This document discusses the pressures organizations face to deliver more with less, faster and with greater security and compliance. It states that a cloud strategy can address these pressures by managing risks, optimizing costs and enabling workload-optimized deployments. The document advocates for a sound cloud migration strategy and notes the journey to the cloud is inevitable.
Your Agile, Modern Data Delivery Platformsyed_javed
Lyftron eliminates traditional ETL/ELT bottlenecks with automatic data pipeline and make data instantly accessible to BI user with the modern cloud compute of Spark & Snowflake.
Lyftron connectors automatically convert any source into normalized, ready-to-query relational format and provide search capability on your enterprise data catalog.
by Gavin Adams, IoT Specialist Solutions Architect AWS and Anton Shmagin, Partner Solutions Architect AWS
Join us for AWS IoT day at the AWS San Francisco Loft. AWS IoT enables you to easily connect and manage millions of devices securely. You can gather data from, run sophisticated analytics on, and take actions in real-time on your diverse fleet of IoT devices from edge to the cloud. You will build IoT applications with AWS IoT experts. AWS IoT provides edge-based software and cloud-based services so you can easily build IoT applications. Edge-based software, including AWS Greengrass, enables you to securely connect devices, gather data and take intelligent actions locally even when Internet connectivity is down. Cloud-based services, including AWS IoT Core, allow you to quickly onboard large and diverse fleets, maintain fleet health, and keep fleets secure.
The IoT is here to stay. As with any other trend in the history of computer software, it’s starting to produce a new generation of cloud platforms. This tech talk will identify and explain what to look for when evaluating an IoT cloud platform to ensure a successful deployment of IoT strategies.
Raleigh DevDay 2017: AWS Greengrass Technical Deep Dive with DemoAmazon Web Services
AWS Greengrass extends AWS onto devices so they can act locally on generated data while taking advantage of the cloud. It allows devices to respond quickly to local events, operate offline, and reduce IoT application costs. Key concepts include Greengrass cores that run Lambda functions locally, device SDKs, and groups that allow devices to communicate locally and with the cloud. Technical features include local Lambda functions, device shadows to represent state, messaging between devices, and AWS-level security.
Azure Arc is a set of technologies that extends Azure management and services to infrastructure located on-premises, in multiple clouds, and at the edge. It allows users to organize and govern assets, deploy and manage Kubernetes applications at scale across environments, and deploy and manage data services anywhere while maintaining centralized security and governance from Azure. Key benefits include a unified view of assets, configuration and deployment using infrastructure as code, automated updates and patching, elastic scaling on-premises, and consistent security across locations.
An Evolving Security Landscape – Security Patterns in the CloudAmazon Web Services
Availability of cloud computing is helping Financial Services organizations realize accelerated go-to-market speeds, global scalability, and cost efficiencies. This new world forces considerations for security programs – what is different in the cloud and what do I do differently? AWS Security Architects will share protocols that need to be considered in the cloud, on premises, or in a hybrid model. They will also share best practices, lessons learned, efficiencies, and design patterns and architectures unique to cloud.
1) The document introduces AWS IoT and discusses how it addresses challenges of connecting devices to cloud applications at scale through features like MQTT/HTTP protocols, SDKs for different devices, scalability, security, and integration with other AWS services.
2) It provides an overview of the key components of AWS IoT like the message broker, rules engine, device shadows, and registry. It also discusses pricing and security features.
3) The presentation concludes with a demo of building a simple IoT application with AWS IoT to read and write data and integrate with other AWS services like S3, Cognito, and CloudFront. Next steps are provided to encourage exploring AWS IoT further.
Much is discussed about how IoT is transforming our lives, this session will focus on the business and strategic value from leveraging IoT and provide starting points in the AWS Cloud to accelerate your time to value.
Speaker: Craig Lawton, Public Sector Solutions Architect, Amazon Web Services
Your Agile, Modern Data Delivery Platformsyed_javed
Lyftron eliminates traditional ETL/ELT bottlenecks with automatic data pipeline and make data instantly accessible to BI user with the modern cloud compute of Spark & Snowflake.
Lyftron connectors automatically convert any source into normalized, ready-to-query relational format and provide search capability on your enterprise data catalog.
by Gavin Adams, IoT Specialist Solutions Architect AWS and Anton Shmagin, Partner Solutions Architect AWS
Join us for AWS IoT day at the AWS San Francisco Loft. AWS IoT enables you to easily connect and manage millions of devices securely. You can gather data from, run sophisticated analytics on, and take actions in real-time on your diverse fleet of IoT devices from edge to the cloud. You will build IoT applications with AWS IoT experts. AWS IoT provides edge-based software and cloud-based services so you can easily build IoT applications. Edge-based software, including AWS Greengrass, enables you to securely connect devices, gather data and take intelligent actions locally even when Internet connectivity is down. Cloud-based services, including AWS IoT Core, allow you to quickly onboard large and diverse fleets, maintain fleet health, and keep fleets secure.
The IoT is here to stay. As with any other trend in the history of computer software, it’s starting to produce a new generation of cloud platforms. This tech talk will identify and explain what to look for when evaluating an IoT cloud platform to ensure a successful deployment of IoT strategies.
Raleigh DevDay 2017: AWS Greengrass Technical Deep Dive with DemoAmazon Web Services
AWS Greengrass extends AWS onto devices so they can act locally on generated data while taking advantage of the cloud. It allows devices to respond quickly to local events, operate offline, and reduce IoT application costs. Key concepts include Greengrass cores that run Lambda functions locally, device SDKs, and groups that allow devices to communicate locally and with the cloud. Technical features include local Lambda functions, device shadows to represent state, messaging between devices, and AWS-level security.
Azure Arc is a set of technologies that extends Azure management and services to infrastructure located on-premises, in multiple clouds, and at the edge. It allows users to organize and govern assets, deploy and manage Kubernetes applications at scale across environments, and deploy and manage data services anywhere while maintaining centralized security and governance from Azure. Key benefits include a unified view of assets, configuration and deployment using infrastructure as code, automated updates and patching, elastic scaling on-premises, and consistent security across locations.
An Evolving Security Landscape – Security Patterns in the CloudAmazon Web Services
Availability of cloud computing is helping Financial Services organizations realize accelerated go-to-market speeds, global scalability, and cost efficiencies. This new world forces considerations for security programs – what is different in the cloud and what do I do differently? AWS Security Architects will share protocols that need to be considered in the cloud, on premises, or in a hybrid model. They will also share best practices, lessons learned, efficiencies, and design patterns and architectures unique to cloud.
1) The document introduces AWS IoT and discusses how it addresses challenges of connecting devices to cloud applications at scale through features like MQTT/HTTP protocols, SDKs for different devices, scalability, security, and integration with other AWS services.
2) It provides an overview of the key components of AWS IoT like the message broker, rules engine, device shadows, and registry. It also discusses pricing and security features.
3) The presentation concludes with a demo of building a simple IoT application with AWS IoT to read and write data and integrate with other AWS services like S3, Cognito, and CloudFront. Next steps are provided to encourage exploring AWS IoT further.
Much is discussed about how IoT is transforming our lives, this session will focus on the business and strategic value from leveraging IoT and provide starting points in the AWS Cloud to accelerate your time to value.
Speaker: Craig Lawton, Public Sector Solutions Architect, Amazon Web Services
The document summarizes a talk on cloud security featuring three speakers. Nikola Bozinovic of Frame discussed how their company provides a secure cloud platform for delivering virtual applications and desktops from the cloud. Matt Keil of Palo Alto Networks emphasized the importance of visibility, segmentation, and policy consistency for cloud security. Michael Schmidt of Nutonian described how their AI techniques can discover patterns in large security data sets that may indicate threats.
My presentation to the Cloud Foundry Foundation IoT SIG on Eclipse IoT, with particular focus on the Eclipse IoT cloud server platform.
Thanks to Benjamin Cabe (@kartben) for the materials.
- 2nd Watch is a cloud consulting company that helps enterprises migrate to and manage workloads in the public cloud.
- Common cloud use cases discussed include steady state applications, dynamic applications, batch computing, application development, and cloud native applications.
- A customer use case example is described where 2nd Watch helped a financial services company migrate a line of business application to AWS while ensuring SOC2 compliance for security and privacy of sensitive customer data.
AWS Greengrass extends AWS capabilities to edge devices, allowing them to act locally on generated data using local Lambda functions and message brokers while still connecting to the cloud. It enables devices to respond quickly to local events without relying on cloud connectivity, reducing costs for IoT applications through local processing and AWS-level security. The document provides an overview of AWS Greengrass and its benefits for industries including mining, manufacturing, and more. It demonstrates how Greengrass can process data at the edge through an example deployment at a mining site.
