As every year AWS brings exciting new announcements via AWS re:Invent, continuing the trend this time as well there are some great announcements that we want to share!
Adam Selipsky focused on data and the value that we can create with it. To explain the current state of data, the keynote was build around four common themes. Data can be vast, unfathomable, extreme, but there are also endless possibilities. And these possibilities are facilitated by the new announcements as listed below! Read along.
Adam started with Sustainability, and confirmed the ambition of Amazon to fully run on renewable energy by 2025.
In addition, AWS will be water positive by 2030 that means AWS will return more water to communities and the environment than their data centre consumes. How AWS will return more water than it uses by 2030
After walking through exciting and insightful space exploration, Adam continued to announce various services and features on Data, Analytics, Machine Learning, Security, Compute, and HPC.
Analytics and Machine Learning
Amazon Aurora zero-ETL integration with Redshift
AWS is heading towards a Zero ETL future where they really want to solve complexity around ETL process which is a tedious task for data scientists. With the Aurora integration with Redshift we should be able to do near real-time analytics and machine learning (ML). We don’t have to build complex ETL pipelines.
More about this: Amazon Aurora zero-ETL integration with Redshift
Amazon Redshift Integration with Apache Spark
You can n0w run and build Spark applications on Amazon Redshift and Redshift Serverless.
More about this: Amazon Redshift Integration with Apache Spark
To have good data governance is a need for every organisation and to maintain the right balance between the data discovery and accessing it is a challenging task every organisation faces. To tackle this, AWS announces Amazon Datazone to share, search, and discover data at scale across organisational boundaries with build-in governance. More about Datazone: Amazon Datazone
Amazon Security Lake
To identify potential threats, customers need to enable logging and define it centrally. Some customers’ security teams struggle to define and implement security domain–specific aspects, such as data normalisation as data gets collected from various sources. Some of these data sources include logs from on-premises infrastructure, firewalls, and endpoint security solutions.
To solve this problem, AWS announces Amazon Security Lake. Security Lake automatically collects data from various sources like CloudTrail, Amazon VPC, Amazon Route 53, Amazon S3, and AWS Lambda, as well as security findings via AWS Security Hub. Security Lake automatically partitions and converts incoming log data to a storage and query-efficient Apache Parquet and OCSF (Open Cybersecurity Schema Framework) format, making the data broadly and immediately usable for security analytics.
Right now it is in preview in regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), and Europe (Ireland) Regions.
You can read more about it on this page: Preview: Amazon Security Lake – A Purpose-Built Customer-Owned Data Lake Service | AWS News Blog
Amazon OpenSearch Serverless
Most AWS analytics services have a serverless option, so many customers asked when we are going to have serverless option for OpenSearch as well. Yesterday Adam came with good new: “The time is now”. In the keynote, AWS announced a preview for the serverless option for Amazon OpenSearch Service to reward all the customers that have been asking for this, to allow they to easily run large analytics workloads without managing clusters.
Preview: Amazon OpenSearch Serverless – Run Search and Analytics Workloads without Managing Clusters | AWS News Blog
ML Powered Forecasting with Q
With the new feature ML Powered forecasting of Amazon Quicksight Q non-technical guys can forecast business performance.
AWS Clean Rooms
In order to protect customer privacy while optimising marketing and advertising experiences, AWS introduces AWS Clean Rooms. AWS clean rooms help companies to easily and securely match, analyse and collaborate on combined datasets- without sharing or revealing underlying data.
AWS SimSpace Weaver
Run real time spatial simulation in the cloud without worrying about scalability. This will definitely help city managers to test in the event of natural disasters. More about this service: New AWS SimSpace Weaver–Run Large-Scale Spatial Simulations in the Cloud
C7gn instances for EC2
Designed for network-intensive workloads, data analytics, and tightly-coupled cluster computing jobs. For preview you can follow the link Sign Up Today .
Inf2 instances for EC2
Available in preview today for deep learning (DL) inference applications. Get high performance at the lowest cost in Amazon EC2.
More about the service and announcement: Amazon EC2 Inf2 instances
High Performance Computing
Hpc6id EC2 Instance type
A new instance type suitable for data and memory intensive HPC.
Hpc7g EC2 Instance type (Coming Soon)
Suitable for compute and network intensive HPC powered by Gravity 3E and EFA. This will be coming soon
This new AWS services helps researchers and scientists to store, query and analyse genomic, transcriptomic, omics data. This will improve health and advance scientific discoveries. More about this: Introducing Amazon Omics – A Purpose-Built Service to Store, Query, and Analyze Genomic and Biological Data at Scale | AWS News Blog
AWS Supply Chain
A cloud-based application that helps supply chain leaders mitigate risks and lower costs. It unifies supply chain data, provides ML powered actionable insights, and offers built-in contextual collaboration. AWS Supply Chain connects to your existing enterprise resource planning (ERP) and supply chain management systems.
AWS Supply Chain is available in preview in the following AWS Regions: US East (N. Virginia), US West (Oregon), and Europe (France).
More on it: Announcing AWS Supply Chain (Preview)
Amazon Connect – ML Powered Capabilities for Forecasting, Capacity Planning, Scheduling
With this new feature of Amazon Connect, you can now predict demand with accuracy and optimise schedule to ensure the right person at the right time.
Contact Lens for Amazon Connect
Agent performance management feature launch as a preview. As contact centre manager you can create an evaluation form for agents and define evaluation criteria.
Amazon Connect agent workspace
Step by Step action that helps agents to resolve customer issues. More on the Amazon Connect features: Amazon Connect – New ML-Powered Capabilities for Forecasting, Capacity Planning, Scheduling, and Agent Empowerment | AWS News Blog
GuardDuty – Container Runtime threat detection (Coming Soon)
This is announced as coming soon. With this GuarDuty feature you can detect threats inside running containers.