Extracting real-time information from streaming data generated by mobile devices, sensors, and servers used to require distributed systems skills and writing custom code. This presentation will introduce Kinesis Streams and Kinesis Firehose, the AWS services for real-time streaming big data ingestion and processing.
We’ll provide an overview of the key scenarios and business use cases suitable for real-time processing, and how Kinesis can help customers shift from a traditional batch-oriented processing of data to a continual real-time processing model. We’ll explore the key concepts, attributes, APIs and features of the service, and discuss building a Kinesis-enabled application for real-time processing. This talk will also include key lessons learnt, architectural tips and design considerations in working with Kinesis and building real-time processing applications.
In this webinar, we will also provide an overview of Amazon Kinesis Firehose. We will then walk through a demo showing how to create an Amazon Kinesis Firehose delivery stream, send data to the stream, and configure it to load the data automatically into Amazon S3 and Amazon Redshift.
AWS re:Invent 2016: Industry Opportunities for AWS Partners: Healthcare, Fina...Amazon Web Services
Take advantage of key trends in healthcare, financial services, and digital media and learn what they mean for your service offerings and technology solutions. For healthcare and life sciences, clearing the compliance hurdle and obtaining customer buy-in to bring HIPAA and GxP workloads on AWS. For financial services, automating security and fast-tracking compliance to generate more business (featuring NICE Actimize + Avoka). For media and entertainment, leading an end-to-end digital transformation story with your media customers and understanding where to apply the AWS platform, Elemental Technologies, and M&E partners to accelerate customer adoption. You gain insight into where to add value with consulting engagements and where to build managed services and SaaS offerings.
Have you prepared your AWS environment for detecting and managing security-related events? Do you have all the incident response training and tools you need to rapidly respond to, recover from, and determine the root cause of security events in the cloud? Even if you have a team of incident response rock stars with an arsenal of automated data acquisition and computer forensics capabilities, there is likely a thing or two you will learn from several step-by-step demonstrations of wrangling various potential security events within an AWS environment, from detection to response to recovery to investigating root cause. At a minimum, show up to find out who to call and what to expect when you need assistance with applying your existing, already awesome incident response runbook to your AWS environment.
SRV418 Deep Dive on Accelerating Content, APIs, and Applications with Amazon ...Amazon Web Services
Attend this session to dive deeper into AWS's content delivery service, Amazon CloudFront. Learn how you can use CloudFront to accelerate the delivery of your APIs or applications, including content that cannot be cached, to global clients. We'll also walk you through how you can use Lambda@Edge, which gives you the ability to execute custom code inline with your CloudFront events to customize applications. With Lambda@Edge, you can now generate custom responses right at the edge, allowing you to leverage CloudFront to reduce end-to-end latency and more efficiently filter traffic to your back-end origin servers. We'll walk you through Lambda@Edge use cases and walk through a demo to show how this works.
AWS APAC Webinar Week - Training & Certification MasterclassAmazon Web Services
Enterprises are no longer asking ''Should I move to the cloud?''; instead they're asking ''When and how fast can I adopt the cloud?''. Key questions that we hear from enterprise customers include: Where do I start? What are the technical skill sets needed? What are the necessary skills for architecting cloud applications and hybrid applications? Who will take care of operations on a day to day basis? How do I monitor my cloud for costs, security, availability, performance? Is my organization ready for DevOps, and when does that become important? What specific roles will I need to develop? If any of these questions are familiar to you, attend this session and learn about the skills, learning opportunities, and training available to build the technical and operational capability to take advantage of the AWS cloud. Expect to walk out with a mental roadmap of the cloud skillset you want to develop for your team.
You have heard how containers are great for running microservices, but running and managing large scale applications with microservices architectures is hard and often requires operating complex container management infrastructure. So what exactly is needed to get microservices to run in production at scale?
In this session, we will explore the reasoning and concepts behind microservices and how containers simplify building microservices based applications, and we will walk through a number of patterns used by our customers to run their microservices platforms. We will also dive deep into some of the challenges of running microservices, such as load balancing, service discovery, and secrets management, and we’ll see how Amazon EC2 Container Service (ECS) can help address them. We will also demo how you can easily deploy complex microservices applications using Amazon ECS.
AWS offers you the ability to add additional layers of security to your data at rest in the cloud, providing access control as well scalable and efficient encryption features. Flexible key management options allow you to choose whether to have AWS manage the encryption keys or to keep complete control over the keys yourself. In this session, you will learn how to secure data when using AWS services. We will discuss data encryption using Key Management Service, S3 access controls, edge and host access security, and database platform security features.
Expanding your Data Center with Hybrid Cloud InfrastructureAmazon Web Services
Cloud is a new common for the Hybrid IT strategies. In this session, we will explain what’s different between cloud and your datacenter as well as how to make your Hybrid Cloud strategies
AWS re:Invent 2016: Industry Opportunities for AWS Partners: Healthcare, Fina...Amazon Web Services
Take advantage of key trends in healthcare, financial services, and digital media and learn what they mean for your service offerings and technology solutions. For healthcare and life sciences, clearing the compliance hurdle and obtaining customer buy-in to bring HIPAA and GxP workloads on AWS. For financial services, automating security and fast-tracking compliance to generate more business (featuring NICE Actimize + Avoka). For media and entertainment, leading an end-to-end digital transformation story with your media customers and understanding where to apply the AWS platform, Elemental Technologies, and M&E partners to accelerate customer adoption. You gain insight into where to add value with consulting engagements and where to build managed services and SaaS offerings.
Have you prepared your AWS environment for detecting and managing security-related events? Do you have all the incident response training and tools you need to rapidly respond to, recover from, and determine the root cause of security events in the cloud? Even if you have a team of incident response rock stars with an arsenal of automated data acquisition and computer forensics capabilities, there is likely a thing or two you will learn from several step-by-step demonstrations of wrangling various potential security events within an AWS environment, from detection to response to recovery to investigating root cause. At a minimum, show up to find out who to call and what to expect when you need assistance with applying your existing, already awesome incident response runbook to your AWS environment.
SRV418 Deep Dive on Accelerating Content, APIs, and Applications with Amazon ...Amazon Web Services
Attend this session to dive deeper into AWS's content delivery service, Amazon CloudFront. Learn how you can use CloudFront to accelerate the delivery of your APIs or applications, including content that cannot be cached, to global clients. We'll also walk you through how you can use Lambda@Edge, which gives you the ability to execute custom code inline with your CloudFront events to customize applications. With Lambda@Edge, you can now generate custom responses right at the edge, allowing you to leverage CloudFront to reduce end-to-end latency and more efficiently filter traffic to your back-end origin servers. We'll walk you through Lambda@Edge use cases and walk through a demo to show how this works.
