Summary of AWS blogs for the week of monday Mon Nov 25

In the week of Mon Nov 25 2024 AWS published 87 blog posts – here is an overview of what happened.

Topics Covered

AWS DevOps & Developer Productivity Blog

Introducing Amazon Q Developer in Eclipse IDE: Harnessing AI for Java Development

Amazon has launched a public preview of Amazon Q Developer integrated with the Eclipse IDE. This new feature targets Java developers by embedding powerful AI-driven capabilities in their familiar development environment. By leveraging Amazon Q Developer, Java programmers can now automate and enhance their coding processes using advanced AI techniques.

The integration offers game-changing features such as code suggestions and automated refactoring. These functionalities streamline development workflows and enhance productivity. Developers can expect a significant reduction in manual coding tasks, allowing them to focus on more complex and creative problem-solving aspects of their projects. This tool empowers developers to write cleaner, more efficient code, ultimately accelerating project timelines.

For businesses, this integration can lead to improved project efficiencies and faster time-to-market for applications. By reducing the time spent on routine coding tasks, teams can allocate resources more strategically, focusing on innovation and development of differentiated features. This strategic allocation results in improved cost-efficiency and better utilization of human resources.

Enhancing Cost Management with Amazon Q Developer and AWS Cost Explorer

Amazon Q Developer has introduced a transformative capability for cost management with its general availability release. This feature integrates with AWS Cost Explorer, utilizing Amazon Q Developer’s natural language processing capabilities. It allows users to analyze AWS costs more intuitively, offering a revolutionized approach to cost management.

Initially launched in preview on April 30, 2024, this capability now provides enhanced tools for understanding and managing AWS expenditures. Users can simply input queries in natural language, and the AI-powered system generates detailed cost reports and analyses. This approach demystifies cost data, making it accessible even to non-financial team members.

This advancement holds significant business value by granting better control over cloud spending. Companies can make more informed budgeting decisions and optimize their cloud resource allocations. Consequently, this leads to reduced unnecessary expenditure and improved financial management, enhancing overall business profitability.

SmugMug Boosts Data Modeling Productivity with Amazon Q Developer

SmugMug, the company behind popular photo-sharing platforms SmugMug and Flickr, has significantly increased its data modeling productivity by leveraging Amazon Q Developer. In collaboration with Dr. Geoff Ryder, SmugMug’s engineering team has integrated Amazon Q Developer into their data science workflows to manage vast amounts of photo data more efficiently.

Amazon Q Developer provides SmugMug with advanced AI capabilities that streamline data processing tasks. The platform’s features allow SmugMug’s team to handle complex data models with ease, improving the speed and accuracy of data operations. As a result, the engineering team can focus more on innovative features and enhancements to their user platforms.

This integration offers substantial benefits by reducing the manual workload associated with data management. For SmugMug, this translates to faster implementation of new features and improved service delivery to over 100 million users. Businesses in similar sectors can leverage Amazon Q Developer to achieve operational efficiency, enhancing their data-driven decision-making capabilities.

How KeyCore Can Assist

KeyCore, as a leading AWS consultancy, offers extensive expertise in integrating Amazon Q Developer across various development environments and business use cases. Whether enhancing AI-driven development processes, optimizing cost management, or improving data modeling efficiency, KeyCore can tailor solutions that align with business goals.

Our team provides both professional and managed services to help organizations unlock the full potential of AWS tools. By partnering with KeyCore, businesses can confidently implement these advanced AWS capabilities, ensuring a seamless transition and maximizing the return on their AWS investment.

To learn more about how KeyCore can support your AWS endeavors, visit our website for further information on our offerings.

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AWS for SAP

Amazon CloudWatch Application Insights for SAP High Availability offers crucial tools to bolster business process resilience. This article delves into the key capabilities of this service, which are essential for maintaining and optimizing SAP landscapes. By leveraging CloudWatch Application Insights, businesses can effectively monitor their SAP systems, thus ensuring maximum business continuity.

Key Capabilities of Amazon CloudWatch Application Insights

Amazon CloudWatch Application Insights provides comprehensive observability features designed for SAP environments. These tools enable organizations to monitor trends within their systems, providing insights into potential issues before they affect business operations. By understanding the health of the SAP landscape, businesses can make informed decisions to enhance system performance and resilience.

Monitoring Trends and System Health

One of the standout features of CloudWatch Application Insights is its ability to track and analyze system trends. This capability allows businesses to preemptively identify areas of concern that could impact their SAP operations. Regular monitoring of system health helps ensure that the SAP environment remains robust and capable of supporting critical business processes.

Maximizing Business Continuity

Using the insights gained from CloudWatch, organizations can react proactively to potential disruptions. By identifying and addressing issues early, businesses can maintain uninterrupted service delivery, thereby maximizing business continuity. This proactive approach is essential for companies that rely heavily on their SAP infrastructure for daily operations.

How KeyCore Can Help

At KeyCore, we specialize in helping businesses leverage AWS tools like Amazon CloudWatch Application Insights for SAP. Our team of AWS experts can assist in configuring and optimizing these services to suit specific business needs. Whether it’s setting up advanced monitoring solutions or integrating AWS services into existing workflows, KeyCore provides the expertise to ensure that your SAP landscape is resilient and efficient.

Learn more about our services and how we can support your SAP environment by visiting our website at KeyCore.dk.

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Official Machine Learning Blog of Amazon Web Services

Easily Deploy and Manage Hundreds of LoRA Adapters with SageMaker Efficient Multi-Adapter Inference

The latest addition to Amazon SageMaker’s inference capabilities is the efficient multi-adapter inference feature. This advancement enables users to deploy and manage hundreds of Low-Rank Adaptation (LoRA) adapters seamlessly. By integrating with SageMaker’s inference components, businesses can enhance their machine learning processes with fine-tuned models, optimizing operations through SageMaker APIs. This feature is particularly beneficial for enterprises looking to scale their ML deployments efficiently.

Optimizing Generative AI Applications with Amazon Bedrock’s Prompt Optimization

Amazon Bedrock now offers Prompt Optimization, a tool designed to enhance the performance of generative AI applications. Users can optimize prompts for various scenarios with a simple API call or a click in the Bedrock console, thereby streamlining their operations. This capability is crucial for businesses needing to maintain high efficiency in AI-driven applications, ensuring better resource utilization and improved outcomes.

Enhancing Enterprise Data Search with LLMs Backed by Knowledge Graphs

Amazon Bedrock introduces a powerful semantic search solution utilizing large language models (LLMs) in combination with knowledge graphs from Amazon Neptune. This integration allows business users to perform semantic searches across multiple enterprise data sources, including Amazon S3 and AWS Glue Data Catalog. By enabling natural language queries, enterprises can improve data accessibility, aiding in better data-driven decision-making processes.

The Intersection of AI and Chess: Embodied AI Chess with Amazon Bedrock

Amazon Bedrock showcases a novel application of generative AI in chess, using embodied AI to enhance gameplay. The setup includes a smart chessboard with robotic arms, each controlled by different foundation models (FMs). This real-time interactive platform allows users to explore and test AI strategies, offering insights into the AI’s decision-making in complex games.

Training Models with Large Sequence Lengths Using Amazon SageMaker Model Parallel

The Amazon SageMaker model parallel library (SMP) has expanded its features, now supporting 8-bit floating point (FP8) mixed-precision training. This development improves training performance for models with large sequence lengths. Businesses can benefit from accelerated training times and reduced computational costs, making it an attractive option for enterprises handling extensive data sets.

