Amazon QuickSight is a fast, cloud-powered business analytics service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data. Using our cloud-based service you can easily connect to your data, perform advanced analysis, and create stunning visualizations and rich dashboards that can be accessed from any browser or mobile device.
NEW LAUNCH! Intro to Amazon Athena. Easily analyze data in S3, using SQL.Amazon Web Services
Amazon Athena is a new interactive query service that makes it easy to analyze data in Amazon S3, using standard SQL. Athena is serverless, so there is no infrastructure to setup or manage, and you can start analyzing your data immediately. You don’t even need to load your data into Athena, it works directly with data stored in S3.
In this session, we will show you how easy is to start querying your data stored in Amazon S3, with Amazon Athena. First we will use Athena to create the schema for data already in S3. Then, we will demonstrate how you can run interactive queries through the built-in query editor. We will provide best practices and use cases for Athena. Then, we will talk about supported queries, data formats, and strategies to save costs when querying data with Athena.
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.
Convert and Migrate Your NoSQL Database or Data Warehouse to AWS - May 2017 A...Amazon Web Services
Learning Objectives:
- Understand the use cases for migrating or replicating databases to the cloud
- Learn about the benefits of cloud-native databases for performance and costs reduction
- See how AWS Database Migration Service helps with your migration
- See how AWS Schema Conversion Tool makes conversions simple and quick
Moving or replicating your databases to the cloud should be simple and inexpensive. AWS has recently enhanced the AWS Database Migration Service and the AWS Schema Conversion Tool with new data sources to increase your migration options. You can now export from MongoDB databases and Greenplum, IBM Netezza, HPE Vertica, Teradata, Oracle DW and Microsoft SQL Server data warehouses to AWS. Learn how to export and migrate your data and procedural code with minimal downtime to the cloud database of your choice, including cloud-native offerings such as Amazon Aurora, Amazon DynamoDB and Amazon Redshift.
Getting Started with Serverless Architectures - August 2016 Monthly Webinar S...Amazon Web Services
Serverless architectures allow you to build and run applications and services without having to manage infrastructure. With serverless architectures, your application still runs on servers, but all the server management is done by AWS .
In this webinar, you will learn how to build applications and services using a serverless architecture. We will discuss how you can use AWS Lambda to run code for any type of application or backend service; use Amazon DynamoDB to store application data with high scalability and redundancy; and use Amazon API Gateway to create and manage secure API endpoints. We will run through a demo setting up a web application using this architecture, and we will discuss best practices and patterns used by our customers to run serverless applications.
Learning Objectives:
• Understand the basics of serverless architectures
• Learn how to use Lambda, API Gateway, and DynamoDB to run web applications
NEW LAUNCH! Intro to Amazon Athena. Easily analyze data in S3, using SQL.Amazon Web Services
Amazon Athena is a new interactive query service that makes it easy to analyze data in Amazon S3, using standard SQL. Athena is serverless, so there is no infrastructure to setup or manage, and you can start analyzing your data immediately. You don’t even need to load your data into Athena, it works directly with data stored in S3.
In this session, we will show you how easy is to start querying your data stored in Amazon S3, with Amazon Athena. First we will use Athena to create the schema for data already in S3. Then, we will demonstrate how you can run interactive queries through the built-in query editor. We will provide best practices and use cases for Athena. Then, we will talk about supported queries, data formats, and strategies to save costs when querying data with Athena.
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.
Convert and Migrate Your NoSQL Database or Data Warehouse to AWS - May 2017 A...Amazon Web Services
Learning Objectives:
- Understand the use cases for migrating or replicating databases to the cloud
- Learn about the benefits of cloud-native databases for performance and costs reduction
- See how AWS Database Migration Service helps with your migration
- See how AWS Schema Conversion Tool makes conversions simple and quick
Moving or replicating your databases to the cloud should be simple and inexpensive. AWS has recently enhanced the AWS Database Migration Service and the AWS Schema Conversion Tool with new data sources to increase your migration options. You can now export from MongoDB databases and Greenplum, IBM Netezza, HPE Vertica, Teradata, Oracle DW and Microsoft SQL Server data warehouses to AWS. Learn how to export and migrate your data and procedural code with minimal downtime to the cloud database of your choice, including cloud-native offerings such as Amazon Aurora, Amazon DynamoDB and Amazon Redshift.
Getting Started with Serverless Architectures - August 2016 Monthly Webinar S...Amazon Web Services
Serverless architectures allow you to build and run applications and services without having to manage infrastructure. With serverless architectures, your application still runs on servers, but all the server management is done by AWS .
