Summary of AWS blogs for the week of monday Mon Dec 02

In the week of Mon Dec 02 2024 AWS published 110 blog posts – here is an overview of what happened.

Topics Covered

AWS for SAP

Migration Support Service for RISE with SAP on AWS

AWS and SAP have collaborated to provide a comprehensive migration support service specifically designed for RISE with SAP on AWS. This initiative aims to facilitate the seamless transition of enterprise workloads to the cloud, leveraging the robust infrastructure and services offered by AWS.

Key Features of the Migration Support Service

The service provides strategic guidance and technical support, ensuring that enterprises can effectively migrate their SAP workloads to AWS. With the expertise of Amit Gupta and Sascha Soulier from Enterprise Cloud Services at SAP, the service focuses on optimizing the migration process, addressing potential challenges, and ensuring compliance with industry standards.

Benefits for Enterprises

Enterprises benefit from reduced migration time and cost, enhanced operational efficiency, and increased scalability. By moving to AWS, businesses can leverage advanced cloud technologies to drive innovation and remain competitive in a rapidly evolving market.

Migration Readiness Accelerator for RISE with SAP on AWS

In addition to the migration support service, AWS and SAP have introduced the Migration Readiness Accelerator. This tool is designed to assess and enhance an organization’s preparedness for migrating SAP workloads to AWS.

Components of the Migration Readiness Accelerator

The accelerator comprises a series of assessments and workshops led by SAP experts like Saurabh Sharma. These sessions help organizations identify gaps in their current infrastructure, develop a tailored migration strategy, and ensure a smooth transition to the cloud environment.

Strategic Advantages

By utilizing the Migration Readiness Accelerator, enterprises can mitigate risks associated with cloud migration, improve their strategic planning, and achieve a faster time-to-value. This proactive approach enables organizations to unlock the full potential of SAP solutions on AWS.

How KeyCore Can Help

KeyCore offers specialized services to support enterprises in their journey towards cloud transformation with SAP on AWS. Our expertise in AWS solutions and SAP migration ensures that businesses can achieve their migration goals efficiently and effectively. Whether it’s guiding through the initial assessment or providing end-to-end migration support, KeyCore is your trusted partner in SAP cloud migration.

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Official Machine Learning Blog of Amazon Web Services

Amazon SageMaker JumpStart has expanded its offerings with the addition of Mistral-NeMo-Base-2407 and Mistral-NeMo-Instruct-2407, two advanced large language models from Mistral AI. These models excel at text generation and are now accessible via SageMaker JumpStart, enabling users to deploy and leverage them for a variety of real-world applications. This integration simplifies the process of discovering and utilizing cutting-edge AI models, enhancing efforts in automating content creation, enhancing customer interactions, and other AI-driven tasks.

Trust is a crucial element in AI adoption, and AWS has taken steps to advance AI trust with new responsible AI tools and capabilities. Unveiled at AWS re:Invent 2024, these resources aim to improve the safety, security, and transparency of AI services. They empower users to embark on responsible AI journeys by providing the necessary tools to ensure ethical and reliable AI deployments.

Deploying Retrieval Augmented Generation (RAG) applications is now easier with Amazon SageMaker JumpStart using Facebook AI Similarity Search (FAISS). This advanced methodology allows for efficient document retrieval and similarity searches, optimizing AI-driven search solutions. By leveraging FAISS, businesses can enhance their search and recommendation systems, providing users with more relevant and precise results.

Amazon SageMaker HyperPod training plans radically reduce cluster procurement wait times. Users can now find, review, and create optimal training plans tailored to their compute and timeline needs using AWS CLI or the AWS Management Console. This streamlined process accelerates the deployment of SageMaker training jobs and HyperPod clusters, optimizing resource allocation and fostering more efficient training workflows.

The Amazon Bedrock Marketplace has introduced NVIDIA models, including the Nemotron-4 NIM microservices, at AWS re:Invent 2024. This platform is a centralized hub for discovering, testing, and implementing foundational models, supporting diverse AI initiatives. Users can explore Amazon Bedrock Marketplace’s capabilities and begin leveraging NVIDIA’s cutting-edge AI solutions to enhance their workflows.

Amazon SageMaker and Tecton have joined forces to simplify the development and deployment of production-ready AI applications, particularly for real-time use cases such as fraud detection. This integration reduces time to value by abstracting complex engineering tasks, enabling teams to concentrate on feature and use-case development. It offers a unified framework for both offline training and online serving of ML models, facilitating seamless AI application deployment.

Amazon Bedrock tooling now integrates with SageMaker JumpStart models, offering enhanced deployment capabilities. By combining SageMaker JumpStart’s model hosting with Bedrock’s security and monitoring tools, users can access robust AI solutions. The demonstration using the Gemma 2 9B Instruct model exemplifies the ease of deploying AI models and utilizing Bedrock’s advanced features to enhance operational efficiency and security.

Amazon Bedrock Model Distillation, introduced as a preview, streamlines the model distillation workflow. This post outlines key steps, including setting up permissions, selecting models, providing input datasets, commencing distillation jobs, and evaluating and deploying student models. Bedrock Model Distillation offers a methodical approach to refining AI models, enhancing performance and inference efficiency.

The Amazon Bedrock IDE in Amazon SageMaker Unified Studio empowers users to build generative AI applications quickly. Even without writing code, teams can create AI chat agents to analyze sales performance data through intuitive conversations. This approach democratizes AI model development, enabling business teams to extract insights from both structured and unstructured data sources without managing complex data pipelines.

The integration of Amazon SageMaker Studio and SageMaker HyperPod offers a comprehensive solution for managing the entire ML lifecycle, from development to deployment at scale. This post guides users through scaling ML workloads, emphasizing the collaborative environment provided by SageMaker Studio and HyperPod to support data scientists and ML engineers.

Amazon has introduced the Amazon Kendra GenAI Index, enhancing semantic search and retrieval capabilities for enterprise AI applications. Optimized for Retrieval Augmented Generation (RAG) and intelligent search, this index supports the development of effective digital assistants and search experiences. Businesses can leverage this tool to build more responsive and accurate AI-driven search solutions.

AI apps from AWS Partners are now available in SageMaker, enabling faster development of Generative AI and ML solutions. This integration allows users to securely find, deploy, and use partner AI apps within SageMaker, accelerating AI model development and deployment, enhancing the performance and capabilities of AI applications across various domains.

Amazon QuickSight now integrates with Amazon Q Business, enabling comprehensive querying of both structured and unstructured data. This integration supports over 20 data sources, including Amazon Redshift and PostgreSQL, providing real-time visualizations and answers. By combining structured and unstructured data, users can gain holistic insights and make data-driven decisions more effectively.

The Amazon Q Business custom plugin for New Relic AI offers a unified solution, combining observability insights with Retrieval Augmented Generation (RAG) capabilities. This integration enhances digital experiences by providing a natural language interface for ease of use, enabling users to access recommendations and insights seamlessly.