Custom Orchestration with Amazon Bedrock Agents

Amazon Bedrock Agents now facilitate custom orchestration of generative AI workflows. This feature offers full control over orchestration, enabling real-time adjustments and reusability. By handling state transitions and interactions between Bedrock Agents and AWS Lambda, organizations can tailor agentic workflows to meet specific business needs.

Enhancing Security with Amazon Bedrock Agents for Code Scanning

Amazon Bedrock provides robust solutions for code scanning, optimization, and remediation, essential for maintaining secure code repositories. As cybersecurity threats grow, this feature allows organizations to automate vulnerability scanning and remediation, ensuring compliance with industry standards. This proactive approach is vital in safeguarding digital assets and maintaining regulatory compliance.

Integrating Generative AI Assistants with Slack and Amazon Bedrock

Seamless integration of Slack with AWS generative AI services enables businesses to build natural language assistants. Users can query unstructured datasets through Slack, improving collaboration and productivity. This integration supports knowledge-based productivity gains, offering real-time insights and decision-making support.

Leveraging Salesforce Data with the Amazon Q Salesforce Online Connector

The Amazon Q Salesforce Online connector empowers businesses to unlock the potential of Salesforce data. By enabling access to both structured and unstructured data within Salesforce, companies can harness valuable insights to drive operations and strategic decisions. This tool simplifies data access, enhancing efficiency and data-driven initiatives.

Reducing LLM Hallucinations with Custom Intervention Using Amazon Bedrock Agents

Amazon Bedrock Agents offer a solution to address large language model (LLM) hallucinations. By employing custom intervention techniques, businesses can detect and mitigate hallucinations effectively. This capability is crucial for maintaining the accuracy and reliability of AI applications, ensuring they align with organizational goals.

Deploying Meta Llama 3.1-8B on AWS Inferentia with Amazon EKS

Amazon’s solution for deploying Meta Llama 3.1-8B on Inferentia 2 instances via Amazon EKS combines high performance with cost efficiency. Leveraging the power of Inferentia 2 chips, businesses can achieve high throughput and low latency inference, making it ideal for deploying large language models (LLMs) at scale.

Serving LLMs with vLLM and Amazon EC2 Instances on AWS AI Chips

The deployment of large language models (LLMs) using vLLM on AWS Trainium and Inferentia chips offers high performance and efficiency. This approach democratizes access to powerful AI models, enabling businesses to host and serve LLMs effectively, reducing costs, and increasing operational scalability.

LLMs in Cyber Defense: Insights from SophosAI with Amazon Bedrock and SageMaker

SophosAI highlights the use of large language models (LLMs) in enhancing cybersecurity operations using Amazon Bedrock and SageMaker. By utilizing models like Anthropic’s Claude 3 Sonnet, security operations centers can boost productivity, streamline workflows, and improve threat detection capabilities.

Enhanced Observability for AWS Trainium and Inferentia with Datadog

Datadog’s integration with AWS Neuron provides deep observability into AWS Trainium and Inferentia instances. This capability offers insights into resource utilization, model execution performance, and infrastructure health, enabling businesses to optimize machine learning workloads for high-performance outcomes.

Creating a Virtual Stock Technical Analyst with Amazon Bedrock Agents

Amazon Bedrock Agents enable the creation of a virtual stock technical analyst, capable of responding to natural language queries regarding stock indicators. This AI-driven tool provides valuable insights, assisting businesses in making informed stock market decisions, thus enhancing financial strategies.

Applying SageMaker Studio Lifecycle Configurations with AWS CDK

This guide demonstrates how to set up lifecycle configurations for Amazon SageMaker Studio domains using AWS CDK. These configurations allow administrators to automate controls over SageMaker Studio environments, enhancing governance and operational efficiency within their ML workflows.

Building a Semantic Cache with Amazon OpenSearch Serverless and Bedrock

Amazon introduces a semantic caching strategy using Amazon OpenSearch Serverless and Bedrock. This blueprint optimizes LLM-based applications by caching repeated data patterns, leading to improved system efficiency and reduced latency, crucial for cost-effective AI solution deployment.

Rad AI’s Reduction of Inference Latency by 50% Using SageMaker

Rad AI has leveraged Amazon SageMaker to reduce real-time inference latency by 50%, significantly streamlining radiology reporting tasks. By utilizing state-of-the-art large language models, Rad AI enhances radiologist productivity, demonstrating significant operational improvements in healthcare applications.

Advanced Information Retrieval with Multimodal Prompts in Amazon Bedrock

Amazon Bedrock enables advanced information retrieval through multimodal prompts, facilitating tasks such as object detection, graph querying, and diagram reading. This functionality enhances data interaction capabilities, supporting comprehensive data analysis and visualization in diverse business contexts.

Crexi’s ML Models Deployment Success on AWS

Crexi has successfully deployed its ML models on AWS, creating a powerful AI/ML pipeline framework. This scalable solution meets diverse project requirements, streamlining commercial real estate transactions through efficient data processing and model management, boosting operational efficiency and business value.

How KeyCore Can Help

KeyCore, as the leading AWS consultancy in Denmark, is well-equipped to assist businesses in implementing these advanced AWS machine learning solutions. Our team of experts can guide organizations through the deployment and management of AI models, optimize their infrastructure for performance, and ensure security compliance. Whether it’s leveraging Amazon Bedrock for enhanced data search capabilities or deploying scalable ML models with Amazon SageMaker, KeyCore provides the expertise and support necessary for successful AI integration and transformation, driving both operational efficiency and business growth.

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Announcements, Updates, and Launches

In the realm of “Announcements, Updates, and Launches,” AWS has introduced several significant enhancements that promise to revolutionize data analytics, storage performance, snapshot management, and capacity planning. These updates are tailored to enhance user experience and operational efficiency across a range of AWS services.

Integrated Analytics with Amazon CloudWatch and Amazon OpenSearch Service

AWS has unveiled an integrated analytics experience for Amazon CloudWatch and Amazon OpenSearch Service. This integration enables users to leverage pre-configured OpenSearch dashboards and utilize OpenSearch SQL and PPL for in-depth analysis of CloudWatch logs. A notable advantage is that OpenSearch customers can now perform log analysis without the need for data duplication, streamlining operations and reducing storage costs.

Enhanced Throughput with Amazon FSx for Lustre

Amazon FSx for Lustre has significantly increased its throughput capabilities for GPU instances, achieving up to 12 times the previous capacity. This enhancement is made possible through the integration of Elastic Fabric Adapter and NVIDIA GPUDirect Storage. The increased throughput unlocks new possibilities in fields such as deep learning, autonomous vehicles, and high-performance computing (HPC) workloads, allowing for faster data processing and more efficient resource utilization.

Time-Based Snapshot Copy for Amazon EBS

AWS introduces time-based snapshot copying for Amazon EBS, which allows users to specify exact time frames for snapshot completion, ranging from 15 minutes to 48 hours. This feature is crucial for meeting Recovery Point Objectives (RPOs) in disaster recovery, testing, development, and operations. It provides users with greater control over snapshot timing, enhancing reliability and efficiency in critical workflows.