In this webinar, you will learn how to build applications and services using a serverless architecture. We will discuss how you can use AWS Lambda to run code for any type of application or backend service; use Amazon DynamoDB to store application data with high scalability and redundancy; and use Amazon API Gateway to create and manage secure API endpoints. We will run through a demo setting up a web application using this architecture, and we will discuss best practices and patterns used by our customers to run serverless applications.
Learning Objectives:
• Understand the basics of serverless architectures
• Learn how to use Lambda, API Gateway, and DynamoDB to run web applications
BDA302 Deep Dive on Migrating Big Data Workloads to Amazon EMRAmazon Web Services
Customers are migrating their analytics, data processing (ETL), and data science workloads running on Apache Hadoop, Spark, and data warehouse appliances from on-premise deployments to Amazon EMR in order to save costs, increase availability, and improve performance. Amazon EMR is a managed service that lets you process and analyze extremely large data sets using the latest versions of over 15 open-source frameworks in the Apache Hadoop and Spark ecosystems. This session will focus on identifying the components and workflows in your current environment and providing the best practices to migrate these workloads to Amazon EMR. We will explain how to move from HDFS to Amazon S3 as a durable storage layer, and how to lower costs with Amazon EC2 Spot instances and Auto Scaling. Additionally, we will go over common security recommendations and tuning tips to accelerate the time to production.
Database Migration: Simple, Cross-Engine and Cross-Platform Migrations with M...Amazon Web Services
Learn about the new AWS Database Migration Service, which helps you migrate databases with minimal downtime from on-premises and Amazon EC2 environments to Amazon RDS, Amazon Redshift, Amazon Aurora and EC2 databases. We discuss homogeneous (e.g. Oracle-to-Oracle, PostgreSQL-to-PostgreSQL, etc.) and heterogeneous (e.g. Oracle to Aurora, SQL Server to MariaDB) database migrations. We also talk about the new AWS Schema Conversion Tool that saves you development time when migrating your Oracle and SQL Server database schemas, including PL/SQL and T-SQL procedural code, to their MySQL, MariaDB and Aurora equivalents.
Many businesses want the benefits of AWS like lower cost, flexibility, and agility, but aren’t sure if performing the migration in-house is the best option. By leveraging the expertise of an AWS Premier Consulting Partner like Datapipe, organizations can take the burden off of IT and experience a smooth, automated transition to the cloud. In our upcoming webinar, AWS, Datapipe, and Motus, a vehicle management and reimbursement platform, explain how Motus migrated and automated their workloads on the AWS Cloud, which resulted in a 20% reduction in operational costs. Datapipe takes a 3-fold approach to migration. Using services such as Amazon Route 53 and Amazon CloudWatch, Datapipe will plan, build, and run your new cloud environment on AWS.
Join us to Learn:
• How Datapipe works with organizations to plan, build, and run their new, efficient cloud environments
• How to migrate and manage your organization’s environments to lower operational costs and optimize efficiency
• How Motus lowered their operational IT costs by 20% by automating many of their processes
Who Should Attend:
Cloud Owners, Cloud Architects, IT Administers, IT Architects, Information Architects, DevOps Managers
AWS Speaker: Sai Reddy Thangirala, Solution Architect
Partner Speaker Name: Eric Sakowski, Lead Automation Engineer, DevOps and Automation
Customer Speaker Name: Rick Blaisdell, Chief Technology Officer, Motus
AWS re:Invent 2016: Workshop: Building Your First Big Data Application with A...Amazon Web Services
Want to get ramped up on how to use Amazon's big data web services and launch your first big data application on AWS? Join us in this workshop as we build a big data application in real time using Amazon EMR, Amazon Redshift, Amazon Kinesis, Amazon DynamoDB, and Amazon S3. We review architecture design patterns for big data solutions on AWS, and give you access to a take-home lab so that you can rebuild and customize the application yourself.
Announcing Lambda @ the Edge - December 2016 Monthly Webinar SeriesAmazon Web Services
This session introduces Lambda@Edge, a new AWS Lambda feature that allows developers to perform simple computations at AWS edge locations in response to CloudFront events. This will be of interest to developers who want to build low-latency, customized web experiences. We cover product functionality and details of the programming model, and we walk through potential use cases.
Learning Objectives:
• Learn about the capabilities, features and benefits of AWS Lambda@Edge
• Learn about the different use cases
• Learn how to get started using AWS Lambda@Edge
Amazon Aurora is a relational database engine that combines the speed and reliability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora is designed to be compatible with MySQL 5.6, so that existing MySQL applications and tools can run without requiring modification. AWS Database Migration Service helps you migrate databases to AWS easily and securely. The source database remains fully operational during the migration, minimizing downtime to applications that rely on the database.