AWS APAC Webinar Week - Training & Certification MasterclassAmazon Web Services
Enterprises are no longer asking ''Should I move to the cloud?''; instead they're asking ''When and how fast can I adopt the cloud?''. Key questions that we hear from enterprise customers include: Where do I start? What are the technical skill sets needed? What are the necessary skills for architecting cloud applications and hybrid applications? Who will take care of operations on a day to day basis? How do I monitor my cloud for costs, security, availability, performance? Is my organization ready for DevOps, and when does that become important? What specific roles will I need to develop? If any of these questions are familiar to you, attend this session and learn about the skills, learning opportunities, and training available to build the technical and operational capability to take advantage of the AWS cloud. Expect to walk out with a mental roadmap of the cloud skillset you want to develop for your team.
You have heard how containers are great for running microservices, but running and managing large scale applications with microservices architectures is hard and often requires operating complex container management infrastructure. So what exactly is needed to get microservices to run in production at scale?
In this session, we will explore the reasoning and concepts behind microservices and how containers simplify building microservices based applications, and we will walk through a number of patterns used by our customers to run their microservices platforms. We will also dive deep into some of the challenges of running microservices, such as load balancing, service discovery, and secrets management, and we’ll see how Amazon EC2 Container Service (ECS) can help address them. We will also demo how you can easily deploy complex microservices applications using Amazon ECS.
AWS offers you the ability to add additional layers of security to your data at rest in the cloud, providing access control as well scalable and efficient encryption features. Flexible key management options allow you to choose whether to have AWS manage the encryption keys or to keep complete control over the keys yourself. In this session, you will learn how to secure data when using AWS services. We will discuss data encryption using Key Management Service, S3 access controls, edge and host access security, and database platform security features.
Expanding your Data Center with Hybrid Cloud InfrastructureAmazon Web Services
Cloud is a new common for the Hybrid IT strategies. In this session, we will explain what’s different between cloud and your datacenter as well as how to make your Hybrid Cloud strategies
Shared Responsibility and Setting Up Secure Account StructuresAmazon Web Services
In addition to discussing the AWS Shared Responsibility Model in detail for Infrastructure, Container and Abstract Services, we present a reference architecture for a secure, multi-account enterprise structure, including Mandatory Access Control for logging and separation assurance for different groups and functions within an organisation.
Join us to learn about the state of serverless computing from Dr. Tim Wagner, General Manager of AWS Lambda. Dr. Wagner discusses the latest developments from AWS Lambda and the serverless computing ecosystem. He talks about how serverless computing is becoming a core component in how companies build and run their applications and services, and he also discusses how serverless computing will continue to evolve.
(SEC310) Keeping Developers and Auditors Happy in the CloudAmazon Web Services
Often times, developers and auditors can be at odds. The agile, fast-moving environments that developers enjoy will typically give auditors heartburn. The more controlled and stable environments that auditors prefer to demonstrate and maintain compliance are traditionally not friendly to developers or innovation. We'll walk through how Netflix moved its PCI and SOX environments to the cloud and how we were able to leverage the benefits of the cloud and agile development to satisfy both auditors and developers. Topics covered will include shared responsibility, using compartmentalization and microservices for scope control, immutable infrastructure, and continuous security testing.
Wild Rydes (www.wildrydes.com) needs your help! With fresh funding from its seed investors, Wild Rydes is seeking to build the world’s greatest mobile/VR/AR unicorn transportation system. The scrappy startup needs a first-class webpage to begin marketing to new users and to begin its plans for global domination. Join us to help Wild Rydes build a website using a serverless architecture. You’ll build a scalable website using services like AWS Lambda, Amazon API Gateway, Amazon DynamoDB, and Amazon S3. Join this workshop to hop on the rocket ship!
To complete this workshop, you'll need:
Your laptop
AWS Account
AWS Command Line Interface
Google Chrome
git
Text Editor
As the number of developers and size of your infrastructure on AWS grows, timely investments in self-service and monitoring can help you scale operations without being the bottleneck. You can standardize infrastructure configurations for commonly used products to enable your customers to self-serve infrastructure needs for their apps. Once these resources are provisioned, you can easily understand how they are connected to administer them effectively, and monitor changes to configurations and evaluate drift. In this session, we will discuss how you can achieve a sophisticated level of standardization, configuration compliance, and monitoring using a combination of AWS Service Catalog, AWS Config, and AWS CloudTrail.
(SEC307) A Progressive Journey Through AWS IAM Federation OptionsAmazon Web Services
AWS Identity and Access Management (IAM) offers a continuum of interfaces and configuration options that enables customers to integrate their unique organizational identity structure and operational processes to the AWS platform. In this session we will evaluate the progressive journey of federation options that most customers go through as they widen their integration with IAM. This will include best practices, lessons learned from the field, and examples of actual customer implementations, covering technologies such as SAML, LDAP, and custom identity brokers.
AWS offers you the ability to add additional layers of security to your data at rest in the cloud, providing access control as well scalable and efficient encryption features. Flexible key management options allow you to choose whether to have AWS manage the encryption keys or to keep complete control over the keys yourself. In this session, you will learn how to secure data when using AWS services. We will discuss data encryption using Key Management Service, S3 access controls, edge and host access security, and database platform security features.
AWS Solutions Architect Matt Tavis reviews high availability features for Microsoft Windows Server and SQL Server running on the AWS cloud. Windows Server Failover Clustering (WSFC) and SQL AlwaysOn Availability Groups are part of the underpinnings for many enterprise-class solutions, including Microsoft SharePoint and .NET applications. We will walk through an example implementation and share templates and sample code to help you deploy high availability architectures. Please review this virtual event geared for a technical audience.
Dev ops on aws deep dive on continuous delivery - TorontoAmazon Web Services
Today’s cutting-edge companies have software release cycles measured in days instead of months. This agility is enabled by the DevOps practice of continuous delivery, which automates building, testing, and deploying all code changes. This automation helps you catch bugs sooner and accelerates developer productivity. In this session, we’ll share the processes that Amazon’s engineers use to practice DevOps and discuss how you can bring these processes to your company by using a new set of AWS tools (AWS CodePipeline and AWS CodeDeploy). These services were inspired by Amazon's own internal developer tools and DevOps culture.
DevOps on AWS: Deep Dive on Continuous Delivery and the AWS Developer ToolsAmazon Web Services
Today’s cutting-edge companies have software release cycles measured in days instead of months. This agility is enabled by the DevOps practice of continuous delivery, which automates building, testing, and deploying all code changes. This automation helps you catch bugs sooner and accelerates developer productivity. In this session, we’ll share the processes that Amazon’s engineers use to practice DevOps and discuss how you can bring these processes to your company by using a new set of AWS tools (AWS CodePipeline and AWS CodeDeploy). These services were inspired by Amazon's own internal developer tools and DevOps culture.
