Summary of AWS blogs for the week of monday Mon Sep 23

In the week of Mon Sep 23 2024 AWS published 84 blog posts – here is an overview of what happened.

Topics Covered

Desktop and Application Streaming

Amazon Web Services (AWS) has been recognized as a Leader in the 2024 Gartner Magic Quadrant for Desktop as a Service (DaaS). This recognition highlights AWS’s ability to help IT leaders meet their objectives of reducing costs, ensuring robust security, and delivering exceptional end-user experiences. The acknowledgement from Gartner underscores AWS’s commitment to addressing the challenges faced by IT departments, especially those managing global hybrid workforces.

Cost Reduction and Efficiency

IT leaders are under constant pressure to cut expenses while maintaining high service levels. AWS’s DaaS solutions allow organizations to leverage flexible, pay-as-you-go pricing models. This means companies can scale their desktop environments up or down based on demand, avoiding the need for large capital expenditures on hardware and software.

Security and Compliance

Security is a top priority for any IT leader. AWS’s DaaS offerings come with built-in security features that include encryption, multi-factor authentication, and compliance with global standards such as GDPR and HIPAA. These features ensure that sensitive data is protected against unauthorized access and breaches.

Enhanced User Experience

Delivering a seamless user experience is crucial in today’s fast-paced work environment. AWS DaaS solutions provide high-performance virtual desktops that can be accessed from any device, anywhere. This flexibility supports the needs of a hybrid workforce and ensures that employees can work efficiently and effectively, no matter where they are.

Global Reach and Reliability

AWS’s extensive global infrastructure allows for low-latency access to desktop environments, ensuring that users experience minimal delays. Additionally, AWS’s reliability and uptime guarantees mean that businesses can trust that their virtual desktops will be available whenever they are needed.

How KeyCore Can Help

KeyCore, Denmark’s leading AWS consultancy, offers expert services to help organizations implement and optimize AWS DaaS solutions. With deep knowledge of AWS End User Computing, KeyCore can assist with everything from initial setup to ongoing management and support. By leveraging KeyCore’s expertise, businesses can ensure they are maximizing the benefits of AWS’s DaaS offerings while maintaining a secure, cost-effective, and high-performing virtual desktop environment.

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AWS DevOps & Developer Productivity Blog

Amazon CodeCatalyst is a unified service that streamlines the entire software development lifecycle, empowering teams to build, deliver, and scale applications on AWS. It integrates security into all stages of software development, practicing DevSecOps to ensure security is considered from the earliest phases of development.

Securing Your Software Supply Chain

By incorporating security early in the development process, development teams can mitigate potential risks before they become serious issues. Amazon CodeCatalyst, in conjunction with Amazon Inspector, plays a crucial role in securing the software supply chain. Amazon Inspector is an automated security assessment service that helps identify vulnerabilities and deviations from best practices.

This combination ensures that security is not an afterthought but an integral part of the development lifecycle. Companies leveraging these tools can achieve a more secure and compliant software supply chain, reducing the likelihood of security breaches and ensuring consistent application security.

Amazon ECS Multi-region Deployment

Many businesses deploy their mission-critical workloads across multiple AWS regions. This approach serves geographically dispersed customers, meets disaster recovery objectives, and complies with local laws and regulations. Amazon CodeCatalyst simplifies this process by providing a unified platform for building and delivering applications on AWS.

Amazon ECS (Elastic Container Service) supports the deployment of containerized applications across multiple AWS regions. When combined with Amazon CodeCatalyst, it enables seamless multi-region deployments. This setup ensures high availability and resilience, which are crucial for serving a global customer base and adhering to stringent regulatory requirements.

Streamlining Development with Amazon CodeCatalyst

Amazon CodeCatalyst accelerates and simplifies the development process. It offers an all-in-one platform that integrates various tools and services needed for building, testing, and deploying applications. This holistic approach enhances productivity and reduces the time-to-market for new features and applications.

By using Amazon CodeCatalyst, development teams can focus more on innovation and less on managing the complexities of the development lifecycle. This leads to more efficient development processes and ultimately, a stronger competitive edge in the market.

How KeyCore Can Help

KeyCore is an expert in AWS services, including Amazon CodeCatalyst and Amazon Inspector. KeyCore can assist organizations in implementing these tools to streamline their development lifecycle and enhance their software supply chain security. With KeyCore’s professional and managed services, businesses can ensure that they are leveraging AWS best practices for secure, efficient, and compliant application development and deployment.

Visit KeyCore’s website to learn more about how they can help you optimize your AWS environment and achieve your business goals.

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Official Machine Learning Blog of Amazon Web Services

Discover the latest advancements in machine learning and AI with these summaries of AWS’s official blog posts. Each section provides a concise overview of cutting-edge techniques, real-world applications, and insights into how organizations can leverage AWS technologies to innovate and optimize their operations.

Architecture to AWS CloudFormation Code Using Anthropic’s Claude 3 on Amazon Bedrock

Explore how Anthropic’s Claude 3 Sonnet’s vision capabilities can speed up the transition from architecture to prototype. This post outlines methods for leveraging Claude 3 on Amazon Bedrock to automate and streamline architectural design processes, significantly reducing development time.

Automating Safety Inspection Risk Assessments with Computer Vision: A Case Study with Northpower

Northpower, in collaboration with Sculpt, utilized AWS’s computer vision and AI techniques to automate safety inspection risk assessments. By integrating various datasets, they prioritized tasks for field teams, reducing carbon footprint and effort required to manage public safety risks efficiently.

Empowering Aerospace Workforce with Generative AI on Amazon Q and Amazon Bedrock

Learn how to deploy generative AI-enabled expert chatbots using Amazon Q and Amazon Bedrock. These chatbots, trained on proprietary documents, offer specialized support for aerospace roles, enhancing workforce capabilities and accelerating knowledge dissemination.

Innovative Video Generation with SageMaker HyperPod

This post outlines the architecture of a scalable training platform using Amazon SageMaker HyperPod. It provides a detailed setup guide and demonstrates how research teams can innovate in video generation by leveraging this robust ML infrastructure.

Simplifying Amazon S3 Data Access from SageMaker Studio with S3 Access Grants

Discover how to streamline data access to Amazon S3 for different user personas using IAM principals with S3 Access Grants. This method enhances security and efficiency when working within Amazon SageMaker Studio.

Boosting Employee Productivity with Generative AI on Amazon Bedrock

Explore the Employee Productivity GenAI Assistant Example, a solution that automates writing tasks and enhances productivity using Amazon Bedrock. This approach leverages AWS technologies to streamline and optimize workflow processes.

Creating a Multimodal Social Media Content Generator with Amazon Bedrock

Follow a step-by-step guide to build a social media content generator app using vision, language, and embedding models. Utilize Anthropic’s Claude 3, Amazon Titan Image Generator, and Amazon Titan Multimodal Embeddings via Amazon Bedrock API and Amazon OpenSearch Serverless.

Numerical Analysis with Amazon Bedrock Knowledge Bases

Amazon Bedrock Knowledge Bases offers a powerful solution for numerical analysis on documents. Deploy this solution in an AWS account to analyze various document types effectively, providing valuable insights and data-driven decisions.

Deploying Meta’s Llama 3.2 Models Using Amazon SageMaker JumpStart

Learn how to discover and deploy the Llama 3.2 11B Vision model using SageMaker JumpStart. This post also details the supported instance types and broader capabilities of the Llama 3.2 models available on the platform.

Expanding Vision Use Cases with Llama 3.2 Models from Meta

For the first time, Meta’s Llama models are enhanced with vision capabilities. This post demonstrates how to apply Llama 3.2 11B and 90B models to various vision-based applications, extending their utility beyond traditional text-only functions.

Transforming Legal Tech with Generative AI on AWS

Legal professionals can enhance their work by building generative AI solutions on AWS. This post discusses how to streamline document analysis, preparation of legal drafts, and insight extraction using advanced AI tools.

AI Agents in Contact Centers: A Case Study with DoorDash

Discover how DoorDash implemented a generative AI agent using Amazon Connect, Amazon Lex, and Amazon Bedrock Knowledge Bases. This solution provides a low-latency, self-service experience for delivery workers, enhancing operational efficiency.

Cost Reduction and Improved Concurrency with Amazon SageMaker: Karini AI’s Experience

Karini AI migrated their vector embedding models from Kubernetes to Amazon SageMaker endpoints, achieving a 23% reduction in infrastructure costs and a 30% improvement in concurrency, showcasing the financial and operational benefits of adopting SageMaker.