Amazon SageMaker’s updated inference optimization toolkit introduces new functionalities to optimize generative AI models swiftly. This post delves into the toolkit’s features, guiding users on leveraging these improvements to enhance model performance and streamline inference processes, ultimately accelerating AI-driven insights and applications.

Syngenta has partnered with AWS to develop Cropwise AI, a generative AI assistant powered by Amazon Bedrock Agents. This tool supports sales representatives by transforming complex seed selection data into natural conversations, providing personalized recommendations at scale. This innovative solution empowers Syngenta’s team to enhance their product offerings and customer interactions.

New NVIDIA-powered capabilities in Amazon SageMaker accelerate AI inference workloads. At re:Invent 2024, NVIDIA’s accelerated computing offerings are showcased, demonstrating how users can deploy NVIDIA NIM microservices from AWS Marketplace and access Nemotron-4 models via SageMaker JumpStart for enhanced AI inference performance.

The new scale down to zero feature in SageMaker Inference promises significant cost savings. Announced at AWS re:Invent 2024, this feature allows SageMaker inference endpoints to scale to zero instances, optimizing resource use and reducing expenses, while maintaining the power of AI and ML inference in the cloud.

The introduction of Container Caching in SageMaker Inference marks a significant advancement in auto-scaling for generative AI models. This feature reduces model scaling time, cutting latency by up to 56% when deploying new model copies. It addresses the challenges of scaling large language models, providing faster deployment and enhanced performance.

The Fast Model Loader in SageMaker Inference accelerates autoscaling for Large Language Models (LLMs). Part of a multi-part series announced at AWS re:Invent 2024, Fast Model Loader integrates seamlessly with SageMaker workflows, enabling rapid deployment and scaling of LLMs. This innovation supports efficient model management and showcases customer success stories.

KeyCore, Denmark’s leading AWS consultancy, can assist organizations in navigating these advancements. With expertise in deploying, optimizing, and managing AWS solutions, KeyCore provides comprehensive support to maximize the potential of SageMaker, Bedrock, and other AWS AI offerings. Whether it’s integrating new models, optimizing workflows, or enhancing inference capabilities, KeyCore offers tailored solutions to meet unique business needs, ensuring clients leverage AWS tools effectively for tangible business outcomes.

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Announcements, Updates, and Launches

Introducing Buy with AWS

Buy with AWS offers a streamlined procurement experience, allowing customers to discover and purchase products from the AWS Marketplace directly on AWS Partner websites. By using their AWS account, customers can seamlessly integrate their procurement processes, enhancing convenience and efficiency. This feature simplifies the purchasing workflow and provides an integrated solution for managing software procurement, ensuring that organizations can quickly access the necessary tools and resources.

Amazon SageMaker HyperPod Enhancements

Amazon SageMaker has introduced new HyperPod recipes that accelerate the training and fine-tuning of foundation models. These recipes, including support for models like Llama 3.1 405B, enable users to achieve state-of-the-art performance in model training swiftly. Additionally, flexible training plans and task governance features offer optimized compute resource allocation, helping teams meet their training timelines and budgets while ensuring efficient utilization of resources.

AWS Education Equity Initiative

AWS commits $100 million to promote educational equity through generative AI initiatives. This investment aims to empower socially-minded organizations to develop AI-powered digital learning solutions, targeting underserved students worldwide. By fostering innovative educational platforms, applications, and assistants, AWS seeks to bridge the educational gap and inspire the next generation of innovators.

Amazon Q in QuickSight

Amazon Q in QuickSight introduces a powerful scenario analysis capability that allows business users to solve complex problems more efficiently. With performance up to 10 times faster than traditional spreadsheets, this tool enables rapid decision-making and critical business insights, enhancing overall productivity and strategic planning.

Amazon Bedrock Innovations

Amazon Bedrock introduces several new capabilities, including multimodal toxicity detection with image support, enhanced data processing, intelligent prompt routing, and a robust marketplace for foundation models. These innovations provide developers with the tools needed to build responsible AI applications, optimize performance, and access a wide range of foundation models, ensuring comprehensive support for AI-driven solutions.

Amazon SageMaker Lakehouse and Redshift Enhancements

Amazon SageMaker Lakehouse now supports zero-ETL integrations with applications like Salesforce, SAP, and ServiceNow, along with Amazon Redshift. This simplifies data replication and ingestion, enabling seamless analytics and AI/ML operations. Additionally, integrated access controls in Amazon Athena federated queries provide centralized data governance, further simplifying data management and enhancing security.

Amazon SageMaker Data and AI Governance

The new governance features in Amazon SageMaker provide a unified catalog and granular access controls, allowing secure data and AI asset management. With visual traceability of data lineage, these capabilities bolster trust and governance, facilitating strategic data-driven decisions. The next generation of Amazon SageMaker offers a comprehensive studio for data, analytics, and AI, streamlining operations and innovation.

Amazon Q Business Enhancements

Amazon Q Business introduces new workflow automation capabilities and over 50 action integrations. These enhancements enable enterprises to boost productivity with generative AI-powered workflows, offering seamless task execution across various tools. Additionally, ISVs can leverage new capabilities to integrate generative AI experiences and customize Amazon Q embedded assistants, enhancing user engagement and operational efficiency.

How KeyCore Can Help

KeyCore, as Denmark’s leading AWS consultancy, provides expert guidance and support in leveraging AWS’s latest offerings. From integrating Buy with AWS for streamlined procurement to implementing advanced AI and ML solutions with Amazon SageMaker and Bedrock, KeyCore ensures your organization fully utilizes AWS’s capabilities. Our team can assist in deploying secure and efficient data governance strategies, optimizing workflow automation, and enhancing educational initiatives through generative AI. Learn how we can drive innovation and efficiency in your AWS environment by visiting KeyCore.

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Containers

Amazon EKS Auto Mode is now generally available, introducing a streamlined approach to managing Kubernetes clusters on AWS. This feature simplifies the complexities of Kubernetes management, allowing users to focus more on their applications and less on the infrastructure. Developed in collaboration by experts including Alex Kestner, Ashley Ansari, Robert Northard, and Sheetal Joshi, Amazon EKS Auto Mode automates many of the routine tasks associated with cluster management.

Amazon EKS Auto Mode adjusts the management of Kubernetes clusters by handling tasks such as node provisioning, scaling, and lifecycle management. This automation eliminates the need for users to manually configure and maintain these elements, thereby reducing operational overhead. The service optimizes resource allocation by dynamically adjusting the number of nodes based on workload demands, ensuring efficiency and cost-effectiveness.

Key Features

One of the key features of Amazon EKS Auto Mode is its ability to automatically scale clusters based on real-time needs. This is particularly beneficial for businesses that experience variable workloads, as it ensures they only pay for the resources they use. Additionally, the feature integrates seamlessly with existing AWS services, offering a cohesive cloud ecosystem that enhances performance and reliability.