This document introduces Windows Azure by first explaining what cloud computing is and the benefits it provides such as no need to buy and maintain your own hardware and paying only for what you use. It then describes what Windows Azure is, including its operating system for the cloud and main components like storage, compute, and content delivery. Finally it outlines some common usage scenarios for Windows Azure and provides recommendations on how to get started with it through tools, tutorials, and documentation.
OpenGrid is an open source project that allows users to explore and query public open data from various sources through a single interface. It was originally created in Chicago to provide situational awareness across multiple city departments. WindyGrid, used by Chicago's emergency center, is now built on the OpenGrid codebase while using additional private data. OpenGrid is deployed on Amazon Web Services and is available on their marketplace so other cities and organizations can easily deploy it alongside tools like Plenario that aggregate open data from various portals.
NetApp's Data Fabric provides a unified software-defined architecture that allows for consistent data management across cloud services. It enables flexibility to readily move data between hyperscale clouds like AWS and Azure or private clouds. The Data Fabric establishes a single control plane to monitor and control data flow throughout hybrid cloud environments, maintaining governance and control of data regardless of its location.
In this session, we review how the combined use of Amazon Web Services native tools, advanced modeling, and machine learning techniques can simplify many of the hardest security problems that are within the customer’s responsibility. Join us as we explore how services like Amazon Virtual Private Cloud flow logs, AWS CloudTrail, and Amazon Inspector combine to enable highly automated, scalable, and comprehensive security for your AWS applications. Learn how to effectively harness the data provided by AWS for security, and understand how Cisco Stealthwatch Cloud and AWS create an integrated, effective security solution.
Cloud computing involves sharing configurable computing resources like servers, storage, databases and software that are delivered as an Internet service in a pay-as-you-go model. It provides on-demand access to a shared pool of configurable computing resources like networks, servers, storage, applications and services. Cloud services can be broadly divided into infrastructure as a service, platform as a service and software as a service. Cloud computing offers advantages like lower costs, improved performance, universal access and increased collaboration. However, it also faces challenges like dependence on internet connectivity and potential security and data loss issues.
Autodesk is strengthening its operations with Splunk and AWS by using CloudTrail to log API calls across its AWS accounts and sending the logs to Splunk. This provides Autodesk with a single view of activity across all accounts for security monitoring, compliance auditing, and troubleshooting. Specifically, Autodesk can search logs to investigate incidents, identify compromised hosts, and monitor sign-in locations for security. For compliance, Autodesk can set alerts on sensitive API calls and user creations. Using CloudTrail and Splunk provides Autodesk with a scalable, cost-effective logging solution.
Edge computing pushes applications and data processing closer to data sources like IoT devices to enable low latency and real-time insights. Docker containers are well-suited for edge computing due to their small size, fast deployment, and ability to run on resource-constrained edge devices. A demo showed containers for a learning management system deployed in seconds at an edge location versus minutes for virtual machines. Offloading an ETL application to edge resources also significantly reduced bandwidth usage versus processing in the cloud. Docker provides a lightweight container-based platform to efficiently deliver and manage applications at the edge.
FlexPod is a converged infrastructure solution from NetApp and Cisco that can be deployed and ready for use within 60 minutes (sentence 1). It provides a single management layer for compute, networking and storage to simplify administration and free up IT staff from manual tasks (sentence 2). FlexPod allows independent scalability of compute and storage resources to meet the needs of different workloads (sentence 3).
Securing APIs for ultimate security and privacy with Azure | Codit WebinarCodit
These days, data is the new gold and with businesses being hacked for their data, security is a prime concern. It’s imperative that you protect your business-critical data, such as personal data, financial data or business information, so it doesn’t fall into the wrong hands.
In this Azure focused session, MVP Toon Vanhoutte, will teach you every concept about securing APIs end-to-end – so not just the front door but also the processing behind it, including how to secure your data to be in compliance with GDPR.
Connecting the Unconnected using AWS IoT - AWS Summit Tel Aviv 2017Amazon Web Services
This document discusses connecting devices to AWS IoT services at scale. It covers:
1) Connecting taxis to AWS IoT to send telemetry data and use thing shadows to synchronize device states between the cloud and devices.
2) Architecting IoT solutions for scale using the three pillars of IoT - things, cloud computing, and intelligence - and AWS IoT services.
3) Introducing AWS Greengrass to extend AWS capabilities to edge devices so they can act locally on data and connect to the cloud.
AWS Greengrass is a new software platform for running local compute, data caching and messaging on connected devices. With AWS Greengrass, connected devices can run AWS Lambda functions, keep device data in sync, and communicate with other devices securely – even when not connected to the Internet. Using AWS Lambda, Greengrass ensures your IoT devices can respond quickly to local events, operate with intermittent connections, and minimize the cost of transmitting IoT data to the cloud.
Computing DevOps Summit, London, July 5, 2016Splunk
Splunk's Matt Davies and Vertu's Rob Charlton Presentation at Computing's DevOps Summit in London.
Digital Transformation: The role of machine data in DevOps: increase velocity, improve quality and drive impact
Find out how UK luxury mobile device manufacturer Vertu use machine data for smarter DevOps
Hear how to improve software quality by measuring the metricas that matter
Understand how effective DevOps help Vertu improve their customers’ experience
NetApp is the leading commercial storage vendor for OpenStack and offers the broadest portfolio including FAS, AFF, EF, SolidFire, StorageGRID Webscale and AltaVault. NetApp supports Cinder block storage through FAS, SolidFire and E-Series platforms which provide the right balance of data services, performance and scale. The NetApp Docker Volume Plugin exposes FAS, SolidFire and E-Series storage to container orchestration systems like Mesosphere, Docker, Kubernetes and OpenStack. NetApp is fully integrated with OpenStack APIs and most automation engines, and is committed to continued OpenStack investment as a top contributor to common code bases.
Derive Insight from IoT data in minute with AWSAdrian Hornsby
The document discusses how AWS IoT allows users to connect devices, collect and process IoT data at scale, and take actions. It provides an overview of AWS IoT's key features like connecting and managing devices, processing and acting on data, creating device shadows, and using rules and actions. Examples are given of customers like John Deere, Philips, and BMW using AWS IoT to gather data from devices and leverage AWS services to derive insights and make improvements. A demo of using AWS IoT and other services like Kinesis and S3 to collect and analyze data is also highlighted.
Cloud computing has won and most companies are using more than one public and private clouds. This has created challenges and complexity which are addressed by new technology such as Istio service mesh.
AWS Greengrass extends AWS cloud services to edge devices by allowing local execution of Lambda functions, usage of device shadows to sync state, and local messaging. It addresses the challenges of processing data locally for latency, offline operation, and reducing costs. Greengrass consists of a core component that runs on edge devices and an IoT device SDK. This allows edge devices to act locally while still using cloud services like authentication and rules engines.
Enabling Innovative Business Opportunities Through Secure Cloud Adoption - Se...Amazon Web Services
Innovation is at the heart of the collaboration between Intel, Intel Security and AWS. As cloud adoption is fueling the next industrial revolution, this session will explore the new opportunities offered to you through cloud adoption. You will hear from Intel about the latest technologies that will help accelerate the adoption in the cloud in big data, HPC and IoT. As critical business workloads are rapidly deployed, Security needs to be a core component of this cloud adoption, not an afterthought. It should not prevent you from realizing the benefits of moving to cloud infrastructure. In this session Intel Security will also explore core security capabilities to enable automated visibility, security control and compliance in your AWS cloud environment.
Speaker: Andrew Hurren, Senior Regional Solution Architect, Intel Security, ANZ & Peter Kerney, Enterprise Solutions Architect, Intel
The document summarizes a talk on cloud security featuring three speakers. Nikola Bozinovic of Frame discussed how their company provides a secure cloud platform for delivering virtual applications and desktops from the cloud. Matt Keil of Palo Alto Networks emphasized the importance of visibility, segmentation, and policy consistency for cloud security. Michael Schmidt of Nutonian described how their AI techniques can discover patterns in large security data sets that may indicate threats.
My presentation to the Cloud Foundry Foundation IoT SIG on Eclipse IoT, with particular focus on the Eclipse IoT cloud server platform.
Thanks to Benjamin Cabe (@kartben) for the materials.
- 2nd Watch is a cloud consulting company that helps enterprises migrate to and manage workloads in the public cloud.