Presented by: Danilo Poccia, Technical Evangelist, Amazon Web Services
AWS January 2016 Webinar Series - Getting Started with Big Data on AWSAmazon Web Services
With hundreds of new and sometimes disparate tools, it’s hard to keep pace. Amazon Web Services provides a broad and fully integrated portfolio of cloud computing services to help you build, secure and deploy your big data applications.
Attend this webinar to get an overview of the different big data options available in the AWS Cloud – including popular big data frameworks such as Hadoop, Spark, NoSQL databases, and more. Learn about ideal use cases, cases to avoid, performance, interfaces, and more. Finally, learn how you can build valuable applications with a real-life example.
Learning Objectives:
Learn about big data tools available at AWS
Understand ideal use cases
Learn some of the key considerations such as performance, scalability, elasticity and availability, when selecting big data tools
Who Should Attend:
Data Architects, Data Scientists, Developers
APAC Principal Solutions Architect, Johnathon Meichtry will run through the highlights of 2015 showcasing the biggest announcements and how customers are using these new features. This session will cover the entire breadth of the AWS platform, and is a chance to get a high level overview of all of the announcements, feature updates and new services that AWS has launched in 2015.
Amazon Aurora is a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. This session introduces you to Amazon Aurora, explains common use cases for the service, and helps you get started with building your first Amazon Aurora–powered application.
Learn about the new AWS Database Migration Service, which helps you migrate databases with minimal downtime from on-premises and Amazon EC2 environments to Amazon RDS, Amazon Redshift, Amazon Aurora and EC2 databases. We discuss homogeneous (e.g. Oracle-to-Oracle, PostgreSQL-to-PostgreSQL, etc.) and heterogeneous (e.g. Oracle to Aurora, SQL Server to MariaDB) database migrations. We also talk about the new AWS Schema Conversion Tool that saves you development time when migrating your Oracle and SQL Server database schemas, including PL/SQL and T-SQL procedural code, to their MySQL, MariaDB and Aurora equivalents.
NEW LAUNCH! Introducing AWS Batch: Easy and efficient batch computingAmazon Web Services
AWS Batch is a fully-managed service that enables developers, scientists, and engineers to easily and efficiently run batch computing workloads of any scale on AWS. AWS Batch automatically provisions compute resources and optimizes the workload distribution based on the quantity and scale of the workloads. With AWS Batch, there is no need to install or manage batch computing software, allowing you to focus on analyzing results and solving problems. AWS Batch plans, schedules, and executes your batch computing workloads across the full range of AWS compute services and features, such as Amazon EC2, Spot Instances, and AWS Lambda. AWS Batch reduces operational complexities, saving time and reducing costs. In this session, Principal Product Managers Jamie Kinney and Dougal Ballantyne describe the core concepts behind AWS Batch and details of how the service functions. The presentation concludes with relevant use cases and sample code.
El almacenamiento en la nube es un componente crítico de la informática en la nube, que guarda la información que utilizan las aplicaciones. El análisis de big data, los almacenes de datos, el Internet de las cosas, las bases de datos y las aplicaciones de backup y archivado dependen de algún tipo de arquitectura de almacenamiento de datos. El almacenamiento en la nube, por lo general, es más fiable, escalable y seguro que los sistemas de almacenamiento en las instalaciones tradicionales.
AWS ofrece una gama completa de servicios de almacenamiento en la nube para respaldar los requisitos de conformidad de las aplicaciones y el archivado. Seleccione entre servicios de almacenamiento de objetos, archivos y por bloques, así como opciones de migración de datos a la nube para comenzar a diseñar las bases de su entorno de TI en la nube.
Building Distributed Applications with AWS Step FunctionsAmazon Web Services
This talk covers how you can use the new AWS Step Functions service to coordinate different components of your application, maintain state, and build sophisticated serverless solutions.
AWS re:Invent 2016: Driving Innovation with Big Data and IoT (GPSST304)Amazon Web Services
With unforeseen competitive threats and potential market disruptions, enterprises are seeking to innovate for the benefit of their customers. Business transformation in the digital age requires the successful use of new technologies including the cloud, IoT, and Big Data. Attend this session to learn more about how AWS can help organizations innovate faster around IoT and Big Data. We dive into specific opportunities and approaches for managing billions of connected devices and associated big data workloads on the cloud.
Amazon Aurora New Features - September 2016 Webinar SeriesAmazon Web Services
Amazon Aurora is a fully managed MySQL-compatible database with high-end commercial database features and performance at one-tenth the cost. Since launching Aurora a year ago we have added many new capabilities and features. Some of these features include encryption, database snapshot sharing, enhanced monitoring, cross-region replication, S3 binary snapshot ingestion and customized failover priority. In this session we'll demonstrate how these features work and discuss how you can make the best use of them.