Business Value

For businesses, the value of Amazon EKS Auto Mode lies in its ability to reduce the technical barriers associated with Kubernetes. By automating routine tasks, companies can redirect their IT resources towards innovation and application development rather than infrastructure management. This results in increased agility and faster time-to-market for new applications and features.

How KeyCore Can Help

As a leading AWS consultancy, KeyCore offers expertise in deploying and managing Amazon EKS Auto Mode. Our team can assist businesses in integrating this feature into their existing workflows, ensuring a smooth transition and maximum benefit. Whether through professional services or managed services, KeyCore provides the necessary support to fully leverage this new capability on AWS.

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AWS Quantum Technologies Blog

Amazon Braket and NVIDIA are at the forefront of advancing hybrid quantum-classical computing. This partnership aims to enhance the research and application of hybrid quantum workflows, combining the strengths of quantum and classical computing to tackle complex computational problems.

The Hybrid Quantum-Classical Paradigm

The collaboration between Amazon Braket and NVIDIA focuses on integrating quantum computing capabilities with classical processing power. The hybrid model leverages quantum computers for tasks where they excel, such as certain optimization problems and simulations, while utilizing classical processors for broader computational functions. This synergy is crucial as quantum computing alone is not yet sufficient to handle all aspects of large-scale computations.

Amazon Braket and NVIDIA CUDA-Q Integration

Amazon Braket provides a managed service for accessing quantum computers, making it easier for researchers to experiment with quantum algorithms. By integrating NVIDIA’s CUDA-Q, developers can now design and execute hybrid quantum-classical algorithms more efficiently. This integration allows for seamless communication between quantum processors and NVIDIA’s powerful GPUs, streamlining computational processes and reducing overhead.

Implications for Research and Industry

The combination of Amazon Braket and NVIDIA’s technology opens new avenues for research in fields like drug discovery, material science, and cryptography. Industries can leverage this hybrid approach to solve problems that are currently beyond the reach of classical computers alone. The collaboration promises to foster innovation by providing researchers and developers with the tools needed to explore new quantum applications.

How KeyCore Can Assist

KeyCore is well-equipped to support organizations in adopting and optimizing hybrid quantum workflows. With expertise in AWS technologies and a deep understanding of quantum computing, KeyCore can guide businesses through the complexities of integrating Amazon Braket with NVIDIA CUDA-Q. Whether it is setting up the infrastructure, developing algorithms, or optimizing performance, KeyCore offers tailored solutions to maximize the potential of hybrid quantum-classical computing.

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Official Database Blog of Amazon Web Services

In the following sections, we summarize various articles from the Official Database Blog of Amazon Web Services, providing insights into the latest advancements and features in AWS database solutions.

Accelerating Generative AI with Amazon Bedrock and Aurora Serverless

Amazon has introduced two capabilities in Amazon Bedrock Knowledge Bases that significantly streamline the development of Retrieval-Augmented Generation (RAG) workflows using Amazon Aurora Serverless v2. First, users can effortlessly create an Aurora Serverless v2 knowledge base to utilize with Amazon Bedrock. Secondly, there’s a capability to automate deploying RAG workflows across various environments, enhancing the operational efficiency and scalability of AI applications. These capabilities allow for the seamless integration and scaling of AI-driven solutions with AWS’s robust serverless technologies.

Enhancing PostgreSQL with postgres_get_av_diag() for Autovacuum Monitoring

Amazon RDS for PostgreSQL introduces the function postgres_get_av_diag() to monitor aggressive autovacuum blockers. This function offers actionable insights, allowing administrators to identify and mitigate potential performance and availability risks. By leveraging this function, users can ensure their PostgreSQL environments remain efficient and responsive, thereby maintaining high levels of data availability and performance.

Amazon ElastiCache for Valkey: Essential Use Cases

Valkey, a high-performance, distributed, in-memory key-value data store, originates from a fork of Redis OSS. It provides scalable and low-latency options for modern application development. Despite being new, Valkey maintains full compatibility with Redis OSS, making it a reliable choice for developers aiming for seamless data retrieval and storage capabilities. Its design is particularly suited for caching and real-time analytics, essential for handling large-scale data workloads efficiently.

Automating Pre-Checks for Amazon RDS for MySQL Upgrades

Upgrading major versions in Amazon RDS for MySQL requires meticulous planning due to the diverse features and fixes in each version. AWS provides automation tools to perform pre-checks, ensuring smoother transitions and compatibility with current deployments. This proactive approach minimizes disruptions and streamlines the upgrade process, allowing organizations to leverage the latest database features and enhancements efficiently.

Concurrency Control in Amazon Aurora DSQL

This article delves into effective concurrency control strategies in Amazon Aurora DSQL. It provides insights into crafting efficient transaction patterns and offers examples of retry patterns that manage concurrency control exceptions seamlessly. By understanding these strategies, users can optimize their database operations, ensuring high performance and reliability in concurrent transaction scenarios.

Modernizing Databases with DMS Schema Conversion and Generative AI

The AWS Database Migration Service (DMS) Schema Conversion introduces a generative AI feature that enhances migration workflows. Advanced language models now provide additional recommendations, reducing manual conversion efforts and time. This innovation simplifies the migration process, enabling organizations to modernize their database infrastructure with greater efficiency and precision.

Introducing Amazon Aurora DSQL: A New Era in Serverless SQL Databases

Amazon Aurora DSQL emerges as the fastest serverless distributed SQL database, designed for always-available applications. It offers virtually unlimited scalability without the need for database sharding or instance upgrades. With highest availability and zero infrastructure management, Aurora DSQL redefines database solutions for demanding workloads, providing unmatched flexibility and performance. The introduction of this technology heralds a new era in database management, making it easier to meet dynamic workload demands efficiently.

How KeyCore Can Help

KeyCore, as a leading AWS consultancy in Denmark, offers expert guidance and support for integrating and optimizing AWS database solutions like Amazon Aurora, RDS, and ElastiCache. With our professional and managed services, we assist in implementing advanced features such as generative AI, serverless architectures, and efficient migration strategies. Our team ensures that organizations can leverage AWS’s latest technologies to drive innovation, improve performance, and enhance operational efficiency. Whether it’s crafting tailored databases solutions or managing complex migrations, KeyCore provides the expertise needed to maximize the benefits of AWS cloud services.

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Official Big Data Blog of Amazon Web Services

Amazon MSK Cluster Capacity Planning at REA Group

REA Group, a digital real estate company, utilizes Amazon Managed Streaming for Apache Kafka (Amazon MSK) alongside a data streaming platform named Hydro. This combination enables REA Group to efficiently distribute vast data volumes across various domains and services. Their strategy ensures high performance and cost-effectiveness while effectively scaling to accommodate increasing user demands. The article delves into their approach towards MSK cluster capacity planning, crucial for optimizing resource utilization.