Future-Dated EC2 On-Demand Capacity Reservations

Amazon EC2 has launched a feature for future-dated On-Demand Capacity Reservations, allowing users to secure compute capacity up to 120 days in advance. This capability is designed to ensure seamless performance during peak demand events, such as product launches or seasonal sales, by guaranteeing the availability of necessary compute resources, thereby avoiding potential disruptions.

AWS Weekly Roundup and Upcoming AWS re:Invent 2024

The AWS Weekly Roundup highlighted a plethora of new feature and service launches, signaling the approach of AWS re:Invent 2024. This roundup serves as a prelude to the major announcements expected at re:Invent. AWS also announced a new AI training partnership with Anthropic, underscoring its commitment to advancing AI capabilities. Additionally, attendees can join AWS re:Invent virtually, providing broader access to the event’s insights and innovations.

KeyCore is at the forefront of these AWS advancements, offering expert guidance and implementation support. Whether it’s enhancing data analytics with OpenSearch, optimizing storage solutions with FSx for Lustre, or ensuring reliable snapshot management with EBS, KeyCore’s expertise can help enterprises harness the full potential of these AWS innovations. Our services are designed to maximize business value while aligning with your operational goals. Explore more about how KeyCore’s AWS consultancy services can elevate your business at KeyCore.dk.

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Containers

Transforming Istio into an Enterprise-Ready Service Mesh for Amazon ECS

This article, authored by experts from Solo.io and AWS, explores how Istio is being adapted for enterprise use within Amazon ECS. Amazon Elastic Container Service (ECS) is a managed service that simplifies the deployment, scaling, and management of containerized applications. While ECS already offers robust features, integrating Istio as a service mesh enhances its capabilities significantly.

Enterprise Adoption of Istio

Istio’s integration with ECS transforms it into a powerful tool for managing microservices architecture. The service mesh provides advanced traffic management, security, and observability, which are crucial for enterprise-scale operations. This integration allows organizations to better manage their containerized applications with reduced complexity and increased operational efficiency.

Technical Advantages

By utilizing Istio with ECS, enterprises can benefit from improved load balancing, traffic routing, and security measures. Istio provides mutual TLS authentication, enhancing security across services. Additionally, the mesh offers detailed telemetry and logging, aiding in performance monitoring and troubleshooting.

KeyCore can assist organizations in implementing this advanced service mesh solution, ensuring seamless integration and optimization for enterprise needs.

Unlocking Benefits with Bottlerocket: A Purpose-Built Container OS

Bottlerocket is a Linux-based operating system specifically tailored for running containers, designed to improve efficiency and security in containerized environments. This article highlights the challenges of fleet management at scale and how Bottlerocket addresses them.

Purpose-Built Design

Bottlerocket is optimized for container operations, offering a simplified architecture that reduces overhead and improves performance. Its design focuses on automatic updates and minimal attack surface, which are vital for maintaining security in large-scale deployments.

Fleet Management Benefits

The operating system supports seamless integration with orchestration services, facilitating efficient fleet management. Users can benefit from enhanced operational capabilities and reduced downtime through automated updates and rollbacks.

With its focus on security and scalability, Bottlerocket is an ideal solution for enterprises looking to streamline their container operations. KeyCore provides expert guidance in deploying Bottlerocket, helping businesses maximize its potential and integrate it effectively into their existing infrastructure.

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Official Database Blog of Amazon Web Services

Automating Database Object Deployments in Amazon Aurora Using AWS CodePipeline

In the pursuit of efficient database management, using AWS CodePipeline to automate database object deployments in Amazon Aurora can be transformational. This guide delves into setting up an automated pipeline with AWS CodePipeline, AWS CodeBuild, and AWS Secrets Manager. The architecture is designed to simplify the deployment process, ensuring that database changes are implemented smoothly and quickly. By automating these processes, businesses can channel efforts into innovation and performance enhancements, ultimately elevating customer satisfaction.

Setting up this pipeline involves a meticulous step-by-step process, from configuring CodePipeline to integrating with CodeBuild and securely managing credentials with AWS Secrets Manager. This automation not only reduces manual errors but also accelerates deployment cycles, enabling developers to focus on creating value-driven features. For a detailed walkthrough, refer to the AWS documentation on AWS CodePipeline and AWS CodeBuild.

Migrating Time Series Data to Amazon Timestream for LiveAnalytics

Amazon Timestream now supports LiveAnalytics as a target endpoint for AWS Database Migration Service (AWS DMS), offering a seamless way to handle time-series data. This advancement allows for the migration of data from any AWS DMS-supported source database to Timestream, enhancing data analysis capabilities. The article provides a practical example using a PostgreSQL source endpoint, demonstrating the migration process to Timestream.

The integration of Timestream with AWS DMS broadens the possibilities for real-time analytics and data visualization, helping businesses gain insights from their time-series data. For those looking to leverage these capabilities, the AWS documentation on AWS DMS and Amazon Timestream offers further guidance.

Running Event-Driven Stored Procedures with AWS Lambda for PostgreSQL

The fusion of AWS Lambda with Amazon Aurora PostgreSQL and Amazon RDS for PostgreSQL introduces a new dimension to database management. This approach enables the execution of stored procedures in response to specific events, bridging gaps in cloud operations. By using AWS Secrets Manager for secure connections, this method enhances the manageability and flexibility of stored procedures.

This event-driven architecture allows for the automatic invocation of stored procedures without manual intervention, streamlining operations and improving efficiency. While the integration is powerful, understanding its limitations is key to effective implementation. For comprehensive details, explore the AWS documentation on AWS Lambda and Amazon RDS.

Scaling in Amazon Aurora Serverless v2: Insights from Database Parameters

The two-part series on Aurora Serverless v2 scaling provides an in-depth analysis of how database parameters influence scalability. Part 1 focuses on the minimum and maximum Aurora Capacity Unit (ACU) configurations necessary for optimal scaling. Understanding these parameters is crucial for configuring PostgreSQL-compatible DB instances effectively. The post highlights the impact of these configurations on Aurora Serverless v2 scaling efficiency and addresses factors like workload requirements.

Part 2 of the series dives deeper into how the settings of minimum and maximum ACUs affect the scaling process. It examines the speed and behavior of scaling once initiated, offering insights into achieving optimal performance. For those managing Aurora Serverless v2 instances, these insights are invaluable for fine-tuning database performance. For further information, refer to the AWS documentation on Amazon Aurora Serverless.

How KeyCore Can Assist

KeyCore, as Denmark’s leading AWS consultancy, is well-equipped to assist businesses in navigating these AWS services. Whether it’s automating deployments with CodePipeline, migrating to Amazon Timestream, or optimizing serverless scaling, KeyCore offers both professional and managed services. Our team of AWS experts can tailor solutions to fit your specific requirements, ensuring that your cloud infrastructure is not only efficient but also aligned with your business goals. Learn more about our offerings at KeyCore.

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AWS Cloud Financial Management

AWS has announced the general availability of Data Exports for FOCUS 1.0, providing significant improvements in specification conformance compared to its public preview. FOCUS (FinOps Open Cost and Usage Standard) is an open-source specification supported by the FinOps Foundation, designed to standardize and simplify cloud financial management by normalizing cost and usage data across diverse sources. With this release, users can seamlessly aggregate, query, and analyze their AWS cost and usage data using the FOCUS 1.0 schema. This enhanced capability aids organizations in maintaining a consolidated view of their cloud expenditures, thereby streamlining financial management processes.