Learning Objectives:
• Learn about the newly added features of Aurora
• Learn how to use those features
• Learn when and why to use those features
Who Should Attend:
• IT Managers, DBAs, Enterprise and Solution Architects, Devops Engineers and Developers
database migration simple, cross-engine and cross-platform migrations with ...Amazon Web Services
Learn how you can migrate databases with minimal downtime from on-premises and Amazon EC2 environments to Amazon RDS, Amazon Redshift, Amazon Aurora and EC2 databases using AWS Database Migration Service. We discuss homogeneous (e.g. Oracle-to-Oracle, PostgreSQL-to-PostgreSQL, etc.) and heterogeneous (e.g. Oracle to Aurora, SQL Server to MariaDB) database migrations. We also talk about the new AWS Schema Conversion Tool that saves you development time when migrating your Oracle and SQL Server database schemas, including PL/SQL and T-SQL procedural code, to their MySQL, MariaDB and Aurora equivalents. Best of all, we spend most of the time demonstrating the product and showing use cases designed to help your business.”
The State of Serverless Computing | AWS Public Sector Summit 2017Amazon Web Services
oin us to learn about the state of serverless computing from Dougal Ballantyne, Principal Product Manager, Serverless. Dougal Ballantyne 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. Learn More: https://aws.amazon.com/government-education/
Planning datacenter migrations can involve thousands of workloads and tens of thousands of servers and are often deeply interdependent. Application discovery and dependency mapping are important early first steps in the migration process, but difficult to perform at scale due to the lack of automated tools. AWS Application Discovery Service is a new service (coming soon) that automatically identifies data center applications and dependencies, and baselines application health and performance to help plan your application migration to AWS quickly and reliably. This talk introduces the new Application Discovery Service capabilities for simplifying the planning process for data center and large scale migrations to AWS. We will discuss how you can use the AWS Application Discovery Service data service to examine the applications running your data center, their attributes, and their dependencies and then use this information to help reduce the time, cost, and risk of migrating applications to AWS.
AWS re:Invent 2016: How to Scale and Operate Elasticsearch on AWS (DEV307)Amazon Web Services
Elasticsearch has quickly become the leading open source technology for scaling search and building document services on. Many software providers have come to rely on it to serve the needs of high-performance, production applications.
In this talk, we’ll go deep on lessons learned from three years in production scaling from a few shards to more than 100 spread across 100s of nodes on AWS--to serve real-time queries against 100s of millions of documents.
Attendees will learn:
* How to capacity plan for ES on AWS
* How to scale and reshard on AWS with zero downtime
* What AWS and ES metrics to collect and alert on
* Tips on day to day ES operations
Session sponsored by SignalFx.
Amazon QuickSight is a fast, cloud-powered business intelligence (BI) service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data. In this session, we demonstrate how you can point Amazon QuickSight to AWS data stores, flat files, or other third-party data sources and begin visualizing your data in minutes. We also introduce SPICE - a new Super-fast, Parallel, In-memory, Calculation Engine in Amazon QuickSight, which performs advanced calculations and render visualizations rapidly without requiring any additional infrastructure, SQL programming, or dimensional modeling, so you can seamlessly scale to hundreds of thousands of users and petabytes of data. Lastly, you will see how Amazon QuickSight provides you with smart visualizations and graphs that are optimized for your different data types, to ensure the most suitable and appropriate visualization to conduct your analysis, and how to share these visualization stories using the built-in collaboration tools.
Presented by: Matthew McClean, AWS Partner Solutions Architect, Amazon Web Services
BDA302 Deep Dive on Migrating Big Data Workloads to Amazon EMRAmazon Web Services
Customers are migrating their analytics, data processing (ETL), and data science workloads running on Apache Hadoop, Spark, and data warehouse appliances from on-premise deployments to Amazon EMR in order to save costs, increase availability, and improve performance. Amazon EMR is a managed service that lets you process and analyze extremely large data sets using the latest versions of over 15 open-source frameworks in the Apache Hadoop and Spark ecosystems. This session will focus on identifying the components and workflows in your current environment and providing the best practices to migrate these workloads to Amazon EMR. We will explain how to move from HDFS to Amazon S3 as a durable storage layer, and how to lower costs with Amazon EC2 Spot instances and Auto Scaling. Additionally, we will go over common security recommendations and tuning tips to accelerate the time to production.