Thinking through how you want to run Microsoft Windows Server and application workloads on AWS is straightforward, when you have a game plan. Understanding which service to leverage– like Amazon EC2, Amazon RDS, and Directory Services to name a few – will accelerate the process further. There are also a number of new enhancements to help make things even easier. In this session we will walk through how to think about mapping to the various AWS services available so you can get your deployment or migration project off to the right start. Think of this session as the decoder ring between your on-premises deployment and what you can expect from the AWS cloud for your Microsoft Windows Server and applications.
Amazon Enterprise Applications deliver secure managed desktop and productivity capabilities run on the AWS cloud. These services make it easy for organizations to support a modern workforce, offering flexibility and global scale, keeping data secure, and providing integration with existing IT assets. Come and learn more about Amazon Enterprise Applications, how they are being used today, and how easy it is to get started. This session is for IT professionals and business decision makers interested in learning how to simplify desktop management and productivity for their organizations.
SRV403 Deep Dive on Object Storage: Amazon S3 and Amazon GlacierAmazon Web Services
In this session, storage experts will walk you through Amazon S3 and Amazon Glacier, bulk data repositories that can deliver 99.999999999% durability and scale past trillions of objects worldwide – with cost points competitive against tape archives. Learn about the different ways you can accelerate data transfer into S3 and get a close look at new tools to secure and manage your data more efficiently. See how Amazon Athena runs serverless analytics on your data and hear about expedited and bulk retrievals from Amazon Glacier. Learn how AWS customers have built solutions that turn their data from a cost into a strategic asset, and bring your toughest questions straight to our experts.
AWS APAC Webinar Week - Maintaining Performance & Availability While Lowering...Amazon Web Services
AWS provides you several pricing options that can help you significantly reduce your overall IT cost, including On-Demand Instances, Spot Instances, and Reserved Instances. This session covers high-level architectures and when to use and not to use each of the pricing models for components of those architectures. We walk through several customer examples to illustrate when to use each pricing option. Additionally, we walk through tools that may be useful to determine when to use each pricing model. This session is aimed at technically savvy managers and engineers who need to reduce their cloud spending
With AWS, you can choose the right storage service like including Amazon Simple Storage Service (Amazon S3) and Amazon Elastic Block Storage (Amazon EBS) for the right use case. This session shows the range of AWS choices—from object storage to block storage—that are available to you. The sessions will also include specifics about real-world deployments from customers who are using Amazon S3, Amazon EBS, Amazon Glacier, and AWS Storage Gateway.
Amazon Kinesis provides services for you to work with streaming data on AWS. Learn how to load streaming data continuously and cost-effectively to Amazon S3 and Amazon Redshift using Amazon Kinesis Firehose without writing custom stream processing code. Get an introduction to building custom stream processing applications with Amazon Kinesis Streams for specialized needs.
Amazon Kinesis Analytics is the easiest way to process streaming data in real time with standard SQL without having to learn new programming languages or processing frameworks. Amazon Kinesis analytics enables you to create and run SQL queries on streaming data so that you can gain actionable insights and respond to your business and customer needs promptly. In this session, we will provide an overview of the capabilities of the Amazon Kinesis Analytics. We will show you how you can build an entire stream processing pipeline to collect, ingest, process, and emit streaming data using Amazon Kinesis Analytics, Amazon Kinesis Firehose, and Amazon Kinesis Streams.
Shared Responsibility and Setting Up Secure Account StructuresAmazon Web Services
In addition to discussing the AWS Shared Responsibility Model in detail for Infrastructure, Container and Abstract Services, we present a reference architecture for a secure, multi-account enterprise structure, including Mandatory Access Control for logging and separation assurance for different groups and functions within an organisation.
Join us to learn about the state of serverless computing from Dr. Tim Wagner, General Manager of AWS Lambda. Dr. Wagner discusses the latest developments from AWS Lambda and the serverless computing ecosystem. He talks about how serverless computing is becoming a core component in how companies build and run their applications and services, and he also discusses how serverless computing will continue to evolve.
(SEC310) Keeping Developers and Auditors Happy in the CloudAmazon Web Services
Often times, developers and auditors can be at odds. The agile, fast-moving environments that developers enjoy will typically give auditors heartburn. The more controlled and stable environments that auditors prefer to demonstrate and maintain compliance are traditionally not friendly to developers or innovation. We'll walk through how Netflix moved its PCI and SOX environments to the cloud and how we were able to leverage the benefits of the cloud and agile development to satisfy both auditors and developers. Topics covered will include shared responsibility, using compartmentalization and microservices for scope control, immutable infrastructure, and continuous security testing.
Wild Rydes (www.wildrydes.com) needs your help! With fresh funding from its seed investors, Wild Rydes is seeking to build the world’s greatest mobile/VR/AR unicorn transportation system. The scrappy startup needs a first-class webpage to begin marketing to new users and to begin its plans for global domination. Join us to help Wild Rydes build a website using a serverless architecture. You’ll build a scalable website using services like AWS Lambda, Amazon API Gateway, Amazon DynamoDB, and Amazon S3. Join this workshop to hop on the rocket ship!
To complete this workshop, you'll need:
Your laptop
AWS Account
AWS Command Line Interface
Google Chrome
git
Text Editor
As the number of developers and size of your infrastructure on AWS grows, timely investments in self-service and monitoring can help you scale operations without being the bottleneck. You can standardize infrastructure configurations for commonly used products to enable your customers to self-serve infrastructure needs for their apps. Once these resources are provisioned, you can easily understand how they are connected to administer them effectively, and monitor changes to configurations and evaluate drift. In this session, we will discuss how you can achieve a sophisticated level of standardization, configuration compliance, and monitoring using a combination of AWS Service Catalog, AWS Config, and AWS CloudTrail.
(SEC307) A Progressive Journey Through AWS IAM Federation OptionsAmazon Web Services
AWS Identity and Access Management (IAM) offers a continuum of interfaces and configuration options that enables customers to integrate their unique organizational identity structure and operational processes to the AWS platform. In this session we will evaluate the progressive journey of federation options that most customers go through as they widen their integration with IAM. This will include best practices, lessons learned from the field, and examples of actual customer implementations, covering technologies such as SAML, LDAP, and custom identity brokers.
AWS offers you the ability to add additional layers of security to your data at rest in the cloud, providing access control as well scalable and efficient encryption features. Flexible key management options allow you to choose whether to have AWS manage the encryption keys or to keep complete control over the keys yourself. In this session, you will learn how to secure data when using AWS services. We will discuss data encryption using Key Management Service, S3 access controls, edge and host access security, and database platform security features.