- Common cloud use cases discussed include steady state applications, dynamic applications, batch computing, application development, and cloud native applications.
- A customer use case example is described where 2nd Watch helped a financial services company migrate a line of business application to AWS while ensuring SOC2 compliance for security and privacy of sensitive customer data.
AWS Greengrass extends AWS capabilities to edge devices, allowing them to act locally on generated data using local Lambda functions and message brokers while still connecting to the cloud. It enables devices to respond quickly to local events without relying on cloud connectivity, reducing costs for IoT applications through local processing and AWS-level security. The document provides an overview of AWS Greengrass and its benefits for industries including mining, manufacturing, and more. It demonstrates how Greengrass can process data at the edge through an example deployment at a mining site.
This document introduces Windows Azure by first explaining what cloud computing is and the benefits it provides such as no need to buy and maintain your own hardware and paying only for what you use. It then describes what Windows Azure is, including its operating system for the cloud and main components like storage, compute, and content delivery. Finally it outlines some common usage scenarios for Windows Azure and provides recommendations on how to get started with it through tools, tutorials, and documentation.
OpenGrid is an open source project that allows users to explore and query public open data from various sources through a single interface. It was originally created in Chicago to provide situational awareness across multiple city departments. WindyGrid, used by Chicago's emergency center, is now built on the OpenGrid codebase while using additional private data. OpenGrid is deployed on Amazon Web Services and is available on their marketplace so other cities and organizations can easily deploy it alongside tools like Plenario that aggregate open data from various portals.
NetApp's Data Fabric provides a unified software-defined architecture that allows for consistent data management across cloud services. It enables flexibility to readily move data between hyperscale clouds like AWS and Azure or private clouds. The Data Fabric establishes a single control plane to monitor and control data flow throughout hybrid cloud environments, maintaining governance and control of data regardless of its location.
In this session, we review how the combined use of Amazon Web Services native tools, advanced modeling, and machine learning techniques can simplify many of the hardest security problems that are within the customer’s responsibility. Join us as we explore how services like Amazon Virtual Private Cloud flow logs, AWS CloudTrail, and Amazon Inspector combine to enable highly automated, scalable, and comprehensive security for your AWS applications. Learn how to effectively harness the data provided by AWS for security, and understand how Cisco Stealthwatch Cloud and AWS create an integrated, effective security solution.
Cloud computing involves sharing configurable computing resources like servers, storage, databases and software that are delivered as an Internet service in a pay-as-you-go model. It provides on-demand access to a shared pool of configurable computing resources like networks, servers, storage, applications and services. Cloud services can be broadly divided into infrastructure as a service, platform as a service and software as a service. Cloud computing offers advantages like lower costs, improved performance, universal access and increased collaboration. However, it also faces challenges like dependence on internet connectivity and potential security and data loss issues.
Autodesk is strengthening its operations with Splunk and AWS by using CloudTrail to log API calls across its AWS accounts and sending the logs to Splunk. This provides Autodesk with a single view of activity across all accounts for security monitoring, compliance auditing, and troubleshooting. Specifically, Autodesk can search logs to investigate incidents, identify compromised hosts, and monitor sign-in locations for security. For compliance, Autodesk can set alerts on sensitive API calls and user creations. Using CloudTrail and Splunk provides Autodesk with a scalable, cost-effective logging solution.
Edge computing pushes applications and data processing closer to data sources like IoT devices to enable low latency and real-time insights. Docker containers are well-suited for edge computing due to their small size, fast deployment, and ability to run on resource-constrained edge devices. A demo showed containers for a learning management system deployed in seconds at an edge location versus minutes for virtual machines. Offloading an ETL application to edge resources also significantly reduced bandwidth usage versus processing in the cloud. Docker provides a lightweight container-based platform to efficiently deliver and manage applications at the edge.
FlexPod is a converged infrastructure solution from NetApp and Cisco that can be deployed and ready for use within 60 minutes (sentence 1). It provides a single management layer for compute, networking and storage to simplify administration and free up IT staff from manual tasks (sentence 2). FlexPod allows independent scalability of compute and storage resources to meet the needs of different workloads (sentence 3).
Securing APIs for ultimate security and privacy with Azure | Codit WebinarCodit
These days, data is the new gold and with businesses being hacked for their data, security is a prime concern. It’s imperative that you protect your business-critical data, such as personal data, financial data or business information, so it doesn’t fall into the wrong hands.
In this Azure focused session, MVP Toon Vanhoutte, will teach you every concept about securing APIs end-to-end – so not just the front door but also the processing behind it, including how to secure your data to be in compliance with GDPR.
Connecting the Unconnected using AWS IoT - AWS Summit Tel Aviv 2017Amazon Web Services
This document discusses connecting devices to AWS IoT services at scale. It covers:
1) Connecting taxis to AWS IoT to send telemetry data and use thing shadows to synchronize device states between the cloud and devices.
2) Architecting IoT solutions for scale using the three pillars of IoT - things, cloud computing, and intelligence - and AWS IoT services.
3) Introducing AWS Greengrass to extend AWS capabilities to edge devices so they can act locally on data and connect to the cloud.
AWS Greengrass is a new software platform for running local compute, data caching and messaging on connected devices. With AWS Greengrass, connected devices can run AWS Lambda functions, keep device data in sync, and communicate with other devices securely – even when not connected to the Internet. Using AWS Lambda, Greengrass ensures your IoT devices can respond quickly to local events, operate with intermittent connections, and minimize the cost of transmitting IoT data to the cloud.
Computing DevOps Summit, London, July 5, 2016Splunk
Splunk's Matt Davies and Vertu's Rob Charlton Presentation at Computing's DevOps Summit in London.
Digital Transformation: The role of machine data in DevOps: increase velocity, improve quality and drive impact
Find out how UK luxury mobile device manufacturer Vertu use machine data for smarter DevOps
Hear how to improve software quality by measuring the metricas that matter
Understand how effective DevOps help Vertu improve their customers’ experience
NetApp is the leading commercial storage vendor for OpenStack and offers the broadest portfolio including FAS, AFF, EF, SolidFire, StorageGRID Webscale and AltaVault. NetApp supports Cinder block storage through FAS, SolidFire and E-Series platforms which provide the right balance of data services, performance and scale. The NetApp Docker Volume Plugin exposes FAS, SolidFire and E-Series storage to container orchestration systems like Mesosphere, Docker, Kubernetes and OpenStack. NetApp is fully integrated with OpenStack APIs and most automation engines, and is committed to continued OpenStack investment as a top contributor to common code bases.
Derive Insight from IoT data in minute with AWSAdrian Hornsby
The document discusses how AWS IoT allows users to connect devices, collect and process IoT data at scale, and take actions. It provides an overview of AWS IoT's key features like connecting and managing devices, processing and acting on data, creating device shadows, and using rules and actions. Examples are given of customers like John Deere, Philips, and BMW using AWS IoT to gather data from devices and leverage AWS services to derive insights and make improvements. A demo of using AWS IoT and other services like Kinesis and S3 to collect and analyze data is also highlighted.
Cloud computing has won and most companies are using more than one public and private clouds. This has created challenges and complexity which are addressed by new technology such as Istio service mesh.
AWS Greengrass extends AWS cloud services to edge devices by allowing local execution of Lambda functions, usage of device shadows to sync state, and local messaging. It addresses the challenges of processing data locally for latency, offline operation, and reducing costs. Greengrass consists of a core component that runs on edge devices and an IoT device SDK. This allows edge devices to act locally while still using cloud services like authentication and rules engines.
Enabling Innovative Business Opportunities Through Secure Cloud Adoption - Se...Amazon Web Services
Innovation is at the heart of the collaboration between Intel, Intel Security and AWS. As cloud adoption is fueling the next industrial revolution, this session will explore the new opportunities offered to you through cloud adoption. You will hear from Intel about the latest technologies that will help accelerate the adoption in the cloud in big data, HPC and IoT. As critical business workloads are rapidly deployed, Security needs to be a core component of this cloud adoption, not an afterthought. It should not prevent you from realizing the benefits of moving to cloud infrastructure. In this session Intel Security will also explore core security capabilities to enable automated visibility, security control and compliance in your AWS cloud environment.
