Mai-Lan Tomsen Bukovec, AWS Vice President responsible for Amazon S3-related storage and cloud data migration technology, commented on the Amazon S2024 storage service introduced at re:Invent 3.Related Updates, emphasizing on helping users promote artificial intelligence technology innovation from the storage end.
Since storage plays an important role in cloud services, how to access data more efficiently has become the key to service development. Especially under the current development trend of artificial intelligence technology applications, how to enable artificial intelligence services to find the correct information more quickly and generate correct answers in a short time is closely related to how the data is stored.
In terms of AI training, how to train AI models with high-quality data is actually closely related to storage, which is why Amazon S3 continues to be a key AWS service.
However, as various services continue to grow, the amount of data generated daily continues to grow exponentially, forcing enterprises and developers to carefully consider how to plan their storage architecture. This is especially true with the development of artificial intelligence technology, which generates an unimaginably large amount of data. How to more efficiently access data and then effectively use this massive amount of data for artificial intelligence development has become increasingly important.
Therefore, at this re:Invent 2024 event, AWS boasted that it has helped users save more than $3 billion in storage costs through the Amazon S40 Intelligent-Tiering storage category. In addition, it also added support for the Apache Iceberg open source storage table format and added the Amazon S3 Tables table system that can increase storage speed by 3 times. The Amazon S3 Metadata management system can also be used to find the correct stored data faster by metadata comparison, even if the data changes in the future.
Other updates also include addressing the data processing needs of providing services for global use. It proposes using satellites to correct errors in data processing time caused by different time zones, so that all data can correctly clarify their respective storage and modification times, and thus make different processing decisions. It also uses Amazon DynamoDB global tables to use a fully managed, serverless, multi-regional, multi-purpose database with 99.999% availability. In addition, it also proposes a faster distributed SQL database system Amazon Aurora SQL.
Unstructured data is crucial for the development of artificial intelligence
Mai-Lan Tomsen Bukovec believes that only by establishing good data content can better artificial intelligence technology be developed. AWS is currently continuously updating its Amazon S3 storage service in the hope of allowing users to store data more simply and access it more efficiently.
Current AI technologies have a high demand for unstructured data, so effectively storing the unstructured data generated by Amazon Q technology is crucial. The Amazon SageMaker platform can also be used to accelerate AI model training, enabling more efficient use of data in AI technologies.
Accelerate data integration and migration through artificial intelligence
In addition to enabling more efficient data access and usage, AWS also offers data service migration capabilities, allowing services built in the Microsoft .NET environment to be migrated to the more efficient Linux cloud environment. This allows the service execution speed to be increased by 4 times, and the original VMware virtual environment processes to be converted to cloud-native types, and even reduces the application service integration time on mainframes from several years to several months. This allows enterprises or developers to significantly reduce data integration time and avoid data damage or loss during the migration process.
Mai-Lan Tomsen Bukovec pointed out that in the past, integrating and migrating historically stacked data would have been a considerable challenge within large enterprises or multi-person teams. However, Amazon Q technology can now be used to complete the integration work in parallel without affecting existing work.
Maintain in-depth cooperation with more third-party businesses to provide users with more convenient choices
As for the many innovative database application features that AWS has already introduced, will they also affect the existing cooperative relationships with third-party database service providers?
In this regard, Mai-Lan Tomsen Bukovec believes that there will be no conflict, emphasizing that AWS's main goal is to help users solve more complex problems and provide more options so that users can decide on the appropriate solution for themselves and invest in service construction in a shorter time and with more manpower costs.
In fact, AWS also continues to work closely with many third-party companies to enable their services to be used smoothly on the AWS cloud platform, thereby attracting more users to import services and forming a larger positive development cycle.