AWS Solutions Architect Matt Tavis reviews high availability features for Microsoft Windows Server and SQL Server running on the AWS cloud. Windows Server Failover Clustering (WSFC) and SQL AlwaysOn Availability Groups are part of the underpinnings for many enterprise-class solutions, including Microsoft SharePoint and .NET applications. We will walk through an example implementation and share templates and sample code to help you deploy high availability architectures. Please review this virtual event geared for a technical audience.
Dev ops on aws deep dive on continuous delivery - TorontoAmazon Web Services
Today’s cutting-edge companies have software release cycles measured in days instead of months. This agility is enabled by the DevOps practice of continuous delivery, which automates building, testing, and deploying all code changes. This automation helps you catch bugs sooner and accelerates developer productivity. In this session, we’ll share the processes that Amazon’s engineers use to practice DevOps and discuss how you can bring these processes to your company by using a new set of AWS tools (AWS CodePipeline and AWS CodeDeploy). These services were inspired by Amazon's own internal developer tools and DevOps culture.
DevOps on AWS: Deep Dive on Continuous Delivery and the AWS Developer ToolsAmazon Web Services
Today’s cutting-edge companies have software release cycles measured in days instead of months. This agility is enabled by the DevOps practice of continuous delivery, which automates building, testing, and deploying all code changes. This automation helps you catch bugs sooner and accelerates developer productivity. In this session, we’ll share the processes that Amazon’s engineers use to practice DevOps and discuss how you can bring these processes to your company by using a new set of AWS tools (AWS CodePipeline and AWS CodeDeploy). These services were inspired by Amazon's own internal developer tools and DevOps culture.
Thinking through how you want to run Microsoft Windows Server and application workloads on AWS is straightforward, when you have a game plan. Understanding which service to leverage– like Amazon EC2, Amazon RDS, and Directory Services to name a few – will accelerate the process further. There are also a number of new enhancements to help make things even easier. In this session we will walk through how to think about mapping to the various AWS services available so you can get your deployment or migration project off to the right start. Think of this session as the decoder ring between your on-premises deployment and what you can expect from the AWS cloud for your Microsoft Windows Server and applications.
Amazon Enterprise Applications deliver secure managed desktop and productivity capabilities run on the AWS cloud. These services make it easy for organizations to support a modern workforce, offering flexibility and global scale, keeping data secure, and providing integration with existing IT assets. Come and learn more about Amazon Enterprise Applications, how they are being used today, and how easy it is to get started. This session is for IT professionals and business decision makers interested in learning how to simplify desktop management and productivity for their organizations.
SRV403 Deep Dive on Object Storage: Amazon S3 and Amazon GlacierAmazon Web Services
In this session, storage experts will walk you through Amazon S3 and Amazon Glacier, bulk data repositories that can deliver 99.999999999% durability and scale past trillions of objects worldwide – with cost points competitive against tape archives. Learn about the different ways you can accelerate data transfer into S3 and get a close look at new tools to secure and manage your data more efficiently. See how Amazon Athena runs serverless analytics on your data and hear about expedited and bulk retrievals from Amazon Glacier. Learn how AWS customers have built solutions that turn their data from a cost into a strategic asset, and bring your toughest questions straight to our experts.
AWS APAC Webinar Week - Maintaining Performance & Availability While Lowering...Amazon Web Services
AWS provides you several pricing options that can help you significantly reduce your overall IT cost, including On-Demand Instances, Spot Instances, and Reserved Instances. This session covers high-level architectures and when to use and not to use each of the pricing models for components of those architectures. We walk through several customer examples to illustrate when to use each pricing option. Additionally, we walk through tools that may be useful to determine when to use each pricing model. This session is aimed at technically savvy managers and engineers who need to reduce their cloud spending
With AWS, you can choose the right storage service like including Amazon Simple Storage Service (Amazon S3) and Amazon Elastic Block Storage (Amazon EBS) for the right use case. This session shows the range of AWS choices—from object storage to block storage—that are available to you. The sessions will also include specifics about real-world deployments from customers who are using Amazon S3, Amazon EBS, Amazon Glacier, and AWS Storage Gateway.
Amazon Kinesis provides services for you to work with streaming data on AWS. Learn how to load streaming data continuously and cost-effectively to Amazon S3 and Amazon Redshift using Amazon Kinesis Firehose without writing custom stream processing code. Get an introduction to building custom stream processing applications with Amazon Kinesis Streams for specialized needs.
Amazon Kinesis Analytics is the easiest way to process streaming data in real time with standard SQL without having to learn new programming languages or processing frameworks. Amazon Kinesis analytics enables you to create and run SQL queries on streaming data so that you can gain actionable insights and respond to your business and customer needs promptly. In this session, we will provide an overview of the capabilities of the Amazon Kinesis Analytics. We will show you how you can build an entire stream processing pipeline to collect, ingest, process, and emit streaming data using Amazon Kinesis Analytics, Amazon Kinesis Firehose, and Amazon Kinesis Streams.
Building a Real-Time Geospatial-Aware Recommendation EngineAmazon Web Services
Recommendation engines help your prospects and customers find the most relevant offers and content. In this presentation, you will learn how to use AWS building blocks to build your own location-aware recommendation engine. You’ll see how to store real-time events using Amazon Kinesis and Amazon DynamoDB. See how to easily move data into Amazon Redshift using Kinesis Firehose. As your site or app rises in popularity, you’ll need to track a wider variety of events and scale to handle traffic and usage spikes. Learn architectural patterns for processing large datasets and high-request volume applications.
Hortonworks Data in Motion Webinar Series Part 7 Apache Kafka Nifi Better Tog...Hortonworks
Apache NiFi, Storm and Kafka augment each other in modern enterprise architectures. NiFi provides a coding free solution to get many different formats and protocols in and out of Kafka and compliments Kafka with full audit trails and interactive command and control. Storm compliments NiFi with the capability to handle complex event processing.
Join us to learn how Apache NiFi, Storm and Kafka can augment each other for creating a new dataplane connecting multiple systems within your enterprise with ease, speed and increased productivity.
https://www.brighttalk.com/webcast/9573/224063
Slides of QCon London 2016 talk. How stream processing is used within the Uber's Marketplace system to solve a wide range problems, including but not limited to realtime indexing and querying of geospatial time series, aggregation and computing of streaming data, and extracting patterns from data streams. In addition, it will touch upon various TimeSeries analysis and predictions. The underlying systems utilize many open source technologies such as Apache Kafka, Samza and Spark streaming.