Database Migration: Simple, Cross-Engine and Cross-Platform Migrations with M...Amazon Web Services
Learn about the new AWS Database Migration Service, which helps you migrate databases with minimal downtime from on-premises and Amazon EC2 environments to Amazon RDS, Amazon Redshift, Amazon Aurora and EC2 databases. We discuss homogeneous (e.g. Oracle-to-Oracle, PostgreSQL-to-PostgreSQL, etc.) and heterogeneous (e.g. Oracle to Aurora, SQL Server to MariaDB) database migrations. We also talk about the new AWS Schema Conversion Tool that saves you development time when migrating your Oracle and SQL Server database schemas, including PL/SQL and T-SQL procedural code, to their MySQL, MariaDB and Aurora equivalents.
Many businesses want the benefits of AWS like lower cost, flexibility, and agility, but aren’t sure if performing the migration in-house is the best option. By leveraging the expertise of an AWS Premier Consulting Partner like Datapipe, organizations can take the burden off of IT and experience a smooth, automated transition to the cloud. In our upcoming webinar, AWS, Datapipe, and Motus, a vehicle management and reimbursement platform, explain how Motus migrated and automated their workloads on the AWS Cloud, which resulted in a 20% reduction in operational costs. Datapipe takes a 3-fold approach to migration. Using services such as Amazon Route 53 and Amazon CloudWatch, Datapipe will plan, build, and run your new cloud environment on AWS.
Join us to Learn:
• How Datapipe works with organizations to plan, build, and run their new, efficient cloud environments
• How to migrate and manage your organization’s environments to lower operational costs and optimize efficiency
• How Motus lowered their operational IT costs by 20% by automating many of their processes
Who Should Attend:
Cloud Owners, Cloud Architects, IT Administers, IT Architects, Information Architects, DevOps Managers
AWS Speaker: Sai Reddy Thangirala, Solution Architect
Partner Speaker Name: Eric Sakowski, Lead Automation Engineer, DevOps and Automation
Customer Speaker Name: Rick Blaisdell, Chief Technology Officer, Motus
AWS re:Invent 2016: Workshop: Building Your First Big Data Application with A...Amazon Web Services
Want to get ramped up on how to use Amazon's big data web services and launch your first big data application on AWS? Join us in this workshop as we build a big data application in real time using Amazon EMR, Amazon Redshift, Amazon Kinesis, Amazon DynamoDB, and Amazon S3. We review architecture design patterns for big data solutions on AWS, and give you access to a take-home lab so that you can rebuild and customize the application yourself.
Announcing Lambda @ the Edge - December 2016 Monthly Webinar SeriesAmazon Web Services
This session introduces Lambda@Edge, a new AWS Lambda feature that allows developers to perform simple computations at AWS edge locations in response to CloudFront events. This will be of interest to developers who want to build low-latency, customized web experiences. We cover product functionality and details of the programming model, and we walk through potential use cases.
Learning Objectives:
• Learn about the capabilities, features and benefits of AWS Lambda@Edge
• Learn about the different use cases
• Learn how to get started using AWS Lambda@Edge
Amazon Aurora is a relational database engine that combines the speed and reliability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora is designed to be compatible with MySQL 5.6, so that existing MySQL applications and tools can run without requiring modification. AWS Database Migration Service helps you migrate databases to AWS easily and securely. The source database remains fully operational during the migration, minimizing downtime to applications that rely on the database.
Presented by: Danilo Poccia, Technical Evangelist, Amazon Web Services
AWS January 2016 Webinar Series - Getting Started with Big Data on AWSAmazon Web Services
With hundreds of new and sometimes disparate tools, it’s hard to keep pace. Amazon Web Services provides a broad and fully integrated portfolio of cloud computing services to help you build, secure and deploy your big data applications.
Attend this webinar to get an overview of the different big data options available in the AWS Cloud – including popular big data frameworks such as Hadoop, Spark, NoSQL databases, and more. Learn about ideal use cases, cases to avoid, performance, interfaces, and more. Finally, learn how you can build valuable applications with a real-life example.
Learning Objectives:
Learn about big data tools available at AWS
Understand ideal use cases
Learn some of the key considerations such as performance, scalability, elasticity and availability, when selecting big data tools
Who Should Attend:
Data Architects, Data Scientists, Developers
APAC Principal Solutions Architect, Johnathon Meichtry will run through the highlights of 2015 showcasing the biggest announcements and how customers are using these new features. This session will cover the entire breadth of the AWS platform, and is a chance to get a high level overview of all of the announcements, feature updates and new services that AWS has launched in 2015.
Amazon Aurora is a MySQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. This session introduces you to Amazon Aurora, explains common use cases for the service, and helps you get started with building your first Amazon Aurora–powered application.