Announcing the public preview of the enhanced AWS Pricing Calculator, now available within the AWS Billing and Cost Management Console. This feature allows users to generate accurate cost estimates for new workloads or changes to existing AWS usage, considering eligible discounts. The tool is designed to save time while improving estimation accuracy for workload migrations across regions, workload modifications, or new workload planning. Users can access the calculator by logging into the AWS Billing and Cost Management Console and selecting the “Pricing Calculator” option under the “Budget and Planning” section, or by visiting the pricing calculator page directly.

AWS has enhanced its Cost Anomaly Detection service, introducing the ability to identify multiple root causes for cost anomalies. This new feature aids FinOps professionals and cloud financial managers in quickly pinpointing and resolving the underlying causes of unexpected cost increases. By offering deeper insights and facilitating faster resolution times, this enhancement supports FinOps teams in optimizing cloud spending and maintaining financial accountability. The updated Cost Anomaly Detection tool provides a more efficient and comprehensive approach to addressing cost anomalies, streamlining the process for financial managers.

KeyCore stands ready to assist organizations in leveraging these AWS tools for optimized cloud financial management. Our experts can guide you through implementing Data Exports for FOCUS 1.0, utilizing the enhanced Pricing Calculator, and maximizing the benefits from the improved Cost Anomaly Detection service. Whether it’s through professional services or managed services, KeyCore ensures that your organization effectively navigates and manages AWS costs, enhancing your financial operations and strategic planning capabilities. Learn more about how KeyCore can help at KeyCore.dk.

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AWS Training and Certification Blog

AWS Certifications are a gateway to professional growth and recognition in the cloud computing industry. They are instrumental in accelerating career progression by validating expertise in AWS technologies. This article delves into the certification journeys of seasoned AWS professionals, showcasing how these credentials have propelled their careers in dynamic and regulated industries.

The Journey to AWS Certification

For many, the journey to AWS Certification begins with understanding the vast array of AWS services and their applications in solving complex industry challenges. The professionals share how they navigated the extensive learning path, choosing certifications that aligned with their career goals and industry requirements. They emphasize the importance of setting clear objectives and selecting the right certification paths, whether starting with foundational certifications or targeting more specialized credentials.

Career Impact of AWS Certifications

Obtaining AWS Certifications has had a substantial impact on their careers. Certifications not only validated their skills but also opened doors to new opportunities and roles within their organizations. The credentials were particularly beneficial in showcasing their expertise to stakeholders in regulated industries, where demonstrating compliance and proficiency in cloud technologies is critical.

Best Practices for AWS Certification Exam Preparation

Preparation is key to success in AWS Certification exams. The professionals share best practices, including leveraging a mix of hands-on experience, structured learning resources, and practice exams. They suggest integrating AWS training courses, participating in study groups, and engaging with AWS online communities to deepen understanding and reinforce learning.

How KeyCore Can Assist

KeyCore offers tailored AWS training and certification services designed to equip professionals with the skills necessary to excel in AWS Certification exams. With our expertise, individuals can navigate their certification journey confidently and effectively. We provide comprehensive learning resources, hands-on workshops, and expert guidance to ensure successful certification outcomes.

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Microsoft Workloads on AWS

.NET Observability with Amazon CloudWatch Application Signals

This article explores how to integrate Amazon CloudWatch Application Signals with .NET applications deployed on an Amazon Elastic Kubernetes Service (EKS) cluster. The key feature of this integration is the use of the CloudWatch Observability Add-On for EKS. This add-on allows .NET applications to automatically emit telemetry signals using OpenTelemetry, facilitating detailed monitoring and observability of applications in the cloud.

Amazon CloudWatch Application Signals offers a powerful solution for enhancing application observability. By capturing telemetry data, users can gain insights into application performance, optimize resource allocation, and improve troubleshooting efforts. The integration is particularly advantageous for businesses relying on .NET applications within containerized environments, providing them with a seamless observability solution that aligns with their cloud-native strategies.

Setting Up Windows Server Failover Cluster Shared Storage on AWS Outposts Rack

This article provides guidance on using Microsoft Windows Server Storage Spaces Direct to create Clustered Shared Volumes for Windows Server Failover Clusters on an AWS Outposts rack. As organizations increasingly migrate workloads to the cloud, maintaining robust and resilient infrastructure is crucial. AWS Outposts offers a hybrid cloud solution that extends AWS infrastructure and services to virtually any on-premises facility.

Windows Server Failover Clusters are essential for high availability and disaster recovery scenarios. By deploying these clusters on AWS Outposts, businesses can leverage AWS’s scalable infrastructure while retaining on-premises data processing capabilities. The article details the process of setting up shared storage, ensuring that critical applications remain operational and accessible, even in the event of hardware failures.

KeyCore’s Expertise in Microsoft Workloads on AWS

KeyCore is equipped to assist organizations in optimizing their Microsoft workloads on AWS. With expertise in leveraging AWS services such as Amazon CloudWatch, EKS, and AWS Outposts, KeyCore can provide tailored solutions to enhance observability, scalability, and resilience. Whether it’s integrating advanced monitoring tools like CloudWatch Application Signals or deploying robust failover clusters on AWS Outposts, KeyCore ensures seamless migration and efficient cloud operations. Businesses can rely on KeyCore to support their cloud transformation journey, maximizing the benefits of AWS infrastructure while maintaining high performance and reliability.

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Official Big Data Blog of Amazon Web Services

Scaling RISE with SAP Data and AWS Glue

The AWS Glue OData connector for SAP leverages the SAP ODP (Operational Data Provisioning) framework, utilizing the OData protocol for efficient data extraction. The framework operates on a provider-subscriber model, facilitating seamless data transfers between SAP systems and other non-SAP targets. This blog post highlights the process of extracting data from SAP and implementing incremental data transfers using SAP ODP’s OData framework with source delta tokens. By using this approach, organizations can maintain up-to-date data synchronization between their SAP environments and AWS data stores, enhancing the accuracy and timeliness of data analytics.

Amazon EMR and S3 Glacier for Big Data Solutions

Amazon EMR simplifies the process of handling big data by integrating seamlessly with Amazon S3 Glacier. This integration allows for cost-effective data processing by optimizing the way data is stored and accessed. The blog post walks through setting up Amazon EMR on EC2 instances alongside S3 Glacier, providing a step-by-step guide on maximizing performance while minimizing costs. This setup is ideal for organizations looking to archive large datasets efficiently, ensuring that data storage costs remain manageable without sacrificing accessibility.

Enhancing Data Workloads with Amazon Redshift Multi-Data Warehouse Writes

The general availability of Amazon Redshift’s multi-data warehouse writes via data sharing marks a significant milestone. This capability enables users to scale write workloads effectively, improving ETL performance across various types and sizes of warehouses. By aligning warehouse resources with workload demands, organizations can achieve optimal performance. This feature is particularly beneficial for businesses requiring rapid data processing and transformation, providing the flexibility needed to handle diverse and dynamic data workloads effectively.

Near Real-Time Analytics with Amazon Aurora and Amazon Redshift

The integration of Amazon Aurora MySQL-Compatible Edition with Amazon Redshift, alongside dbt Cloud, unlocks the potential for near real-time analytics. This Zero-ETL integration allows organizations to perform analytics on transaction data almost instantaneously. By leveraging dbt Cloud for data transformations, businesses can focus on crafting and utilizing business rules to derive actionable insights. This capability is essential for responding promptly to time-sensitive events, enhancing decision-making processes by providing timely data insights.

