Summary of AWS blogs for the week of monday Mon Aug 05

In the week of Mon Aug 05 2024 AWS published 88 blog posts – here is an overview of what happened.

Topics Covered

AWS DevOps & Developer Productivity Blog

Code Clarity: Enhancing Code Understanding and Efficiency with Amazon Q Developer

Software developers often find themselves managing legacy code. While writing new code is essential, a significant amount of time is dedicated to refactoring and maintaining existing codebases. Amazon Q Developer addresses these challenges by enhancing code understanding and efficiency. This tool assists developers in navigating and comprehending complex code structures, thereby improving productivity and reducing the time needed for code maintenance.

Amazon Q Developer uses advanced techniques to analyze codebases, making it easier for developers to understand the intricacies of existing code. This clarity leads to more efficient refactoring and enhanced code quality. By leveraging Amazon Q Developer, teams can ensure that their code remains maintainable and robust over time.

Generating Accurate Git Commit Messages with Amazon Q Developer CLI Context Modifiers

Clear and concise Git commit messages are vital for effective version control and collaboration. However, providing additional context in commit messages can be challenging, especially for complex projects. Amazon Q Developer’s CLI Context Modifiers offer a solution by analyzing code changes and generating meaningful commit messages.

This feature ensures that commit messages accurately reflect the changes made, facilitating better communication among team members. By automating the generation of context-rich commit messages, Amazon Q Developer enhances the overall efficiency of version control processes, leading to improved collaboration and project management.

Implementing Identity-Aware Sessions with Amazon Q Developer

In the realm of technology and authentication, understanding identity is paramount. Amazon Q Developer enables identity-aware sessions within the AWS console, enhancing security and user experience. This capability ensures that actions within the console are accurately attributed to the correct user, improving traceability and accountability.

By implementing identity-aware sessions, organizations can enhance their security posture and ensure compliance with various regulations. Amazon Q Developer’s identity management features streamline user authentication processes, providing a seamless and secure experience for AWS users.

Deploying a Serverless Web Application with AWS CDK Using Amazon Q Developer

Amazon Q Developer, a Generative AI-powered assistant, accelerates Infrastructure as Code (IaC) development using the AWS Cloud Development Kit (CDK). IaC allows developers to define and manage infrastructure components through code, enhancing consistency and reliability. Amazon Q Developer aids in deploying serverless web applications by simplifying the IaC development process.

This tool offers guided assistance, helping developers and DevOps engineers efficiently set up and manage serverless infrastructures. The integration of Amazon Q Developer with AWS CDK ensures that best practices are followed, leading to optimized cloud deployments and reduced operational overhead.

How KeyCore Can Help

At KeyCore, we specialize in leveraging advanced AWS tools like Amazon Q Developer to enhance development and operational efficiency. Our experts can assist in integrating these tools into your workflows, ensuring that your team benefits from improved code clarity, accurate Git commit messages, robust identity management, and efficient serverless deployments. Contact KeyCore to learn how we can optimize your AWS environment and drive your business forward.

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Official Machine Learning Blog of Amazon Web Services

Deltek, a leader in project-based business solutions, partnered with AWS Generative AI Innovation Center to implement a RAG-based Q&A solution for government solicitation documents. Utilizing services like Amazon Textract, Amazon OpenSearch Service, and Amazon Bedrock, Deltek streamlined the process of answering questions on both single and multiple solicitation documents. This integration enhances Deltek’s ability to serve over 30,000 clients efficiently.

Cisco’s Latency Improvements with SageMaker

Cisco achieved a remarkable 50% latency improvement for Webex by implementing Amazon SageMaker’s faster autoscaling feature. Webex, known for its cloud-based collaboration tools, leverages AI and ML to enhance user experiences and overcome geographical, linguistic, and technical barriers. By integrating AWS services, Cisco not only improved performance but also maintained its commitment to security and privacy.

Generative AI for Cisco’s Contact Centers

Cisco’s adoption of Amazon SageMaker Inference components has revolutionized their contact center operations. By integrating generative AI, Cisco can analyze call transcripts to better understand customer issues and improve agent productivity. The addition of conversational AI, including chatbots and virtual agents, has automated personalized communications and provided deeper insights into customer sentiment, ultimately optimizing workflows and enhancing customer interactions.

Insights from Box with Amazon Q Box Connector

Box, a leading cloud content management platform, partnered with AWS to offer seamless access to content and insights via the Amazon Q Box connector. This integration allows organizations to manage diverse digital assets effectively, driving successful business outcomes and exceptional customer experiences.

Twilio’s SQL Generation with Amazon Bedrock

Twilio, a prominent AWS customer, leveraged Amazon Bedrock to enable natural language-driven data exploration of its BI data using Looker Modeling Language. This approach simplifies querying processes, making data insights more accessible and actionable for business users.

AI Assistant Response Accuracy with Knowledge Bases for Amazon Bedrock

Advancements in large language models (LLMs) have paved the way for more accurate AI chatbots and virtual assistants. By utilizing Knowledge Bases for Amazon Bedrock and a reranking model, businesses can significantly improve the response accuracy of their AI assistants, enhancing overall customer satisfaction.

Automating ML Model Approval with Amazon SageMaker

The article outlines a method to automate the machine learning model approval process using Amazon SageMaker Model Registry and SageMaker Pipelines. This automation ensures compliance while delivering innovative solutions to customers efficiently, reducing the need for manual monitoring.

Custom Generative AI Applications with Amazon Bedrock

Amazon Bedrock helps businesses build secure, compliant foundations for generative AI applications. By offering multiple customization techniques, Bedrock allows companies to tailor models to meet specific business needs, enhancing their AI capabilities.

Code Generation in Software Development with Amazon Bedrock

Generative AI models, like those offered by Amazon Bedrock, have transformed software development by automating code generation from natural language prompts. This capability enhances developer productivity and streamlines DevOps workflows, making software development more efficient.

Inference of AudioCraft MusicGen Models with SageMaker

Music generation models, powered by AI and deep learning, can convert descriptive text into music compositions. Amazon SageMaker enables users to infer AudioCraft MusicGen models, democratizing music production and allowing individuals without formal training to create high-quality music.

RAG Solution with Amazon Bedrock and AWS CloudFormation

Building an end-to-end RAG solution involves integrating Knowledge Bases for Amazon Bedrock with AWS CloudFormation. This state-of-the-art approach combines retrieval and foundation models to create effective question-answering systems, enhancing information retrieval capabilities.

Faster LLMs with Speculative Decoding and AWS Inferentia2

Large language models (LLMs) have grown significantly in size, enhancing their ability to perform NLP tasks. Using speculative decoding and AWS Inferentia2, AWS offers solutions to speed up these large models, improving efficiency and reducing latency in processing complex language tasks.

Cataloging Audio Programs with Amazon Transcribe and Bedrock

Amazon Transcribe and Knowledge Bases for Amazon Bedrock offer tools for cataloging, querying, and searching audio programs. These tools enhance information retrieval systems by indexing audio content, making it easier to find and manage relevant data in the digital age.

How KeyCore Can Help

KeyCore, as the leading AWS consultancy in Denmark, offers expertise in integrating AWS services to meet specific business needs. Whether it’s implementing generative AI solutions like Deltek, improving performance with SageMaker, or automating processes, KeyCore provides comprehensive support. Contact KeyCore to leverage the full potential of AWS for your organization.

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Announcements, Updates, and Launches

Amazon has announced the release of Amazon Titan Image Generator v2, now available in Amazon Bedrock, offering groundbreaking creative capabilities. This new version includes features such as image conditioning, color control, background removal, and subject preservation via fine-tuning for brand consistency. These enhancements ensure that graphics meet specific brand requirements while providing unprecedented flexibility and creativity for users.

Key Features of Amazon Titan Image Generator v2

The Amazon Titan Image Generator v2 introduces several advanced features to boost creative workflows:

  • Image Conditioning: Adjust the visual attributes of images to match desired creative effects.
  • Color Control: Precisely manage color schemes to ensure consistency across all digital assets.
  • Background Removal: Easily isolate subjects from backgrounds, streamlining the creation process.
  • Subject Preservation: Fine-tune images to maintain core subject elements, ensuring brand alignment.