Speaker: Andrew Hurren, Senior Regional Solution Architect, Intel Security, ANZ & Peter Kerney, Enterprise Solutions Architect, Intel
This document discusses the role of cloud and analytics in IoT. It begins by explaining how IoT connects billions of devices via networks to deliver connected industry solutions. The key value is the data these devices collect. The document then covers several topics:
- IoT technology enablers like cloud computing, protocols, sensors, and gateways
- How sensor data is collected, processed at the edge and in the cloud, analyzed, and used in applications
- Popular IoT and cloud platforms that provide services for device management, data ingestion, storage, processing and analytics
- Security considerations and methods for IoT like authentication, authorization and encryption
- Programming tools and frameworks for developing applications and connecting
DataPalooza at the San Francisco Loft: In this workshop you will use AWS and Intel technologies to learn how to build, deploy, and run ML inference on the cloud as well as on the IoT Edge. You will learn to use Amazon SageMaker with Intel C5 Instances, AWS DeepLens, AWS Greengrass, Amazon Rekognition, and AWS Lambda to build an end-to-end IoT solution that performs machine learning.
Understand the core concepts of “Cloud Computing” and how businesses around the world are running the infrastructure that supports their websites to lower costs, improve time-to-market, and enable rapid scalability matching resource to demands of users. Whether you are an enterprise looking for IT innovation, agility and resiliency or small and medium business who wants to accelerate growth without a big upfront investment in cash or time for technology, the AWS Cloud provides a complete set of services at zero upfront costs which are available with a few clicks and within minutes.
This document provides an overview and introduction to Amazon Web Services (AWS). It discusses AWS's global infrastructure including regions and availability zones. It also describes various AWS computing, storage, database, deployment/administration and application services like EC2, S3, RDS, Elastic Beanstalk, and CloudFront. The document emphasizes AWS's scalability, elasticity, pay-as-you-go model and how customers can build fault tolerant and dynamic applications on AWS.
Why integration is key in IoT solutions? (Sam Vanhoutte @Integrate2017)Codit
While working on several Internet of Things projects with different customers in Europe, it became clear that Integration matters more than ever. Building an overall IoT solution requires many different technologies and skills. The Architect role is crucial to combining different services into one solid solution. Integration skills are extremely important in building robust and scalable IoT solutions. Every phase of the IoT value chain requires integration, since IoT solutions are distributed and decoupled by nature. Retro-fitting existing devices? Routing of telemetry data? Or even exposing analytics results through secured APIs? All these challenges require integration skills. Skills that are very familiar to specialists in the Integration business. This presentation will explain why these are great times to be an Integration expert and how we can help tackling current challenges.
Join us for a series of introductory and technical sessions on AWS Big Data solutions. Gain a thorough understanding of what Amazon Web Services offers across the big data lifecycle and learn architectural best practices for applying those solutions to your projects.
We will kick off this technical seminar in the morning with an introduction to the AWS Big Data platform, including a discussion of popular use cases and reference architectures. In the afternoon, we will deep dive into Machine Learning and Streaming Analytics. We will then walk everyone through building your first Big Data application with AWS.
As the CTO of a new startup, you have taken up a challenge of improving the EDM music festival experience. At venues with multiple stages, festival-goers are always looking to identify DJ stage areas with the liveliest atmosphere. This causes them to constantly move around between different stages and miss out on having fun.
In this workshop you will use AWS and Intel technologies to learn how to build, deploy, and run ML inference on the cloud as well as on the IoT Edge. You will learn to use Amazon SageMaker with Intel C5 Instances, AWS DeepLens, AWS Greengrass, Amazon Rekognition, and AWS Lambda to build an end-to-end IoT solution that performs machine learning.
Modernizing upstream workflows with aws storage - john malloryAmazon Web Services
Modernizing Upstream Workflows with AWS Storage
Accelerating seismic data retrieval, getting better data protection and reliability, and providing a common AWS data platform for compute and graphic intensive processing, simulation and visualization workloads.
Modernizing and transforming exploration and production workflows with AWS Storage services
Accelerating seismic data retrieval, getting better data protection and reliability, and providing a common AWS data platform for compute and graphic intensive processing, simulation and visualization workloads.
Capturing and processing streaming sensor data from remote oil rigs with Snowball Edge
Providing a Data Lake foundation for a next generation Digital Oilfield IoT analytics platform with Amazon S3
Speaker: John Mallory - AWS Storage Business Development Manager
Building Complex Workloads in Cloud - AWS PS Summit CanberraAmazon Web Services
In this session we will explore technologies & solutions to deploy ever increasing complex workload like High Performance Computing, Big Data and AI seamlessly to the cloud. You will hear from two strategic partners on how they have used AWS cloud and Intel technologies to accelerate innovation for their customers.
Speaker: Jason Jacobs, Industry Manager, ANZ Public Sector, Intel Corporation with Aileen Gemma Smith CEO, Vizalytics and Zack Levy, DevOps Partner, Deloitte Consulting
Cross platform mobile backend with mobile servicesJames Quick
This document discusses Microsoft Azure Mobile Services, which provide a comprehensive set of services to enable developers to quickly build, deploy, and manage cross-platform mobile applications. Azure Mobile Services allow storing data in SQL databases or NoSQL stores, provide backend services for authentication, push notifications, and more. The services can be accessed from any mobile or web application using client SDKs or a REST API.
This document provides an overview of an AWS event. It includes details about the AWS business including $16B in annual revenue and over 135,000 active customers. It discusses the breadth of AWS services and tools available, positioning AWS as a leader in cloud infrastructure. The document outlines how AWS gives customers superpowers with super sonic speed and pace of innovation. It provides examples of how customers are using AWS services to transform their businesses.
This document provides an overview of Amazon Web Services (AWS) and its cloud computing infrastructure and services. It describes AWS's global footprint including regions and availability zones. It then discusses various AWS computing, storage, database, deployment/administration and application services like EC2, S3, RDS, IAM, Elastic Beanstalk and more. The document concludes with a proposed example application architecture using several AWS services.
This is the complete deck presented at the Westin Calgary Hotel, on August 16th, 2016.
It covers the current state of the AWS Big Data Solution set. Contains several use cases of Big Data, Machine Learning, and a tutorial on how to implement and use Big Data on the AWS Cloud Platform.
This document provides an overview of cloud computing and Microsoft Azure. It discusses how cloud computing allows for rapid setup of environments, elastic scaling, and reduced costs. It introduces key concepts of cloud computing like virtualization, automation, and pay-per-use pricing models. The document discusses how the cloud handles infrastructure management, providing resources and services on-demand. It outlines the architecture of cloud applications including load balancing, high availability, and multi-tenancy. Finally, it summarizes different Azure services like compute, storage, databases, and PaaS offerings and how they fit on the continuum from infrastructure to platform services.
MongoDB IoT City Tour STUTTGART: The Microsoft Azure Platform for IoTMongoDB
Presented by, Dr Christian Geuer-Pollmann, Senior Technology Evangelist at Microsoft.
The presentation gives a solid overview to the Microsoft Azure platform, with a special emphasis on scenarios for IoT workloads. First, Christian provides an introduction to Microsoft Azure’s IaaS compute and networking infrastructure (i.e. virtual machines, virtual networks, load balancers and HA concepts). The second part of the presentation focuses on higher-order services in Azure, such as relational data bases, machine learning, search, and NoSQL offerings. Last, Christian explains how the Azure Service Bus and the Intelligent Systems Services fit into the overall IoT landscape.
This document discusses cloud computing and job opportunities in the cloud computing sector. It begins by defining cloud computing and describing its characteristics, service models, and deployment models. It then discusses key cloud technologies like Amazon Web Services, cloud storage, and utility computing using Amazon EC2. The document outlines several commercial cloud offerings and concerns about cloud computing. Finally, it proposes four courses of study to acquire skills in cloud infrastructure, servers, storage, and virtualization, along with the technologies, certifications, and job roles associated with each course.
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Amazon Web Services
Il Forecasting è un processo importante per tantissime aziende e viene utilizzato in vari ambiti per cercare di prevedere in modo accurato la crescita e distribuzione di un prodotto, l’utilizzo delle risorse necessarie nelle linee produttive, presentazioni finanziarie e tanto altro. Amazon utilizza delle tecniche avanzate di forecasting, in parte questi servizi sono stati messi a disposizione di tutti i clienti AWS.
In questa sessione illustreremo come pre-processare i dati che contengono una componente temporale e successivamente utilizzare un algoritmo che a partire dal tipo di dato analizzato produce un forecasting accurato.
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Amazon Web Services
La varietà e la quantità di dati che si crea ogni giorno accelera sempre più velocemente e rappresenta una opportunità irripetibile per innovare e creare nuove startup.