Day 5 - Real-time Data Processing/Internet of Things (IoT) with Amazon KinesisAmazon Web Services
Amazon Kinesis is a fully managed service for real-time processing of streaming data at massive scale. Amazon Kinesis can collect and process hundreds of terabytes of data per hour from hundreds of thousands of sources, allowing you to easily write applications that process information in real-time, from sources such as web site click-streams, marketing and financial information, manufacturing instrumentation and social media, and operational logs and metering data.
Reasons to attend:
- This session, will provide you with an overview of Amazon Kinesis.
- Learn about sample use cases and real life case studies.
- Learn how Amazon Kinesis can be integrated into your own applications.
Amazon Kinesis is a fully managed service for real-time processing of streaming data at massive scale. Amazon Kinesis can collect and process hundreds of terabytes of data per hour from hundreds of thousands of sources, allowing you to easily write applications that process information in real-time, from sources such as web site click-streams, marketing and financial information, manufacturing instrumentation and social media, and operational logs and metering data.
This introductory webinar, presented by Adi Krishnan, Senior Product Manager for Amazon Kinesis, will provide you with an overview of the service, sample use cases, and some examples of customer experiences with the service so you can better understand its capabilities and see how it might be integrated into your own applications.
Real-time Streaming and Querying with Amazon Kinesis and Amazon Elastic MapRe...Amazon Web Services
Originally, Hadoop was used as a batch analytics tool; however, this is rapidly changing, as applications move towards real-time processing and streaming. Amazon Elastic MapReduce has made running Hadoop in the cloud easier and more accessible than ever. Each day, tens of thousands of Hadoop clusters are run on the Amazon Elastic MapReduce infrastructure by users of every size — from university students to Fortune 50 companies. We recently launched Amazon Kinesis – a managed service for real-time processing of high volume, streaming data. Amazon Kinesis enables a new class of big data applications which can continuously analyze data at any volume and throughput, in real-time. Adi will discuss each service, dive into how customers are adopting the services for different use cases, and share emerging best practices. Learn how you can architect Amazon Kinesis and Amazon Elastic MapReduce together to create a highly scalable real-time analytics solution which can ingest and process terabytes of data per hour from hundreds of thousands of different concurrent sources. Forever change how you process web site click-streams, marketing and financial transactions, social media feeds, logs and metering data, and location-tracking events.
Real-time Streaming and Querying with Amazon Kinesis and Amazon Elastic MapRe...Amazon Web Services
Originally, Hadoop was used as a batch analytics tool; however, this is rapidly changing, as applications move towards real-time processing and streaming. Amazon Elastic MapReduce has made running Hadoop in the cloud easier and more accessible than ever. Each day, tens of thousands of Hadoop clusters are run on the Amazon Elastic MapReduce infrastructure by users of every size — from university students to Fortune 50 companies. We recently launched Amazon Kinesis – a managed service for real-time processing of high volume, streaming data. Amazon Kinesis enables a new class of big data applications which can continuously analyze data at any volume and throughput, in real-time. Adi will discuss each service, dive into how customers are adopting the services for different use cases, and share emerging best practices. Learn how you can architect Amazon Kinesis and Amazon Elastic MapReduce together to create a highly scalable real-time analytics solution which can ingest and process terabytes of data per hour from hundreds of thousands of different concurrent sources. Forever change how you process web site click-streams, marketing and financial transactions, social media feeds, logs and metering data, and location-tracking events.
Introducing Amazon Kinesis: Real-time Processing of Streaming Big Data (BDT10...Amazon Web Services
"This presentation will introduce Kinesis, the new AWS service for real-time streaming big data ingestion and processing.
We’ll provide an overview of the key scenarios and business use cases suitable for real-time processing, and discuss how AWS designed Amazon Kinesis to help customers shift from a traditional batch-oriented processing of data to a continual real-time processing model. We’ll provide an overview of the key concepts, attributes, APIs and features of the service, and discuss building a Kinesis-enabled application for real-time processing. We’ll also contrast with other approaches for streaming data ingestion and processing. Finally, we’ll also discuss how Kinesis fits as part of a larger big data infrastructure on AWS, including S3, DynamoDB, EMR, and Redshift."
Amazon Kinesis Platform – The Complete Overview - Pop-up Loft TLV 2017Amazon Web Services
Real-Time Streaming Analytics became popular amongst many verticals and use cases. In AdTech, Gaming, Financial Service and IoT, AWS customers are leveraging Amazon Kinesis platform to ingest billions of events every day and process them in real-time. In this session, we will discuss Amazon Kinesis Streams, Amazon Kinesis Firehose and Amazon Kinesis Analytics. We will show best practice and design patterns in integrating Amazon Kinesis platform with other services like Amazon EMR, Redshift, Amazon Elasticsearch and AWS lambda as well as 3rd party connectors like storm, Spark and more.
BDA307 Real-time Streaming Applications on AWS, Patterns and Use CasesAmazon Web Services
In this session, you will learn best practices for implementing simple to advanced real-time streaming data use cases on AWS. First, we’ll review decision points on near real-time versus real time scenarios. Next, we will take a look at streaming data architecture patterns that include Amazon Kinesis Analytics, Amazon Kinesis Firehose, Amazon Kinesis Streams, Spark Streaming on Amazon EMR, and other open source libraries. Finally, we will dive deep into the most common of these patterns and cover design and implementation considerations.
Amazon Kinesis is the AWS service for real-time streaming big data ingestion and processing. This talk gives a detailed exploration of Kinesis stream processing. We'll discuss in detail techniques for building, and scaling Kinesis processing applications, including data filtration and transformation. Finally we'll address tips and techniques to emitting data into S3, DynamoDB, and Redshift.
This session is recommended for anyone interested in understanding how to use AWS big data services to develop real-time analytics applications. In this session, you will get an overview of a number of Amazon's big data and analytics services that enable you to build highly scaleable cloud applications that immediately and continuously analyze large sets of distributed data. We'll explain how services like Amazon Kinesis, EMR and Redshift can be used for data ingestion, processing and storage to enable real-time insights and analysis into customer, operational and machine generated data and log files. We'll explore system requirements, design considerations, and walk through a specific customer use case to illustrate the power of real-time insights on their business.
This presentation from the AWS Lab at Cloud Expo Europe 2014 contains details of newly announced services from Amazon Web Services, including Amazon Kinesis, Amazon WorkSpaces, AWS CloudTrail (beta), Amazon AppStream and Amazon RDS for PostgreSQL (beta)
Leapfrog into Serverless - a Deloitte-Amtrak Case Study | Serverless Confere...Gary Arora
This talk was delivered at the Serverless Conference in New York City in 2017. Deloitte and Amtrak built a Serverless Cloud-Native solution on AWS for real-time operational datastore and near real-time reporting data mart that modernized Amtrak's legacy systems & applications. With Serverless solutions, we are able leapfrog over several rungs of computing evolution.