With these capabilities, Amazon Titan Image Generator v2 is set to revolutionize how businesses approach digital content creation, providing tools that cater to both creative and branding needs.

How KeyCore Can Assist

KeyCore, as the leading Danish AWS Consultancy, can help implement Amazon Titan Image Generator v2 within your existing AWS architecture. Our team of experts can provide tailored solutions to leverage these new features for your specific business needs, ensuring a seamless integration and optimized use of Amazon Bedrock’s enhanced creative capabilities.

AWS Weekly Roundup (Aug 5, 2024)

This week’s AWS updates highlight several significant advancements across various services, reflecting the dynamic nature of the AWS ecosystem.

Amazon Q Business

Amazon Q Business has been updated to further integrate AI capabilities, enhancing its functionality and making it more user-friendly. These improvements aim to streamline business processes and provide deeper insights through analytics.

AWS CloudFormation

AWS CloudFormation received updates to its stack management features, enabling more efficient deployment and management of AWS resources. This includes improved stack set operations and enhanced drift detection capabilities.

Amazon WorkSpaces

Amazon WorkSpaces now supports additional configurations and performance enhancements, allowing for a more flexible and robust virtual desktop experience. These updates ensure better scalability and user productivity.

How KeyCore Can Assist

KeyCore is well-positioned to help businesses make the most of these AWS updates. Whether it’s integrating the latest AI features of Amazon Q Business, optimizing AWS CloudFormation stacks, or configuring Amazon WorkSpaces, our experts provide comprehensive support and consultancy to maximize your AWS investment.

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Containers

Cordial’s Journey Implementing Bottlerocket and Karpenter in Amazon EKS: An Overview

Introduction to Cordial and Their Needs

Cordial is a cross-channel marketing platform providing tools to automate marketing strategies. This automation allows technology teams to focus on their core strengths, such as building and creativity. By using Cordial’s platform, companies can delegate data access and management to marketers, enabling seamless migration, transformation, and delivery of complex data.

Why Bottlerocket and Karpenter?

Amazon EKS is a managed Kubernetes service that simplifies the deployment, management, and scalability of containerized applications. Cordial chose to use Bottlerocket and Karpenter within Amazon EKS to enhance their infrastructure. Bottlerocket is an open-source operating system designed for hosting containers. It provides improved security, manageability, and operational efficiency compared to traditional operating systems. Karpenter is a flexible, efficient, and cost-effective Kubernetes cluster autoscaler.

Implementation Details

The integration of Bottlerocket and Karpenter with Amazon EKS was strategic for Cordial. Bottlerocket offered a minimal attack surface and simplified updates, while Karpenter ensured optimal resource utilization by dynamically scaling the cluster based on workloads. This combination led to a more secure and responsive environment for Cordial’s marketing automation platform.

Business Value

By leveraging Bottlerocket and Karpenter, Cordial achieved significant improvements in performance and cost-efficiency. The platform’s ability to handle complex data tasks with minimal manual intervention allowed Cordial to streamline operations and reduce overhead. This, in turn, enabled technology teams to concentrate on innovation and delivering high-quality solutions for their clients.

How KeyCore Can Help

KeyCore, the leading Danish AWS consultancy, offers expert guidance and support for integrating advanced AWS technologies like Bottlerocket and Karpenter. With specialized knowledge in Amazon EKS and containerized solutions, KeyCore can assist businesses in optimizing their infrastructure, enhancing security, and achieving greater efficiency. By partnering with KeyCore, companies can leverage cutting-edge tools and methodologies to transform their operations and stay ahead in a competitive market.

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AWS Quantum Technologies Blog

The Australian Red Cross Lifeblood (Lifeblood) has collaborated with AWS to optimize their rostering process, enhancing efficiency and effectiveness in managing blood donation collection. This collaboration combines advanced AWS technologies with Lifeblood’s extensive operational data to streamline staff scheduling, ensuring a balanced workload and improved donor experience.

Understanding the Collaboration

Lifeblood, a non-profit organization, collects over 1.6 million blood donations annually across Australia. Managing the logistics for such a vast operation requires meticulous planning and scheduling of staff. With AWS’s expertise, Lifeblood aimed to develop a robust, data-driven rostering system to address these challenges.

Implementing AWS Quantum Technologies

AWS introduced quantum-inspired optimization techniques, leveraging Amazon Braket, AWS’s fully managed quantum computing service. This integration allows for solving complex scheduling problems that traditional computing methods struggle with. By using quantum-inspired algorithms, Lifeblood can now process large datasets and diverse variables more efficiently, leading to optimal scheduling decisions.

Technical Approach

The technical team from AWS and Lifeblood used a combination of machine learning models and quantum-inspired optimization algorithms. The process involves:

  • Data Collection: Gathering historical rostering data and operational metrics.
  • Model Training: Using machine learning to predict staffing needs based on various factors such as donation patterns and staff availability.
  • Optimization: Applying quantum-inspired algorithms to generate optimal rosters that consider numerous constraints and preferences.

Business Value

This collaboration has significantly reduced the time and effort required for rostering, enabling Lifeblood to allocate resources more effectively. The optimized scheduling ensures that the right number of staff are available at the right times, enhancing donor satisfaction and operational efficiency. Additionally, the use of advanced AWS technologies positions Lifeblood at the forefront of innovation in non-profit operations.

How KeyCore Can Help

KeyCore, as the leading Danish AWS consultancy, can assist organizations in leveraging AWS’s quantum technologies to optimize operations similar to Lifeblood. KeyCore’s expertise in AWS services ensures that businesses can implement advanced solutions tailored to their unique needs, driving efficiency and innovation. Contact KeyCore for professional and managed services to explore how AWS quantum technologies can transform your operational workflows.

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Official Database Blog of Amazon Web Services

Public blockchain networks like Bitcoin and Ethereum offer open access to their data, but interpreting this data is often a complex task. This post on Amazon Bedrock and AWS Public Blockchain datasets provides a solution for interacting with blockchain data in natural language. The article details Amazon Bedrock’s functionalities, the solution architecture, and gives practical examples of prompts to use. It also shares interesting insights from the data and explains how the solution can be expanded to integrate different data sources.

Solution Architecture and Examples

Amazon Bedrock facilitates the process by converting the byte-encoded data into human-readable formats. The blog post reviews the architecture of this solution and provides example prompts that users can utilize to query blockchain data. This makes it simpler for users to extract meaningful information without delving into technical complexities.

Extending the Solution

Furthermore, the post discusses how to extend the solution to integrate with various data sources, enhancing its versatility and application range. This section is particularly useful for developers looking to adapt the solution to their unique needs.

Integrating AI/ML capabilities into business services can be challenging, especially when dealing with large amounts of relational data from on-premises SQL Server databases. This post highlights how Amazon RDS for SQL Server and Amazon SageMaker Canvas can be combined to streamline this process. By leveraging the integration points between these managed services, businesses can develop AI/ML solutions that utilize existing relational database workloads with minimal effort and no coding required.

Native Integration and Predictive Models

The blog explains how the seamless integration between Amazon RDS and SageMaker Canvas allows for the easy development of predictive AI/ML models. This native integration removes the need for extensive coding, making it accessible for businesses looking to enhance their services with AI/ML capabilities.

Business Benefits

Businesses can leverage these capabilities to gain predictive insights from their data, improving decision-making and customer experiences. The post provides a detailed use case to illustrate the practical applications and benefits of this integrated solution.

Real-time vector search capabilities are revolutionizing customer experiences across various industries by leveraging unstructured data such as text, images, and videos. This post discusses how Amazon MemoryDB powers real-time vector search capabilities, enabling businesses to transform their customer engagement and personalization standards.

Unstructured Data and Customer Experience

By harnessing the potential of unstructured data, businesses can deliver more personalized and engaging customer experiences. The post highlights the importance of real-time search in the context of generative AI and its impact on various industries.