Tuttavia gestire grandi quantità di dati può apparire complesso: creare cluster Big Data su larga scala sembra essere un investimento accessibile solo ad aziende consolidate. Ma l’elasticità del Cloud e, in particolare, i servizi Serverless ci permettono di rompere questi limiti.
Vediamo quindi come è possibile sviluppare applicazioni Big Data rapidamente, senza preoccuparci dell’infrastruttura, ma dedicando tutte le risorse allo sviluppo delle nostre le nostre idee per creare prodotti innovativi.
Ora puoi utilizzare Amazon Elastic Kubernetes Service (EKS) per eseguire pod Kubernetes su AWS Fargate, il motore di elaborazione serverless creato per container su AWS. Questo rende più semplice che mai costruire ed eseguire le tue applicazioni Kubernetes nel cloud AWS.In questa sessione presenteremo le caratteristiche principali del servizio e come distribuire la tua applicazione in pochi passaggi
Vent'anni fa Amazon ha attraversato una trasformazione radicale con l'obiettivo di aumentare il ritmo dell'innovazione. In questo periodo abbiamo imparato come cambiare il nostro approccio allo sviluppo delle applicazioni ci ha permesso di aumentare notevolmente l'agilità, la velocità di rilascio e, in definitiva, ci ha consentito di creare applicazioni più affidabili e scalabili. In questa sessione illustreremo come definiamo le applicazioni moderne e come la creazione di app moderne influisce non solo sull'architettura dell'applicazione, ma sulla struttura organizzativa, sulle pipeline di rilascio dello sviluppo e persino sul modello operativo. Descriveremo anche approcci comuni alla modernizzazione, compreso l'approccio utilizzato dalla stessa Amazon.com.
Come spendere fino al 90% in meno con i container e le istanze spot Amazon Web Services
L’utilizzo dei container è in continua crescita.
Se correttamente disegnate, le applicazioni basate su Container sono molto spesso stateless e flessibili.
I servizi AWS ECS, EKS e Kubernetes su EC2 possono sfruttare le istanze Spot, portando ad un risparmio medio del 70% rispetto alle istanze On Demand. In questa sessione scopriremo insieme quali sono le caratteristiche delle istanze Spot e come possono essere utilizzate facilmente su AWS. Impareremo inoltre come Spreaker sfrutta le istanze spot per eseguire applicazioni di diverso tipo, in produzione, ad una frazione del costo on-demand!
In recent months, many customers have been asking us the question – how to monetise Open APIs, simplify Fintech integrations and accelerate adoption of various Open Banking business models. Therefore, AWS and FinConecta would like to invite you to Open Finance marketplace presentation on October 20th.
Event Agenda :
Open banking so far (short recap)
• PSD2, OB UK, OB Australia, OB LATAM, OB Israel
Intro to Open Finance marketplace
• Scope
• Features
• Tech overview and Demo
The role of the Cloud
The Future of APIs
• Complying with regulation
• Monetizing data / APIs
• Business models
• Time to market
One platform for all: a Strategic approach
Q&A
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Amazon Web Services
Per creare valore e costruire una propria offerta differenziante e riconoscibile, le startup di successo sanno come combinare tecnologie consolidate con componenti innovativi creati ad hoc.
AWS fornisce servizi pronti all'utilizzo e, allo stesso tempo, permette di personalizzare e creare gli elementi differenzianti della propria offerta.
Concentrandoci sulle tecnologie di Machine Learning, vedremo come selezionare i servizi di intelligenza artificiale offerti da AWS e, anche attraverso una demo, come costruire modelli di Machine Learning personalizzati utilizzando SageMaker Studio.
OpsWorks Configuration Management: automatizza la gestione e i deployment del...Amazon Web Services
Con l'approccio tradizionale al mondo IT per molti anni è stato difficile implementare tecniche di DevOps, che finora spesso hanno previsto attività manuali portando di tanto in tanto a dei downtime degli applicativi interrompendo l'operatività dell'utente. Con l'avvento del cloud, le tecniche di DevOps sono ormai a portata di tutti a basso costo per qualsiasi genere di workload, garantendo maggiore affidabilità del sistema e risultando in dei significativi miglioramenti della business continuity.
AWS mette a disposizione AWS OpsWork come strumento di Configuration Management che mira ad automatizzare e semplificare la gestione e i deployment delle istanze EC2 per mezzo di workload Chef e Puppet.
Scopri come sfruttare AWS OpsWork a garanzia e affidabilità del tuo applicativo installato su Instanze EC2.
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsAmazon Web Services
Vuoi conoscere le opzioni per eseguire Microsoft Active Directory su AWS? Quando si spostano carichi di lavoro Microsoft in AWS, è importante considerare come distribuire Microsoft Active Directory per supportare la gestione, l'autenticazione e l'autorizzazione dei criteri di gruppo. In questa sessione, discuteremo le opzioni per la distribuzione di Microsoft Active Directory su AWS, incluso AWS Directory Service per Microsoft Active Directory e la distribuzione di Active Directory su Windows su Amazon Elastic Compute Cloud (Amazon EC2). Trattiamo argomenti quali l'integrazione del tuo ambiente Microsoft Active Directory locale nel cloud e l'utilizzo di applicazioni SaaS, come Office 365, con AWS Single Sign-On.
Dal riconoscimento facciale al riconoscimento di frodi o difetti di fabbricazione, l'analisi di immagini e video che sfruttano tecniche di intelligenza artificiale, si stanno evolvendo e raffinando a ritmi elevati. In questo webinar esploreremo le possibilità messe a disposizione dai servizi AWS per applicare lo stato dell'arte delle tecniche di computer vision a scenari reali.
Amazon Web Services e VMware organizzano un evento virtuale gratuito il prossimo mercoledì 14 Ottobre dalle 12:00 alle 13:00 dedicato a VMware Cloud ™ on AWS, il servizio on demand che consente di eseguire applicazioni in ambienti cloud basati su VMware vSphere® e di accedere ad una vasta gamma di servizi AWS, sfruttando a pieno le potenzialità del cloud AWS e tutelando gli investimenti VMware esistenti.
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
Crea la tua prima serverless ledger-based app con QLDB e NodeJSAmazon Web Services
Molte aziende oggi, costruiscono applicazioni con funzionalità di tipo ledger ad esempio per verificare lo storico di accrediti o addebiti nelle transazioni bancarie o ancora per tenere traccia del flusso supply chain dei propri prodotti.
Alla base di queste soluzioni ci sono i database ledger che permettono di avere un log delle transazioni trasparente, immutabile e crittograficamente verificabile, ma sono strumenti complessi e onerosi da gestire.
Amazon QLDB elimina la necessità di costruire sistemi personalizzati e complessi fornendo un database ledger serverless completamente gestito.
In questa sessione scopriremo come realizzare un'applicazione serverless completa che utilizzi le funzionalità di QLDB.
Con l’ascesa delle architetture di microservizi e delle ricche applicazioni mobili e Web, le API sono più importanti che mai per offrire agli utenti finali una user experience eccezionale. In questa sessione impareremo come affrontare le moderne sfide di progettazione delle API con GraphQL, un linguaggio di query API open source utilizzato da Facebook, Amazon e altro e come utilizzare AWS AppSync, un servizio GraphQL serverless gestito su AWS. Approfondiremo diversi scenari, comprendendo come AppSync può aiutare a risolvere questi casi d’uso creando API moderne con funzionalità di aggiornamento dati in tempo reale e offline.
Inoltre, impareremo come Sky Italia utilizza AWS AppSync per fornire aggiornamenti sportivi in tempo reale agli utenti del proprio portale web.
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareAmazon Web Services
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
In queste slide, gli esperti AWS e VMware presentano semplici e pratici accorgimenti per facilitare e semplificare la migrazione dei carichi di lavoro Oracle accelerando la trasformazione verso il cloud, approfondiranno l’architettura e dimostreranno come sfruttare a pieno le potenzialità di VMware Cloud ™ on AWS.
1) The document discusses building a minimum viable product (MVP) using Amazon Web Services (AWS).
2) It provides an example of an MVP for an omni-channel messenger platform that was built from 2017 to connect ecommerce stores to customers via web chat, Facebook Messenger, WhatsApp, and other channels.
3) The founder discusses how they started with an MVP in 2017 with 200 ecommerce stores in Hong Kong and Taiwan, and have since expanded to over 5000 clients across Southeast Asia using AWS for scaling.