Gary Arora is a Cloud Solutions Architect at Deloitte Consulting, specializing on Azure & AWS.
Learn best practices for building a real-time streaming data architecture on AWS with Spark Streaming, Amazon Kinesis, and Amazon Elastic MapReduce (EMR). Get a closer look at how to ingest streaming data scalably and durably from data producers like mobile devices, servers, and even web browsers, and design a stream processing application with minimal data duplication and exactly-once processing.
Presented by: Guy Ernest, Principal Business Development Manager, Amazon Web Services
Customer Guest: Harry Koch, Solutions Architecture, Philips
BDA307 Real-time Streaming Applications on AWS, Patterns and Use CasesAmazon Web Services
In this session, you will learn best practices for implementing simple to advanced real-time streaming data use cases on AWS. First, we will review decision points on near real-time versus real time scenarios. Next, we will take a look at streaming data architecture patterns that include Amazon Kinesis Analytics, Amazon Kinesis Firehose, Amazon Kinesis Streams, Spark Streaming on Amazon EMR, and other open source libraries. Finally, we will dive deep into the most common of these patterns and cover design and implementation considerations.
(BDT403) Best Practices for Building Real-time Streaming Applications with Am...Amazon Web Services
Amazon Kinesis is a fully managed, cloud-based service for real-time data processing over large, distributed data streams. Customers who use Amazon Kinesis can continuously capture and process real-time data such as website clickstreams, financial transactions, social media feeds, IT logs, location-tracking events, and more. In this session, we first focus on building a scalable, durable streaming data ingest workflow, from data producers like mobile devices, servers, or even a web browser, using the right tool for the right job. Then, we cover code design that minimizes duplicates and achieves exactly-once processing semantics in your elastic stream-processing application, built with the Kinesis Client Library. Attend this session to learn best practices for building a real-time streaming data architecture with Amazon Kinesis, and get answers to technical questions frequently asked by those starting to process streaming events.
Amazon Kinesis is a fully managed service for real-time processing of streaming data at massive scale. In this webinar, developers will learn how to build and deploy a streaming data processing application with Amazon Kinesis. We will cover the following: - A brief overview of Amazon Kinesis and drill down on key technical concepts. - Amazon Kinesis Client Library capabilities that enable customers to build fault tolerant, continuous processing applications that scale elastically. - The role of the supporting connector library for moving data into stores like S3 and Redshift. - Best practices for streaming data ingestion and processing with Amazon Kinesis.
이제 빅데이터란 개념은 익숙한 것이 되었지만 이를 비지니스에 적용하고 최대의 효과를 얻는 방법에 대한 고찰은 여전히 필요합니다. 소중한 데이터를 쉽게 저장 및 분석하고 시각화하는 것은 비즈니스에 대한 통찰을 얻기 위한 중요한 과정입니다.
이 강연에서는 AWS Elastic MapReduce, Amazon Redshift, Amazon Kinesis 등 AWS가 제공하는 다양한 데이터 분석 도구를 활용해 보다 간편하고 빠른 빅데이터 분석 서비스를 구축하는 방법에 대해 소개합니다.
By 2020, 50% of all new software will process machine-generated data of some sort (Gartner). Historically, machine data use cases have required non-SQL data stores like Splunk, Elasticsearch, or InfluxDB.
Today, new SQL DB architectures rival the non-SQL solutions in ease of use, scalability, cost, and performance. Please join this webinar for a detailed comparison of machine data management approaches.
AWS re:Invent 2016: Beeswax: Building a Real-Time Streaming Data Platform on ...Amazon Web Services
Amazon Kinesis is a platform of services for building real-time, streaming data applications in the cloud. Customers can use Amazon Kinesis to collect, stream, and process real-time data such as website clickstreams, financial transactions, social media feeds, application logs, location-tracking events, and more. In this session, we first cover best practices for building an end-to-end streaming data applications using Amazon Kinesis. Next, Beeswax, which provides real-time Bidder as a Service for programmatic digital advertising, will talk about how they built a feature-rich, real-time streaming data solution on AWS using Amazon Kinesis, Amazon Redshift, Amazon S3, Amazon EMR, and Apache Spark. Beeswax will discuss key components of their solution including scalable data capture, messaging hub for archival, data warehousing, near real-time analytics, and real-time alerting.
AWS April 2016 Webinar Series - Getting Started with Real-Time Data Analytics...Amazon Web Services
It is becoming increasingly important to analyze real time streaming data. It allows organizations to remain competitive by uncovering relevant, actionable insights. AWS makes it easy to capture, store, and analyze real-time streaming data.
In this webinar, we will guide you through some of the proven architectures for processing streaming data, using a combination of tools including Amazon Kinesis Streams, AWS Lambda, and Spark Streaming on Amazon Elastic MapReduce (EMR). We will then talk about common use cases and best practices for real-time data analysis on AWS.
Learning Objectives:
Understand how you can analyze real-time data streams using Amazon Kinesis, AWS Lambda, and Spark running on Amazon EMR
Learn use cases and best practices for streaming data applications on AWS
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.
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.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
4. INDEX
A. What is real-time?
B. Examples and Challenges
C. Kinesis and beyond
1. Kinesis Stream
2. Kinesis Firehose
3. Kinesis Analytics (SQL)
4. DynamoDB Streams
5. ElasticSearch
6. IoT Rule Engine
D. Demo
5. v
Examples
• Algorithmic Trading < 10 msec
• Real time bidding < 100 msec
• Common IoT scenarios < 5 to 10 sec
• Infrastructure Monitoring Dashboard < 1 min
• Google Maps Traffic < 5 mins
• Social Network and Media recommendation < 15 min to a Day
• Most Business Analytics Scenarios < 30 mins
• Social Network listening < Depends on how fast you want to respond>!
6. INDEX
A. What is real-time?
B. Examples and Challenges
C. Kinesis and Beyond
1. Kinesis Stream
2. Kinesis Firehose
3. Kinesis Analytics (SQL)
4. DynamoDB Streams
5. ElasticSearch
6. IoT Rule Engine
D. Demo
8. v
Examples
• Algorithmic Trading < 10 msec
• Real time bidding < 100 msec
• Common IoT scenarios < 5 to 10 sec
• Infrastructure Monitoring Dashboard < 1 min
• Google Maps Traffic < 5 mins
• Social Network and Media recommendation < 15 min to a Day
• Most Business Analytics Scenarios < 30 mins
• Social Network listening < Depends on how fast you want to respond!