Performance and Scalability

Amazon MemoryDB offers high performance and scalability, making it an ideal solution for businesses looking to implement real-time vector search capabilities. The blog details the technical aspects of MemoryDB and its advantages in handling unstructured data.

Performing a blue/green deployment switchover in Amazon Aurora MySQL-Compatible Edition is a crucial task, but having a rollback strategy is equally important. This post provides a comprehensive guide on setting up and executing a rollback strategy post switchover.

Steps for Switchover

The blog outlines the steps involved in performing a blue/green deployment switchover, ensuring that the process is smooth and efficient. It provides detailed instructions on how to prepare for the switchover, execute it, and monitor the transition.

Rollback Strategy

In addition to the switchover steps, the post emphasizes the importance of having a rollback strategy. It guides readers through the process of setting up and performing a rollback, ensuring that any issues encountered during the switchover can be promptly addressed.

Ensuring the security of your Amazon RDS and Aurora configurations is critical. This post introduces new security configuration checks provided by Prowler for AWS, focusing on Amazon RDS and Aurora.

Security Checks and Integration

Prowler offers hundreds of security checks across various AWS services. The blog highlights the new Amazon RDS and Aurora security checks and their integration with AWS Security Hub. This integration allows users to centrally manage and monitor their security configurations.

Benefits for AWS Users

The new security checks help AWS users ensure their RDS and Aurora instances are securely configured, reducing the risk of potential security breaches. The post explains the benefits of these checks and how they can enhance the overall security posture of AWS environments.

Migrating an on-premises MySQL database to Amazon Aurora MySQL can be streamlined using AWS DMS homogeneous data migrations and Network Load Balancer. This post provides a step-by-step guide to perform this migration over a private network.

Migration Steps

The blog details the steps involved in migrating an on-premises MySQL database to Amazon Aurora MySQL. It covers the setup of AWS DMS for homogeneous data migration and the configuration of the Network Load Balancer to ensure a secure and efficient migration process.

Private Network Configuration

By using a private network, the migration process is more secure and reliable. The post explains how to configure the private network for the migration, ensuring that data is transferred securely and efficiently.

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AWS Training and Certification Blog

As organizations increasingly turn to artificial intelligence (AI) to drive innovation and stay competitive, it’s critical for executives to understand the basics of generative AI. The new classroom course, Generative AI for Executives, is specifically created to equip c-suite and senior business leaders with the essential knowledge and tools needed to lead generative AI initiatives effectively. Whether from technical or non-technical backgrounds, this course ensures that every executive can make informed decisions and guide their teams successfully in the AI domain.

Course Overview

The Generative AI for Executives course covers fundamental concepts and practical applications of generative AI. It provides a comprehensive understanding of how generative AI works, its potential use cases, and its impact on business strategies. This course is tailored to address the unique needs and challenges faced by senior business leaders.

Key Learning Objectives

  • Understanding the basics of generative AI and its components.
  • Identifying business opportunities where generative AI can be applied.
  • Developing strategies to implement generative AI initiatives effectively.
  • Navigating the ethical considerations and risks associated with AI deployment.

Business Value

By participating in this course, executives can gain a strategic advantage in integrating AI into their business operations. The knowledge acquired will enable them to steer AI projects, optimize processes, and drive innovation within their organizations. This, in turn, can lead to increased efficiency, improved customer experiences, and higher competitiveness in the market.

How KeyCore Can Help

KeyCore offers specialized consulting services to help organizations leverage generative AI to its fullest potential. With expertise in AWS and AI technologies, KeyCore can assist in developing tailored AI strategies, implementing robust AI solutions, and ensuring successful adoption across various business units. Contact KeyCore today to learn how they can support your generative AI initiatives and drive business growth.

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Official Big Data Blog of Amazon Web Services

Migrate Amazon Redshift from DC2 to RA3 to accommodate increasing data volumes and analytics demands
As businesses strive to make informed decisions, the amount of data being generated and required for analysis is growing exponentially. Dafiti, an ecommerce company, recognizes the importance of using data to drive strategic decision-making processes. With the ever-increasing volume of data available, Dafiti faced the challenge of effectively managing and extracting valuable insights from this vast pool of information. They needed to gain a competitive edge and make data-driven decisions that align with company objectives. The growing need for storage space to maintain data from over 90 sources and the functionality available on the new Amazon Redshift node types, including managed storage, data sharing, and zero-ETL integrations, led them to migrate from DC2 to RA3 nodes. This article shares their migration process and impressions of the new setup.

How AppsFlyer modernized their interactive workload by moving to Amazon Athena and saved 80% of costs
AppsFlyer develops a leading measurement solution focused on privacy, enabling marketers to gauge the effectiveness of their marketing activities. They manage an enormous volume of 100 billion events every day. This post explores how AppsFlyer modernized their Audiences Segmentation product by using Amazon Athena. By leveraging Athena’s capabilities, AppsFlyer was able to significantly reduce costs by 80% while maintaining high performance and efficiency.

Stream data to Amazon S3 for real-time analytics using the Oracle GoldenGate S3 handler
Modern business applications rely on timely and accurate data, with increasing demand for real-time analytics. There is a growing need for efficient and scalable data storage solutions. Data is often stored in different datasets and needs to be consolidated before meaningful and complete insights can be drawn. This is where replication using Oracle GoldenGate S3 handler becomes crucial. By streaming data to Amazon S3, businesses can achieve real-time analytics and integrate their datasets effectively.

Query AWS Glue Data Catalog views using Amazon Athena and Amazon Redshift
AWS Glue Data Catalog views is a new feature that allows customers to create a common view schema and single metadata container. This container can hold view-definitions in different dialects and be used across engines like Amazon Redshift and Amazon Athena. This blog post demonstrates how to define and query a Data Catalog view on top of open source table formats such as Iceberg across Athena and Amazon Redshift. It also includes configurations to restrict access to the underlying database and tables, with an AWS CloudFormation template provided for setup.

Introducing AWS Glue Data Quality anomaly detection
AWS Glue Data Quality now includes anomaly detection capabilities. This feature allows users to identify and handle data anomalies effectively. The post provides an example demonstrating how the feature works and includes an AWS CloudFormation template to deploy the setup and experiment with the feature. This addition enhances the data quality management process, ensuring more reliable and accurate data for analysis.

OpenSearch optimized instance (OR1) is game changing for indexing performance and cost
Amazon OpenSearch Service has introduced the OR1 instance type, optimized for indexing performance and cost efficiency. This new instance type is designed to improve real-time search, monitoring, and analysis of business and operational data. Use cases include application monitoring, log analytics, observability, and website search. The OR1 instance type offers significant improvements in indexing performance while reducing costs, making it a valuable addition for businesses relying on OpenSearch.

AWS Glue mutual TLS authentication for Amazon MSK
In today’s landscape, data streams continuously from various sources, such as social media interactions and IoT device readings. This torrent of real-time information presents both challenges and opportunities for businesses. To harness the power of this data effectively, organizations need robust systems for ingesting, processing, and analyzing streaming data. AWS Glue’s mutual TLS authentication for Amazon MSK helps ensure secure data streaming, enhancing the reliability and security of real-time data processing.

Enrich, standardize, and translate streaming data in Amazon Redshift with generative AI
Amazon Redshift ML enables users to build, train, and deploy machine learning models directly in the Redshift environment. Now, users can integrate pretrained large language models (LLMs) from Amazon SageMaker JumpStart into their Redshift ML workflows. This integration allows for a wide variety of natural language processing use cases, such as text summarization, sentiment analysis, named entity recognition, and more. The feature simplifies the application of advanced ML models on analytical data, providing powerful tools for data enrichment, standardization, and translation within the Redshift data warehouse.

How Amazon GTTS runs large-scale ETL jobs on AWS using Amazon MWAA
The Amazon Global Transportation Technology Services (GTTS) team owns a set of products called INSITE, which are user-facing applications solving business problems across various transportation domains. These applications serve around 10,000 customers globally each month. This post details how GTTS runs large-scale ETL jobs on AWS using Amazon Managed Workflows for Apache Airflow (MWAA). The use of MWAA enables efficient and scalable ETL processes, ensuring timely and accurate data processing for transportation management.