Price-Performance Improvements with Intel Accelerators on Amazon OpenSearch Service

Amazon OpenSearch Service, now supporting vector search, sees significant price-performance boosts thanks to Intel Accelerators. Running OpenSearch 2.17+ domains on C/M/R 7i instances can achieve up to a 51% improvement in price-performance compared to previous R5 instances. These enhancements reduce the total cost of ownership (TCO) while delivering substantial savings. This development is crucial for organizations leveraging OpenSearch for complex search and analytics functions, providing a more efficient and cost-effective infrastructure solution.

Apache XTable and AWS Lambda for Open Table Format Conversions

Apache XTable, paired with the AWS Glue Data Catalog, provides an innovative approach to background conversions of open table formats on Amazon S3-based data lakes. This solution offers scalability and cost-efficiency, ensuring minimal disruptions to existing data pipelines. By automating the conversion process, organizations benefit from enhanced data interoperability and streamlined data management workflows. This setup is particularly useful for businesses managing vast data lakes, seeking to optimize data accessibility and utility without incurring additional operational complexities.

At KeyCore, we specialize in empowering organizations to leverage these AWS capabilities effectively. Whether it’s implementing complex data extraction and transformation processes or optimizing big data infrastructures, our expertise ensures that businesses maximize their return on investment from AWS technologies. We provide tailored solutions and managed services that align with unique business needs, driving innovation and operational excellence. Visit KeyCore to learn more about how we can assist your organization.

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Networking & Content Delivery

The integration of AWS Cloud WAN with AWS Direct Connect provides a robust solution for building hybrid connectivity architectures. This combination allows for seamless connectivity between on-premises environments and the AWS Cloud. Businesses looking to enhance their global network architecture can leverage AWS Cloud WAN’s built-in support for AWS Direct Connect attachments. This integration facilitates the creation of efficient and scalable hybrid networks, supporting both local and international connectivity needs.

Best Practices for Designing Global Hybrid Networks

When designing hybrid connectivity architectures using AWS Cloud WAN and AWS Direct Connect, it is important to consider several best practices. Organizations should ensure that their network design aligns with their business objectives and requirements. This includes planning for redundancy, optimizing data transfer paths, and assessing security protocols. By doing so, businesses can create a resilient, flexible, and secure network infrastructure that supports their global operations.

Enabling Seamless Connectivity

With AWS Cloud WAN, organizations can unify their network management across multiple regions and locations. This capability is essential for businesses with a global presence, as it enables consistent policy enforcement and centralized control. Additionally, AWS Direct Connect provides dedicated, low-latency connectivity to AWS, further enhancing the performance and reliability of hybrid cloud environments.

Charting Your AWS Networking Journey at re:Invent 2024

From December 2nd to December 6th, Las Vegas will host re:Invent 2024, a major event for cloud professionals and businesses. Attendees can participate in sessions focused on the latest AWS networking technologies and solutions. This event offers a unique opportunity to connect with industry leaders and explore new innovations that can enhance their networking strategies.

Opportunities for Learning and Networking

re:Invent 2024 will provide attendees with insights into emerging trends in cloud networking. With a wide array of sessions and workshops, participants can gain hands-on experience and deepen their knowledge of AWS technologies. This event is an invaluable opportunity for networking professionals to stay ahead of the curve and explore ways to optimize their cloud operations.

How KeyCore Can Assist

KeyCore can help organizations leverage the integration of AWS Cloud WAN and AWS Direct Connect to build efficient hybrid connectivity architectures. Our expertise in AWS services ensures that businesses can design, implement, and manage their global networks effectively. Whether planning to attend re:Invent 2024 or exploring AWS networking solutions, KeyCore offers the guidance and support needed to achieve optimal results.

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AWS Compute Blog

Faster Scaling with Amazon EC2 Auto Scaling Target Tracking

Amazon EC2 Auto Scaling allows users to fully leverage AWS cloud’s elasticity, offering automated mechanisms to provision and pay for precisely the resources needed. By utilizing Target Tracking, AWS users can maintain optimal performance and cost-efficiency through automated scaling based on pre-defined metrics, such as CPU utilization. This ensures that applications have sufficient resources to handle traffic while minimizing costs during lower demand periods.

The introduction of Target Tracking simplifies the scaling process, allowing businesses to focus on application performance without the complexity of manual scaling configurations. This feature is ideal for applications with dynamic workloads, as it dynamically adjusts the number of EC2 instances to meet demand, enhancing responsiveness and reliability.

Hosting Containers at the Edge with Amazon ECS and AWS Outposts

In the modern digital landscape, businesses seek to process data closer to the source, leveraging the edge of the network. Amazon ECS with AWS Outposts enables users to run containerized workloads on-premises, closer to data sources. This approach minimizes latency and enhances the performance of applications requiring real-time data processing, such as IoT or analytics.

By utilizing ECS and AWS Outposts, organizations can achieve seamless integration with AWS services while maintaining low-latency communication with local resources. This hybrid cloud solution offers the flexibility of cloud computing, coupled with the proximity benefits of edge computing.

Introducing Provisioned Mode for Kafka Event Source Mappings with AWS Lambda

AWS has announced the general availability of Provisioned Mode for AWS Lambda Event Source Mappings, specifically for Apache Kafka event sources like Amazon MSK and self-managed Kafka. This mode allows users to define a fixed number of processing units, offering predictable performance and cost management as Lambda functions process Kafka streams.

Provisioned Mode is particularly beneficial for workloads requiring steady processing capacity or when predictability is essential. It complements AWS Lambda’s existing on-demand capabilities, providing users with flexibility in managing event-driven applications.

Implementing Transactions Using JMS2.0 in Amazon MQ for ActiveMQ

The transactional capabilities of the ActiveMQ broker in Amazon MQ can be effectively utilized using the Java Messaging System (JMS) 2.0 API. This API offers a simplified approach to managing transactions, ensuring message integrity and consistency across distributed systems.

Implementing transactions with JMS2.0 helps businesses maintain reliable messaging patterns, crucial for applications requiring high data consistency and reliability. This post provides insights into leveraging Amazon MQ’s transactional features for robust messaging solutions.

Automating Event Validation with Amazon EventBridge Schema Discovery

Event-driven architectures often face challenges in event validation due to diverse domains and varying event formats. Amazon EventBridge Schema Discovery provides an automated solution to manage these challenges by detecting, storing, and validating event schemas.

This approach allows businesses to maintain governance over their events while accelerating the development of event-driven applications. With automated schema management, organizations can ensure that their event-driven systems evolve smoothly without compromising on validation accuracy.

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AWS Storage Blog

Manage Costs for Replicated Delete Markers in a Disaster Recovery Setup on Amazon S3

Businesses are increasingly aware of the necessity to protect vital data from disasters such as fires, floods, or ransomware attacks. Creating an effective disaster recovery (DR) strategy involves a thorough evaluation of cost-effective solutions that also meet compliance requirements. Amazon S3 offers a range of features that aid in this process, including S3 object tags, S3 Versioning, and S3 Lifecycle. These tools allow organizations to manage costs associated with replicated delete markers efficiently.