Amazon SageMaker Lakehouse for Enterprises

Amazon SageMaker Lakehouse offers a streamlined solution for enterprise-wide data access, integrating data from diverse sources like Amazon S3, Amazon Redshift, and AWS Glue Data Catalog. By utilizing AWS Lake Formation for permission management, it facilitates secure access across the organization. This unified approach empowers teams to utilize their preferred analytical tools, enhancing capabilities such as predicting customer churn.

Fine-Grained Access Control with AWS Glue 5.0

AWS Glue 5.0 introduces fine-grained access control (FGAC), leveraging AWS Lake Formation’s policy definitions. FGAC allows meticulous control over access to data lake resources, including tables, columns, and rows. The post provides insights on implementing FGAC within AWS Glue 5.0 through detailed Lake Formation permissions.

Open Table Formats in AWS Glue 5.0

In the evolving big data landscape, open table formats like Iceberg, Hudi, and Delta Lake offer new possibilities. AWS Glue 5.0 supports these formats, enhancing data storage and analysis. This post reviews recent updates and improvements, illustrating their implementation in the AWS Glue framework.

Unveiling AWS Glue 5.0 for Apache Spark

AWS Glue 5.0 has launched, enhancing data integration workloads on AWS. With upgrades to Apache Spark 3.5.2 and Python 3.11, the new version promises accelerated insights and scalability. The article highlights performance improvements and key features, offering guidance on getting started with AWS Glue 5.0.

Utilizing AWS Glue Iceberg Rest Catalog with Apache Spark

This article explores the integration of open-source Apache Spark with AWS Glue Iceberg REST Catalog. It details configuring third-party engines and performing read/write operations on Amazon S3 tables. AWS Lake Formation manages metadata and data access, utilizing temporary credential vending.

Visual ETL Flows with Amazon SageMaker Unified Studio

Amazon SageMaker Unified Studio (preview) provides a cohesive environment for data and AI development. The post demonstrates building low-code and no-code visual ETL flows, facilitating seamless data ingestion and transformation. This approach supports multiple data sources, enhancing data processing efficiency.

Zero-ETL Integration with AWS Glue and SageMaker Lakehouse

AWS introduces zero-ETL integration, simplifying data processing from platforms like Salesforce and ServiceNow to Amazon SageMaker Lakehouse. This feature supports data replication and versioning, utilizing Apache Iceberg’s capabilities. The article outlines a use case involving ServiceNow data, emphasizing advantages like time travel within zero-ETL integrations.

Governing Amazon Athena Federated Queries

This post details Amazon Athena’s integration with SageMaker Unified Studio for executing federated queries across platforms like Redshift and Snowflake. SageMaker Lakehouse enables federated catalogs, enhancing data presentation and security. The post also covers column-level security permissions using AWS Lake Formation.

The Next Generation of Amazon SageMaker

At AWS re:Invent 2024, Amazon SageMaker was showcased as the central hub for data, analytics, and AI. The update aims to streamline analytics and AI workload integration, facilitating collaboration and reducing data silos. It emphasizes robust governance and security, speeding up AI application development.

ANZ Institutional Division’s Federated Data Platform

ANZ Institutional Division has embraced a federated data platform, inspired by data mesh principles. This transformation empowers domain teams to create data products, optimizing business outcomes. The post discusses the challenges and initial successes of implementing a data product mindset.

Automated Table Statistics with AWS Glue Data Catalog

AWS Glue Data Catalog now automates collecting statistics for new tables, integrating with Amazon Redshift Spectrum and Amazon Athena’s cost-based optimizer. This automation enhances query performance and reduces costs. The post examines how these statistics improve data platform efficiency.

Introducing the HubSpot Connector for AWS Glue

This introduction to the HubSpot connector for AWS Glue demonstrates its potential to unify HubSpot data with data from AWS accounts and other SaaS services. By consolidating data in AWS, businesses can enhance and analyze it, providing a comprehensive data integration experience.

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Networking & Content Delivery

In the realm of AWS Networking & Content Delivery, two noteworthy advancements are enhancing the capabilities of cloud networking: AWS PrivateLink support for VPC resources and Amazon VPC Lattice. These innovations offer improved security, connectivity, and network architecture simplification across AWS environments and beyond. Below is a detailed exploration of each technology and its business implications.

Extending SaaS Capabilities with AWS PrivateLink

AWS PrivateLink enables secure and private connectivity to shared resources across Virtual Private Clouds (VPCs) and AWS accounts. It extends further to on-premises environments, ensuring that sensitive data does not traverse the public internet. This functionality is crucial for organizations seeking to enhance their SaaS offerings, safeguarding data while maintaining high-efficiency communication paths.

The primary use cases for AWS PrivateLink include allowing third-party services to connect securely to VPC resources and enabling internal services to communicate privately across different AWS accounts. By leveraging PrivateLink, businesses can enforce tighter security controls, reduce latency, and streamline network management.

Implementation best practices involve careful planning of endpoint services and security policies. It’s important to map out the network architecture to achieve optimal resource allocation and maintainance of network efficiency. By following AWS documentation and best practice guidelines, organizations can deploy PrivateLink with minimal disruption to existing services.

Modernizing Networks with Amazon VPC Lattice

Amazon VPC Lattice offers a powerful framework for modernizing enterprise network architectures on AWS. It provides seamless integration with all AWS compute services and supports a wide range of application and transport protocols, enhancing the flexibility of network design. This modernization is vital for enterprises aiming to adopt microservices architectures or hybrid cloud models.

VPC Lattice simplifies network connectivity by abstracting complex network setups, which reduces the overhead for network management. Its support for modern security features ensures enterprise networks are resilient against threats, maintaining compliance and reinforcing data protection measures.

Using VPC Lattice, organizations can achieve streamlined operations and simplified network configurations. This enables IT teams to focus more on innovation rather than infrastructure management. As a part of AWS’s commitment to evolving its networking capabilities, VPC Lattice exemplifies the shift towards more adaptable and robust cloud-native network solutions.

How KeyCore Can Assist

KeyCore, as the leading AWS Consultancy in Denmark, offers expert guidance on implementing AWS networking solutions. With detailed knowledge and experience in deploying AWS PrivateLink and VPC Lattice, KeyCore can assist in designing, executing, and optimizing network architectures tailored to business needs. Our professional and managed services ensure seamless integration and operation of these AWS features, providing ongoing support and troubleshooting to maximize your cloud environment’s potential. Visit KeyCore for more information on how we can elevate your AWS infrastructure.

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AWS Storage Blog

In today’s data-driven landscape, businesses handling vast amounts of data, often in the order of petabytes, face the challenge of optimizing both storage and processing. This optimization is crucial to derive timely and cost-effective insights from data. One popular choice among customers for achieving enhanced storage and query performance is Apache Parquet. Not only does Parquet offer efficient data compression and encoding, but it also allows businesses to manage large datasets more effectively.