Build a real-time analytics solution with Apache Pinot on AWS
This post provides a step-by-step guide to building a real-time OLAP datastore on AWS using Apache Pinot on Amazon EC2. The guide focuses on achieving near real-time visualization using Tableau. Apache Pinot is suitable for both batch processing and real-time analytics use cases. The post specifically highlights the steps to set up a near real-time analytics solution, making it a valuable resource for businesses looking to leverage real-time data insights on AWS.

Introducing data products in Amazon DataZone: Simplify discovery and subscription with business use case based grouping
Amazon DataZone now allows data producers to group data assets into well-defined, self-contained packages called data products tailored for specific business use cases. For example, a marketing analysis data product can bundle various data assets such as marketing campaign data, pipeline data, and customer data. This feature simplifies data discovery and subscription, making it easier for users to find and utilize relevant data for their business needs.

Set up cross-account AWS Glue Data Catalog access using AWS Lake Formation and AWS IAM Identity Center with Amazon Redshift and Amazon QuickSight
This post covers how to enable trusted identity propagation with AWS IAM Identity Center, Amazon Redshift, and AWS Lake Formation residing on separate AWS accounts. It demonstrates setting up cross-account sharing of an S3 data lake for enterprise identities using AWS Lake Formation to enable analytics using Amazon Redshift. Additionally, it shows how to use Amazon QuickSight to build insights using Redshift tables as the data source. The guide ensures secure and efficient cross-account data access and analytics.

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Networking & Content Delivery

An increasing number of organizations are adopting IPv6 in their environments, driven by government mandates, public IPv4 space exhaustion, and private IPv4 scarcity. To accommodate workload growth, integrate new business needs (for example, mergers and acquisitions), expand into other regions, and increase developer productivity, it is essential to design and implement a scalable and extensible IPv6 addressing plan on AWS. By leveraging the vast address space of IPv6, organizations can easily manage their network without the constraints imposed by limited IPv4 addresses. The flexibility of IPv6 allows for hierarchical addressing, which improves routing efficiency and simplifies network management.

Amazon Web Services (AWS) has found widespread adoption in the satellite communication and aerospace sectors, serving not only as a platform for modernizing their overall IT infrastructure but also for delivering network connectivity solutions. One prominent example showcases how a leading satellite and aerospace company, Thales Avionics, used AWS to build a virtual data center. By leveraging AWS services, Thales was able to provide in-flight WiFi service, enhancing the passenger experience. This cloud-based approach enabled Thales to scale their operations quickly and efficiently, meeting the demands of a growing user base while maintaining high service quality.

In the dynamic landscape of web applications and APIs, ensuring fast, reliable, and secure access for all customers is crucial. With traditional implementations, users of global applications often face latency and reliability challenges due to the complexity of the global internet infrastructure. AWS Global Accelerator enables users to improve application performance by providing static IP addresses as a fixed entry point to applications. This service routes traffic to the nearest AWS edge location, reducing latency and improving availability. AWS Global Accelerator also offers automatic health checks and rerouting of traffic to healthy endpoints, ensuring consistent performance even during localized failures.

Salesforce is an AWS Partner and a trusted global leader in customer relationship management (CRM). Hyperforce, the next-generation Salesforce architecture, is built on Amazon Web Services (AWS). When business applications developed on Hyperforce are integrated with on-premises systems, traffic in both directions will flow over the internet. For customers in heavily regulated industries, such as finance and healthcare, this can pose significant security and compliance risks. By using AWS Direct Connect, organizations can establish private connectivity between Salesforce and their on-premises network, bypassing the public internet. This dedicated connection provides increased security, lower latency, and more consistent network performance, ensuring that sensitive data remains protected and compliant with industry regulations.

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AWS Compute Blog

This blog post provides a comprehensive guide on enabling high availability of Amazon EC2 instances on AWS Outposts servers. Written by Brianna Rosentrater, a Hybrid Edge Specialist Solutions Architect, and Jessica Win, a Software Development Engineer, it is divided into two parts to cover all necessary details and provide ample examples and considerations.

Introduction to AWS Outposts

AWS Outposts allows enterprises to run AWS infrastructure and services on-premises, ensuring a seamless hybrid experience. However, ensuring high availability (HA) for EC2 instances on AWS Outposts requires specialized techniques and custom logic. This two-part series delves into these aspects to help developers and sysadmins achieve robust HA setups.

Part 1: Setting the Foundation

In the first part, the authors discuss the basics of HA and why it’s crucial for workloads that require uninterrupted availability. They introduce the key concepts of AWS Outposts and its integration with the broader AWS ecosystem. Emphasis is placed on understanding the architectural considerations and the role of Amazon Elastic Block Store (EBS), Amazon Virtual Private Cloud (VPC), and Availability Zones (AZs) in establishing a resilient environment.

Part 2: Implementation and Automation

The second part dives into the implementation details, providing code samples and scripts for automating the HA setup. It includes step-by-step instructions to configure custom logic that can detect instance failures and automatically launch replacement instances. Critical considerations such as monitoring, alerting, and failure domain isolation are also covered to ensure a robust HA solution.

Business Value

By achieving high availability for EC2 instances on AWS Outposts, businesses can maintain continuous operations even during unexpected outages, leading to increased reliability and customer satisfaction. This setup is especially beneficial for industries with stringent uptime requirements.

How KeyCore Can Help

KeyCore, the leading Danish AWS consultancy, offers specialized services to implement high availability setups for EC2 instances on AWS Outposts. With expert knowledge and practical experience, KeyCore can tailor HA solutions specific to business needs, ensuring seamless integration and optimal performance.

Improving Performance with Amazon APerf

Tyler Jones, a Senior Solutions Architect at AWS, discusses how Amazon APerf can significantly enhance the performance of workloads. In this blog post, Jones focuses on the Renaissance Finagle-http benchmark, a tool used to measure the performance of HTTP servers. Initially, the performance was 50% below the target. However, using Amazon APerf, it was improved to 36% above the target.

Performance Tuning

Performance discrepancies can arise due to various reasons such as configuration errors, code bugs, or hardware differences. Amazon APerf helps identify and rectify these issues by providing detailed performance insights. Through systematic tuning and configuration adjustments, significant improvements can be achieved.

Business Value

Enhancing performance through tools like Amazon APerf can lead to faster application responses and improved user experiences. For businesses, this can translate to higher customer satisfaction and lower operational costs.

How KeyCore Can Help

KeyCore offers in-depth performance tuning services using tools like Amazon APerf. By leveraging our expertise, businesses can optimize their workloads for peak performance, ensuring that their applications run efficiently and cost-effectively.

Migrating On-premises Workloads to AWS Outposts Rack

This post, authored by Craig Warburton, Sedji Gaouaou, and Brian Daugherty from AWS, covers the migration of on-premises workloads to AWS Outposts rack. AWS Outposts rack delivers the benefits of cloud computing while keeping data and applications on-premises, which is crucial for organizations with stringent data residency requirements.

Migration Steps

The blog post outlines the steps required for a successful migration, including assessment, planning, and execution. Key considerations such as network connectivity, data synchronization, and workload compatibility are discussed in detail. The authors provide practical tips and best practices to ensure a smooth transition.

Business Value

Migrating to AWS Outposts rack enables businesses to leverage cloud capabilities like scalability and flexibility while maintaining data control and compliance. This hybrid approach can lead to cost savings, improved operational efficiency, and enhanced data security.

How KeyCore Can Help

KeyCore specializes in hybrid cloud solutions and can assist businesses in migrating their on-premises workloads to AWS Outposts rack. Our experts provide end-to-end support, from initial assessment to post-migration optimization, ensuring a seamless and successful transition.

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AWS for M&E Blog

Customers with live streaming video needs often want flexibility in deploying their services. AWS Media Services are designed with redundancy, allowing users to balance resiliency and cost. Stateful services for video ensure that live channels remain uninterrupted even in case of failure, providing robust and resilient streaming solutions.

Flexibility and Redundancy

Not all live streaming channels are the same. AWS Media Services provide the flexibility to choose different configurations based on specific requirements. With the ability to automatically switch between redundant channels, the service ensures continuous streaming without manual intervention.