Driving Equitable Climate Solutions with AI: The AI for Equity Challenge

The AI for Equity Challenge, launched by IRCAI, Zindi, and AWS, aims to empower organizations to use AI and cloud technologies for climate action, gender, and health. This global competition focuses on creating impactful solutions for vulnerable populations.

Enhancing Just Walk Out Technology with Multi-Modal AI

This post highlights advancements in Just Walk Out technology, powered by a multi-modal foundation model. Utilizing a transformer-based architecture, this technology is designed for physical stores, streamlining and enhancing the shopping experience.

Generating Synthetic Data for RAG Systems with Amazon Bedrock

Learn how to use Anthropic Claude on Amazon Bedrock to generate synthetic data for evaluating RAG systems. This method helps improve the efficiency and accuracy of your data analysis processes.

Optimizing Traffic Lights with Amazon Rekognition

Amazon Rekognition can mitigate congestion at traffic intersections, reducing operations and maintenance costs. This blog post details how to leverage Rekognition for efficient traffic management and improved urban mobility.

Accelerating ML Workflows with Amazon Q Developer in SageMaker Studio

This real-world use case demonstrates how Amazon Q Developer can accelerate ML workflows. By analyzing the Diabetes 130-US hospitals dataset, this post guides you through developing an ML model to predict hospital readmission likelihood.

Governing Generative AI in the Enterprise with SageMaker Canvas

Learn strategies for governing access to Amazon Bedrock and SageMaker JumpStart models within SageMaker Canvas. This post explains how to create granular IAM policies to control model invocation and endpoint provisioning.

Transforming Home Ownership with AI: Rocket Mortgage’s Journey with AWS

Rocket Mortgage’s use of AWS services sets a new standard in the industry. This post shows how to use AI and cloud technologies to enhance customer service and streamline operations, providing a blueprint for transformation in client interactions and processes.

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Announcements, Updates, and Launches

Amazon Web Services (AWS) continues to innovate and expand its offerings, providing new tools and services to enhance performance and efficiency. Here is a summary of the latest announcements, updates, and launches in the AWS ecosystem.

New Amazon EC2 C8g and M8g Instances: Sustainable Computing Excellence

The new Amazon EC2 C8g and M8g instances are designed for compute-intensive and general-purpose workloads, respectively. These instances are powered by the latest AWS Graviton4 processors, offering unmatched computing power and energy efficiency. They are optimized for memory-intensive applications such as in-memory databases and real-time analytics. Organizations can leverage these new instances to achieve high performance while maintaining a sustainable and energy-efficient IT infrastructure.

Meta’s Llama 3.2 Models in Amazon Bedrock: Advanced Generative AI

Meta has introduced the Llama 3.2 model family, now available in Amazon Bedrock. These models represent a significant advancement in generative AI with enhanced capabilities and broader applicability. The Llama 3.2 models support multimodal vision, enabling both language processing and image recognition. This addition allows businesses to leverage cutting-edge AI for various applications, from content generation to complex data analysis.

AI21 Labs’ Jamba 1.5 Models in Amazon Bedrock: Long-Context Language Processing

AI21 Labs has made its Jamba 1.5 models available in Amazon Bedrock, bringing high-performance long-context language processing capabilities. These models can handle up to 256K tokens and support JSON output, making them suitable for complex language tasks. Furthermore, Jamba 1.5 models offer multilingual support across nine languages, providing a versatile tool for global enterprises needing advanced language processing solutions.

AWS Weekly Roundup: Highlights from AWS Community Days and New Releases

The latest AWS Weekly Roundup highlights various new releases and events. Notably, the introduction of Amazon EC2 X8g Instances, Amazon Q generative SQL for Amazon Redshift, and the AWS SDK for Swift. Additionally, AWS Community Days have been taking place worldwide. A special mention goes to AWS Community Day Argentina, where Jeff Barr delivered a keynote and shared engaging stories with the community, including a humorous anecdote about following Bill Gates to a McDonald’s.

These updates demonstrate AWS’s ongoing commitment to providing innovative solutions and fostering community engagement. Businesses can leverage these new tools and services to enhance their operations, drive efficiency, and stay at the forefront of technological advancements.

How KeyCore Can Help

KeyCore, the leading AWS consultancy in Denmark, can help organizations maximize the benefits of these new AWS offerings. Our team of experts provides both professional and managed services to ensure seamless integration and optimal use of AWS resources. Whether it’s deploying the new EC2 instances, utilizing advanced AI models, or integrating new AWS services into your workflow, KeyCore has the expertise to support your business needs. Visit our website to learn more about how we can assist you.

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Containers

Migrating from AWS App Mesh to Amazon ECS Service Connect

AWS has announced the discontinuation of AWS App Mesh, set to take effect on September 30th, 2026. Current customers will still have access to all functionalities of AWS App Mesh, including the creation of new resources and onboarding new accounts through AWS CLI and AWS CloudFormation, until this date.

Transition Plan

AWS aims to ensure a smooth transition for existing AWS App Mesh customers to Amazon ECS Service Connect. Amazon ECS Service Connect is designed to offer enhanced features and capabilities, providing a robust and efficient service mesh solution.

Key Benefits of Amazon ECS Service Connect

Amazon ECS Service Connect simplifies the process of connecting and managing microservices within ECS, offering several advantages:
– **Ease of Integration**: Seamless integration with existing ECS clusters.
– **Enhanced Security**: Built-in security features that ensure safe communication between services.
– **Scalability**: Designed to handle large-scale microservice architectures without performance loss.

Migration Steps

The migration process from AWS App Mesh to Amazon ECS Service Connect involves several steps:
1. **Assessment**: Evaluate existing AWS App Mesh configurations and identify dependencies.
2. **Planning**: Map out the migration strategy, considering service dependencies and downtime minimization.
3. **Execution**: Gradual transition of services to Amazon ECS Service Connect, ensuring continuous operation.

How KeyCore Can Assist

KeyCore, as a leading Danish AWS consultancy, offers comprehensive migration services to streamline the transition from AWS App Mesh to Amazon ECS Service Connect. KeyCore’s team of experts can provide:
– **Assessment and Planning**: Detailed evaluation of current infrastructure and strategic planning for a seamless migration.
– **Implementation Support**: Hands-on assistance with the technical migration process, ensuring minimal disruption to services.
– **Post-Migration Optimization**: Ongoing support to optimize the new service mesh environment for performance and reliability.

For a smooth transition to Amazon ECS Service Connect, trust KeyCore’s expertise to guide through every step of the process. Visit [KeyCore](https://www.keycore.dk) to learn more about how they can support your migration journey.

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Official Database Blog of Amazon Web Services

Amazon Web Services (AWS) offers a comprehensive set of database solutions that cater to various needs. Let’s delve into some recent advancements and insights shared in the Official Database Blog of AWS.

Troubleshooting Amazon RDS for MySQL and MariaDB Errors

Managing databases on Amazon RDS for MySQL or Amazon RDS for MariaDB can sometimes lead to encountering errors. This article discusses common MySQL and MariaDB errors found in error logs and application logs. It also provides insight into their potential root causes and effective troubleshooting steps.

Typical issues include connectivity problems, query performance bottlenecks, and replication delays. Solutions often involve adjusting configuration settings, analyzing slow query logs, and ensuring proper resource allocation. Tools like Amazon CloudWatch and Performance Insights can be invaluable in diagnosing these issues.

By understanding the nature of these errors and leveraging AWS tools, database administrators can maintain optimal performance and reliability of their MySQL and MariaDB databases on Amazon RDS.

High Availability and Fast Disaster Recovery with Amazon Aurora PostgreSQL

A large financial AWS customer implemented a robust solution for high availability and disaster recovery using Amazon Aurora PostgreSQL. The solution featured Global Database and Amazon RDS Proxy to achieve sub-minute failover within Availability Zones and quick recovery across AWS Regions.

The customer aimed to ensure uninterrupted service for their wealth management portal. By partnering with AWS, they designed a system that minimized downtime and provided seamless failover processes. The architecture involved multi-region setups and automated recovery mechanisms to meet stringent high availability requirements.

This case study highlights how AWS’s advanced database solutions can help enterprises achieve their business continuity goals efficiently.

Optimizing Amazon Timestream Compute Units

Amazon Timestream is purpose-built for time series data management. This post explores Timestream Compute Units (TCUs), which are integral to optimizing cost and performance. Understanding and managing TCUs help in controlling costs while ensuring efficient data processing.

The article provides guidance on estimating the required compute units for different workloads. It also discusses strategies for optimizing usage, such as monitoring TCU consumption and adjusting configurations based on usage patterns.