10. v
Challenges
A. Speed of Analytics and Response
B. Volume of data
A. Maturity or Capabilities of Analytics Framework
B. Storing and Presentation of results
12. v
Some statistics about what AWS Data Services
• Metering service
• 10s of millions records per second
• Terabytes per hour
• Hundreds of thousands of sources
• Auditors guarantee 100% accuracy at month end
• Data Warehouse
• 100s extract-transform-load (ETL) jobs every day
• Hundreds of thousands of files per load cycle
• Hundreds of daily users
• Hundreds of queries per hour
14. v
Internal AWS Metering Service
Workload
• 10s of millions records/sec
• Multiple TB per hour
• 100,000s of sources
Pain points
• Doesn’t scale elastically
• Customers want real-time
alerts
• Expensive to operate
• Relies on eventually consistent
storage
15. v
Our Big Data Transition
Old requirements
• Capture huge amounts of data and process it in hourly or daily batches
New requirements
• Make decisions faster, sometimes in real-time
• Scale entire system elastically
• Make it easy to “keep everything”
• Multiple applications can process data in parallel
16. A General Purpose Data Flow
Many different technologies, at different stages of evolution
Client/Sensor Aggregator Continuous
Processing
Storage Analytics +
Reporting
?
17. v
Kinesis
Movement or activity in response to a stimulus.
A fully managed service for real-time processing of high-
volume, streaming data. Kinesis can store and process
terabytes of data an hour from hundreds of thousands of
sources. Data is replicated across multiple Availability
Zones to ensure high durability and availability.
19. Scenarios Accelerated Ingest-Transform-Load Continual Metrics/ KPI Extraction Responsive Data Analysis
Data Types
IT infrastructure, Applications logs, Social media, Fin. Market data, Web Clickstreams, Sensors, Geo/Location data
Software/
Technology
IT server , App logs ingestion IT operational metrics dashboards Devices / Sensor Operational
Intelligence
Digital Ad Tech./
Marketing
Advertising Data aggregation Advertising metrics like coverage,
yield, conversion
Analytics on User engagement with
Ads, Optimized bid/ buy engines
Financial Services Market/ Financial Transaction order data
collection
Financial market data metrics Fraud monitoring, and Value-at-Risk
assessment, Auditing of market order
data
Consumer Online/
E-Commerce
Online customer engagement data
aggregation
Consumer engagement metrics like
page views, CTR
Customer clickstream analytics,
Recommendation engines
Customer Scenarios across Industry Segments
1 2 3
20. What Biz. Problem needs to be solved?
Mobile/ Social Gaming Digital Advertising Tech.
Deliver continuous/ real-time delivery of game insight
data by 100’s of game servers
Generate real-time metrics, KPIs for online ad performance
for advertisers/ publishers
Custom-built solutions operationally complex to
manage, & not scalable
Store + Forward fleet of log servers, and Hadoop based
processing pipeline
• Delay with critical business data delivery
• Developer burden in building reliable, scalable
platform for real-time data ingestion/ processing
• Slow-down of real-time customer insights
• Lost data with Store/ Forward layer
• Operational burden in managing reliable, scalable platform
for real-time data ingestion/ processing
• Batch-driven real-time customer insights
Accelerate time to market of elastic, real-time
applications – while minimizing operational overhead
Generate freshest analytics on advertiser performance to
optimize marketing spend, and increase responsiveness to
clients
21. INDEX
A. What is real-time?
B. Examples and Challenges
C. Kinesis and Beyond
1. Kinesis Stream
2. Kinesis Firehose
3. Kinesis Analytics (SQL)
4. DynamoDB Streams
5. ElasticSearch
6. IoT Rule Engine
D. Demo
22. INDEX
A. What is real-time?
B. Examples and Challenges
C. Kinesis and Beyond
1. Kinesis Stream
2. Kinesis Firehose
3. Kinesis Analytics (SQL)
4. DynamoDB Streams
5. ElasticSearch
6. IoT Rule Engine
D. Demo
23. v
Amazon Kinesis Streams
Build your own data streaming applications
• Easy administration: Simply create a new stream, and set the desired level of capacity
with shards. Scale to match your data throughput rate and volume.
• Build real-time applications: Perform continual processing on streaming big data using
Kinesis Client Library (KCL), Apache Spark/Storm, AWS Lambda, and more.
• Low cost: Cost-efficient for workloads of any scale.
24. Kinesis Architecture
Amazon Web Services
AZ AZ AZ
Durable, highly consistent storage replicates data
across three data centers (availability zones)
Aggregate and
archive to S3
Millions of
sources producing
100s of terabytes
per hour
Front
End
Authentication
Authorization
Ordered stream
of events supports
multiple readers
Real-time
dashboards
and alarms
Machine learning
algorithms or
sliding window
analytics
Aggregate analysis
in Hadoop or a
data warehouse
Inexpensive: $0.028 per million puts
Run code in response to an event and
automatically manage compute.
26. Kinesis Stream:
Managed ability to capture and store data
• Streams are made of Shards
• Each Shard ingests data up to
1MB/sec, and up to 1000 TPS
• Each Shard emits up to 2 MB/sec
• All data is stored for 24 hours
• Scale Kinesis streams by adding or
removing Shards
• Replay data inside of 24Hr. Window
27. Putting Data into Kinesis
Simple Put interface to store data in Kinesis
• Producers use a PUT call to store data in a Stream
• PutRecord {Data, PartitionKey, StreamName}
• A Partition Key is supplied by producer and used to
distribute the PUTs across Shards
• Kinesis MD5 hashes supplied partition key over the hash
key range of a Shard
• A unique Sequence # is returned to the Producer upon a
successful PUT call
29. Building Kinesis Processing Apps: Kinesis Client Library
Client library for fault-tolerant, at least-once, Continuous Processing
o Java client library, source available on Github
o Build & Deploy app with KCL on your EC2 instance(s)
o KCL is intermediary b/w your application & stream
Automatically starts a Kinesis Worker for each shard
Simplifies reading by abstracting individual shards
Increase / Decrease Workers as # of shards changes
Checkpoints to keep track of a Worker’s location in the
stream, Restarts Workers if they fail
o Integrates with AutoScaling groups to redistribute workers to
new instances
30. Amazon Kinesis Connector Library
Customizable, Open Source code to Connect Kinesis with S3, Redshift, DynamoDB
S3
DynamoDB
Redshift
Kinesis
ITransformer
• Defines the
transformation
of records
from the
Amazon
Kinesis
stream in
order to suit
the user-
defined data
model
IFilter
• Excludes
irrelevant
records from
the
processing.
IBuffer
• Buffers the set
of records to
be processed
by specifying
size limit (# of
records)&
total byte
count
IEmitter
• Makes client
calls to other
AWS services
and persists
the records
stored in the
buffer.
31. v
USE Cases
Ultra Low Latency Analytics (seconds)
Complex Computations
• => Complex algorithm execution
• => Tuple Processing – every bit of data processed independently vs.
aggregation where it goes from 1st row to last row.