Using S3 object tagging, businesses can categorize and manage data for lifecycle policies. S3 Versioning ensures data is protected by keeping multiple versions of an object. S3 Lifecycle policies can be configured to automate the deletion of outdated or unnecessary data, thus reducing storage costs. Together, these features provide a robust framework for maintaining an economical DR setup without compromising on data protection and compliance.

Migrating Data Access and Azure Active Directory with Amazon FSx for NetApp ONTAP

In the current digital landscape, enterprises encounter numerous challenges with data center modernization as part of their digital transformation journey. Traditional on-premises solutions often come with high costs, complex management, and an inability to handle data growth efficiently. Organizations with complex file-sharing systems and user permissions struggle to maintain user experiences and security.

Amazon FSx for NetApp ONTAP offers a solution by streamlining the integration of enterprise IDCs, especially those using Azure Active Directory, with cloud environments. This integration helps preserve user experience while enhancing data management and security. Leveraging the capabilities of FSx for NetApp ONTAP, organizations can modernize their data centers, reduce costs, and scale efficiently to meet growing data demands.

How KeyCore Can Assist

KeyCore, as Denmark’s leading AWS consultancy, offers expertise in implementing AWS storage solutions tailored to specific business needs. Our professional services can guide businesses in optimizing their disaster recovery strategies using Amazon S3 features, ensuring cost-effectiveness and regulatory compliance. Moreover, KeyCore’s managed services assist enterprises in seamlessly migrating and integrating their data access systems with Amazon FSx for NetApp ONTAP, enhancing modernization efforts while maintaining security and user experience. For more information on how KeyCore can support your organization’s AWS journey, visit KeyCore.dk.

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AWS Partner Network (APN) Blog

AI-led Application Modernization with Infosys LEAP

Modern businesses are increasingly recognizing that digital transformation is not just an option, but a critical necessity for competitive advantage. The process of regular modernization of technology stacks, driven by this digital imperative, becomes crucial for staying ahead in the market. Infosys has introduced its Live Enterprise Application Development Platform (LEAP) to address this need. Through AI-driven approaches, LEAP facilitates the modernization of applications by transforming legacy systems into more agile and scalable solutions. This not only enhances operational efficiency but also supports the acceleration of innovation.

By leveraging AWS services in tandem with the LEAP platform, businesses can seamlessly integrate their existing systems with cutting-edge cloud capabilities. This hybrid approach ensures that companies can maintain a competitive edge while optimizing costs and resources. Infosys, supported by AWS, enables organizations to harness the full potential of AI in their modernization journey, ensuring that their digital transformation initiatives are both robust and future-proof.

New AWS Competency, Service Delivery, Service Ready, and MSP Partners

In October 2024, AWS welcomed 216 new and renewed AWS Partners into its elite programs, underscoring the expanding ecosystem’s dedication to excellence. These programs include AWS Competency, AWS Managed Service Provider (MSP), AWS Service Delivery, and AWS Service Ready initiatives. These designations cover various workloads, solutions, and industries, helping AWS customers identify partners that can effectively meet core business objectives. This growing network of specialized partners ensures that customers can maximize the business benefits offered by AWS.

These partnerships are focused on customer success, delivering solutions that align with specific needs and objectives. By working with AWS Partners who have achieved these designations, businesses can confidently leverage AWS technologies to drive their digital strategies forward. The recognition of these partners signifies their expertise and commitment to delivering high-quality solutions and services.

Streamlining the AWS Foundational Technical Review (FTR)

AWS has streamlined the Foundational Technical Review (FTR) process to better support partners in adopting AWS technical best practices. Significant updates include extending the renewal period and waiving the FTR requirement for partners who have completed an AWS Well-Architected Framework Review. These changes aim to simplify the process, making it easier for partners to comply with AWS standards.

The FTR ensures that partners’ solutions adhere to AWS’s high standards of security, reliability, and operational excellence. By aligning their offerings with AWS best practices, partners can enhance the performance and value of their solutions. This streamlined process benefits both partners and customers, as it facilitates the delivery of robust, well-architected solutions that meet the highest AWS standards.

How KeyCore Can Help

KeyCore is uniquely positioned to assist organizations in navigating these advancements in AWS offerings. With expertise in application modernization, KeyCore leverages platforms like Infosys LEAP to transform legacy systems effectively. Furthermore, as an AWS Partner, KeyCore helps businesses connect with the right AWS Competency, Service Delivery, and MSP partners to achieve their specific objectives. The firm’s deep understanding of AWS technical reviews and frameworks enables them to guide partners through the streamlined FTR processes, ensuring compliance and excellence in solution delivery.

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AWS Cloud Operations Blog

AWS Organizations offers a centralized approach to managing AWS accounts in a multi-account environment. However, as businesses evolve, the need arises to streamline and clean up these accounts. This is especially relevant during mergers and acquisitions, cleanup efforts to minimize costs from unused resources, or when decommissioning a venture.

Understanding AWS Organizations Cleanup

Cleaning up AWS Organizations involves closing multiple AWS accounts or even an entire organization. This process is crucial for optimizing resource management and reducing unnecessary expenditures. AWS Organizations provides capabilities to simplify these processes, allowing businesses to maintain an efficient and cost-effective cloud environment.

Steps for Efficient Cleanup

To streamline cleanup strategies, businesses should adopt a structured approach. Begin by identifying unused accounts and resources that can be decommissioned. Next, leverage AWS Organizations’ features to manage account closures and resource deallocation. This includes understanding account dependencies and ensuring that all critical data and configurations are preserved or migrated appropriately.

Business Value of Streamlined Cleanup

Optimizing AWS Organizations not only reduces costs but also enhances security and compliance by removing inactive accounts that might become vulnerabilities. Furthermore, a streamlined account landscape simplifies management, allowing IT teams to focus on strategic initiatives rather than maintenance tasks.

How KeyCore Can Assist

KeyCore, as Denmark’s leading AWS consultancy, offers expert guidance in managing AWS Organizations cleanup. Our team can help design and implement efficient cleanup strategies tailored to specific business needs, ensuring a smooth transition and maximum resource optimization. Leveraging our expertise, businesses can achieve a cost-effective and well-organized AWS environment efficiently.

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AWS for Industries

Simplify Monte Carlo Simulations with AWS Serverless Services

Organizations in the financial services sector, including insurance providers, are leveraging AWS Step Functions Distributed Map and AWS Lambda to execute Monte Carlo simulations and machine learning data processing at scale. These technologies streamline complex processes critical for product development and risk analysis. AWS offers a robust, serverless infrastructure that eliminates the need for managing underlying resources, thus enabling efficient scaling and cost management. By using AWS, organizations can enhance their computational capabilities, thereby facilitating rapid innovation and more accurate risk assessments.

Boost Automotive Productivity with Generative AI

The automotive industry is increasingly adopting generative AI to enhance productivity by automating cumbersome processes. Notably, AI helps in creating request for proposal (RFP) documents, reducing errors, and saving time. Automation driven by AI not only optimizes resource allocation but also accelerates product development cycles. With AWS’s advanced AI technologies, automotive enterprises can innovate faster and streamline operations, ultimately leading to increased market competitiveness.

Generative AI for Retail: Key Trends in 2025

Retailers are poised to continue their exploration of generative AI as a transformative tool in 2025. This technology is set to enhance customer experiences by offering personalized recommendations and streamlining supply chain operations. Generative AI can help retailers predict trends, manage inventory efficiently, and deliver tailored shopping experiences. By leveraging AWS’s AI capabilities, retailers can stay ahead in a competitive market, ensuring that they meet evolving consumer expectations.