By fine-tuning TCU allocation, businesses can achieve an optimal balance between performance and cost, making Timestream a more effective tool for time series data management.

Apollo Tyres’ Tyre Genealogy Solution with Amazon Neptune and Amazon Bedrock

This joint post with Apollo Tyres reveals how the company built an advanced tyre genealogy solution using Amazon Neptune and Amazon Bedrock. Apollo Tyres, a global leader in tyre manufacturing, needed a robust system to track the lifecycle of each tyre from production to end-of-life.

By leveraging Amazon Neptune’s graph database capabilities and the aggregation power of Amazon Bedrock, Apollo Tyres developed a solution that enhanced traceability and improved quality control. The system integrates data from various sources, providing a comprehensive view of each tyre’s journey.

This innovative solution not only streamlines operations but also ensures compliance with industry standards and improves customer satisfaction.

Migrating SQL Server Databases to Babelfish for Aurora PostgreSQL

This post provides a step-by-step guide for migrating SQL Server databases to Babelfish for Aurora PostgreSQL. The approach uses change tracking with a linked server to replicate ongoing changes.

The process begins with setting up change tracking in SQL Server Web Edition, followed by configuring the linked server feature in Babelfish. This allows continuous synchronization between the source and target databases, ensuring data consistency throughout the migration.

By employing this method, businesses can achieve a smooth transition to Aurora PostgreSQL while maintaining high data fidelity and minimizing downtime.

How KeyCore Can Help

KeyCore, the leading AWS consultancy in Denmark, offers extensive expertise in implementing and optimizing AWS database solutions. Whether it’s troubleshooting RDS errors, designing high availability architectures, optimizing Timestream usage, or executing seamless database migrations, KeyCore provides tailored services to meet specific business needs.

Our professional services include strategic consulting, architecture design, and implementation support, while our managed services ensure ongoing optimization and maintenance of AWS environments. Partner with KeyCore to leverage AWS’s full potential and drive your database initiatives to success.

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AWS Training and Certification Blog

In today’s rapidly evolving technological landscape, AWS Training and Certification provides a comprehensive suite of learning opportunities designed to equip individuals with in-demand skills and certifications. This article summarizes recent enhancements in AWS training offerings, including a new learning pathway for AI certification and exciting new courses introduced in September 2024.

Pathway to AWS Certified AI Practitioner with AWS Educate

AWS Educate has launched a new learning pathway aimed at preparing learners aged 13 and up for the AWS Certified AI Practitioner certification exam. This pathway includes a curated list of courses that cover:

  • Cloud basics
  • Core AWS services
  • Machine learning foundations
  • Generative AI

Through various educational materials such as videos, articles, knowledge checks, and hands-on labs, learners can gain essential AI skills at their own pace. Additionally, participants can earn digital badges to showcase their achievements.

Exciting Course and Certification Updates in September 2024

In September 2024, AWS introduced 21 new digital training products on AWS Skill Builder, including:

  • Seven new digital courses
  • A game-based learning exam prep option named AWS Escape Room: Exam prep for AWS Certified AI Practitioner AIF
  • A generative AI course specifically designed for AWS Partners: AWS Partner: Artificial Intelligence and Machine Learning (AI/ML) on AWS (Business)

These new offerings provide flexible and engaging ways for learners to prepare for certifications and stay updated with emerging technologies.

Unlocking the Power of Generative AI

Generative AI is transforming industries and redefining problem-solving approaches. Recognizing the need for continuous learning and upskilling, AWS offers a comprehensive set of training and certification opportunities focused on generative AI. These courses help professionals stay ahead of the curve and acquire the skills needed to leverage generative AI effectively in their respective fields.

How KeyCore Can Help

KeyCore is committed to helping clients navigate their AWS learning journeys. Our team of AWS-certified professionals can provide customized training plans, hands-on labs, and one-on-one coaching to ensure your team is fully prepared for AWS certifications. Whether it’s through our professional services or managed services, KeyCore is here to support your organization’s growth and proficiency in AWS technologies.

For more information on how KeyCore can assist with AWS training and certification, visit our website at KeyCore.

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Official Big Data Blog of Amazon Web Services

Amazon EMR Serverless observability, Part 1: Monitor Amazon EMR Serverless workers in near real time using Amazon CloudWatch focuses on the newly launched job worker metrics in Amazon CloudWatch for EMR Serverless. This feature helps monitor vCPUs, memory, ephemeral storage, and disk I/O allocation and usage metrics at an aggregate worker level for Spark and Hive jobs in near real time. By utilizing these CloudWatch metrics, users can keep track of the performance and resource usage of their EMR Serverless workers efficiently.

Introduction to EMR Serverless Observability

Amazon EMR Serverless now includes job worker metrics in Amazon CloudWatch, enabling real-time monitoring. Users can observe metrics such as vCPU usage, memory allocation, ephemeral storage, and disk I/O at a worker level. This capability simplifies tracking for Spark and Hive jobs.

Apply enterprise data governance and management using AWS Lake Formation and AWS IAM Identity Center explores a solution leveraging AWS Lake Formation and AWS IAM Identity Center. It addresses challenges in managing and governing legacy data during digital transformation. This approach ensures the preservation of historical data, compliance with governance controls, and secure, role-based access to data while maintaining robust audit trails.

Enterprise Data Governance

Using AWS Lake Formation and AWS IAM Identity Center, enterprises can manage legacy data amid digital transformation. These tools preserve historical data, enforce compliance, and maintain user entitlements. The solution offers secure, role-based access and robust audit trails for data governance.

Enrich your serverless data lake with Amazon Bedrock demonstrates how to enhance a serverless data lake using Amazon Bedrock. It illustrates the integration of Amazon Bedrock with the AWS Serverless Data Analytics Pipeline architecture using Amazon EventBridge, AWS Step Functions, and AWS Lambda. This integration automates various data enrichment tasks, making the process cost-effective and scalable.

Data Lake Enrichment

Organizations can enrich their serverless data lakes with Amazon Bedrock. The integration involves Amazon EventBridge, AWS Step Functions, and AWS Lambda, automating data enrichment tasks. This method is both cost-effective and scalable, making it ideal for processing large datasets.

Achieve cross-Region resilience with Amazon OpenSearch Ingestion describes solutions for cross-Region resiliency using an active-active replication model with Amazon OpenSearch Ingestion and Amazon S3. It covers configurations for both OpenSearch Service managed clusters and OpenSearch Serverless collections, using OpenSearch Serverless as an example. These solutions ensure that relationships do not need reestablishing during a failback.

Cross-Region Resilience

The post details cross-Region resiliency solutions with Amazon OpenSearch Ingestion and Amazon S3. An active-active replication model is employed, ensuring that relationships remain intact during failback. The configurations apply to both OpenSearch Service managed clusters and OpenSearch Serverless collections.

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Networking & Content Delivery

Today, AWS introduced support for security group referencing on AWS Transit Gateway. This new feature allows inbound security rules to reference security groups defined in other Amazon Virtual Private Clouds (Amazon VPCs) attached to a transit gateway within the same AWS Region. This functionality enhances security management over complex network architectures by simplifying the enforcement of security rules across different VPCs.

Enhanced Security Management

With security group referencing, administrators can centralize security control, ensuring consistent security postures across multiple VPCs. This removes the need for complex and repetitive rule definitions, minimizing the risk of misconfigurations. It also enhances the ability to quickly adapt to network changes by simply updating the referenced security groups.

Integration and Use Cases

Businesses can leverage this feature to streamline the management of large, interconnected AWS environments. For instance, a company with multiple VPCs can now easily manage access policies by referencing security groups rather than configuring individual security rules for each VPC.

Comcast Corporation, a global media and technology company, has achieved faster time-to-market for new product launches, increased resiliency, and reduced operational overhead by using AWS Transit Gateway and AWS Direct Connect. AWS Transit Gateway simplifies network topologies and enables centralized network management, which is crucial for global operations like Comcast’s.

Benefits of AWS Transit Gateway

By leveraging AWS Transit Gateway, Comcast has streamlined its network architecture, making it easier to manage and scale. This has led to reduced operational overhead as network configurations are more straightforward. Additionally, using AWS Direct Connect has improved the reliability and performance of their cloud services, ensuring a better user experience.

Faster Global Expansion

With AWS solutions, Comcast can quickly set up new regional operations, speed up product launches, and ensure consistent network policies across all regions. This agility is essential for maintaining a competitive edge in the fast-paced tech industry.