Learn about the new AWS Database Migration Service, which helps you migrate databases with minimal downtime from on-premises and Amazon EC2 environments to Amazon RDS, Amazon Redshift, Amazon Aurora and EC2 databases. We discuss homogeneous (e.g. Oracle-to-Oracle, PostgreSQL-to-PostgreSQL, etc.) and heterogeneous (e.g. Oracle to Aurora, SQL Server to MariaDB) database migrations. We also talk about the new AWS Schema Conversion Tool that saves you development time when migrating your Oracle and SQL Server database schemas, including PL/SQL and T-SQL procedural code, to their MySQL, MariaDB and Aurora equivalents.
NEW LAUNCH! Introducing AWS Batch: Easy and efficient batch computingAmazon Web Services
AWS Batch is a fully-managed service that enables developers, scientists, and engineers to easily and efficiently run batch computing workloads of any scale on AWS. AWS Batch automatically provisions compute resources and optimizes the workload distribution based on the quantity and scale of the workloads. With AWS Batch, there is no need to install or manage batch computing software, allowing you to focus on analyzing results and solving problems. AWS Batch plans, schedules, and executes your batch computing workloads across the full range of AWS compute services and features, such as Amazon EC2, Spot Instances, and AWS Lambda. AWS Batch reduces operational complexities, saving time and reducing costs. In this session, Principal Product Managers Jamie Kinney and Dougal Ballantyne describe the core concepts behind AWS Batch and details of how the service functions. The presentation concludes with relevant use cases and sample code.
El almacenamiento en la nube es un componente crítico de la informática en la nube, que guarda la información que utilizan las aplicaciones. El análisis de big data, los almacenes de datos, el Internet de las cosas, las bases de datos y las aplicaciones de backup y archivado dependen de algún tipo de arquitectura de almacenamiento de datos. El almacenamiento en la nube, por lo general, es más fiable, escalable y seguro que los sistemas de almacenamiento en las instalaciones tradicionales.
AWS ofrece una gama completa de servicios de almacenamiento en la nube para respaldar los requisitos de conformidad de las aplicaciones y el archivado. Seleccione entre servicios de almacenamiento de objetos, archivos y por bloques, así como opciones de migración de datos a la nube para comenzar a diseñar las bases de su entorno de TI en la nube.
Building Distributed Applications with AWS Step FunctionsAmazon Web Services
This talk covers how you can use the new AWS Step Functions service to coordinate different components of your application, maintain state, and build sophisticated serverless solutions.
AWS re:Invent 2016: Driving Innovation with Big Data and IoT (GPSST304)Amazon Web Services
With unforeseen competitive threats and potential market disruptions, enterprises are seeking to innovate for the benefit of their customers. Business transformation in the digital age requires the successful use of new technologies including the cloud, IoT, and Big Data. Attend this session to learn more about how AWS can help organizations innovate faster around IoT and Big Data. We dive into specific opportunities and approaches for managing billions of connected devices and associated big data workloads on the cloud.
Amazon Aurora New Features - September 2016 Webinar SeriesAmazon Web Services
Amazon Aurora is a fully managed MySQL-compatible database with high-end commercial database features and performance at one-tenth the cost. Since launching Aurora a year ago we have added many new capabilities and features. Some of these features include encryption, database snapshot sharing, enhanced monitoring, cross-region replication, S3 binary snapshot ingestion and customized failover priority. In this session we'll demonstrate how these features work and discuss how you can make the best use of them.
Learning Objectives:
• Learn about the newly added features of Aurora
• Learn how to use those features
• Learn when and why to use those features
Who Should Attend:
• IT Managers, DBAs, Enterprise and Solution Architects, Devops Engineers and Developers
database migration simple, cross-engine and cross-platform migrations with ...Amazon Web Services
Learn how you can migrate databases with minimal downtime from on-premises and Amazon EC2 environments to Amazon RDS, Amazon Redshift, Amazon Aurora and EC2 databases using AWS Database Migration Service. We discuss homogeneous (e.g. Oracle-to-Oracle, PostgreSQL-to-PostgreSQL, etc.) and heterogeneous (e.g. Oracle to Aurora, SQL Server to MariaDB) database migrations. We also talk about the new AWS Schema Conversion Tool that saves you development time when migrating your Oracle and SQL Server database schemas, including PL/SQL and T-SQL procedural code, to their MySQL, MariaDB and Aurora equivalents. Best of all, we spend most of the time demonstrating the product and showing use cases designed to help your business.”
