services and products. During its annual re: Invent conference, Amazon launched a variety of new applications and product upgrades that will enhance the user experience. AWS’s latest features and services revolve around analytics, storage, machine learning, database management, supply chain management, and improving cloud computing security. Keep reading to learn more about the recent developments AWS unveiled recently.
Analyzing data and managing it can be difficult for any business. To ease data analytics and management for businesses, Amazon announced several updates to its AWS data services. These new features include the integration of Amazon Aurora zero-ETL with Amazon Redshift. AWS’s new data service updates also support Amazon Redshift integration for Apache Spark. Experts claim this integration will make the ETL (extract, transform, and load) process outdated.
Other data analytics tools announced at re:Invent are AWS Datazone and Clean Rooms. AWS Datazone is a new data management service designed to help businesses discover, catalog, share, and govern their data on the AWS cloud, third-party sources, and on-premises storage. It’s important to understand AWS Datazone uses machine learning to build catalogs and generate metadata that’s easy to search.
With Datazone, you can set data free within your organization without compromising security. That way, admins and employees can easily manage and govern access to business information. AWS Clean Rooms allows companies to share sensitive data with external partners for research, manufacturing, and marketing while protecting IP addresses. There are also improvements on Amazon Quicksight and Amazon data security monitoring with Amazon Security Lake.
Amazon’s major announcement on security updates was the launch of Amazon Security Lake. This new cybersecurity service automatically centralizes data security from the cloud and on-premises data sources into a data lake in an AWS user’s account. With this in mind, migrating to AWS is a sure way to mitigate the risk of data security breaches.
Not to mention, AWS migration experts help you design and build a secure landing zone on AWS that meets your business needs. You’ll also migrate your workloads to the AWS cloud securely with minimal or zero interruptions. In addition to launching Amazon Security Lake, AWS released new updates for Amazon Inspector, an automated vulnerability management solution. Amazon Macie, AWS machine learning security, and privacy service also got upgrades.
Another major announcement made by AWS at re: Invent 2022 was the addition of new artificial intelligence features. By increasing AI features in its cloud services, AWS is hoping enterprises will get a higher return on their data. New AI features in AWS include Amazon Textract Analyze Lending, New Search Features On Amazon Kendra, call analytics for Amazon Transcribe, new imaging and analytics in Amazon HealthLake, and enhancements to Amazon CodeWhisperer.
Enhancements in Amazon’s artificial intelligence features play a significant role in improving workflows within enterprises and help enhance the customer experience. For instance, using Amazon Textract Analyze Lending can boost accuracy and loan document processing tasks. This advanced AI feature is perfect for mortgage companies and other lenders that need to process large volumes of documents to extract critical data to make informed decisions.
With improved search capabilities on Amazon Kendra, such as Tabular search in HTML and language expansion, users can find accurate answers in HTML documents in tabular format using natural language queries. Language expansion helps AWS users to ask questions in natural language and get answers in supported languages like Chinese, Korean, Spanish, French, Germany, Japanese, and Portuguese.
Apart from security, companies switching to the cloud want platforms that provide access to a variety of high-performance cloud computing features. Cloud users also want these features to be cost-effective. One way Amazon intends to meet this consumer demand is by providing new in-house computing chips capable of handling complex workloads like weather prediction and medical developments at a high speed.
The latest in-house chips launched by Amazon are second-generation Infrentia chips, Graviton 3E, EC2 instances, and Nitro v5. According to Amazon, EC2 instances boost high-performance computing tasks and support intensive tasks with higher computing performance, large memory, and local disk storage. This capability helps reduce job completion time for data-intensive tasks. Graviton 3E is ideal for workloads that follow vector instructions, as it increases performance by 35% when executing high-performance tasks.
In its effort to help businesses use the cloud efficiently for data science, AWS unveiled new feature updates and tools for its machine learning service, SageMaker. Improvements in Amazon SageMaker will enhance governance attributes within the machine learning service and add new tools to its notebooks. According to AWS, governance updates aim to enhance granular access and streamline workflow.
With the number of machine models increasing, enterprises have a hard time getting privilege access controls. Forming governance processes to input data sets, model use descriptions, risk rating, and other document model information are also challenging for many businesses. Other challenges machine learning and data engineering teams face include monitoring deployed models for bias and navigating access policies outlined in ad hoc lists or spreadsheets.
To mitigate these challenges, AWS has added a new update dubbed Role Manager to SageMaker. Amazon SageMaker Role Manager helps administrators to define permissions for users and control access easily. AWS also unveiled Amazon SageMaker Model Cards that aim to help data management teams transition from manual record keeping. Besides improving governance in SageMaker, AWS added new capabilities to SageMaker Studio Notebook to boost collaboration within the workspace and make data preparation more efficient.
Over the past few years, businesses across all sectors have experienced unexpected volatility in demand and supply chains. Natural events, geopolitical crises, and mass shortages of resources are key factors causing supply chain disruptions. These disruptions have put a lot of pressure on enterprises to plan for supply chain uncertainties and respond promptly to changes in consumer demand while maintaining low operational costs.
To successfully handle supply chain issues, the demand for supply chain applications has increased at a rapid pace among businesses. Amazon Web Services is hoping to leverage this opportunity by providing a cloud-based supply chain application. This application integrates with machine learning to help businesses, especially those that rely on multiple ERP systems, to get a unified view of supply chain-related components like logistics, suppliers, and inventory.
Amazon Web Services supply chain is designed to provide a map-based visualization of data in real time. Inventory managers can use the map-based interface through the AWS Management Console. That way they can prevent potential supply chain disruptions and find responses to issues like logistics and promoting sustainability.
Amazon is always innovating new tools to address issues like pricing, high performance, cost, and the need for multiple cloud options. Some of the latest tools Amazon launched at its annual conference include enhanced data analytics and management systems like Datazone and Clean Rooms, and the AWS supply chain. Other developments unveiled are security upgrades, such as Amazon Security Lake, AWS machine learning enhancements, additional AI features, and high-performance in-house processors.