Amazon Virtual Private Cloud (Amazon VPC) endpoints, including gateway and interface endpoints, enable organizations to privately access supported AWS services and VPC endpoint services powered by AWS PrivateLink. These endpoints offer multiple benefits, such as enhanced security, performance, and cost efficiency.

Seamless Migration

Migrating workloads to use VPC endpoints can be accomplished with minimal downtime. This enables businesses to maintain high availability while upgrading their network architecture. As a result, organizations can achieve better security and performance without significant disruptions.

Key Benefits

By adopting VPC endpoints, businesses can reduce data transfer costs, improve security by keeping traffic within the AWS network, and simplify network management. This leads to an overall more robust and efficient cloud infrastructure.

How KeyCore Can Help

KeyCore, the leading Danish AWS consultancy, can assist organizations in implementing these advanced AWS networking features. From setting up AWS Transit Gateway with security group referencing to migrating workloads to VPC endpoints, KeyCore offers both professional and managed services. Our expertise ensures that businesses can optimize their AWS environments, reduce operational overhead, and enhance security. Learn more about our offerings at KeyCore.

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AWS for M&E Blog

The PGA TOUR, known as the world’s premier membership organization for touring professional golfers, utilizes machine learning and generative AI from AWS to enhance its Media Asset Management (MAM) systems. This collaboration, highlighted by Byron Chapman, Director of Media Asset Management & Media Workflows at PGA TOUR, and Andres Carjuzaa, Co-Founder & CTO of Around, showcases how advanced technology optimizes the management and distribution of media assets.

Enhancing Media Asset Management

The PGA TOUR hosts numerous tournaments, requiring efficient handling of vast amounts of media data. By integrating AWS’s machine learning and AI capabilities, they streamline the MAM processes, making it easier to manage, categorize, and retrieve media assets. AWS’s services enable automated tagging, a feature that significantly reduces manual efforts and enhances the accuracy of media management.

Leveraging Machine Learning and Generative AI

Machine learning models from AWS analyze media content to generate metadata, such as identifying players, locations, and key moments in the footage. Generative AI further enhances the workflow by creating supplemental content, such as highlight reels and promotional clips, without extensive manual intervention. This not only saves time but also ensures high-quality output aligned with the PGA TOUR’s standards.

Business Value and Efficiency

By implementing these advanced technologies, the PGA TOUR gains considerable business value. The automation of media processing tasks allows the organization to focus more on creative and strategic initiatives. Improved media asset management ensures that content is readily available for broadcasters, sponsors, and fans, enhancing the overall viewer experience and engagement.

How KeyCore Can Help

KeyCore, as the leading Danish AWS consultancy, offers expertise in integrating AWS’s machine learning and AI services into media workflows. Our professional and managed services can help organizations like the PGA TOUR to optimize their media asset management systems, ensuring efficient data handling and high-quality content production. With our deep understanding of AWS technologies, we provide tailored solutions that drive operational excellence and business growth.

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AWS Storage Blog

Effective October 28, 2024, new customers will no longer be able to create new Amazon FSx File Gateways (FSx File Gateway). To use the service, it is necessary to create an FSx File Gateway before this date. The transition from Amazon FSx File Gateway to Amazon FSx for Windows File Server is recommended. Customers can start using FSx File Gateway by accessing the Storage Gateway console in AWS.

Transitioning to Amazon FSx for Windows File Server

Existing users should plan their migration from FSx File Gateway to Amazon FSx for Windows File Server. This transition is essential to ensure continuous access to file shares. Detailed instructions and best practices for this migration process can be found in the AWS documentation.

KeyCore’s Assistance with Migration

KeyCore offers expert services to facilitate the seamless transition from FSx File Gateway to Amazon FSx for Windows File Server. Our team ensures minimal disruption and optimized configuration for enhanced performance.

The global data creation and consumption is predicted to surge to 175 zettabytes by 2025. Organizations need swift, reliable, and scalable cloud migration solutions to move their growing on-premises datasets to the cloud. Amazon FSx for NetApp ONTAP with Cloud Write mode streamlines petabyte-scale data migrations, making it an ideal solution for data center lease renewals, terminations, or other migration triggers.

Advantages of Cloud Write Mode

Cloud Write mode enhances data migration efficiency by providing high throughput and reliability. This ensures data integrity and speeds up the migration process.

KeyCore’s Role in Data Migration

KeyCore specializes in large-scale data migrations, leveraging Amazon FSx for NetApp ONTAP. Our services ensure a smooth transition with optimized performance and minimal downtime.

Effective management of storage costs is crucial as data grows. Amazon S3 Lifecycle policies allow organizations to transition data to cheaper storage based on custom filtering criteria. This helps in optimizing storage costs by moving files to less expensive cold storage classes.

Custom Filtering Criteria

Organizations can define custom criteria for transitioning data, ensuring that storage costs align with their specific needs and requirements. This flexibility is key to maintaining cost-effective data infrastructure.

KeyCore’s Expertise in Cost Optimization

KeyCore provides tailored solutions for optimizing storage costs using Amazon S3 Lifecycle policies. Our team helps define and implement effective data transition strategies.

Lyrebird Studio, a leading global developer, and software publisher, has improved performance and reduced costs for generative AI workloads using Amazon S3 Express One Zone. This solution provides a responsive user experience with minimal downtime, crucial for Lyrebird Studio’s millions of users who enjoy creating social content through accessible mobile apps.

Benefits of S3 Express One Zone

Amazon S3 Express One Zone offers low-latency access to data, which is essential for performance-intensive generative AI workloads. This helps in delivering a superior user experience while keeping costs manageable.

KeyCore’s Support for Generative AI Workloads

KeyCore assists organizations like Lyrebird Studio in optimizing their generative AI workloads using Amazon S3 Express One Zone. Our expertise ensures high performance and cost efficiency, driving better outcomes for end-users.

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AWS Architecture Blog

Software as a Service (SaaS) applications provide transformative solutions to businesses worldwide by delivering on-demand software to a global audience. However, building a successful SaaS platform requires meticulous architectural planning, especially considering the challenges of multi-tenancy. It is crucial to ensure that each tenant’s data remains isolated and protected from unauthorized access.

Designing Multi-Tenant SaaS Systems

Multi-tenant SaaS systems must handle multiple customers (tenants) sharing the same infrastructure while ensuring their data remains isolated and secure. This requires implementing strategies such as tenant isolation, resource allocation, and data partitioning. Using AWS services like Amazon RDS for database partitioning and Amazon S3 for object storage can help achieve this. Additionally, AWS Identity and Access Management (IAM) can be used for fine-grained access control to ensure data security.

Architectural Considerations

Key architectural considerations for a multi-tenant SaaS system include scalability, data isolation, and cost efficiency. AWS offers various services and tools to address these needs. For instance, Amazon Elastic Kubernetes Service (EKS) can manage containerized applications, offering scalability and isolation through namespaces. Additionally, AWS Lambda can help in building serverless functions for cost-effective compute resources.

Ensuring Data Security

Data security is paramount in multi-tenant systems. Encrypting data at rest and in transit using AWS Key Management Service (KMS) is essential. Implementing audit logging with AWS CloudTrail can also help monitor and manage access to tenant data, ensuring compliance with security standards and regulations.

AWS customers often seek to run their systems within budget while avoiding unnecessary costs. This post provides practical advice on designing scalable and cost-efficient three-tier architectures using serverless technologies within the AWS Free Tier. With AWS, businesses can start small and scale cost-effectively as demand increases.

Three-Tier Architecture Overview

A three-tier architecture typically includes a presentation layer (frontend), an application layer (backend), and a data layer. AWS services like Amazon S3 (storage), AWS Lambda (compute), and Amazon API Gateway (interface) can be used to create a cost-effective and scalable architecture. By leveraging the AWS Free Tier, businesses can reduce initial costs while developing their applications.

Cost-Effective Design Strategies

Using serverless technologies is a practical way to manage costs. AWS Lambda allows businesses to pay only for the compute time they use, and Amazon DynamoDB offers on-demand capacity mode, which adjusts to traffic patterns. Additionally, AWS Free Tier provides access to services like AWS Lambda, Amazon S3, and Amazon RDS at no cost, making it easier for businesses to start small and scale as needed.

Scaling with Demand

As a business grows, its system architecture must scale to meet increasing demand. AWS services like Amazon Auto Scaling and AWS Elastic Load Balancing can help manage traffic and ensure high availability. By designing a flexible architecture, businesses can adapt to changing demands without incurring excessive costs.

How KeyCore Can Help

KeyCore, as the leading Danish AWS Consultancy, offers comprehensive support in designing and implementing multi-tenant SaaS systems and cost-efficient three-tier architectures. Our team of AWS experts can provide tailored solutions to ensure data security, scalability, and cost management. Whether starting with a new SaaS platform or optimizing an existing system, KeyCore delivers the expertise and guidance needed to succeed on AWS.