Your Telecom Cloud Journey on AWS: A Comprehensive Guide

This three-part series explores the journey for telecom companies migrating to AWS, focusing on foundational elements, technical roadmaps, and optimized cloud operations. Part 1 emphasizes establishing a solid cloud foundation, while Part 2 provides a technical roadmap tailored for telecom workloads. Finally, Part 3 discusses optimizing cloud operations to achieve telecom excellence. AWS’s cloud infrastructure supports the scalability and reliability required by telcos, offering a seamless migration path that enhances operational efficiency and service delivery.

Generative AI in Ecommerce: The AI Shopping Assistant

Amazon has harnessed generative AI to transform the ecommerce landscape with its AI Shopping Assistant. This tool simplifies decision-making by providing personalized recommendations and streamlining the customer’s purchase journey. By integrating AI capabilities, retailers can enhance user engagement and satisfaction, ultimately driving sales growth. AWS offers the necessary infrastructure to support such advanced AI applications, ensuring scalability and performance in high-demand environments.

Hyper-Personalized Telecom Billing on AWS

In the telecom sector, hyper-personalization is revolutionizing customer billing experiences. By adopting AWS’s generative AI technologies, telecom companies can offer clear and engaging billing solutions that foster customer loyalty and reduce support calls. This transformation not only improves customer satisfaction but also opens avenues for new revenue streams through personalized service offerings. AWS’s robust platform enables the deployment of these AI-driven solutions, ensuring seamless integration and scalability.

Building a Manufacturing Digital Thread with AWS

Manufacturers are embracing digital transformation through data-driven strategies using AWS’s graph and generative AI technologies. This approach enables companies to harness data throughout the product lifecycle, leading to cost reductions, improved quality, and optimized supply chains. AWS provides the tools necessary for operationalizing a digital thread, offering insights that enhance decision-making and product innovation. By leveraging these technologies, manufacturers can deliver differentiated products and maintain a competitive edge.

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

Organizations worldwide are increasingly leveraging artificial intelligence (AI) and machine learning (ML) to foster innovation and enhance efficiency. The transformative potential of AI spans across various sectors by accelerating research, enriching customer experiences, optimizing business processes, improving patient outcomes, and enhancing public services. However, as they adopt these technologies, ensuring digital sovereignty becomes crucial.

Maintaining Digital Sovereignty

Digital sovereignty refers to the ability of an organization or a nation to control its own data and technology-related decisions. As AI systems become integral to operations, maintaining this sovereignty while embracing AI is paramount. This involves establishing robust data governance frameworks, ensuring compliance with regional regulations, and implementing comprehensive security measures to protect sensitive information.

Strategies for Balancing AI Adoption and Digital Sovereignty

To achieve a balance between AI benefits and digital sovereignty, organizations can adopt several strategies. These include leveraging cloud services that offer strong governance and compliance features, ensuring transparent AI model training processes, and using advanced encryption techniques to safeguard data. Additionally, collaborating with technology partners like AWS can provide the tools and expertise necessary to navigate this complex landscape effectively.

At KeyCore, our expertise in AWS allows us to guide organizations in integrating AI technologies while maintaining control over their data. We offer comprehensive solutions that address compliance, security, and efficiency, ensuring that our clients can fully realize the potential of AI without compromising their digital sovereignty.

Federated Access to Amazon Athena Using AWS IAM Identity Center

Managing federated access to Amazon Athena through AWS IAM Identity Center streamlines authentication and authorization processes. Amazon Athena, a serverless, interactive analytics service, enables users to analyze vast amounts of data efficiently. By leveraging identity federation, organizations can centralize user management, enhancing security and simplifying access control.

Streamlining Authentication with Athena JDBC Driver

One effective method to manage federated access is through the Athena JDBC driver, which incorporates browser-based Security Assertion Markup Language (SAML) authentication. This integration allows secure and efficient user authentication, reducing administrative overhead and improving user experience.

Benefits of Centralized Access Management

Centralizing access management through AWS IAM Identity Center not only enhances security but also provides a scalable approach to managing user permissions. It ensures that only authorized users have the right level of access to sensitive datasets, thus mitigating potential security risks.

KeyCore can assist organizations in implementing federated access solutions for Amazon Athena, ensuring robust security and streamlined operations. Our team of AWS experts can guide the setup and integration process, providing tailored solutions that align with organizational needs and compliance requirements.

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Front-End Web & Mobile

Creating Real-Time Web Games with AWS AppSync Events

Developing a real-time web game involves several key components, and with AWS AppSync events, this process becomes more streamlined and efficient. The core concept revolves around creating an online version of a game where players aim to match four of their tokens in a row. This is achieved by leveraging AWS Amplify Gen 2, which facilitates a seamless connection to an AWS backend.

By utilizing AWS AppSync events, developers can implement real-time interactivity, allowing players to engage with the game and each other through integrated chat functionalities. This feature is crucial for enhancing the user experience by creating a dynamic and interactive gaming environment.

Serverless WebSockets for Pub/Sub with AWS AppSync

AWS AppSync introduces a new dimension to application development with its ability to manage and connect applications to events, data, and AI models effortlessly. The introduction of AWS AppSync events adds a powerful tool to developers’ arsenals, enabling them to create real-time experiences through serverless WebSockets.

This is achieved by publishing updates from any event source to subscribed clients, creating a seamless communication channel through a standalone Pub/Sub service. Notably, this service operates independently of GraphQL, offering developers flexibility in how they implement real-time features in their applications.

The Business Value of AWS AppSync for Real-Time Applications

For businesses, the ability to offer real-time features in applications is a significant competitive advantage. AWS AppSync’s capacity to handle these requirements simplifies the development process and reduces the time to market for new features. This is crucial in industries such as gaming, where user engagement and satisfaction are directly tied to the responsiveness and interactivity of the platform.

How KeyCore Can Help

KeyCore, as the leading AWS consultancy in Denmark, brings a wealth of expertise in leveraging AWS services like AppSync to build advanced, real-time applications. Whether through professional services or managed solutions, KeyCore can help organizations harness the full potential of AWS AppSync to create interactive and dynamic user experiences. By collaborating with KeyCore, businesses can ensure their applications are built on a robust and scalable infrastructure, tailored to their specific needs.

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AWS Contact Center

Organizations are increasingly turning to cloud-based contact center solutions to boost customer service capabilities. Among these, Amazon Connect stands out as a strategic choice for many enterprises. NatWest Group, a prominent banking and financial services institution in the UK, embarked on a journey to enhance their customer service through the implementation of a DevSecOps ecosystem for their Amazon Connect-powered contact center.

Why Amazon Connect?

Amazon Connect is a cloud-based contact center service designed to help businesses deliver superior customer service at a lower cost. Its simplicity, scalability, and rich feature set make it an ideal solution for organizations like NatWest looking to innovate their customer interaction systems. The service allows businesses to set up a contact center in minutes, which can scale to support millions of customers.

Implementing DevSecOps

NatWest recognized the need for a resilient and secure contact center infrastructure. By integrating DevSecOps practices, they ensured that their Amazon Connect environment was not only efficient but also secure and compliant with industry standards. This approach integrates development, security, and operations, enabling automated security checks and continuous compliance. The DevSecOps model is crucial in a financial institution where regulatory compliance and data security are paramount.