Cost Vs. Resiliency

Balancing cost and resiliency is crucial. AWS Media Services enable users to deploy cost-effective solutions that do not compromise on quality. By leveraging AWS’s global infrastructure, users can create a resilient architecture that meets their budget constraints.

AWS Elemental MediaConvert, a cloud-based video transcoding service, now offers Broadcast Mix audio description (AD) outputs from Receiver Mix AD sources. This feature dynamically mixes AD commentary into audio outputs during the transcode process, enhancing accessibility for visually impaired viewers.

Dynamic Audio Description Mixing

MediaConvert can interpret control track data in the source and mix AD commentary into the audio output. This process ensures that viewers receive a seamless experience with audio descriptions integrated into the main audio track.

Optimizing streaming media workflows can significantly reduce the carbon footprint. Part II of the series focuses on codecs and implementation. By choosing the right AWS Region and using efficient codecs, users can minimize energy consumption and environmental impact.

Sustainable Practices

The Sustainability Pillar of the AWS Well-Architected Framework provides best practices for reducing environmental impact. Using efficient codecs and optimizing video encoding workflows can lead to substantial energy savings.

Synamedia, in collaboration with AWS, delivers an optimized on-demand viewing experience with Cloud DVR. This modern solution allows subscribers to watch their favorite shows anytime and anywhere, ensuring a personalized viewing experience.

Cloud-Based Digital Video Recording

Cloud DVR solutions are essential for service providers to offer a seamless viewing experience. By leveraging AWS’s infrastructure, Synamedia ensures that content is available on-demand, enhancing the overall user experience.

How KeyCore Can Help

KeyCore, Denmark’s leading AWS consultancy, helps businesses implement these advanced AWS solutions. Our expertise in AWS Media Services ensures that clients receive robust, cost-effective, and resilient streaming architectures. KeyCore also assists in optimizing media workflows to reduce carbon footprints and integrates Cloud DVR solutions for personalized viewing experiences.

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Integration & Automation

In today’s fast-paced cloud environments, integrating and automating operations is essential for maintaining efficiency and reliability. Two articles delve into solutions that leverage AWS services to streamline such processes.

Restart Amazon ECS Tasks with AWS Lambda and AWS CloudFormation Custom Resources

Running long-term Amazon ECS tasks can often require updated secrets from AWS Secret Manager. Manually updating these secrets can be time-consuming and prone to errors. Fortunately, AWS provides a solution to automate this process.

This solution involves using AWS Lambda and AWS CloudFormation custom resources. By configuring a Lambda function to restart ECS tasks whenever there’s a change in the Secret Manager, one can ensure that tasks always run with the latest secrets. The setup involves the following steps:

  • Create a Lambda function that triggers on Secret Manager changes.
  • Define a CloudFormation custom resource that invokes this Lambda function.
  • Integrate the custom resource into the CloudFormation stack managing the ECS tasks.

This approach ensures that ECS tasks are consistently updated without manual interventions, thereby enhancing security and operational efficiency.

Simplify SQL Queries to Your AWS API Operations Using Steampipe and AWS Plugin

Accessing AWS API data often requires navigating through various AWS management consoles and tools, which can be cumbersome. Steampipe, in conjunction with its AWS plugin, provides a streamlined method to perform SQL queries on AWS API data.

Steampipe allows users to query AWS API data directly from Steampipe itself, or from any Postgres or SQLite database. This functionality simplifies data retrieval and analysis, enabling more efficient decision-making. To set this up:

  • Install Steampipe and the AWS plugin.
  • Configure necessary AWS credentials for access.
  • Write and execute SQL queries to fetch and manipulate data from AWS API.

This approach not only speeds up data access but also reduces the complexity associated with traditional AWS API operations, making it easier for teams to integrate and automate their workflows.

How KeyCore Can Help

KeyCore specializes in leveraging AWS services to optimize and automate business operations. Whether implementing automated ECS task restarts or simplifying data queries with Steampipe, KeyCore provides the expertise needed to streamline these processes. KeyCore’s team of AWS-certified professionals can design, deploy, and manage custom solutions tailored to specific business needs, ensuring operational efficiency and security. Visit KeyCore to learn more about how these services can benefit your organization.

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AWS Storage Blog

In the ever-evolving landscape of data protection and disaster recovery, AWS continues to offer robust solutions to meet enterprise needs. This article summarizes various innovative approaches and services provided by AWS to enhance data resiliency, accelerate processes, and ensure secure connectivity.

Building Cyber Resiliency with AWS Backup Logically Air-Gapped Vault

AWS Backup is a centralized tool for data protection, catering to the diverse security and regulatory needs of enterprises. However, the rising threat of ransomware has created a demand for enhanced resiliency. AWS introduces the concept of a logically air-gapped vault within AWS Backup. This feature enables organizations to create multiple backup copies, significantly improving their disaster recovery posture. Enterprises can utilize this logically isolated vault to store backups that are immune to ransomware attacks, ensuring that recovery objectives are met without the need for extensive custom code.

Accelerating Healthcare Hiring with Amazon S3 Express One Zone

Vivian Health, a platform connecting travel nurses with job opportunities, leverages Amazon S3 Express One Zone to streamline its hiring process. By utilizing this storage class, Vivian Health optimizes its recruitment tooling, enabling recruiters and hiring managers to quickly match qualified candidates to job openings. The low-latency and cost-effective nature of Amazon S3 Express One Zone allows Vivian Health to handle large volumes of data efficiently, ensuring that the healthcare hiring process is fast and seamless.

Private Connectivity for AWS Elastic Disaster Recovery via AWS Direct Connect

For large-scale disaster recovery (DR) implementations, network performance is crucial. AWS Direct Connect provides a dedicated network connection between an organization’s on-premises environment and AWS, facilitating efficient data replication. This reliable and high-bandwidth connection ensures that data is transferred swiftly and securely, allowing enterprises to maintain their DR objectives. By using AWS Direct Connect, organizations can achieve a seamless and resilient DR strategy, minimizing downtime and data loss.

Application Consistent EBS Snapshots for Linux by DXC

Enterprises running mission-critical applications on AWS often require stringent data consistency and integrity for their backups. DXC employs a method to create application-consistent Amazon EBS snapshots for Linux systems. This involves leveraging AWS tools to ensure that backups capture the entire application state, making them viable for disaster recovery, application rollback, compliance, and audit purposes. The approach ensures that data is consistently backed up without impacting the performance of the running applications.

Attaching an EC2 Key Pair to an AWS Backup Restore of VMware VMs

Organizations using VMware virtual machines (VMs) on AWS and on-premises often utilize AWS Backup for centralized data protection. When restoring a VMware VM to an Amazon EC2 instance, a common challenge is the absence of an associated EC2 key pair. AWS provides a solution to attach an EC2 key pair during the restore process, simplifying the recovery operations. This feature ensures that the restored instances are accessible and secure, enhancing the overall efficiency of the backup and restore workflow.

How KeyCore Can Help

At KeyCore, Denmark’s leading AWS consultancy, we specialize in helping enterprises implement and optimize AWS storage and backup solutions. Our team of experts can assist in setting up logically air-gapped vaults, streamlining data migrations with Amazon S3, establishing private connectivity for disaster recovery, creating application-consistent snapshots, and ensuring secure restore operations for VMware environments. With our deep expertise in AWS, we ensure that enterprises achieve their data protection and disaster recovery goals effectively. Contact KeyCore to leverage our professional and managed services for your AWS storage needs.

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AWS Developer Tools Blog

The AWS SDK for Java 1.x entered maintenance mode on July 31, 2024, signaling the need for users to migrate to the AWS SDK for Java 2.x. The newer version offers access to new features, enhanced performance, and continued support from AWS.

Migration Tool Introduction

The AWS team acknowledges the challenge of migrating from one SDK version to another. To address this, AWS has released a preview of a Migration Tool specifically designed to facilitate this transition. This tool aims to simplify the migration process and save developers valuable time.