Leveraging Apache Iceberg for Enhanced Data Management

Beyond just choosing Parquet for its performance benefits, many organizations are turning to Apache Iceberg to further organize their Parquet datasets. Iceberg provides advanced database-like features that are particularly beneficial in big data environments. Among these features are:

  • Schema Evolution: This allows for changes in the data schema over time without the need for costly rewrites.
  • Time Travel: Facilitates querying historical data, enabling analytics on past states of the data.
  • ACID Transactions: Ensures data consistency and reliability, even in complex data operations.

Performance Improvements with Amazon S3 Tables

Amazon S3 Tables integrate these technologies to offer remarkable improvements in query performance, reportedly by up to three times. The use of compaction plays a pivotal role in these performance enhancements. Compaction organizes and consolidates data files, significantly reducing the amount of data that needs to be scanned during a query. This not only speeds up query execution but also reduces the computational resources required, resulting in cost savings.

How KeyCore Can Assist

KeyCore, as a leading AWS consultancy in Denmark, can help businesses leverage these technologies for optimal performance and cost-effectiveness. With expertise in deploying and managing AWS storage solutions, KeyCore can assist in implementing Apache Iceberg and optimizing data architecture for Amazon S3. This ensures businesses can efficiently manage their data while gaining insights faster and at a lower cost. For more details on how KeyCore can support your data management needs, visit our website.

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AWS Architecture Blog

Efficient Satellite Imagery Supply with AWS Serverless at BASF Digital Farming GmbH

BASF Digital Farming GmbH, in collaboration with xarvio Digital Farming Solutions, is revolutionizing the way satellite imagery is supplied to farmers. Their mission is to enhance farmers’ decision-making abilities through the xarvio FIELD MANAGER platform, which requires the swift provision of the latest satellite imagery. By leveraging AWS Serverless technologies, they have optimized their operations to deliver these crucial images effectively and efficiently.

Utilizing AWS’s suite of serverless services, BASF Digital Farming GmbH has been able to process and distribute satellite imagery with remarkable speed. This approach reduces the need for traditional server management, enabling the team to focus on improving their agronomic decision support tools. The scalable nature of AWS serverless solutions ensures that BASF can handle varying loads, providing seamless access to satellite data whenever and wherever needed.

Optimizing Serverless Developer Experience on AWS

For developers exploring serverless architecture for the first time, or for those seeking to enhance their development cycle, AWS offers a comprehensive array of resources to streamline the journey from code to production. AWS’s serverless offerings empower developers to accelerate their feedback loops and improve their overall development experience.

The collection of tools and resources provided by AWS allows developers to focus on writing code without worrying about server management or scalability issues. By using AWS services such as AWS Lambda, Amazon API Gateway, and AWS Amplify, developers can enhance their productivity and reduce time-to-market for their applications. These services facilitate a more agile and responsive development process, allowing developers to test, deploy, and iterate rapidly.

How KeyCore Can Help

KeyCore, the leading AWS Consultancy in Denmark, is well-equipped to assist businesses in leveraging AWS serverless technologies. Our expertise in professional and managed services ensures that organizations can optimize their operations with bespoke solutions tailored to their unique needs. Whether it’s enhancing satellite imagery delivery or improving serverless development workflows, KeyCore provides the guidance and support necessary to maximize the value of AWS technologies.

Our team of AWS-certified experts is ready to help navigate complex architectures and implement efficient solutions that empower businesses to achieve their digital transformation goals. By partnering with KeyCore, organizations can confidently harness the full potential of AWS serverless technologies to drive innovation and growth.

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AWS Partner Network (APN) Blog

Amazon SageMaker, a comprehensive platform on AWS, has been revamped to offer a more streamlined experience for handling data analytics and AI workloads. The new generation of Amazon SageMaker features a Unified Studio, Lakehouse, and advanced governance tools, making it easier for AWS Partners to enhance their solutions. This integrated platform aims to simplify the entire data and AI workflow, providing a cohesive environment that combines multiple AWS services.

New Initiatives for AWS Partner Success

At re:Invent 2024, several initiatives were introduced to boost AWS Partner success. These innovations focus on co-selling with AWS, improving collaboration, and accelerating the sale of Partner solutions on AWS Marketplace. By leveraging cutting-edge AI technologies, these initiatives aim to drive unprecedented growth and offer significant customer value by streamlining processes and enhancing Partner solutions.

Maximizing Co-Sell Opportunities

AWS has launched new strategies to assist Partners in co-selling with AWS. This includes building scalable co-sell systems, providing enhanced Partner benefits, and offering co-marketing opportunities. These measures are designed to increase customer lead generation and create more robust collaborative environments, driving joint success in customer deals.

Partner Connections

The Partner Connections feature in AWS Partner Central, now in preview, helps AWS Partners connect with each other to co-sell and develop differentiated solutions. This integrated experience allows Partners to accelerate deal closures and deliver enhanced value to customers, providing an efficient platform for collaboration.

AWS Consumer Goods Competency

The AWS Consumer Goods Competency connects industry customers with Partners who offer innovative technology solutions for the rapidly evolving consumer goods industry. With a focus on changing customer preferences, supply chain disruptions, and emerging technologies, this specialization supports comprehensive business transformation by delivering expert consulting services and advanced technology solutions.

Digital Sovereignty with AWS Partners

In today’s digital landscape, digital sovereignty and compliance are critical, especially for public sector organizations and regulated industries. The AWS Digital Sovereignty Competency connects customers with trusted Partners to help manage digital assets while meeting compliance requirements, allowing organizations to leverage cloud benefits securely.

Amazon Security Lake Ready Solutions

Addressing the challenge of managing vast amounts of security data, AWS introduces the Amazon Security Lake Ready Specialization. This initiative provides AWS customers with scalable and user-friendly security data management solutions, enabling efficient operations and effective threat detection across organizational environments.

AI Security for AWS Competency Partners

As AI transforms application development, new security risks arise. AWS has introduced an AI security category for Security Competency Partners, helping customers identify Partners with expertise in securing AI environments. This initiative focuses on data privacy, model integrity, and preventing threats, ensuring robust security for AI applications.

Data and AI Governance and Security Initiative

AWS has launched a Data & AI Governance and Security partner initiative to tackle complex data management challenges. By partnering with elite Service and Software partners, AWS offers curated solutions to help organizations maintain compliance and ethical standards while innovating responsibly. The initiative provides tools, expertise, and increased visibility, benefiting both Partners and customers.

Regional and Global AWS Partners of the Year

The 2024 AWS Partner Awards celebrated exceptional innovation and customer success among Partners in Europe, Middle East, Africa, and globally. Recognized for specialization, innovation, and cooperation, these Partners have demonstrated remarkable results, reinforcing AWS’s commitment to building strong partnerships.