Business Value

The implementation of Amazon Connect with DevSecOps practices provides NatWest with several business advantages. It enhances customer experience by reducing wait times and enabling personalized service. The flexibility of Amazon Connect allows for the easy addition of new features, helping NatWest to quickly adapt to changing customer needs. Moreover, the DevSecOps approach ensures ongoing security and compliance, reducing the risks associated with data breaches and regulatory penalties.

How KeyCore Can Help

KeyCore provides expert consulting and managed services for organizations looking to implement Amazon Connect solutions. Our team of AWS-certified professionals can help design, implement, and optimize Amazon Connect environments to meet specific business requirements. By leveraging our expertise in DevSecOps, KeyCore ensures that your contact center is not only efficient but also secure and compliant with industry standards. Whether your organization is just starting with Amazon Connect or looking to enhance an existing deployment, KeyCore offers the guidance and support needed to achieve your customer service goals.

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Innovating in the Public Sector

Transforming Healthcare with Open Source EMR Systems

In regions where healthcare demands surpass available resources, open source technologies on Amazon Web Services (AWS) can revolutionize the healthcare experience for both providers and patients. The Bahmni system, an open source electronic medical records (EMR) solution, exemplifies this innovation. By providing rapid access to health records and test results, Bahmni allows doctors to have better information and more time for patient care. Initially launched in a hospital in central India, Bahmni has expanded to over 500 hospitals across 50 countries, enhancing healthcare in remote and resource-constrained areas.

Generating Insights with Amazon Bedrock for Governors for Schools

Governors for Schools, a UK-based charity, leverages Amazon Bedrock to extract valuable insights from unstructured documents. With AWS’s financial support and technical expertise from over 100 AWS employees, the charity efficiently processes documents to improve school governance. This partnership underscores the potential of AWS technologies like Amazon Bedrock in enhancing educational administration by transforming data into actionable insights.

Building Generative AI Conversational Experiences on AWS

Amazon Web Services (AWS) offers multiple options for creating chat-based assistants infused with generative artificial intelligence (AI). These capabilities are essential for developing conversational experiences that can adapt and provide dynamic interactions. This article guides through the selection process of suitable AWS tools and services for building AI-powered chat solutions, ensuring seamless integration and deployment.

INRIX and AWS: Generative AI Hackathon Collaboration

Hackathons are known for boosting productivity and fostering innovation. AWS partners with organizations like INRIX, Inc., a leader in automotive and transportation services, to host generative AI hackathons. These events utilize AWS’s cost-effective utility model, enabling rapid experimentation and innovation. This collaboration highlights how AWS supports creative problem-solving and technological advancement in various sectors.

Streamlining Naturalization Applications with Amazon Bedrock

Public sector entities face challenges in processing large volumes of document-heavy applications. Amazon Bedrock addresses these issues by streamlining processes such as naturalization applications. By automating and enhancing data handling, it reduces backlogs, shortens processing times, and lowers costs, demonstrating its value in improving public sector efficiency.

Establishing a Cloud Center of Excellence for Digital Transformation

A Cloud Center of Excellence (CCoE) can significantly mitigate the risks associated with digital transformation, which often fail due to time delays, cost overruns, and incomplete functionality. Utilizing the AWS Cloud Adoption Framework (AWS CAF), a CCoE provides structured guidance and expertise to navigate digital transformation successfully, ensuring alignment with enterprise objectives.

Penn State’s Campus Resource App Development with AWS

In collaboration with Modo Labs, Penn State developed “Penn State Go,” a mobile app platform, using AWS technologies. This app serves as an all-in-one resource for students, providing easy access to campus services. The partnership exemplifies how AWS and no-code platforms can create personalized digital experiences, aligning with the needs of digital-native users in educational institutions.

Stop Soldier Suicide’s Mission with AWS and Pariveda

Stop Soldier Suicide (SSS) collaborates with AWS and Pariveda to tackle the alarming rate of suicides among US service members and veterans. The Black Box Project employs AWS Professional Services to analyze data from devices of those lost to suicide, aiming to uncover warning signs and improve postvention, intervention, and prevention strategies. This initiative highlights AWS’s role in facilitating impactful social projects.

Responsible AI Use in Government Procurement

Integrating artificial intelligence (AI) into government procurement presents both opportunities and challenges. This article explores how procurement professionals can balance innovation with regulatory compliance, emphasizing the responsible use of AI. AWS technologies support this balance by providing tools that ensure ethical and efficient AI integration into public sector operations.

How KeyCore Can Help

KeyCore, as Denmark’s leading AWS consultancy, can offer expert guidance and implementation support in these innovative public sector projects. With extensive knowledge in AWS services and solutions, KeyCore helps organizations leverage technologies like Bahmni, Amazon Bedrock, and generative AI to achieve transformational outcomes. Whether it’s enhancing healthcare systems, streamlining bureaucratic processes, or supporting digital transformation, KeyCore provides tailored solutions to meet specific needs and drive success.

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The Internet of Things on AWS – Official Blog

Unlocking the Power of Edge Intelligence with AWS

In the modern, data-driven economy, the ability to make rapid, informed decisions is critical for businesses striving to enhance customer experiences and improve operational efficiency. Traditional cloud-based data processing often fails to meet the demands of real-time decision-making, especially in environments like manufacturing plants where immediate insights are needed. For instance, sensor data could detect potential machine failures, but if the analysis is too slow, it might not prevent disruptions.

Edge Intelligence

AWS Edge services empower businesses by processing data closer to the source, significantly reducing latency. This approach allows for quick, local data analysis and immediate decision-making, enabling enterprises to act swiftly and efficiently in real-time scenarios. By leveraging AWS IoT Greengrass and AWS Lambda, companies can run ML models and execute actions directly at the edge, ensuring that processes are optimized and potential issues are addressed promptly.

Such edge intelligence solutions enhance operational efficiency and can lead to substantial cost savings. They also provide a foundation for innovative applications, such as real-time predictive maintenance, which can further streamline operations and reduce downtime.

AWS IoT Services Alignment with US Cyber Trust Mark

The rapid growth of IoT devices underscores the necessity for robust cybersecurity frameworks to protect data and maintain service reliability. The US Cyber Trust Mark is an initiative addressing these cybersecurity challenges, promoting sustained growth and secure IoT environments.

Cybersecurity with AWS

AWS IoT services align with the US Cyber Trust Mark to ensure secure IoT deployments. By adopting AWS security best practices, companies can safeguard their data and infrastructure against potential threats. This includes implementing encryption, access controls, and continuous monitoring to detect and mitigate risks proactively.

With AWS IoT Core, businesses can manage device connections securely and efficiently, ensuring data is protected throughout its lifecycle. This alignment not only enhances security but also builds consumer trust in IoT products, fostering broader market adoption and innovation.

How KeyCore Can Help

KeyCore, as an expert in AWS consulting, can aid businesses in harnessing the power of AWS Edge Intelligence and IoT services. By providing tailored solutions that address specific operational needs, KeyCore ensures that companies can achieve real-time decision-making capabilities and robust cybersecurity postures. Whether it’s deploying edge computing solutions or aligning with cybersecurity standards, KeyCore’s expertise ensures seamless integration and maximum business value.

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