Key Benefits of AWS SDK for Java 2.x

The AWS SDK for Java 2.x brings several advantages over its predecessor, including:

  • Enhanced performance: The newer version is optimized for better efficiency, which translates to faster application performance.
  • New features: Regular updates and new features continue to be introduced, ensuring that developers have access to the latest AWS services and enhancements.
  • Improved support: With AWS SDK for Java 1.x in maintenance mode, support for new features is limited. Migrating to 2.x ensures ongoing support and updates.

How the Migration Tool Helps

The migration tool is designed to automate many of the manual tasks involved in transitioning to the new SDK. It provides detailed guidance and a streamlined process to ensure a smooth migration. By using this tool, developers can reduce the time and effort required to upgrade their applications, allowing them to focus on building and improving their AWS-powered solutions.

How KeyCore Can Assist

KeyCore is ready to assist organizations in migrating to the AWS SDK for Java 2.x. With deep expertise in AWS services and a strong track record of successful migrations, KeyCore can ensure a seamless transition. Our team can provide comprehensive support, from initial analysis and planning to execution and post-migration optimization. Contact KeyCore to learn more about our migration services and how we can help your organization leverage the benefits of the AWS SDK for Java 2.x.

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AWS Architecture Blog

In today’s fast-paced software as a service (SaaS) landscape, tenant portability is a critical capability for SaaS providers seeking to stay competitive. By enabling seamless movement between tiers, tenant portability allows businesses to adapt to changing needs. However, manual orchestration of portability requests can be a significant bottleneck, hindering scalability and requiring substantial resources.

Importance of Tenant Portability

Tenant portability ensures that SaaS providers can offer flexible subscription models. This flexibility enables customers to upgrade, downgrade, or shift across different service tiers based on their evolving requirements. In turn, this adaptability enhances customer satisfaction and retention.

Challenges of Manual Orchestration

Manually managing tenant portability can be resource-intensive and error-prone. Such processes often require significant human intervention, which can cause delays and impede scalability. This bottleneck is particularly problematic in dynamic environments where rapid adjustments are necessary.

Automating Tenant Portability

Automating the movement of tenants across tiers can mitigate these challenges. By leveraging AWS services such as AWS Lambda, AWS Step Functions, and Amazon DynamoDB, businesses can create automated workflows that handle tenant portability efficiently. For example, AWS Lambda can be used to trigger portability workflows, while AWS Step Functions can orchestrate the necessary steps to complete the process.

Business Value

Automating tenant portability not only reduces the operational burden but also ensures a seamless customer experience. This can lead to higher customer satisfaction and loyalty, which are critical in the competitive SaaS market. Additionally, automated processes can scale more effectively, allowing SaaS providers to grow without being hampered by manual bottlenecks.

How KeyCore Can Help

KeyCore, the leading Danish AWS Consultancy, specializes in helping businesses implement efficient and scalable AWS architectures. Our team can assist in designing and automating tenant portability solutions tailored to your specific needs. By leveraging our expertise, you can ensure a seamless transition for your tenants across different service tiers, thereby enhancing customer satisfaction and operational efficiency.

Contact KeyCore today to learn more about how we can help you automate your SaaS tenant portability and stay competitive in the dynamic SaaS landscape.

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AWS Partner Network (APN) Blog

We are excited to highlight 182 AWS Partners that received new or renewed specializations in July for our global AWS Competency, AWS Managed Service Provider (MSP), AWS Service Delivery, and AWS Service Ready programs. These designations span workload, solution, and industry, and help AWS customers identify top AWS Partners that can deliver on core business objectives. AWS Partners are focused on your success, helping customers take full advantage of the business benefits AWS has to offer.

Unlocking the Power of AWS for Accelerated AI/ML Enablement: Eviden’s DeepRacer Journey

The AWS DeepRacer platform provides a fun and engaging way to get into AI and machine learning. Exposure to the AWS DeepRacer platform gives racers the opportunity to learn about reward function strategy, hyperparameter tuning, and Python programming. Eviden recognized the potential to expand the learning outcomes beyond these core concepts. They leveraged the AWS DeepRacer to build a comprehensive AI/ML training program that goes beyond initial learning, helping participants gain skills in real-world applications.

Unleash Supercomputing Power with HPC-NOW: An Open-Source HPC Solution on AWS

This post introduces “HPC-NOW” – an open-source, integrated solution developed by Shanghai HPC-NOW Technologies Co., Ltd in collaboration with AWS. HPC-NOW allows HPC practitioners to efficiently manage and scale their HPC workloads on the AWS cloud. The post also presents a real-world customer success story for Computational Fluid Dynamics (CFD) simulations, achieving higher resolution and reduced runtime while eliminating the costs associated with maintaining physical clusters. HPC-NOW’s integration with AWS services ensures high performance and scalability, providing a cost-effective solution for HPC workloads.

Building a Modern Call Center with SnapLogic and Amazon Connect

SnapLogic is an AWS Advanced Technology Partner and AWS Competency Partner. Through its visual, automated approach to integration, SnapLogic uniquely empowers business and IT users to accelerate integration needs for applications, data warehouse, big data, and analytics initiatives. Using SnapLogic with Amazon Connect, businesses can quickly build and deploy modern call centers that are scalable and efficient. This integration allows businesses to improve customer interactions while reducing operational costs.

Equip Your Sellers for Success: Introducing the Generative AI Sales Course for AWS Partners

As generative AI transforms businesses in 2024, sales teams need new skills to unleash its full potential—from creating accurate ROI estimates to crafting compelling value propositions. The new AWS Partner: Generative AI Sales course, available in the Generative AI Center of Excellence, helps sellers translate service knowledge into value-driving proof-of-concepts and scalable deployments. This course prepares AWS Partners to better support customers in leveraging generative AI technologies to achieve their business goals.

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AWS Cloud Operations & Migrations Blog

AWS Mainframe Modernization is now available in Terraform, expanding the capabilities of Infrastructure as Code (IaC) for AWS Mainframe Modernization. This service is a cloud-native platform designed to migrate, modernize, execute, and operate mainframe applications. By offering analysis and transformation tools along with a fully-managed and resilient runtime environment, AWS Mainframe Modernization simplifies the operation of modernized applications. Now, users can define these modernizations using Terraform, further streamlining the process.

Infrastructure as Code with Terraform

Terraform enables users to define their infrastructure in code, providing the benefits of version control and automation. With AWS Mainframe Modernization now supporting Terraform, users can leverage these IaC benefits for their mainframe applications. This integration allows for more efficient and reliable modernization processes, reducing errors and increasing consistency.

KeyCore can assist organizations in leveraging Terraform for AWS Mainframe Modernization. Our expertise ensures a smooth transition, helping to maximize the benefits of IaC in modernizing legacy mainframe applications.

Streamlining Compliance Management with AWS Config

Managing compliance controls is crucial for businesses operating in regulated environments. AWS Config custom rules and conformance packs provide a powerful solution for this challenge. By using AWS CloudFormation Guard (cfn-guard), an open-source domain-specific language (DSL), organizations can write custom policy rules that enforce compliance. Conformance packs bundle these rules, making it easier to manage and deploy compliance controls across multiple AWS accounts.

KeyCore offers guidance and support in implementing AWS Config custom rules and conformance packs, ensuring robust compliance management tailored to your specific regulatory needs.

Improving Observability with Amazon CloudWatch AppSignals

As the use of Generative AI applications increases, so does the need for granular observability into these applications. Amazon CloudWatch AppSignals addresses this by providing detailed metrics and insights into prompt metrics, token usage, costs, and model IDs for transactions. Additionally, it offers visibility into output quality factors such as potential toxicity and harm, enabling better monitoring and management of AI applications.

KeyCore can help organizations enhance their AI application observability using Amazon CloudWatch AppSignals, ensuring comprehensive monitoring and improved operational insights.

Unlocking the Power of Amazon CloudWatch Alarms

Effective observability and operational excellence rely on actionable metrics. Amazon CloudWatch Alarms provide a way to receive alerts based on specific metrics, enabling teams to take timely and appropriate actions. Understanding which metrics require action and which are just noise is critical for efficient operations. Amazon CloudWatch Alarms help differentiate between these, ensuring teams can focus on the metrics that matter.