Resource Control Policies Launch Partners

By integrating Resource Control Policies (RCPs), AWS Partner Network Launch Partners are aiding customers in managing and enforcing access controls on AWS resources. These solutions help align with security policies, mitigate external access risks, and simplify policy enforcement, ensuring secure operations across AWS environments.

How KeyCore Can Help

As a leading AWS consultancy, KeyCore is uniquely positioned to help organizations navigate these advancements. With extensive expertise in AWS services and solutions, KeyCore can assist in leveraging the latest AWS features, optimizing co-sell opportunities, and implementing robust security and governance frameworks. Whether enhancing existing operations or exploring new AWS capabilities, KeyCore provides tailored solutions to meet specific business needs, driving innovation and ensuring compliance. Visit KeyCore to learn more about how their services can benefit your organization.

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AWS Cloud Enterprise Strategy Blog

Executives today face an environment where technology and business trends are simultaneously transforming industries at an unprecedented pace. To navigate this dynamic landscape, it is essential for leaders to distinguish the trends that offer opportunities for innovation and growth from those that pose potential disruptions. Understanding these trends is not just about staying competitive but also about leveraging them to propel business success.

Identifying Key Trends

The first step in managing these changes is recognizing which trends are significant. Executives should prioritize trends that either open new avenues for growth or threaten to disrupt existing business models. These include technological advancements like artificial intelligence, machine learning, and cloud computing, as well as business practices evolving in response to digital transformation.

Experimentation and Adaptation

Once key trends are identified, experimentation becomes vital. This involves piloting new technologies and business models in controlled environments to evaluate their potential impact. Successful experimentation can reveal insights that inform strategic decisions and drive innovation. It also equips businesses to adapt quickly, thereby maintaining competitiveness and relevance in a rapidly changing market.

Strategic Alignment and Leadership

For organizations to thrive, it is crucial that technology trends are aligned with business strategy. Leaders must ensure that their teams are agile and capable of implementing changes effectively. This requires a cultural shift towards embracing innovation and continuous learning. By fostering an environment where experimentation is encouraged, companies can become more resilient to disruptions.

How KeyCore Can Assist

At KeyCore, we specialize in guiding organizations through the complexities of cloud-based transformations. Our expertise in AWS solutions enables us to help enterprises identify and harness emerging trends effectively. We offer tailored professional and managed services designed to align with strategic business objectives, ensuring that companies not only adapt to but also flourish in an ever-evolving technological landscape.

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AWS HPC Blog

Boosting HPC Workload Performance with Storage Caching

For enterprises aiming to enhance their High-Performance Computing (HPC) workloads on AWS, leveraging a storage caching server can significantly elevate performance. This approach involves constructing a high-speed EC2 cache, which is both cost-effective and efficient, priced under $4 per hour. By creating this cache, businesses can expect reduced latency in file reads, resulting in faster data processing and improved workload efficiency. The cache server serves as an intermediary storage layer that accelerates data retrieval and optimizes resource utilization, making it an indispensable component for performance-driven HPC tasks.

Implementing Multi-Node LLM Inference with Advanced AWS Technologies

The exponential growth in Large Language Models (LLMs) has necessitated robust deployment solutions that can efficiently handle extensive parameters, such as the 405 billion-parameter Llama 3.1. Technologies like TensorRT-LLM and Triton, integrated with Amazon Elastic Kubernetes Service (EKS), provide a seamless mechanism to deploy these models across multiple nodes. This multi-node deployment strategy ensures scalability and performance, accommodating the demanding computational requirements of state-of-the-art LLMs. By utilizing EKS, organizations can manage containerized applications with ease, orchestrating resources to meet the dynamic needs of LLM inference workloads. This integration allows businesses to harness the power of advanced AI models, driving innovation and maintaining competitive advantage in data-driven fields.

How KeyCore Can Assist

KeyCore, as a leading AWS consultancy, offers expertise in implementing both storage caching solutions and complex AI model deployments. Our team can guide organizations through the process of setting up high-speed EC2 caches, ensuring optimal cost-performance balance for HPC workloads. Additionally, we assist clients in deploying and scaling LLM inference workloads using cutting-edge AWS technologies. With a focus on maximizing efficiency and innovation, KeyCore delivers tailored solutions that align with business objectives, driving success in the cloud computing landscape. Contact us to explore how KeyCore’s professional and managed services can transform your AWS environment.

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AWS Cloud Operations Blog

AWS re:Invent 2024 heralded exciting announcements that promise to revolutionize cloud operations. In an insightful presentation by Nandini Ramani, VP of Search, Observability & Cloud Ops, AWS unveiled a series of innovative capabilities designed to transform IT operations.

Key AWS Cloud Operations Announcements

At the forefront, AWS introduced tools that enhance automation and efficiency in managing cloud environments. These tools are pivotal in streamlining operations, reducing manual intervention, and minimizing operational risks. Additionally, improvements in observability were highlighted, focusing on providing deeper insights and visibility into cloud workloads, which are crucial for maintaining optimal performance and quickly resolving issues.

Enhanced Observability and Monitoring

AWS has upgraded its suite of observability and monitoring tools to offer more comprehensive analytics. These upgrades are designed to provide accurate, real-time data that can help organizations proactively manage their cloud resources. By leveraging machine learning, AWS aims to deliver predictive insights, which can foresee potential bottlenecks or performance degradations before they impact operations.

Automating IT Operations

New automation capabilities were also introduced to automate routine tasks, allowing IT teams to focus on strategic initiatives. This includes automated scaling, patch management, and configuration updates, which help maintain the reliability and security of cloud infrastructures. These advancements reduce the burden on IT staff and ensure a robust and efficient operating environment.

How KeyCore Can Assist

KeyCore, as Denmark’s leading AWS consultancy, is ideally positioned to help organizations leverage these new capabilities. With extensive expertise in professional and managed services, KeyCore can provide tailored solutions that integrate AWS’s latest innovations into existing cloud architectures. Whether automating operations or enhancing observability, KeyCore can ensure that businesses maximize the value of AWS’s offerings, driving both operational excellence and business growth.

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AWS for Industries

Automating Physician Documentation with AWS HealthScribe

The administrative burden in healthcare, particularly with electronic health record (EHR) documentation, is substantial, consuming an average of 4.5 hours per day for physicians. This significant time investment detracts from patient care and contributes to physician burnout, affecting 48% of healthcare workers. Contrast AI is leveraging AWS HealthScribe to automate EHR documentation, freeing up valuable time for healthcare providers. By streamlining administrative tasks, this technology not only reduces burnout but also enhances the quality of patient care, addressing the projected shortage of healthcare professionals.