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AWS Partner Network (APN) Blog

Modern IT infrastructures are complex and diverse, with resources spanning physical, virtual, and cloud environments. Managing these dynamic environments effectively requires comprehensive visibility and integration capabilities. Read on to explore the latest advancements in AWS infrastructure management and how KeyCore can help streamline your operations.

Achieving Business-Aware AWS Infrastructure Visibility with ServiceNow

ServiceNow’s solution integrates with AWS to provide business-aware visibility for IT infrastructures. Modern infrastructures are highly heterogeneous, encompassing multiple vendor and provider resources. To manage these complex environments, it’s essential to have up-to-date visibility into all assets. ServiceNow’s integration with AWS enables users to achieve this by maintaining an accurate inventory of resources and their business context.

This integration leverages ServiceNow’s Service Graph Connector for AWS to populate the CMDB (Configuration Management Database) with AWS resource data. This data includes details such as relationships, configurations, and metrics, enabling administrators to manage cloud resources more effectively. The end result is improved operational efficiency and better alignment of IT resources with business needs.

Integrating Telecom Network Workloads with Juniper Cloud-Native Router (JCNR) on AWS

The Juniper Cloud-Native Router (JCNR) on AWS facilitates seamless connectivity between on-premises telecom networks and 5G core workloads running on AWS. JCNR uses EVPN routing over VXLAN to create a secure, scalable, and performant hybrid cloud network. This setup allows multi-tenant environments and bridges on-premises layer 2 segments with AWS VPC subnets.

The JCNR simplifies the deployment of distributed network workloads and edge computing architectures, enabling telecom operators to extend their network capabilities to the cloud. This integration ensures consistent performance and security while expanding the reach of telecom services.

Accelerate VMware Migrations to AWS with Nutanix NC2

For organizations looking to migrate VMware-based workloads to AWS, Nutanix NC2 offers a streamlined solution. Nutanix NC2 provides a consistent infrastructure and operations experience, enabling users to rehost existing workloads without extensive modifications. This accelerates the migration process and reduces the risk of disruptions.

NC2 on AWS supports various migration strategies, including re-platforming on fully managed AWS services. This flexibility allows organizations to modernize their infrastructure at their own pace while leveraging the benefits of the cloud, such as scalability, reliability, and cost efficiency.

Rebuilding Enterprise-Grade AWS Network for Cadent Gas by HCLTech

In the rapidly evolving technology landscape, many customers are transitioning from traditional MPLS networks to Software Defined Wide Area Networks (SD-WAN) using the internet. HCLTech helped Cadent Gas rebuild its network infrastructure on AWS, moving towards a Zero-Trust Architecture. This approach ensures that no entity, internal or external, is trusted by default, and continuous monitoring is implemented to scrutinize behavior.

This transition to a modern, zero-trust network architecture provides enhanced security, flexibility, and performance, aligning with the latest industry trends and customer needs.

Armakuni Uses Karpenter for Resilient Workload Scaling and Cost Efficiencies

Armakuni leveraged Karpenter, an open-source autoscaler developed by AWS for Kubernetes, to optimize its applications on AWS Elastic Kubernetes Service (EKS). Karpenter enables efficient autoscaling and automatic selection of right-sized infrastructure, leading to significant operational cost reductions.

By using Karpenter, Armakuni achieved resilient workload scaling, ensuring that applications consistently perform well under varying loads. This approach not only enhances performance but also optimizes resource utilization, contributing to overall cost efficiency.

How KeyCore Can Help

KeyCore, Denmark’s leading AWS consultancy, can assist in implementing and optimizing these solutions to meet your specific business needs. Whether you need comprehensive visibility into your AWS infrastructure, seamless integration of telecom networks, accelerated VMware migrations, or efficient workload scaling, KeyCore’s expertise ensures successful outcomes.

Our professional services team can guide you through the complexities of modern IT infrastructure management, while our managed services offer ongoing support to ensure your systems remain optimized and secure. Visit our website to learn more about how KeyCore can support your AWS journey.

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AWS Cloud Enterprise Strategy Blog

Generative AI is revolutionizing industries by harnessing vast amounts of data. The cloud’s capability to store and process large datasets has propelled the rise of powerful foundation models. Businesses can leverage these models by fine-tuning them or utilizing retrieval augmented generation (RAG) to customize them for specific business needs. KeyCore understands the technical intricacies involved in managing and optimizing data for generative AI, ensuring businesses maximize the value derived from their AI initiatives.

Data: The Fuel for Generative AI

Data serves as the cornerstone for generative AI. Cloud platforms enable the storage and processing of enormous datasets, essential for training robust AI models. These foundation models can be fine-tuned or adapted using advanced techniques like RAG to meet unique business requirements. This adaptability empowers enterprises to create tailored AI solutions that drive innovation and efficiency.

Empowering Businesses with Tailored AI Models

Businesses can achieve competitive advantages by tailoring generative AI models. Fine-tuning these models allows for alignment with specific industry needs, enhancing performance and relevance. Techniques such as RAG enable organizations to incorporate domain-specific knowledge into pre-trained models, improving context and accuracy. This customization is vital for staying ahead in a data-driven world.

Capitalizing on India’s educational strengths, the article highlights the importance of learning in cloud technology. Recounting personal experience with early computing, the narrative emphasizes that the capacity to learn is a gift, and the willingness to learn is a choice. The advancements in cloud technology have opened new avenues for learning and skill development, particularly in tech-driven economies like India. KeyCore recognizes the potential of leveraging cloud technology to foster continuous learning and skill enhancement, critical for staying relevant in a fast-evolving industry.

Learning as a Key Driver in Cloud Technology

Continuous learning is essential in the rapidly evolving cloud technology landscape. Early exposure to computing, such as the Sinclair ZX81, underscores the importance of embracing technological change. Cloud platforms provide vast resources for learning and development, equipping individuals and organizations with the skills needed to thrive. Emphasizing learning as a strategic priority helps maintain a competitive edge in tech-centric economies.

The guide on generative AI cost optimization offers strategies to maximize AI’s value without escalating costs. It covers various aspects of the AI lifecycle, from model selection and data management to financial operations practices (FinOps). By implementing these strategies, businesses can achieve significant cost savings while maintaining high performance and innovation standards in their AI initiatives. KeyCore provides expert guidance in optimizing AI investments, ensuring businesses derive maximum value from their AI projects.

Cost Optimization in Generative AI

Effective cost management is crucial in realizing the full potential of generative AI. Businesses can optimize costs by carefully selecting models that balance performance and expense. Efficient data management practices minimize storage and processing costs, while FinOps practices ensure financial accountability and transparency. Implementing these strategies enables organizations to sustain innovation without compromising on budgetary constraints.

KeyCore’s Expertise

KeyCore offers comprehensive services to help businesses navigate the complexities of generative AI and cloud technology. From data management and model customization to cost optimization and learning enablement, KeyCore’s expertise ensures businesses can leverage cloud technologies to their fullest potential. Partnering with KeyCore means gaining access to advanced technical knowledge and strategic insights, driving success in the digital age.

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AWS HPC Blog

Harnessing the power of agent-based modeling for equity market simulation and strategy testing: Financial professionals: Simulate realistic market conditions with Simudyne’s agent-based modeling on AWS and Red Hat OpenShift. Learn how HKEX leverages these insights.

Simulating Realistic Market Conditions

Financial professionals can significantly benefit from using Simudyne’s agent-based modeling on AWS and Red Hat OpenShift. This technology allows for the simulation of realistic market conditions by modeling the behavior and interactions of individual market participants. HKEX, one of the leading financial hubs, leverages these insights to enhance their market strategy testing and development.

Benefits for Financial Professionals

Using agent-based modeling helps in creating more accurate and realistic simulations. This approach provides deep insights into market dynamics, enabling better decision-making and strategy testing. It is especially useful in stress-testing financial strategies under various market conditions.

Customizing your HPC environment: building AMIs for AWS Parallel Computing Service: Don’t settle for one-size-fits-all HPC. Unlock the power of custom AMIs in AWS Parallel Computing Service. Discover why tailored images are crucial for security, performance, and your workflows

Tailored HPC Environments

One-size-fits-all solutions often fall short in high-performance computing (HPC). Custom Amazon Machine Images (AMIs) for AWS Parallel Computing Service allow for a tailored HPC environment that meets specific security, performance, and workflow needs. Custom AMIs ensure that the resources are optimized and secure, enhancing overall efficiency.