This document discusses pitch decks and fundraising materials. It explains that venture capitalists will typically spend only 3 minutes and 44 seconds reviewing a pitch deck. Therefore, the deck needs to tell a compelling story to grab their attention. It also provides tips on tailoring different types of decks for different purposes, such as creating a concise 1-2 page teaser, a presentation deck for pitching in-person, and a more detailed read-only or fundraising deck. The document stresses the importance of including key information like the problem, solution, product, traction, market size, plans, team, and ask.
This document discusses building serverless web applications using AWS services like API Gateway, Lambda, DynamoDB, S3 and Amplify. It provides an overview of each service and how they can work together to create a scalable, secure and cost-effective serverless application stack without having to manage servers or infrastructure. Key services covered include API Gateway for hosting APIs, Lambda for backend logic, DynamoDB for database needs, S3 for static content, and Amplify for frontend hosting and continuous deployment.
This document provides tips for fundraising from startup founders Roland Yau and Sze Lok Chan. It discusses generating competition to create urgency for investors, fundraising in parallel rather than sequentially, having a clear fundraising narrative focused on what you do and why it's compelling, and prioritizing relationships with people over firms. It also notes how the pandemic has changed fundraising, with examples of deals done virtually during this time. The tips emphasize being fully prepared before fundraising and cultivating connections with investors in advance.
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...Amazon Web Services
This document discusses Amazon's machine learning services for building conversational interfaces and extracting insights from unstructured text and audio. It describes Amazon Lex for creating chatbots, Amazon Comprehend for natural language processing tasks like entity extraction and sentiment analysis, and how they can be used together for applications like intelligent call centers and content analysis. Pre-trained APIs simplify adding machine learning to apps without requiring ML expertise.
Amazon Elastic Container Service (Amazon ECS) è un servizio di gestione dei container altamente scalabile, che semplifica la gestione dei contenitori Docker attraverso un layer di orchestrazione per il controllo del deployment e del relativo lifecycle. In questa sessione presenteremo le principali caratteristiche del servizio, le architetture di riferimento per i differenti carichi di lavoro e i semplici passi necessari per poter velocemente migrare uno o più dei tuo container.
[To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
This presentation is a curated compilation of PowerPoint diagrams and templates designed to illustrate 20 different digital transformation frameworks and models. These frameworks are based on recent industry trends and best practices, ensuring that the content remains relevant and up-to-date.
Key highlights include Microsoft's Digital Transformation Framework, which focuses on driving innovation and efficiency, and McKinsey's Ten Guiding Principles, which provide strategic insights for successful digital transformation. Additionally, Forrester's framework emphasizes enhancing customer experiences and modernizing IT infrastructure, while IDC's MaturityScape helps assess and develop organizational digital maturity. MIT's framework explores cutting-edge strategies for achieving digital success.
These materials are perfect for enhancing your business or classroom presentations, offering visual aids to supplement your insights. Please note that while comprehensive, these slides are intended as supplementary resources and may not be complete for standalone instructional purposes.
Frameworks/Models included:
Microsoft’s Digital Transformation Framework
McKinsey’s Ten Guiding Principles of Digital Transformation
Forrester’s Digital Transformation Framework
IDC’s Digital Transformation MaturityScape
MIT’s Digital Transformation Framework
Gartner’s Digital Transformation Framework
Accenture’s Digital Strategy & Enterprise Frameworks
Deloitte’s Digital Industrial Transformation Framework
Capgemini’s Digital Transformation Framework
PwC’s Digital Transformation Framework
Cisco’s Digital Transformation Framework
Cognizant’s Digital Transformation Framework
DXC Technology’s Digital Transformation Framework
The BCG Strategy Palette
McKinsey’s Digital Transformation Framework
Digital Transformation Compass
Four Levels of Digital Maturity
Design Thinking Framework
Business Model Canvas
Customer Journey Map
Structural Design Process: Step-by-Step Guide for BuildingsChandresh Chudasama
The structural design process is explained: Follow our step-by-step guide to understand building design intricacies and ensure structural integrity. Learn how to build wonderful buildings with the help of our detailed information. Learn how to create structures with durability and reliability and also gain insights on ways of managing structures.
Company Valuation webinar series - Tuesday, 4 June 2024FelixPerez547899
This session provided an update as to the latest valuation data in the UK and then delved into a discussion on the upcoming election and the impacts on valuation. We finished, as always with a Q&A
Discover timeless style with the 2022 Vintage Roman Numerals Men's Ring. Crafted from premium stainless steel, this 6mm wide ring embodies elegance and durability. Perfect as a gift, it seamlessly blends classic Roman numeral detailing with modern sophistication, making it an ideal accessory for any occasion.
https://rb.gy/usj1a2
How to Implement a Real Estate CRM SoftwareSalesTown
To implement a CRM for real estate, set clear goals, choose a CRM with key real estate features, and customize it to your needs. Migrate your data, train your team, and use automation to save time. Monitor performance, ensure data security, and use the CRM to enhance marketing. Regularly check its effectiveness to improve your business.
Zodiac Signs and Food Preferences_ What Your Sign Says About Your Tastemy Pandit
Know what your zodiac sign says about your taste in food! Explore how the 12 zodiac signs influence your culinary preferences with insights from MyPandit. Dive into astrology and flavors!
Understanding User Needs and Satisfying ThemAggregage
https://www.productmanagementtoday.com/frs/26903918/understanding-user-needs-and-satisfying-them
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
In this webinar, we won't focus on the research methods for discovering user-needs. We will focus on synthesis of the needs we discover, communication and alignment tools, and how we operationalize addressing those needs.
Industry expert Scott Sehlhorst will:
• Introduce a taxonomy for user goals with real world examples
• Present the Onion Diagram, a tool for contextualizing task-level goals
• Illustrate how customer journey maps capture activity-level and task-level goals
• Demonstrate the best approach to selection and prioritization of user-goals to address
• Highlight the crucial benchmarks, observable changes, in ensuring fulfillment of customer needs
IMPACT Silver is a pure silver zinc producer with over $260 million in revenue since 2008 and a large 100% owned 210km Mexico land package - 2024 catalysts includes new 14% grade zinc Plomosas mine and 20,000m of fully funded exploration drilling.
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Part 2 Deep Dive: Navigating the 2024 Slowdownjeffkluth1
Introduction
The global retail industry has weathered numerous storms, with the financial crisis of 2008 serving as a poignant reminder of the sector's resilience and adaptability. However, as we navigate the complex landscape of 2024, retailers face a unique set of challenges that demand innovative strategies and a fundamental shift in mindset. This white paper contrasts the impact of the 2008 recession on the retail sector with the current headwinds retailers are grappling with, while offering a comprehensive roadmap for success in this new paradigm.
The 10 Most Influential Leaders Guiding Corporate Evolution, 2024.pdfthesiliconleaders
In the recent edition, The 10 Most Influential Leaders Guiding Corporate Evolution, 2024, The Silicon Leaders magazine gladly features Dejan Štancer, President of the Global Chamber of Business Leaders (GCBL), along with other leaders.
Taurus Zodiac Sign: Unveiling the Traits, Dates, and Horoscope Insights of th...my Pandit
Dive into the steadfast world of the Taurus Zodiac Sign. Discover the grounded, stable, and logical nature of Taurus individuals, and explore their key personality traits, important dates, and horoscope insights. Learn how the determination and patience of the Taurus sign make them the rock-steady achievers and anchors of the zodiac.
Industrial Tech SW: Category Renewal and CreationChristian Dahlen
Every industrial revolution has created a new set of categories and a new set of players.
Multiple new technologies have emerged, but Samsara and C3.ai are only two companies which have gone public so far.
Manufacturing startups constitute the largest pipeline share of unicorns and IPO candidates in the SF Bay Area, and software startups dominate in Germany.
Top mailing list providers in the USA.pptxJeremyPeirce1
Discover the top mailing list providers in the USA, offering targeted lists, segmentation, and analytics to optimize your marketing campaigns and drive engagement.
1. With Amazon Web Services
Kavitha Mohammad
Director, Industry Solutions Group, Intel
2. Intel Confidential – Do Not Forward 2
Pressure to deliver
more Do more with less
Deliver across many locations
Delivery broader services
Pressure to deliver
faster Limited room for failure and downtime
Don’t disrupt operations waiting
for upgrades, patches.
Pressure to secure
and comply Enforce security and maintain privacy
Adhere to policies/governance
1. Manages the risks associated with putting certain
workloads in the cloud versus keeping on premise.
2. Optimizes IT resources and costs
3. Enables a deployment model that is
workload optimized for every application
A Cloud Strategy
addresses these pressures and….