Consumer Goods Industry Transformation with AWS Competency Partners

The consumer goods sector is undergoing rapid transformation driven by shifts in customer preferences and technological advancements. AWS Consumer Goods Competency Partners are at the forefront of this change, helping companies leverage emerging technologies to enhance efficiency and innovation. According to McKinsey Global Institute, the industry is poised for significant advancements over the next decade. By embracing AWS solutions, businesses can optimize supply chains, enhance customer experiences, and maintain regulatory compliance, ensuring they stay competitive in a rapidly evolving market.

Agentic AI Systems in Healthcare

Guest-authored by GE Healthcare, this article explores the potential of agentic AI systems to tackle pressing challenges in healthcare. Despite remarkable medical advancements like CRISPR and 3D-printed organs, healthcare still faces inefficiencies and strain. AI systems can address these challenges by optimizing processes and improving patient outcomes. By integrating agentic AI, healthcare providers can enhance operational efficiency and focus more on patient-centric care, potentially transforming the sector’s legacy from inefficiencies to innovation.

Maturity of 5G Mobile Packet Core as a Cloud Workload

Comcast’s deployment of its 5G mobile packet core, developed by Nokia, on the AWS public cloud marks a significant milestone. This evolution demonstrates the public cloud’s capability to support complex network functions. The maturity of the 5G mobile core as a cloud workload indicates that cloud-based solutions can now reliably handle demanding telecom operations, facilitating seamless integration and scalability for service providers.

Retailers and Generative AI with Amazon Bedrock

Historically, retailers stored and processed data in system-specific silos, only transferring necessary data to Enterprise Data Warehouses (EDW). As data volumes grew, retailers transitioned to data lakes, centralizing all data. Today, with generative AI and Amazon Bedrock, retailers can enhance data operations and software delivery. These technologies enable smarter data management, improving decision-making and operational efficiency by providing comprehensive insights and facilitating innovation in retail strategies.

Streamlining Medical Imaging with NVIDIA NIMs and AWS

Medical imaging AI is yet to fully benefit clinicians due to integration challenges. NVIDIA NIMs, combined with AWS services, simplify AI deployment in medical imaging, addressing scalability and consistency issues. These solutions streamline the incorporation of AI in clinical workflows, enhancing diagnostic accuracy and efficiency. By facilitating seamless scaling to support millions of studies annually, this integration promises a consistent end-user experience, crucial for widespread AI adoption in medical imaging.

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AWS Marketplace

Enhancing product discovery and purchasing experiences on AWS Partner websites is now even simpler with the introduction of “Buy with AWS”. This feature allows customers to seamlessly discover and purchase software directly from seller websites, utilizing the extensive repository of listings available in the AWS Marketplace. By integrating with AWS Marketplace, sellers can offer streamlined procurement processes, ensuring customers have an efficient and frictionless buying experience. This integration not only simplifies the purchasing process but also aligns with the digital-first strategies many enterprises are adopting.

The “Buy with AWS” feature effectively reduces the complexity involved in traditional procurement methods. Customers can benefit from a unified buying experience, leveraging their existing AWS accounts to manage purchases and subscriptions effortlessly. By enabling seamless integration between seller websites and AWS Marketplace, customers can rapidly access the software solutions they need, enhancing productivity and innovation. Additionally, sellers benefit from enhanced visibility and a wider reach within the AWS ecosystem, potentially increasing sales and customer satisfaction.

Getting Started with Databricks on AWS Marketplace

The AWS Marketplace offers a newly streamlined launch experience for the Databricks Data Intelligence Platform, allowing users to easily create and configure their own Databricks workspace. This simplified process facilitates swift deployment, enabling users to quickly harness the power of Databricks for their data analytics needs. The platform provides a robust foundation for building advanced data science models and performing large-scale data transformations.

To demonstrate the platform’s capabilities, a hands-on example of running a classification model is provided, which predicts annual income from census data. This practical use case illustrates the efficiency and power of Databricks in handling complex datasets. Users can leverage this platform to enhance their data-driven strategies, increasing accuracy in predictive modeling and gaining deeper insights from their data. The collaboration between Databricks and AWS Marketplace ensures customers receive comprehensive support and access to the latest innovations in data intelligence.

How KeyCore Can Assist

KeyCore, as a leading AWS consultancy in Denmark, offers expert guidance and support in leveraging AWS Marketplace solutions. Whether integrating “Buy with AWS” into existing e-commerce platforms or deploying advanced data analytics tools like Databricks, KeyCore provides tailored services to maximize business value. Our team of AWS-certified professionals can help optimize procurement processes, ensure seamless integration, and drive innovation through effective data utilization. Discover how KeyCore can enhance your AWS Marketplace strategy, boosting efficiency and expanding your digital capabilities by visiting KeyCore today.

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The latest AWS security, identity, and compliance launches, announcements, and how-to posts.

Geographic IP Filtering with AWS Network Firewall

AWS Network Firewall, a managed service simplifying the deployment of essential network protections within virtual private clouds (VPCs), introduces a noteworthy feature: Geographic IP Filtering. This new capability empowers users to filter traffic based on geographic location, facilitating easier compliance with regional regulations. With Geographic IP Filtering, organizations can swiftly manage and control the geographical flow of data, enhancing security measures and aligning with local compliance requirements. This feature provides businesses with the tools necessary to safeguard data transfers against unauthorized access from specific regions, thereby ensuring stronger adherence to international data protection laws.

Transition to Post-Quantum Cryptography in AWS

Amazon Web Services (AWS) embarks on a crucial migration to post-quantum cryptography (PQC), fortifying its security framework against future quantum computing threats. As part of AWS’s shared responsibility model, PQC features will be both automatically enabled for all customers and offered as optional enhancements for those seeking additional compliance measures. This strategic move is designed to bolster data security against the advent of quantum computational capabilities, ensuring that AWS customers remain safeguarded from potential vulnerabilities. By preparing for the post-quantum era, AWS demonstrates its commitment to providing cutting-edge security solutions that anticipate technological advancements and safeguard critical information.

Generative AI and Regulatory Insights in Australian Financial Services

The Australian Prudential Regulation Authority (APRA) offers new insights into the adoption of generative AI within the financial services sector. In remarks delivered at the AFIA Risk Summit 2024, APRA member Therese McCarthy Hockey emphasizes the regulator’s positive stance on the rapid integration of generative AI by banks, insurance companies, and superannuation funds. APRA’s guidance provides clarity and a regulatory framework that supports the responsible deployment of AI technologies, encouraging institutions to harness the transformative potential of AI while managing associated risks effectively. This forward-looking approach aims to balance innovation with safety, ensuring the financial sector can leverage generative AI for enhanced operational efficiency and customer service.

How KeyCore Can Assist

At KeyCore, Denmark’s leading AWS consultancy, we offer expert guidance and implementation support for AWS’s latest security features, including Geographic IP Filtering and post-quantum cryptography. Our team provides strategic insights and technical assistance to help organizations navigate the complexities of AWS security enhancements. Additionally, we assist financial institutions in aligning with regulatory guidance on generative AI adoption, ensuring that they can safely and effectively integrate these technologies into their operations. With our deep knowledge and experience, KeyCore is committed to guiding businesses through the evolving landscape of AWS security and compliance.