• => Moving Window Analysis – moving car from 2nd to 3rd min and then
5th to 6th min.
32. INDEX
A. What is real-time?
B. Examples and Challenges
C. Kinesis and Beyond
1. Kinesis Stream
2. Kinesis Firehose
3. Kinesis Analytics (SQL)
4. DynamoDB Streams
5. ElasticSearch
6. IoT Rule Engine
D. Demo
33. v
Amazon Kinesis Firehose
Load massive volumes of streaming data into Amazon S3 and Amazon Redshift
• Zero administration: Capture and deliver streaming data into S3, Redshift, and other
destinations without writing an application or managing infrastructure.
• Direct-to-data store integration: Batch, compress, and encrypt streaming data for
delivery into data destinations in as little as 60 secs using simple configurations.
• Seamless elasticity: Seamlessly scales to match data throughput w/o intervention
Capture and submit streaming
data to Firehose
Firehose loads streaming data
continuously into S3 and Redshift
Analyze streaming data using your favorite BI
tools
34. v
Amazon Kinesis Firehose to Redshift
A two-step process
• Use customer-provided S3 bucket as an intermediate destination
• Still the most efficient way to do large scale loads to Redshift.
• Never lose data, always safe, and available in your S3 bucket.
• Firehose issues customer-provided COPY command synchronously. It
continuously issues a COPY command once the previous COPY
command is finished and acknowledged back from Redshift.
1
2
35. v
USE Cases
Kinesis Firehose used when needed to do batch with more frequency. As
long as analysis can be done with SQL.
Micro-batching scenarios with latencies more 60 second tolerable
In case of Redshift Target – Analytics that can be achieved with standard SQL
and User Defined Functions (UDFs)
Most “Real-Time Business Insights”
kind of scenarios can be easily supported with
Kinesis Firehose + Redshift!
36. INDEX
A. What is real-time?
B. Examples and Challenges
C. Kinesis and Beyond
1. Kinesis Stream
2. Kinesis Firehose
3. Kinesis Analytics (SQL)
4. DynamoDB Streams
5. ElasticSearch
6. IoT Rule Engine
D. Demo
37. v
Amazon Kinesis Analytics
Analyze data streams continuously with standard SQL
• Apply SQL on streams: Easily connect to data streams and apply existing SQL skills.
• Build real-time applications: Perform continual processing on streaming big data
with sub-second processing latencies
• Scale elastically: Elastically scales to match data throughput without any operator
intervention.
Announcement Only!
Amazon Confidential
Connect to Kinesis streams,
Firehose delivery streams
Run standard SQL queries against
data streams
Kinesis Analytics can send processed data to
analytics tools so you can create alerts and
respond in real-time
38. v
USE Cases
Low latency time series analytics
Analytics that can be achieved with confines of supported SQL
• - Running Totals
• - Moving Averages
• - Number of people entering a stadium
39. INDEX
A. What is real-time?
B. Examples and Challenges
C. Kinesis and Beyond
1. Kinesis Stream
2. Kinesis Firehose
3. Kinesis Analytics (SQL)
4. DynamoDB Streams
5. ElasticSearch
6. IoT Rule Engine
D. Demo
40. v
Amazon DynamoDB Streams – time-ordered sequence of item-
level changes
• Time and partition ordered log
• Provides a stream of inserts, deletes, updates
• Old item
• New item
• Primary key
• Change type
• Stream items delivered exactly once
• Streams are asynchronous
• Scales with your table
DynamoDB DynamoDB Streams
41. v
USE Cases
Ultra Low Latency Analytics (seconds) when data is available in
Kinesis and DynamoDB Stream, e.g.
Energy meters data coming into Kinesis, to continuously update
billing info.
Changes to social network profile stored in DynamoDB, to transmit
updates to connection immediately (e.g. user adds a new job to his
profile).
42. INDEX
A. What is real-time?
B. Examples and Challenges
C. Kinesis and Beyond
1. Kinesis Stream
2. Kinesis Firehose
3. Kinesis Analytics (SQL)
4. DynamoDB Stream and Kinesis Stream processing using Lambda
5. ElasticSearch
6. IoT Rule Engine
D. Demo
43. v
How Elasticsearch can help
• Combined with Logstash and Kibana, the ELK stack provides a tool for
real-time analytics and data visualization
53. v
USE Cases
Real-Time Dashboards (Kibana)
Alerting (Percolator API)
Real-Text Analytics, as in Social Media Listening
Real-Time Geospatial Queries and Geospatial Analysis
54. INDEX
A. What is real-time?
B. Examples and Challenges
C. Kinesis & Beyond
1. Kinesis Stream
2. Kinesis Firehose
3. Kinesis Analytics (SQL)
4. DynamoDB Stream and Kinesis Stream processing using Lambda
5. ElasticSearch
6. IoT Rule Engine
D. Demo
55. v
AWS IoT
“Securely connect one or one-billion devices to AWS,
so they can interact with applications and other devices”
56. v
AWS IoT
DEVICE SDK
Set of client libraries to connect,
authenticate and exchange
messages
DEVICE GATEWAY
Communicate with devices via
MQTT and HTTP
AUTHENTICATION
AUTHORIZATION
Secure with mutual
authentication and encryption
RULES ENGINE
Transform messages
based on rules and route
to AWS Services
AWS Services
- - - - -
3P Services
DEVICE SHADOW
Persistent thing state during
intermittent connections
APPLICATIONS
AWS IoT API
DEVICE REGISTRY
Identity and Management of
your things
57. v
USE Cases
Processing sensor data (millions of data points from hundreds of thousands of
sensors) in real time for Alerting
Redirecting sensor data for multi-data-point analysis to Kinesis, DynamoDB
60. INDEX
A. What is real-time?
B. Examples and Challenges
C. Kinesis & Beyond
1. Kinesis Stream
2. Kinesis Firehose
3. Kinesis Analytics (SQL)
4. DynamoDB Stream and Kinesis Stream processing using Lambda
5. ElasticSearch
6. IoT Rule Engine
D. Demo
61. v
Demo Time.
Website - https://secure.amitksh.net/cdn/webinarWeek.html
Real time updates from Kinesis - https://secure.amitksh.net/rtChart.html
65. Online Labs & Training
Gain confidence and hands-on
experience with AWS.
Watch free Instructional Videos and
explore Self-Paced Labs
Instructor Led Classes
Learn how to design, deploy and
operate highly available, cost-effective
and secure applications on AWS in
courses led by qualified AWS instructors
Validate your technical expertise
with AWS and use practice exams
to help you prepare for AWS
Certification
AWS Certification
More info at http://aws.amazon.com/training