KeyCore can assist in setting up and managing Amazon CloudWatch Alarms, ensuring your organization can effectively monitor and respond to critical metrics, enhancing overall operational excellence.

KeyCore, as the leading Danish AWS consultancy, offers both professional and managed services to help organizations leverage AWS technologies effectively. Whether it’s modernizing mainframe applications, managing compliance, enhancing AI observability, or setting up CloudWatch Alarms, KeyCore provides the expertise and support needed to achieve your business goals.

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AWS for Industries

In April 2023, the Office of the Superintendent of Financial Institutions (OSFI) released a revised Guideline B-10 on Third-Party Risk Management. Effective from May 1, 2024, this update applies to all federally regulated financial institutions (FRFIs) and marks the first revision since 2009. The new guideline aims to modernize the regulatory framework to manage third-party risks effectively. AWS supports financial services customers in aligning with these regulations through robust compliance measures, secure infrastructure, and specialized cloud services. AWS offers comprehensive compliance documentation, automated compliance checks via AWS Config, and helps institutions implement secure architectures. This ensures that financial entities can focus on core business operations while staying compliant. KeyCore’s experts can assist in seamlessly integrating AWS solutions to meet these updated regulatory requirements, ensuring optimized compliance without disrupting business operations.

Transforming Oil and Gas with Amazon Bedrock

bpx energy, operating bp’s US onshore portfolio, aims to increase production volumes by 30% by 2025. To achieve this, bpx leverages Amazon Bedrock, a generative AI tool that enhances operational insights. Amazon Bedrock aids in predictive maintenance, optimizing production schedules, and reducing downtime. By integrating Bedrock with existing systems, bpx gains actionable insights, leading to more efficient operations and increased productivity. The implementation of these advanced technologies underscores the importance of digital transformation in competitive environments. KeyCore can guide energy companies through the integration of AI and machine learning solutions like Amazon Bedrock, driving efficiency and productivity gains in the oil and gas sector.

Augmented Reality and Generative AI for Frontline Workers

Manufacturing and field services face challenges such as productivity issues, efficiency gaps, and worker safety concerns due to an aging workforce. Generative AI combined with augmented reality (AR) offers innovative solutions to these problems. AR can provide real-time assistance and training to frontline workers, while generative AI can deliver expert knowledge and predictive insights. This dual approach helps bridge the knowledge gap, improve safety, and enhance productivity. Enterprises adopting these technologies can expect a more capable and efficient workforce. KeyCore specializes in deploying AR and AI solutions tailored to the unique needs of manufacturing and field service operations, ensuring a seamless transition to advanced worker assistance technologies.

Application Deployment in China’s Automotive Industry

Since 2008, China has led the world in automobile production. Global automakers face unique challenges when deploying cloud services like AWS within China due to regulatory and operational constraints. Successful deployment strategies involve localized compliance, data residency, and tailored solutions to meet regional requirements. AWS provides a suite of tools and services, including Amazon CloudFront and AWS Outposts, to facilitate secure and compliant operations within China. These tools help automakers balance global cloud efficiencies with local regulatory adherence. KeyCore assists automakers in navigating the complexities of the Chinese market by providing expertise in AWS deployment strategies, ensuring compliance and operational excellence.

KeyCore’s team of AWS-certified professionals can help organizations across various industries leverage AWS services to meet their unique challenges. From regulatory compliance in financial services to operational efficiency in energy and manufacturing, and localized deployment strategies in the automotive industry, KeyCore offers tailored solutions and expert guidance. Contact KeyCore today to learn how we can help your organization succeed with AWS.

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

Generative AI–based applications have grown in popularity in the last couple of years. Applications built with large language models (LLMs) have the potential to increase the value companies bring to their customers. In this blog post, AWS delves deep into network perimeter protection for generative AI applications, exploring various areas of network security crucial for these advanced applications.

Network Perimeter Security Protections for Generative AI

Network perimeter security is vital for generative AI applications. These applications, built using large language models (LLMs), require robust security measures to safeguard sensitive data and maintain operational integrity. The blog emphasizes the importance of setting up firewalls, intrusion detection systems, and secure gateways. AWS recommends using tools like AWS WAF, AWS Shield, and AWS Firewall Manager to establish a fortified network perimeter around generative AI applications.

Spring 2024 SOC 2 Report Now Available in Japanese, Korean, and Spanish

In response to customer feedback and regulatory requirements, AWS has made the Spring 2024 SOC 2 report available in Japanese, Korean, and Spanish. This report helps customers meet compliance and assurance needs by providing detailed information on AWS’s control environment relevant to security, availability, and confidentiality. By offering the report in multiple languages, AWS aims to facilitate broader access and understanding among international stakeholders, ensuring transparent communication about security practices and compliance.

Hardening the RAG Chatbot Architecture Powered by Amazon Bedrock

Deploying chatbots powered by Amazon Bedrock entails addressing risks such as data exposure, model exploits, and ethical concerns. AWS provides a blueprint for secure design and mitigation of anti-patterns specific to these chatbots. Key security measures include implementing encryption, access controls, and governance frameworks. AWS emphasizes the importance of guarding against data leaks and ensuring that chatbot interactions adhere to ethical standards, thus enhancing trust and security in AI-driven customer interactions.

SaaS Authentication: Identity Management with Amazon Cognito User Pools

Amazon Cognito serves as a scalable customer identity and access management (CIAM) service, capable of handling millions of users. The blog provides guidance on selecting the appropriate multi-tenancy model depending on specific use cases. AWS outlines the advantages and disadvantages of different models, offering insight into optimal deployment strategies. This helps organizations securely manage user authentication and authorization, ensuring a seamless and secure user experience.

How AWS Tracks and Prevents the Cloud’s Biggest Security Threats

AWS leverages its vast global infrastructure and advanced threat intelligence capabilities to identify and mitigate security threats before they cause harm. The blog highlights AWS’s proactive measures, including real-time threat detection and automated responses. By utilizing AWS’s comprehensive security services, organizations can protect their most sensitive data against emerging threats, benefiting from AWS’s commitment to maintaining a secure and resilient cloud environment.

How KeyCore Can Help

KeyCore is at the forefront of implementing advanced AWS security, identity, and compliance solutions. Our team of experts ensures that your generative AI applications are protected with robust network perimeter security. We assist in navigating AWS compliance reports available in multiple languages, ensuring your organization meets international regulatory standards. Our comprehensive services include designing secure chatbot architectures, optimizing SaaS authentication with Amazon Cognito, and leveraging AWS threat intelligence to safeguard your cloud environment. Trust KeyCore to enhance your AWS security posture and compliance efforts.

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AWS Contact Center

Generative artificial intelligence (AI) was the hot topic for most of 2023 and continues to be a focus in 2024. The technology is rapidly evolving, presenting new and creative use cases daily. For customer experience (CX), the promise of generative AI is both clear and exciting. This technology can significantly enhance customer interactions, making them more personalized and efficient.

Benefits of Generative AI in Amazon Connect

Amazon Connect, AWS’s cloud-based contact center service, integrates generative AI to transform customer service. Key benefits include:

  • Personalization: AI-driven insights allow for highly personalized interactions, tailoring responses based on customer history and behavior.
  • Efficiency: Automating routine tasks and providing agents with real-time suggestions enhances productivity and reduces handling times.
  • Scalability: Generative AI scales effortlessly to meet peak demand periods without compromising service quality.

Implementing Generative AI in Amazon Connect

Integrating generative AI within Amazon Connect is straightforward, thanks to AWS’s robust ecosystem. Key steps include:

  • Data Integration: Connect existing customer databases to Amazon Connect for seamless data flow.
  • AI Models: Utilize AWS pre-trained models or customize models with Amazon SageMaker to tailor AI behavior.
  • Continuous Improvement: Leverage AWS tools to monitor performance and continuously optimize AI models.

Business Value

Incorporating generative AI into customer service operations can significantly improve customer satisfaction and loyalty. Personalized interactions lead to higher customer retention rates and increased lifetime value. Additionally, the efficiencies gained in handling times and resource allocation directly impact the bottom line, making customer service operations more cost-effective.