Importance of Customization

Customizing AMIs provides significant benefits, such as improved security and performance. Tailoring these images to specific workflows ensures that computational tasks are handled efficiently, meeting the unique requirements of different projects.

Discontinuation of NICE EnginFrame effective September 25th, 2025: After careful consideration, we have made the decision to discontinue NICE EnginFrame including NICE EnginFrame views, effective September 25, 2025. If you want to continue using NICE EnginFrame beyond the end-of-support date, we recommend contacting NI-SP, an AWS partner with decades of experience implementing and supporting NICE EnginFrame for enterprises.

End of Support for NICE EnginFrame

NICE EnginFrame and its views will be discontinued effective September 25, 2025. For those who wish to continue using NICE EnginFrame, it is recommended to contact NI-SP, a trusted AWS partner with extensive experience in implementing and supporting this service. NI-SP can help transition seamlessly and ensure ongoing support.

Action Required

Enterprises currently using NICE EnginFrame should plan their transition strategy. By working with experienced partners, organizations can mitigate risks and ensure continuity of their HPC workflows.

Recent improvement to Open MPI AllReduce and the impact to application performance: Our team engineered some Open MPI optimizations for EFA to enhance performance of HPC codes running in the cloud. By improving MPI_AllReduce they improved scaling – matching commercial MPIs. Tests show gains for apps including Code Saturne and OpenFOAM on both Arm64 and x86 instances. Check out how these tweaks can speed up your HPC workloads in the cloud.

Enhanced Application Performance

Significant improvements have been made to Open MPI AllReduce, particularly for Elastic Fabric Adapter (EFA) to boost HPC code performance in the cloud. These optimizations enhance the scaling capabilities, making them comparable to commercial MPI implementations. Applications like Code Saturne and OpenFOAM have shown noticeable performance gains on both Arm64 and x86 instances.

Performance Gains

By improving MPI_AllReduce, AWS has enabled better performance for cloud-based HPC workloads. These enhancements facilitate faster computations and better scaling, crucial for complex simulations and data processing tasks.

AWS Batch enables near-real-time energy production forecasts using NVIDIA Earth-2: Using AWS Batch and NVIDIA Earth-2, we built a scalable workflow that explores millions of scenarios at a fraction of the cost of traditional methods. This innovative approach not only provides rapid energy calculations, but also shows the potential of AI-driven meteorology.

AI-Driven Energy Forecasts

AWS Batch combined with NVIDIA Earth-2 allows for near-real-time energy production forecasts. This scalable workflow can explore millions of scenarios, providing rapid energy calculations at a reduced cost compared to traditional methods. This showcases the potential of AI-driven meteorology in optimizing energy production.

Cost Efficiency and Speed

This innovative workflow not only reduces costs but also speeds up the forecasting process. By leveraging AI and scalable cloud resources, energy companies can make more informed decisions and improve operational efficiency.

How KeyCore Can Help

KeyCore, Denmark’s leading AWS consultancy, offers expert guidance and solutions in high-performance computing, financial modeling, and energy forecasting. Our professional services team can help design and implement custom HPC environments, optimize MPI performance, and transition from legacy frameworks like NICE EnginFrame. Our managed services ensure ongoing support and optimization, allowing clients to focus on their core business activities while leveraging advanced AWS technologies. Learn more about how we can elevate your cloud solutions at KeyCore.

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AWS Cloud Operations Blog

Accelerating Migrations and IT Tasks for DKB using AWS Systems Manager

Deutsche Kreditbank AG (DKB), one of Germany’s largest direct banks, embarked on a significant IT transformation in 2023 by migrating their back-office IT infrastructure to Amazon Web Services (AWS). This migration included a wide range of infrastructure elements such as backup systems, networking components, and both Windows and Linux servers. The project was not without its challenges, as DKB had to manage risks like downtime, data integrity, and security vulnerabilities. By leveraging AWS Systems Manager, DKB was able to automate many of the routine IT tasks, streamline the migration process, and significantly reduce operational overhead.

For businesses in regulated industries, this case study demonstrates how AWS’s comprehensive suite of management tools can mitigate risks and improve operational efficiency during cloud migrations. AWS Systems Manager allowed DKB to maintain high standards of compliance and security while enhancing their overall IT agility. This resulted in a more resilient and efficient infrastructure, capable of supporting DKB’s growing customer base of over five million users.

Centrally Detecting and Investigating Security Findings with AWS Organizations Integrations

Detecting and investigating security risks is critical for safeguarding AWS environments from potential threats. Ensuring the confidentiality, integrity, and availability of data and resources is paramount for business continuity. AWS offers a range of governance and security services designed to help organizations manage these risks effectively. Services like AWS Organizations, AWS Control Tower, and AWS Config provide centralized governance and simplified management across multiple AWS accounts.

With AWS Organizations, businesses can establish centralized security policies and automate their enforcement across the entire organization. AWS Control Tower further simplifies governance by offering a pre-configured environment based on best practices. Additionally, AWS Config tracks and records configuration changes, enabling continuous monitoring and automated compliance checks. Together, these services empower businesses to maintain robust security postures and streamline the investigation of security findings, ensuring quick and effective responses to potential threats.

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AWS for Industries

The telecommunications (telecom) industry is undergoing a transformative shift driven by advancements in artificial intelligence (AI) and machine learning (ML). Small Language Models (SLMs), which can run efficiently on Internet of Things (IoT) and edge devices, are at the forefront of this revolution. SLMs are scaled-down versions of large language models (LLMs) that deliver comparable performance while being less resource-intensive. This innovation offers telecoms new opportunities to enhance customer experiences, optimize network operations, and introduce new services efficiently.

Advantages of Small Language Models

SLMs bring several benefits to the telecom industry. They enable real-time data processing on edge devices, reducing latency and improving response times. This capability is crucial for applications requiring immediate feedback, such as voice assistants or real-time translation services. Additionally, SLMs help reduce costs by minimizing the need for extensive cloud resources, making it feasible for telecom companies to deploy AI-driven solutions at scale.

Real-World Applications

Telecom companies can leverage SLMs to enhance customer support through AI-powered chatbots and virtual assistants. These models can handle a high volume of queries efficiently, providing instant resolutions and improving customer satisfaction. Moreover, SLMs can be used for predictive maintenance, analyzing data from network equipment to foresee potential failures and schedule timely repairs, thus improving network reliability.

How KeyCore Can Help

KeyCore offers expertise in deploying AI and ML solutions tailored to the telecom industry. With experience in integrating SLMs into existing infrastructures, KeyCore can help telecom companies unlock new opportunities, streamline operations, and deliver superior customer experiences.

Many Telco use cases use Equal Cost Multipath (ECMP) for traffic distribution, enhancing high availability (HA), resilience, and fast failover. AWS Direct Connect and AWS Transit Gateways currently support ECMP (Equal-Cost Multi-Path routing) specifically for connections from on-premises environments to the AWS cloud. However, within an Amazon VPC (Virtual Private Cloud), only a single destination can be specified per route.

Virtual IPs for Multipath Load Balancing

To achieve multipath load balancing within an Amazon VPC, Virtual IPs (VIPs) can be utilized. VIPs allow multiple routes to the same destination, enabling traffic distribution across multiple paths. This setup enhances network resilience, ensures high availability, and provides fast failover capabilities. Implementing VIPs within an Amazon VPC allows for more efficient traffic management and improved utilization of network resources.

Implementation Steps

To implement multipath load balancing using VIPs, define multiple routes in the route table, each leading to the VIP. Ensure each route has an equal cost metric to distribute traffic evenly. Additionally, configure your virtual appliances or instances to recognize and handle traffic directed to the VIP, ensuring seamless load balancing and failover.

How KeyCore Can Help

KeyCore’s team of AWS experts can assist in designing and implementing multipath load balancing solutions within Amazon VPCs. By leveraging Virtual IPs, KeyCore ensures optimal network performance, high availability, and resilience for Telco clients.

In today’s rapidly evolving industrial landscape, the manufacturing sector is leading the way in using digital technology to revolutionize processes and improve efficiency. However, as this technological revolution unfolds, organizations encounter significant challenges in adopting and implementing Industry 4.0 solutions, particularly for globally decentralized organizations. One of the primary challenges is scalability.

Cloud Provider-Agnostic Edge Solutions

To address scalability challenges, a cloud provider-agnostic edge solution can be employed. This approach ensures that edge devices and systems can operate seamlessly across different cloud environments, providing flexibility and reducing vendor lock-in. By deploying edge solutions that are not tied to a specific cloud provider, organizations can achieve consistent performance and reliability, regardless of their chosen cloud infrastructure.