A Sound Cloud Migration Strategy is Needed
The Journey to the cloud is inevitable
3. Intel Confidential – Do Not Forward 3
WiFi + LP WiFi
Bluetooth®
Technology + BTLE
3G/4G/LTE(GPRS)
ZigBee*, Zwave
6 LoWPAN*
WiHart*
Ethernet
RFIDSensor
Sensor
Sensor
Actuator
Sensor
Actuator
AWS IoT
Device SDK
Gateway
AUTHENTICATION
AUTHORIZATIONSecure with mutual authentication
and encryption
MESSAGE
BROKERCommunicate with
devices via MQTT
and HTTP
Device attributes
REGISTR
YIdentity and
Management of your
things
AWS IoT API
RULES
ENGINETransform messages
based on rules and
route to AWS Services
SHADOW
Persistent thing state
during intermittent
connections
AWS Services
-----
3P Services
APPLICATIONS
Device Security, Configuration
& Management
ODM GW
Manufacturer
Device Inventory
MCU
I/O
MCU
IOT: Intel – AWS Solution
4. Intel Confidential – Do Not Forward 4
Smart INFRA - Video analytics Gov’t
IP Camera NVR
Device Mgt.
(ONVIF)
Storage (HDFS, HBase,
etc.)
Edge Device
Real-time Stream Processing
(Spark Streaming, Storm, etc.)
Backend (Cloud) Analytics
APILibrary&APIMgmt(Mashery)
Compute
(Spark, MapReduce, etc.)
Data Input
(Flume, Kafka, etc.)
• Video Encode
• Video Storage
• Object Detection
• (Region of Interest)
• Distributed analytics algorithms & frameworks for high volume and high
complexity (real-time) video analysis
• API for 3rd-party algorithm and service integrations
Based
Analytics
Platform
Analytics
Applications
Tracking in Public
Environment
Search by Face …
Analytics
Algorithms &
Frameworks
Face
Detection
Fatial
Detection
…
Machine Leaning
(e.g., classifier)
5. Intel Confidential – Do Not Forward 5
Big Data Solution on AWS
Storage Content
& Delivery
EBS
Block Storage for EC2
Instances
Glacier
Archive Storage in the Cloud
AWS Import/Export Snowball
Large-scale Data Transport
S3
Scalable Object Storage in the Cloud
AWS Storage Gateway
Integrates On-Premise Storage
with the Cloud
Elastic File System
Fully Managed File System for EC2
CloudFront
Global Content Delivery Network
Database
RDS
Fully Managed MySQL, PostgreSQL,
Oracle, SQL Server, MariaDB and
Amazon Aurora
Redshift
Fast, Powerful, Full Managed,
Petabyte-scale Data Warehouse
Service
Elasticache
Memcached and Redis In Memory
Cache Service
DynamoDB
Predictable and Scalable NoSQL
Data Store
Analytics
Elastic Map Reduce
Fully Managed Hadoop Framework
Kinesis
Managed Streaming Data Platform
Data Pipeline
Orchestration for Data Driven
Workflows
Elasticsearch
Deploy, Operate and Scale
Elasticsearch and Clusters
Machine Learning
Build Smart Applications Quickly and
Easily
6. Intel Confidential – Do Not Forward 6
Edu: Cloud benefits span from IT to the clas
Students
and Faculty
Deliver Engagement with
Students and Teachers
Collaborate
Any Way
Private
Cloud BI
APP
Public
Cloud
Across Any Device
Less tech updates = more learning time
Mobility
Access to more content
Added services (analytics, etc.)
Collaboration & information sharing
Scalability to grow
Easily managed
Agility to handle spikes
Automatic patches & updates
Ease of deployments
Cost flexibility (CapEx vs OpEx)
Built-in redundancy
Educational
Benefits
IT BENEFITS
7. Intel Confidential – Do Not Forward 7
SMART HOME: ALEXA
AWS Cloud
Process the Voice command by
Cloud Servers – then Automates
Scenarios/Scenes
Intel Based
Broadband Modem
Intel GRX 750
WiFi access point
router
Intel based Smart hub
http://www.cybertan.com.tw
/Products/ZE250.html
“Alexa, turn on
Good Night”
“Alexa, turn on
Good Morning”
Things
Bluetooth
Z Wave
ZigBee
The Smart Tiny Home Powered by Intel & Amazon Alexa
8. Intel Confidential – Do Not Forward 8
HPC Today: Two (Connected) Worlds
Supercomputing
The “rest” of HPC
9. Intel Confidential – Do Not Forward 9
Example HPC Cloud Use Cases
Compute Demand
vs. Cluster Size
Cluster size
Compute Demand
Wasted
Resources
Missed
Opportunity
Burst capacity to expand on-premise
resources
As means to make on-premise systems
more valuable
Sandbox to explore new ideas without
disrupting production systems
As “on ramp” for new users of HPC
As vehicle to deliver new HPC-powered
services
Image courtesy of Cycle Computing
10. Intel Confidential – Do Not Forward 10
Ai is transforming industries
Consum
er
Health Finance Retail
Governm
ent
Energy
Transpor
t
Industrial Other
Smart
Assistants
Chatbots
Search
Personalization
Augmented
Reality
Robots
Enhanced
Diagnostics
Drug
Discovery
Patient Care
Research
Sensory
Aids
Algorithmic
Trading
Fraud Detection
Research
Personal
Finance
Risk Mitigation
Support
Experience
Marketing
Merchandising
Loyalty
Supply Chain
Security
Defense
Data
Insights
Safety &
Security
Resident
Engagement
Smarter
Cities
Oil & Gas
Exploration
Smart
Grid
Operational
Improvement
Conservation
Automated Cars
Automated
Trucking
Aerospace
Shipping
Search &
Rescue
Factory
Automation
Predictive
Maintenance
Precision
Agriculture
Field
Automation
Advertising
Education
Gaming
Professional &
IT Services
Telco/Media
Sports
Early adoption
exampl
es
Source: Intel forecast
11. Intel Confidential – Do Not Forward
TEL’S DATA STRATEGY:
VIRTOUS CYCLE
OF GROWTH
11
12. Intel Confidential – Do Not Forward
TEL + AMAZON
Things &
devices
CLOUD &
DATA
CENTER
12
Editor's Notes
Expert: TBD
Virtually any Big Data Application including fraud detection, recommendation engine, IOT
Amazon EMR managed Hadoop framework, runs Apache, Spark
Amazon Athena analyze petabytes of data in Amazon S3
Amazon Kinesis near realt time analytics
Database S3 (obecjt storage), Dyanmo DB (NoSQL), Aurora (RDSM)
Data Warehousing Amazon Redshift
Business Intellgince Amazon Quick Sight
AI Amazon Lex,
Amazon Alexa and Amazon products like the Echo, can be used to control your smart home throughout the day simply by using your voice. With today's number of devices in the home being used simultaneoulsy for things like streaming content, virtual reality and home management and security systems - Intel technologies bring optimal performance for improved speed and network coverage so your WiFi is as reliable as your electricity.
Key Intel technology / Products to highlight
Smart Speaker Lenovo Smart Assistant based on Intel Pentium based processor provides far field enable speech input with Amazon Alexa Voice Assistant
Connectivity Intel GRX 750 router and IRX extender provides WiFi and Internet connectivity into the home
Smart Hub (Hardware) Intel’s IOT reference Cybertan IOT smart home hub with multiple RF and WSN (WiFi/Zigbee, BLE, Z-wave/3G/4G interfaces)
Standards (Software) Intel’s Smart Home Developer Acceleration Platform (Home Lake) and Open Connectivity Foundation (OCF)
Which industries are the earliest adopters of AI? Generally, those segments with clear use cases, high purchasing power, and high rewards for making decisions quickly and/or more accurately will adopt AI fastest. Here are the segments that we believe will lead AI through 2020, ordered by market opportunity.
Consumer
Smart Assistants – personal assistant that anticipates, optimizes, automates daily life (e.g. Amazon Alexa, Apple Siri, Google Assistant, Microsoft Cortana, Facebook Jarvis home automation, X.ai virtual assistant Amy)
Chatbots – 24/7/365 no waiting access to an informative or helpful agent (e.g. WeChat, Bank of America, Uber, Pizza Hut, Alaska Airlines, Amtrak, etc.)