The State of Serverless Computing | AWS Public Sector Summit 2017Amazon Web Services
oin us to learn about the state of serverless computing from Dougal Ballantyne, Principal Product Manager, Serverless. Dougal Ballantyne 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. Learn More: https://aws.amazon.com/government-education/
Planning datacenter migrations can involve thousands of workloads and tens of thousands of servers and are often deeply interdependent. Application discovery and dependency mapping are important early first steps in the migration process, but difficult to perform at scale due to the lack of automated tools. AWS Application Discovery Service is a new service (coming soon) that automatically identifies data center applications and dependencies, and baselines application health and performance to help plan your application migration to AWS quickly and reliably. This talk introduces the new Application Discovery Service capabilities for simplifying the planning process for data center and large scale migrations to AWS. We will discuss how you can use the AWS Application Discovery Service data service to examine the applications running your data center, their attributes, and their dependencies and then use this information to help reduce the time, cost, and risk of migrating applications to AWS.
AWS re:Invent 2016: How to Scale and Operate Elasticsearch on AWS (DEV307)Amazon Web Services
Elasticsearch has quickly become the leading open source technology for scaling search and building document services on. Many software providers have come to rely on it to serve the needs of high-performance, production applications.
In this talk, we’ll go deep on lessons learned from three years in production scaling from a few shards to more than 100 spread across 100s of nodes on AWS--to serve real-time queries against 100s of millions of documents.
Attendees will learn:
* How to capacity plan for ES on AWS
* How to scale and reshard on AWS with zero downtime
* What AWS and ES metrics to collect and alert on
* Tips on day to day ES operations
Session sponsored by SignalFx.
Amazon QuickSight is a fast, cloud-powered business intelligence (BI) service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data. In this session, we demonstrate how you can point Amazon QuickSight to AWS data stores, flat files, or other third-party data sources and begin visualizing your data in minutes. We also introduce SPICE - a new Super-fast, Parallel, In-memory, Calculation Engine in Amazon QuickSight, which performs advanced calculations and render visualizations rapidly without requiring any additional infrastructure, SQL programming, or dimensional modeling, so you can seamlessly scale to hundreds of thousands of users and petabytes of data. Lastly, you will see how Amazon QuickSight provides you with smart visualizations and graphs that are optimized for your different data types, to ensure the most suitable and appropriate visualization to conduct your analysis, and how to share these visualization stories using the built-in collaboration tools.
Presented by: Matthew McClean, AWS Partner Solutions Architect, Amazon Web Services
Deep Dive on Amazon QuickSight - January 2017 AWS Online Tech TalksAmazon Web Services
The volume of data businesses create and process is growing every day. To get the most value out of this data, companies often invest in traditional BI tools. These tools however require investments in costly on-premises hardware and software. It takes weeks or months of data engineering time to build complex data models; not to mention the additional infrastructure needed to maintain fast query performance as data sets grow. In a nutshell, traditional BI tools are expensive and complex, and prevent companies from making analytics ubiquitous among business users. Amazon QuickSight is built from the ground up to solve these problems by bringing the scale and flexibility of the AWS Cloud and by providing a business user focused experience to business analytics.
Learning Objectives:
• Learn about the capabilities and features of Amazon QuickSight
• Learn about the benefits of Amazon QuickSight
• Learn about the different use cases
• Learn how to get started using Amazon QuickSight
• Understand how to connect to your data sources in the cloud or on-premises
• Learn how to use QuickSight’s SPICE and AutoGraph technologies to quickly spin-up charts and graphs
• Discover insights with your colleagues via Stories and become an analytics pro without any complex BI knowledge
We built event-driven user interfaces for decades. What about bringing the same approach to mobile, web, and IoT backend applications? You have to understand how data flows and what is the propagation of changes, using reactive programming techniques. You can focus on the core functionalities to build and the relationships among the resources you use. Your application behaves similarly to a “spreadsheet”, where depending resources are updated automatically when something “happens”, and is decomposed into scalable microservices without having to manage the infrastructure. The resulting architecture is efficient and cost effective to run on AWS and managing availability, scalability and security becomes part of the implementation itself.
A dive deep into the AWS IoT service that was announced at AWS re:Invent in October. We will cover the components of the AWS IoT platform, demonstrate the AWS IoT Console and command line experience and the client-side SDKs that AWS provides to help developers build rich applications for their devices, whilst removing the heavy lifting associated with creating a scalable, secure and reliable set of cloud services to support these applications.
Next Generation Open Data Platforms | AWS Public Sector Summit 2016Amazon Web Services
AWS provides a comprehensive toolkit for building applications that enable sharing and analyzing data at any scale. Come learn about how the City of Chicago and Department of Interior are using the cloud to create sophisticated open data applications. Tom Schenk, Chief Data Officer of the City of Chicago will talk about the OpenGrid project, an award-winning open-source geographical information system that supports real-time monitoring of city-focused and citizen services data retrieval using open data. Jerry Johnston, Director of the Information and Technology Management Division, Office of the Chief Information Officer at the U.S. Department of the Interior (DOI), will discuss the evolution of the National Spatial Data Infrastructure (NSDI) which aims to create a national network of distributed geospatial data that can be used to support a wide range of public and private sector applications.