Benefits of Agnostic Edge Solutions

Cloud provider-agnostic edge solutions offer several benefits. They enhance scalability by allowing organizations to extend their digital operations to various geographical locations without relying on a single cloud provider. This flexibility ensures that operations remain efficient and responsive, even as the organization grows and expands. Additionally, this approach improves resilience and redundancy, ensuring that systems remain operational even if one cloud provider experiences issues.

How KeyCore Can Help

KeyCore specializes in developing and deploying cloud provider-agnostic edge solutions for the manufacturing sector. By leveraging KeyCore’s expertise, organizations can overcome scalability challenges, ensuring their Industry 4.0 initiatives are successful and future-proof.

During Mergers and Acquisitions (M&A) activity, Healthcare and Life Science (HCLS) customers face additional administrative challenges integrating the technical, legal, and business systems of the target and acquirer companies. For non-technical stakeholders, it is crucial to understand the technical challenges of integrations that will impact business operations.

Top Technical M&A Challenges

One of the primary challenges is data integration. Combining data from different systems requires careful planning and execution to ensure data integrity and consistency. Another challenge is ensuring compliance with regulatory requirements, which can vary significantly between regions and organizations. Additionally, integrating different IT infrastructures and applications can be complex and time-consuming, often requiring significant customization and development work.

Strategies for Overcoming Challenges

To overcome these challenges, organizations must adopt a structured approach to integration. This includes conducting thorough due diligence to identify potential issues and developing a detailed integration plan. Leveraging cloud-based solutions can also simplify the integration process, providing scalable and flexible infrastructure to support the combined entity.

How KeyCore Can Help

KeyCore provides comprehensive support for HCLS customers during M&A activities. With expertise in data integration, regulatory compliance, and IT infrastructure, KeyCore ensures that technical challenges are addressed efficiently, minimizing disruption and ensuring a smooth transition.

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AWS Messaging & Targeting Blog

Sending automated transactional emails, such as account verifications and password resets, is a common requirement for web applications hosted on Amazon EC2 instances. Amazon Simple Email Service (SES) offers multiple interfaces for sending emails, including SMTP, API, and the SES console itself. The type of SES credential used depends on the method chosen for sending emails.

Using IAM Roles for SES

Instead of hardcoding credentials in your application, leveraging IAM roles provides a more secure and manageable way to grant email sending permissions. This method eliminates the risk of credential exposure and simplifies the permission management process.

Setting Up IAM Roles

To begin, create an IAM role with the necessary SES permissions. Attach this role to your EC2 instance. When your application runs on this instance, it can assume the IAM role to send emails without requiring hardcoded credentials.

Benefits of IAM Roles

Using IAM roles offers several advantages:

  • Security: Reduces the risk of credential exposure since the credentials are not hardcoded or stored in the application.
  • Manageability: Simplifies the process of rotating and managing credentials.
  • Scalability: Easily applies to multiple instances without additional configuration.

Implementation

The implementation involves creating an IAM policy with SES permissions, creating an IAM role, and attaching this role to the EC2 instance. Below is an example IAM policy for sending emails via SES:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Action": [
        "ses:SendEmail",
        "ses:SendRawEmail"
      ],
      "Resource": "*"
    }
  ]
}

Once the IAM role is attached to your EC2 instance, the application can use the AWS SDK to send emails without hardcoded credentials. Here’s an example in TypeScript:

import { SESClient, SendEmailCommand } from "@aws-sdk/client-ses";

const client = new SESClient({ region: "us-east-1" });

const sendEmail = async () => {
  const params = {
    Source: "sender@example.com",
    Destination: {
      ToAddresses: ["recipient@example.com"],
    },
    Message: {
      Subject: {
        Data: "Test email",
      },
      Body: {
        Text: {
          Data: "Hello, this is a test email sent using AWS SDK.",
        },
      },
    },
  };

  try {
    const data = await client.send(new SendEmailCommand(params));
    console.log("Email sent successfully:", data);
  } catch (error) {
    console.error("Error sending email:", error);
  }
};

sendEmail();

How KeyCore Can Help

KeyCore, Denmark’s leading AWS consultancy, can assist businesses in setting up secure and efficient email solutions using Amazon SES and IAM roles. Our professional services team can help design and implement the necessary IAM policies and roles, ensuring secure email sending from EC2 instances. Our managed services team can continuously monitor and manage these configurations, providing peace of mind and allowing you to focus on your core business operations.

To learn more about how KeyCore can enhance your AWS infrastructure, visit our website.

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AWS Marketplace

Amazon EKS customers can now streamline the observability of their Kubernetes clusters by deploying the SolarWinds Observability EKS add-on, which is available in the AWS Marketplace. With this new release, users can subscribe to the add-on directly within the AWS Management Console for Amazon EKS, enabling a seamless integration without the need to switch between different interfaces.

Easy Subscription Process

Subscribing to the SolarWinds Observability EKS add-on is straightforward. Customers can find and subscribe to the add-on within the AWS Marketplace section of the AWS Management Console. This integration ensures that users can quickly start monitoring their Kubernetes clusters without the hassle of manual configurations or third-party tool installations.

Benefits of the SolarWinds Observability EKS Add-on

Using the SolarWinds Observability EKS add-on provides several advantages:

  • Enhanced Cluster Visibility: Gain comprehensive insights into the performance and health of Kubernetes clusters.
  • Seamless Integration: The add-on integrates directly with Amazon EKS, eliminating the need for external tools.
  • Scalable Monitoring: The solution scales with your cluster, ensuring continuous monitoring as your environment grows.

Reference Architecture

The reference architecture for this solution illustrates how SolarWinds integrates with Amazon EKS to provide observability. In this setup, SolarWinds acts as the vendor add-on, collecting and analyzing data from the Kubernetes clusters to deliver actionable insights.

How KeyCore Can Help

KeyCore, as the leading AWS consultancy in Denmark, can assist businesses in deploying and optimizing the SolarWinds Observability EKS add-on. Our expertise in AWS services ensures that our clients can leverage this tool to gain valuable visibility into their Kubernetes clusters, improving operational efficiency and performance. We provide both professional and managed services to help organizations integrate and maintain their observability solutions effectively.

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

How to Migrate 3DES Keys from a FIPS to a Non-FIPS AWS CloudHSM Cluster

On August 20, 2024, AWS announced the general availability of the new AWS CloudHSM hardware security module (HSM) instance type, hsm2m.medium (hsm2). This new instance type provides enhanced features compared to the previous hsm1.medium (hsm1). The hsm2 instance supports Federal Information Processing Standards (FIPS) with added functionality for better scalability and security.

When migrating 3DES keys from a FIPS to a non-FIPS CloudHSM cluster, the process involves creating key material in the FIPS-compliant cluster and securely exporting it to the non-FIPS cluster. This ensures that data encryption remains robust during the transition, enhancing security measures without compromising compliance.

Managing Identity Source Transition for AWS IAM Identity Center

AWS IAM Identity Center facilitates user access management to AWS resources and applications. It allows the creation and management of identities within its identity store or connects seamlessly to other identity sources. Organizations sometimes need to change their identity source configuration, which requires careful planning to ensure a smooth transition.

During such transitions, it is critical to update configurations in AWS IAM Identity Center to reflect the new identity source. This process includes verifying user access permissions and ensuring consistent authentication mechanisms to maintain security and compliance across the organization.

2024 H1 IRAP Report Now Available on AWS Artifact for Australian Customers

AWS has released the 2024 H1 Information Security Registered Assessors Program (IRAP) report, now accessible via AWS Artifact. The IRAP assessment, completed by an independent Australian Signals Directorate (ASD) certified assessor, includes seven additional AWS services now assessed at the PROTECTED level.

Australian customers can use this report to ensure that their use of AWS services complies with stringent government security standards, reinforcing their trust in AWS for handling sensitive information.

How AWS WAF Threat Intelligence Features Help Protect the Player Experience for Betting and Gaming Customers

The betting and gaming industry is a lucrative target for sophisticated bots due to its data-rich environment. AWS Web Application Firewall (WAF) employs advanced threat intelligence features to safeguard personal identifiable information (PII) and financial data, particularly in microtransactions and in-game purchases.

By leveraging AWS WAF, gaming companies can mitigate bot attacks and enhance player experience by ensuring secure and uninterrupted access to gaming services.