How KeyCore Can Help

KeyCore offers expert guidance in integrating generative AI with Amazon Connect. Their team provides end-to-end support, from initial assessment to full implementation and optimization. Businesses can benefit from KeyCore’s deep AWS expertise, ensuring a seamless integration process and maximizing the value from generative AI technologies. Visit KeyCore to learn more about their AWS consultancy services.

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Innovating in the Public Sector

Amazon Web Services (AWS) is playing a significant role in transforming public sector operations with innovative solutions that leverage advanced technology. Below are summaries of key articles highlighting AWS’s contributions to healthcare, AI assurance, public sector innovation, and more.

Transforming Healthcare for Incarcerated Individuals

The Centers for Medicare & Medicaid Services (CMS) recently allowed states to extend Medicaid coverage to incarcerated individuals. AWS provides a suite of services to support this initiative, aiming to ensure continuity of care, reduce relapse risk, and improve health management. The four key areas where AWS services can help include data storage, telehealth, analytics, and reentry services. Read on to discover how AWS and its partners facilitate these advancements, contributing to better healthcare outcomes for incarcerated individuals.

Insights from the 2024 AWS Public Sector Symposium Canberra

The AWS Worldwide Public Sector Symposium in Canberra highlighted the role of generative artificial intelligence (AI) in Australia and New Zealand. Iain Rouse, AWS director and country leader for the region, opened the keynote, followed by Dave Levy, vice president of Worldwide Public Sector at AWS. The session focused on AI innovation and its implications for public sector operations. For more detailed highlights, dive into the keynote session’s key points and takeaways.

National Framework for AI Assurance in Australian Government

Australia is progressing with a national framework for AI assurance. AWS is committed to helping government agencies implement AI solutions that adhere to Australia’s AI Ethics Principles. This involves using AWS tools and services to support responsible AI and machine learning (ML) development. The framework ensures that AI innovations align with ethical standards while maintaining the agility of cloud-based solutions. Learn more about how AWS aids in responsibly advancing AI in the public sector.

Introducing the Amazon Trusted AI Challenge

Amazon has launched the Amazon Trusted AI Challenge, a global university competition aimed at fostering secure innovation in generative AI technology. This year’s challenge focuses on responsible AI and the security aspects of large language model (LLM) coding. Participants are encouraged to develop innovative solutions that prioritize AI security and ethical considerations. This initiative underscores Amazon’s commitment to advancing safe and trustworthy AI technologies.

Accelerating Innovation and Procurement with State Agencies

Contrary to common misconceptions, state agencies are actively innovating for their constituents. AWS experts share examples from New Mexico and North Carolina, demonstrating significant advancements in public sector innovation. Additionally, AWS provides tips for accelerating procurement processes and maintaining visibility over rapidly deployed workloads. Explore how state agencies can leverage AWS to drive innovation and streamline procurement.

How KeyCore Can Help

KeyCore, as Denmark’s leading AWS consultancy, is well-positioned to assist public sector organizations in leveraging AWS’s powerful tools and services. From transforming healthcare systems to implementing responsible AI solutions, KeyCore provides expertise in both professional and managed services. Our team ensures that your organization can effectively utilize AWS to achieve its goals, driving innovation and operational efficiency. Contact us to learn how KeyCore can support your public sector initiatives.

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The Internet of Things on AWS – Official Blog

The Internet of Things (IoT) devices have become essential in everyday life. They include mobile phones, wearables, connected vehicles, smart homes, smart factories, and other connected devices. Coupled with advanced computing capabilities and various sensing and networking mechanisms, these devices can automate and make real-time decisions. Integrating IoT with generative AI on AWS opens up new possibilities for intelligent automation and improved decision-making.

Integrating IoT and Generative AI on AWS

With IoT devices generating massive amounts of data, there is a growing need to process and analyze this data efficiently. Generative AI models can help by providing insights and automating processes. AWS offers a range of services that can be leveraged to integrate IoT and generative AI, including AWS IoT Core, AWS IoT Analytics, AWS Lambda, and Amazon SageMaker. These services enable the creation of intelligent applications that can learn from data, make predictions, and optimize operations.

Use Cases and Benefits

Integrating IoT and generative AI on AWS can benefit various industries. For example, in manufacturing, predictive maintenance can reduce downtime and improve productivity. In healthcare, wearable devices can monitor patient health and alert medical professionals to potential issues. In smart homes, AI-powered systems can optimize energy usage and enhance security. Overall, the combination of IoT and generative AI can lead to more efficient and intelligent systems, driving innovation and improving quality of life.

Improved Utility Asset Management

As electricity use is expected to rise significantly, utility companies need to manage their assets more efficiently. AWS IoT and generative AI technologies can help by providing real-time data and insights. For example, electric vehicles (EVs) will drive a significant increase in domestic electricity demand. Distributed Resources (DER) deployments, such as solar PV systems, will also increase. With AWS IoT and generative AI, utility companies can optimize asset management, improve maintenance, and enhance grid stability.

Monitoring and Predictive Maintenance

One key application is the monitoring and predictive maintenance of utility assets. By collecting data from sensors and using generative AI models, utility companies can predict when equipment is likely to fail and perform maintenance proactively. This can reduce downtime, lower maintenance costs, and improve service reliability. AWS services such as AWS IoT Core, AWS IoT Analytics, and Amazon SageMaker can be used to build and deploy these predictive maintenance solutions.

KeyCore’s Expertise

KeyCore, as the leading Danish AWS consultancy, can help organizations leverage AWS IoT and generative AI technologies to improve operations. Our team of experts can assist in designing and implementing solutions that integrate IoT and generative AI, providing valuable insights and automation. Whether it’s optimizing utility asset management, enhancing manufacturing processes, or improving healthcare monitoring, KeyCore has the expertise to help organizations achieve their goals. Visit our website to learn more about our services and how we can assist with your IoT and AI projects.

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AWS Open Source Blog

The Open Cybersecurity Schema Framework (OCSF) is enhancing the way cybersecurity data is managed with the release of version 1.3.0. OCSF is a collaborative, open-source initiative driven by AWS and prominent cybersecurity partners. It aims to standardize and streamline cybersecurity data management with a unified schema for common security events.

Key Enhancements in OCSF 1.3.0

Version 1.3.0 introduces several significant upgrades. One notable feature is the expanded schema, which now supports more types of security events. This broadens the framework’s applicability, making it easier for security teams to integrate disparate data sources.

Additionally, the versioning criteria have been defined more clearly. This helps organizations maintain consistency and compatibility as they adopt new changes over time. The improved criteria allow for seamless updates and better long-term data management strategies.

Streamlining Cybersecurity Data

The goal of OCSF is to bring cohesion to what can often be a chaotic landscape of cybersecurity data. By providing a standardized schema, OCSF enables unified data ingestion and analysis, reducing the complexity and overhead associated with managing different data formats and sources.

This standardization makes it easier to share and correlate data across different systems, enhancing overall threat detection and response capabilities. Organizations can implement more robust security measures, leveraging the standardized data to gain deeper insights and faster detection of potential threats.

Business Value of OCSF

From a business perspective, OCSF delivers substantial value by reducing the need for custom integrations and data transformations. This results in lower costs and faster deployments. Security teams can focus more on threat detection and response, rather than on managing data discrepancies.

The collaborative nature of the project means that it is continuously evolving, incorporating feedback from a wide range of industry experts. This ensures that the framework remains relevant and effective in addressing emerging cybersecurity challenges.

How KeyCore Can Help

KeyCore offers expert services to help organizations adopt and implement OCSF. Our team can assist in integrating the framework into existing security infrastructures, ensuring seamless data management and enhanced threat detection capabilities. We provide both professional and managed services, tailored to meet specific cybersecurity needs and to maximize the benefits of OCSF.

With KeyCore’s deep expertise in AWS and cybersecurity, organizations can leverage the full potential of OCSF to achieve a more secure and cohesive data environment. Contact us to learn how we can support your journey towards optimized cybersecurity data management.

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