Search – ability to more intelligently search more data types including image, video, context, etc (e.g. Improved Google search, Google Photos, ReSnap)
Personalization – ability to automatically adjust content/recommendations to suit individuals (e.g. Entefy, Netflix recommendation engine, Amazon personalized shopping recommendations)
Augmented Reality – overlay information on our field of view in real-time to identify interesting or undesirable things (e.g. Intel Project Alloy, Google Translate using smartphone camera)
Robots – personal robots that are able to perform household, yard, or other chores (e.g. Jibo robot for day-to-day functions, Roomba follow-ons)
Health (SME: Kristina Kermanshahche, Ketan Paranjape)
Enhanced Diagnosis – a tool for doctors to augment their own diagnosis with more data, experience, precision and accuracy (e.g. radiology image analysis, Journal of American Medicine Association paper on retina scan for diabetic retinopathy, skin lesion classification to recognize melanoma with 98% accuracy, medical history scraping, treatment outcome prediction)
Drug Discovery – computational drug discovery that intelligently hones in on the most promising treatments (e.g. speeding pharma drug development)
Patient Care – machines that aid with monitoring, treatment, and/or recovery of patients (e.g. visual patient monitoring, autonomous robotic surgery, friendly medication and/or physical therapy robots)
Research – instantly sifting through hundreds of new research papers and clinical trials that are published each day to make new connections (e.g. AI at University of North Carolina’s Lineberger Comprehensive Cancer Center)
Sensory Aids – filling in for various senses that are absent or challenged (e.g. visual aid, audio aid)
Finance (SME: Robert Geva)
Algorithmic Trading – augment rule-based algorithmic trading models and data sources using AI (e.g. Kensho analysis of myriad data to predict stock movement)
Fraud Detection – ability to identify fraudulent transactions and/or claims (e.g. USAA identifies fraud using Intel’s Saffron technology)
Research – ability to intelligently assemble, parse, and extract meaning from troves of data that influence asset prices (e.g. Quid, FSI firm reducing time to insight for portfolio managers through smart knowledge management system)
Personal Finance – smarter recommendations, lower risk lending, greater efficiency (e.g. active portfolio recommendations, quickly parsing more data before issuing loan, automatic reading of check scans, etc.)
Risk Mitigation – detect risk factors and/or reduce the burden of regulation and minimize errors through automated compliance (e.g. IBM+Promontory Financial Group using natural language processing to detect excursions)
Retail (SME: Janet Kerby, Chris Hunt)
Support – bots providing shopping, ordering and support in lifelike interaction (e.g. My Starbucks Barista, KLM Dutch Airline customer support via social media, Nieman Marcus visual search, Pizza Hut order pizza via bot, Adobe Digital’s digital mirror that recommends clothes, intelligent phone menu routing based on NLP, ViSenze recommending similar items based on image, Adobe Digital’s digital mirror that recommends clothes)
Experience – deliver winning consumer experiences in-store (e.g. Amazon Go checkout-free grocery store, Macy’s mobile shopping assistant, Lowes Lowebots that roam stores answering simple questions and tracking inventory)
Marketing – precision marketing to consumers, promoting products and services how and where they want to hear (e.g. North Face “Expert Personal Shopper” on website)
Merchandising – better planning through accelerated and expanded insight into consumer buying patterns (e.g. Stitch Fix virtual styling, Skechers.com analyzing clicks in real-time to bring similar catalog items forward, Wal-mart pairing products that sell together, Cosabella evolutionary website tweaks)
Loyalty – transform the consumer experience through segmentation (e.g. Under Armour health app that constantly collects user data to deliver personalized fitness recommendations)
Supply Chain – optimize the supply chain and inventory management for efficiency and innovate new business models (e.g. OnProcess technology’s use of predictive analytics for inventory management)
Security – improve security of all consumer and business digital assets, such as real-time shoplifting/lifter detection, multi-factor identity verification, data breach detection (e.g. Mastercard pay with your face, Walmart facial recognition to catch shoplifters)
Government (SME: Harris Joyce)
Defense – drones, connected soldiers, defense strategy (e.g. military/surveillance drones, autonomous rescue vehicles, augmented connected soldier, real-time threat assessment and strategy recommendation)
Data Insights – analyze massive amounts of data to identify opportunities/inefficiencies in bureaucracy, cybersecurity threats and more, to ultimately implement better systems and policies (e.g. MIT AI that detects cyber security threats)
Crime Preventionusing AI to predict and help recover from disasters thanks to ability to quickly process large amounts of unstructured data and optimize limited resources (e.g. 1Concern, BlueLineGrid)
Safety & Security – crowd analytics, behavioral/sentiment analytics, social media analytics, face/vehicle recognition, online identity recognition, real-time video analytics, using AI to predict and help recover from disasters thanks to ability to quickly process large amounts of unstructured data and optimize limited resources (e.g. police analyzing social media to adjust police presence, license plate readers in police cars, 1Concern, BlueLineGrid)
Resident Engagement – new tools to facilitate citizen engagement like chatbots, at-risk citizen identification, (e.g. Amelia chatbot in North London Enfield council, North Carolina chatbot to help state employees with IT inquiries)
Smarter Cities – traffic/pedestrian management, lighting management, weather management, energy conservation, services analytics (e.g. San Francisco and Pittsburgh using sensors and AI to optimize traffic flow)
Energy (SME: Noe Garcia, Tonya Cosby)
Oil & Gas Exploration – automated geophysical feature detection (e.g. oil & gas producers using AI to augment traditional modeling & simulation)
Smart Grid – predictive and real-time intelligent generation, allocation, and storage of power to meet variable demand (e.g. GridSense, SoloGrid)
Operational Improvement – safety and efficiency improvements through predictive and/or insightful AI (e.g. GE Oil and Gas using predictive analytics and AI to predict and preempt potential operational problems)
Conservation – intelligent buildings, computing and appliances that reduce power consumption and are more efficient than producing another kWh of electricity (e.g. Google DeepMind datacenter energy reductions)
Transport (SME: Len Klebba)
Automated Cars – autonomous cars driving on the roadways (e.g. BMW, Google, Uber, many others)
Automated Trucking – autonomous trucks driving on the roadways (e.g. Daimler)
Aerospace – autonomous planes and other aerial vehicles (e.g. Boeing’s evolution of autopilot and drones)
Shipping – autonomous package delivery via drone or other vehicle (e.g. Amazon package delivery drone)
Search & Rescue – ability to deploy autonomous robot to search and rescue victims in potentially hazardous environments (e.g. war casualty extraction, miner rescue, firefighting, avalanche rescue)
Industrial (SME: Mary Bunzel, Esther Baldwin)
Factory Automation – highly-productive, efficient and safe factories with robots that can see, hear and adapt to their environment to produce goods with incredible quality and speed (e.g. assembly line)
Predictive Maintenance – ability to detect patterns that indicate the likelihood of an upcoming fault that would require maintenance (e.g. airline being able to adjust schedule to perform preventive maintenance before a failure)
Precision Agriculture – ability to deliver the precise amount of water, nutrients, sunlight, weed killer, etc to a particular crop or individual plant (e.g. farmer using visual weed search to zap only weeds with RoundUp, automated sorting of produce for market)
Field Automation – ability to automate heavy equipment beyond the factory walls (e.g. mining, excavation, construction, road repair)
Other
Advertising – interactive ads, adaptive ads, personalized ads, real-time ads (e.g. AdBrain, MetaMarkets, Proximic, RocketFuel)
Education – virtual mentors, foreign language instruction, automated study sheets, personalized assignments, cheating detection, deliberate practice, machine-to-machine instruction (e.g. Intelligent Tutor Systems, Content Technologies Inc, PR2 robot from Cornell)
Gaming – dynamic and interactive video game experiences (e.g. Xbox Kinect, Playstation Eye, Wii)
Professional & IT Services – sales, marketing, legal research, accounting/tax, assisted counseling, customized IT recommendations (e.g. Pinsent Masons law firm that emulates human decision-making, Salesforce use of AI)
Telco/Media – customized content/ads, network optimization, quality of service, mobile/home security (e.g. media company customizing tv show recommendations and ads, network operator ensuring efficient and high-quality delivery/repair, wireless company using multi-factor security)
Sports – intelligent analytics for injury prevention and betting (e.g. Kinduct injury prevention, Microsoft Cortana predicting football games)
Here is an even broader list of industries that will be impacted by AI: Advertising, Aerospace, Agriculture, Automotive, Building Automation, Business, Education, Fashion, Finance, Gaming, Government, Healthcare, IT, Investment, Legal, Life Sciences, Logistics, Manufacturing, Media & Entertainment, Oil/Gas/Mining, Real Estate, Retail, Sports & Fitness, Telecommunications, Transportation
Sources: Intel forecast (IDC, GII Research, Tractica, Technavio, Market Research Store, Allied Market Research, BCC Research)