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AWS Contact Center

In the competitive landscape of modern business, providing exceptional customer experience (CX) is essential. Insights and analytics are transforming organizations’ approaches to understanding, predicting, and responding to customer needs. Amazon Connect leads this transformation by offering advanced AI-powered analytics. These tools enable businesses to extract valuable insights from their customer interactions, enhancing their ability to deliver personalized and timely experiences.

AI-Powered Analytics with Amazon Connect

Amazon Connect leverages AI to provide powerful analytics capabilities that help businesses elevate their contact center operations. By analyzing customer interactions, companies can gain a deeper understanding of customer behavior and preferences. This understanding allows organizations to anticipate customer needs and provide more effective support, ultimately improving customer satisfaction and loyalty. With Amazon Connect, businesses can seamlessly integrate AI-driven insights into their contact center operations, facilitating a more proactive and responsive approach to customer service.

Generative AI-Enhanced Self-Service

Amazon Connect simplifies the creation and management of self-service experiences with its new features powered by generative AI. These enhancements allow businesses to offer superior customer service at lower costs. Companies can now build self-service options more easily, reducing the need for live agent intervention and enabling customers to resolve issues quickly on their own. This not only leads to increased customer satisfaction but also optimizes operational efficiency by freeing up resources to handle more complex inquiries.

Secure Collection of Sensitive Information

In an era where digital interactions are paramount, Amazon Connect Chat provides a secure platform for collecting sensitive information. Whether processing payments, updating shipping addresses, or verifying identities, organizations must ensure compliance with regulations such as PCI DSS and GDPR. Amazon Connect offers robust security features that protect sensitive data, ensuring that businesses can maintain compliance while delivering seamless chat interactions. This capability is crucial for building customer trust and safeguarding company reputation in a data-driven world.

With the combination of AI-powered analytics, generative AI-enhanced self-service, and secure data collection capabilities, Amazon Connect empowers businesses to transform their contact centers into dynamic, customer-centric hubs. KeyCore, as an expert AWS consultancy, can assist organizations in implementing these features effectively, ensuring that they maximize their investment in Amazon Connect. Whether through professional services or managed solutions, KeyCore provides the guidance and support needed to leverage AWS technologies for superior customer service experiences.

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Innovating in the Public Sector

Democratizing Data Access with AWS Open Data Sponsorship

The AWS Open Data Sponsorship Program is revolutionizing data accessibility by making high-value, cloud-optimized datasets publicly available on Amazon Web Services (AWS). This initiative democratizes data by partnering with providers to offer datasets for public analysis on AWS, fostering the development of new cloud-based techniques and tools. The program is a catalyst for community development, benefitting from shared datasets. As of this quarter, AWS has made 39 new or updated datasets available, contributing to a collection of over 100 petabytes of data available for public use.

Enhancing Governance with AWS Multi-Account Strategy

Adopting a multi-account strategy is crucial for AWS public sector customers seeking improved cloud governance and compliance. By migrating from a shared account model to a multi-account environment, public sector customers can enhance security and operational efficiency. The transition involves strategic preparation and migration methods that AWS public sector customers can implement to leverage the benefits of a multi-account structure effectively.

Boosting Skills and Jobs with AWS Tech Alliance

The AWS Skills to Jobs Tech Alliance is reshaping the technology landscape in Germany by enhancing cloud skills and creating tech jobs. This initiative has engaged over 53,000 learners and partnered with more than 650 employers and 970 educational institutions across 11 countries since its 2023 launch. Germany’s engineering and industrial sectors, including automotive and pharmaceuticals, are benefiting significantly from the Tech Alliance’s contributions.

Innovations from AWS re:Invent 2024

During AWS re:Invent 2024, an Innovation Session led by Dave Levy of the Worldwide Public Sector showcased AWS’s role in empowering customers to tackle challenges using cloud technology and generative AI. The session highlighted transformative initiatives, inspiring customer stories, and technological advancements that are helping AWS public sector customers enhance life on Earth.

Advancing Women’s Health Research with AWS Support

AWS is committed to transforming healthcare through cloud technologies. At AWS re:Invent 2024, AWS announced up to $2 million in AWS credits to support ARPA-H Sprint for Women’s Health awardees. This initiative aims to address critical challenges in women’s health, underscoring AWS’s dedication to advancing crucial research and solutions in the healthcare sector.

AWS IMAGINE Grant: Fostering Nonprofit Sector Innovation

The AWS IMAGINE Grant for 2024-2025 highlights AWS’s partnership with the nonprofit sector to harness transformative technologies like generative AI. This year’s cohort of winners, the largest to date, reflects AWS’s commitment to supporting organizations that utilize cloud technologies to maximize impact and productivity, fostering responsible innovation for societal and environmental betterment.

Accelerating AI Adoption with AWS Partner Transformation Program

AWS is dedicated to enhancing cloud innovation journeys for its partners, particularly in the public sector, through the AWS Partner Transformation Program (PTP). This program provides comprehensive assessment, training, and enablement, empowering partners to build successful AWS-based businesses and accelerate their generative AI adoption.

Generative AI at Wharton School

The Wharton School of the University of Pennsylvania is leveraging generative AI to enhance student learning. Supported by AWS, Wharton will introduce a virtual teaching assistant in 2024, enabling real-time responses to course-related queries. This innovation marks a significant step in integrating AI into educational environments.

Enhancing Public Safety with CentralSquare on AWS

CentralSquare is transforming justice and public safety solutions by exclusively building on AWS infrastructure. Their secure, reliable, and fast technology solutions are crucial for justice and public safety agencies, providing secure cloud migration crucial for operational efficacy in critical moments.

Resilient Edge Computing with Satellite Resiliency for AWS Outposts

Satellite Resiliency for AWS Outposts offers a robust solution for cloud-connected edge computing in remote areas. This Partner-managed solution ensures business continuity by routing traffic over Low Earth Orbit (LEO) satellite connections when terrestrial connectivity is unavailable, enhancing data residency and resource management for geographically dispersed environments.

Streamlining Configuration Management with External Repositories

Organizations deploying the Landing Zone Accelerator (LZA) on AWS can improve configuration management by using GitHub as a repository for configuration files. This approach allows better version control, collaboration, and automation, streamlining the management and deployment process for AWS solutions.

KeyCore: Your Partner in AWS Innovation

KeyCore is committed to delivering advanced AWS solutions tailored to public sector needs. By leveraging our expertise in AWS services and cloud technologies, we help organizations achieve optimized data access, enhanced security, and innovative solutions. Partner with KeyCore to navigate AWS’s transformative offerings and drive your organization’s cloud journey forward.

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