Six Tips to Improve the Security of Your AWS Transfer Family Server

AWS Transfer Family supports secure file transfers using protocols like AS2, SFTP, FTPS, and FTP. To improve the security of AWS Transfer Family servers, consider the following six tips:

  • Enable server-side encryption to protect data at rest
  • Use VPC endpoints to control network access
  • Employ IAM policies for strict access control
  • Implement multi-factor authentication (MFA) for user login
  • Regularly audit server logs for suspicious activities
  • Update and patch server software to mitigate vulnerabilities

These practices help ensure that data transfers are secure and comply with organizational security policies.

How KeyCore Can Help

KeyCore provides expert guidance and implementation services for AWS security, identity, and compliance needs. Whether migrating keys between CloudHSM clusters, managing IAM Identity Center transitions, or enhancing the security of AWS Transfer Family servers, KeyCore’s team of AWS-certified consultants can ensure robust, compliant, and secure AWS environments. Contact KeyCore to leverage their expertise in optimizing and securing your AWS infrastructure.

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AWS Contact Center

In today’s rapidly evolving digital landscape, businesses with contact centers are increasingly looking to leverage the power of artificial intelligence (AI) to enhance both user experience and agent productivity. One such powerful tool is Amazon Connect, a cloud-based contact center solution offered by AWS.

Enhancing Customer Interactions with AI-Powered IVR/IVA

Companies are integrating AI-powered Interactive Voice Response (IVR) and Intelligent Virtual Assistants (IVA) to modernize their contact centers. By doing so, they can significantly improve the efficiency and effectiveness of customer interactions.

With features like agent assist and intelligent bots, businesses can ensure that customers receive quick and accurate responses to their queries. This not only enhances customer satisfaction but also reduces the workload on human agents, allowing them to focus on more complex issues.

Seamless Integration with Amazon Connect

Amazon Connect facilitates the seamless integration of these AI-powered tools into existing contact center infrastructures. By leveraging AWS’s robust suite of AI and machine learning services, businesses can create highly sophisticated IVR and IVA systems.

For instance, Amazon Lex can be used to build conversational interfaces, while Amazon Polly can convert text into lifelike speech. These integrations enable the creation of dynamic and natural customer interactions, further enhancing the user experience.

Business Value of AI-Powered Contact Centers

The modernization of contact centers with AI brings significant business value. Improved customer interactions lead to higher customer satisfaction and retention rates. Additionally, the automation of routine tasks reduces operational costs and increases agent productivity.

By investing in AI-powered solutions, businesses can stay ahead of the competition and ensure they are providing the best possible service to their customers.

How KeyCore Can Help

KeyCore, Denmark’s leading AWS consultancy, specializes in helping businesses integrate AI-powered solutions into their contact centers. Our experts can guide you through the entire process, from initial planning and setup to ongoing support and optimization.

Whether you are looking to implement Amazon Connect or enhance your existing contact center infrastructure with AI, KeyCore has the expertise and experience to help you achieve your goals. Contact us today to learn more about how we can assist with your contact center modernization efforts.

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Innovating in the Public Sector

During the 79th United Nations General Assembly (UNGA) session in New York, AWS’s Vice President of Worldwide Public Sector, Dave Levy, engaged with global leaders to discuss AWS’s approach to solving global challenges through technology. Levy participated in the Concordia Annual Summit and two Atlantic Council panels, highlighting AWS’s use of generative AI and cloud services to drive worldwide impact. This event underscored AWS’s commitment to leveraging technology for global advancement.

Mitigating Inadvertent IPv6 Prefix Advertisement with AWS Automation

As federal agencies transition to the Trusted Internet Connections (TIC) 3.0 framework, they will utilize AWS to connect to the internet, bypassing traditional TIC networks. Successful migration requires meticulous planning and coordination to ensure seamless IPv6 connectivity. Agencies must manage their IPv6 prefix advertisements with AWS using mechanisms like Bring Your Own IP addresses (BYOIP). This process entails adjustments in routing policies, firewall rules, and security controls to accommodate new IPv6 prefixes.

Accelerating Drug Development through Enhanced Health Data Management on AWS

Healthcare and life sciences organizations can speed up drug development by adopting data mesh and Data as a Product (DaaP) principles. By leveraging AWS services, these organizations can unlock the full potential of their health data, leading to faster and more efficient drug development. AWS supports effective data management and alignment with data mesh principles, facilitating the rapid delivery of life-saving treatments to patients.

Ensuring Secure Data Exchange in Government Using AWS

Government agencies using AWS for data storage benefit from AWS’s stringent security controls and standards. AWS services provide unique opportunities to enhance networking and security strategies, ensuring resilient and secure data transfer mechanisms. This post offers guidance on best practices and prescriptive approaches for implementing secure data exchange solutions among government agencies using AWS services.

Understanding AWS Marketplace Contracts

AWS Marketplace introduces a new approach to software procurement. AWS acts as the marketplace provider, while software vendors, channel partners, and professional services providers serve as sellers. This system simplifies contracts and streamlines the procurement process, bringing transparency and efficiency to software acquisition. AWS Marketplace helps organizations navigate the complexities of procuring IT solutions.

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The Internet of Things on AWS – Official Blog

The automotive industry is experiencing a remarkable transformation driven by software innovation. Cars are no longer just modes of transportation; they are intelligent machines equipped with advanced driver assistance systems (ADAS), sophisticated infotainment, and connectivity features. To enable these functionalities, car manufacturers need to manage vast amounts of data efficiently.

Building a Connected Car Physical Prototype with AWS IoT Services

Leveraging AWS IoT services, automotive companies can create connected car prototypes that showcase real-world applications. AWS IoT Core facilitates secure communication between sensors and the cloud. Similarly, AWS IoT Greengrass extends cloud capabilities to edge devices, enabling data processing even when connectivity is limited.

By integrating AWS IoT services, car companies can collect and analyze data from multiple sources, including on-board sensors, external environments, and user interactions. This data can be used to enhance ADAS functionalities, improve infotainment systems, and ensure seamless connectivity. Moreover, AWS IoT Analytics provides powerful tools for processing and analyzing this data, enabling actionable insights to improve vehicle performance and user experience.

Business Value

Implementing AWS IoT services in connected car prototypes offers significant business value. Automotive companies can accelerate the development and deployment of innovative features, reducing time-to-market. Enhanced ADAS and connectivity features can improve customer satisfaction and brand loyalty. Furthermore, real-time data analytics can help manufacturers identify issues early, reducing maintenance costs and enhancing vehicle safety.

How KeyCore Can Help

KeyCore, as Denmark’s leading AWS consultancy, can assist automotive companies in leveraging AWS IoT services to build connected car prototypes. KeyCore’s expertise in AWS IoT Core, AWS IoT Greengrass, and AWS IoT Analytics ensures that clients can successfully integrate these technologies to enhance their vehicles’ capabilities. From initial planning to deployment and maintenance, KeyCore provides comprehensive support to help automotive companies achieve their goals.

Efficient baggage tracking systems are crucial in the aviation industry for ensuring timely and intact delivery of passengers’ belongings. Errors in baggage handling and tracking can lead to flight delays, missed connections, lost luggage, and dissatisfied customers, ultimately damaging an airline’s reputation and causing significant financial losses.

Reliable Airline Baggage Tracking Solution Using AWS IoT and Amazon MSK

AWS IoT and Amazon Managed Streaming for Apache Kafka (MSK) can be combined to create a reliable baggage tracking solution. AWS IoT Core enables the secure transfer of data from baggage sensors to the cloud. Amazon MSK manages the ingestion and processing of this data in real-time, ensuring seamless tracking throughout the baggage handling process.

By integrating these services, airlines can monitor the location and status of baggage at all times. AWS IoT Device Management and AWS IoT Analytics further enhance the solution by providing tools for managing devices and analyzing data, respectively. This ensures that airlines can quickly identify and resolve any issues in the baggage handling process, minimizing disruptions and improving customer satisfaction.

Business Value

Implementing a baggage tracking solution using AWS IoT and Amazon MSK offers significant business benefits. Airlines can reduce the incidence of lost or delayed luggage, leading to improved customer satisfaction and loyalty. Real-time tracking data enables proactive management of baggage handling, reducing operational disruptions and associated costs. Additionally, airlines can leverage data analytics to identify trends and optimize their baggage handling processes.

How KeyCore Can Help

KeyCore can assist airlines in implementing reliable baggage tracking solutions using AWS IoT and Amazon MSK. With extensive experience in AWS IoT Core, Amazon MSK, and data analytics, KeyCore provides end-to-end support for developing and deploying these solutions. KeyCore’s expertise ensures that airlines can achieve seamless baggage tracking, enhancing operational efficiency and customer satisfaction.

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