Women in Technology: Supporting Diversity in a Technical WorkplaceAmazon Web Services
Diversity in the technical workforce is a valuable asset for all companies, because it encourages different types of thinking and taps into the full potential of your team. Come learn from one AWS organization how a fast-moving, fast-growing team has put in place a "diversity circle" for personal and professional development. This program provides a peer mentoring group that builds skills and establishes informal networking support. The host and active participants of this two-year program will share tips and best practices for running a diversity peer mentoring group that spans engineering, product management, and operations.
Using amazon machine learning to identify trends in io t data technical 201Amazon Web Services
Internet of Things is creating a tidal wave of new data including events, correlations, business value, and much more. With the proliferation of new data sets, it also introduces more potential issues, errors, and spurious values.
In this session, we will explore using Amazon Machine Learning to analyse and understand the new data collected within your IoT solution. In addition, we will learn how to discover patterns, trends, anomalies, and correlations by demonstrating the capabilities of Amazon Machine Learning and SparkML running on AWS Cloud.
Speaker: Simon Elisha, Solutions Architect, Amazon Web Services
DevOps en Amazon: Un vistazo a nuestras herramientas y procesosAmazon Web Services
(Diapositivas de presentación son en inglés.)
Mientras equipos de desarrollo transicionan a arquitecturas basadas en la nube y adoptan procesos más ágiles, las herramientas que necesitan para ayudarles en sus ciclos de desarrollo cambiarán. En esta sesión, os llevaremos por la transición que Amazon hizo a una arquitectura orientada a servicios hace más de una década. Compartiermos las lecciones aprendidas, los procesos que adoptamos y las herramientas que construimos para incrementar la agilidad y la fiabilidad. También os introduciremos a AWS CodeCommit, AWS CodePipeline, y AWS CodeDeploy, tres servicios que han nacido de la propia experiencia interna de DevOps en Amazon.
This session shows how AWS Mobile Hub can help to reduce the complexity of building mobile apps.
View webinar on demand: https://www.brighttalk.com/webcast/9019/195087
Containers have become key in modern application design. It is relatively easy to run a few containers on your laptop, but building and maintaining an entire infrastructure to run and manage containerized apps is hard and requires a lot of undifferentiated heavy lifting.
In this session, we will discuss some of the core architectural principles underlying Amazon ECS, a highly scalable, high performance service to run and manage distributed applications using the Docker container engine. We will explore the advanced scheduling capabilities of Amazon ECS and dive deep into the Amazon ECS Service Scheduler, which optimizes for long-running applications by monitoring container health, restarting failed containers, and load balancing.
The Modern Day Pressures and Trends Driving Cloud Access RequirementsAmazon Web Services
As the business landscape continues to shift towards cloud services, the need for businesses to move their critical applications and data from public internet connections to secure, private connections is growing. In this session you will learn how the telecoms industry is evolving its connectivity services to adopt cloud and data centre concepts such as orchestration, on-demand and pay for what you use. We will explore what you should look for and expect for direct cloud connectivity provided by these new and emerging services and what they can do for your business.
Vijay Rangarajan, Partner Solutions Architect, Amazon Web Services, APAC
Mark Daley, Director for Corporate Strategy and Product, Epsilon
How Crownbet Disrupted the Australian Market, One Instance at a Time - Sessio...Amazon Web Services
In 2014, BetEasy (now Crownbet) started life off as a humble start up business, with Gus D'Onofrio at the helm of their IT department. Less than 3 years later Crownbet is now a leading Australian online Bookmaker and a household retail brand.
Find out how Crownbet implemented pioneering strategies to successfully disrupt the mature bookmaker market. Gus will share Crownbet's Cloud journey, key success and learning points, as well as how they worked with Bulletproof to implement AWS.
Speakers: Gus D'Onofrio, CTO & Head of Technology, Crownbet & Mark Randall, Director of Sales & Marketing, Bulletproof
Amazon QuickSight is a fast BI service that makes it easy for you to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data. QuickSight is built to harness the power and scalability of the cloud, so you can easily run analysis on large datasets, and support hundreds of thousands of users. In this session, we’ll demonstrate how you can easily get started with Amazon QuickSight, uploading files, connecting to S3 and Redshift and creating analyses from visualizations that are optimized based on the underlying data. Once we’ve built our analysis and dashboard, we’ll show you easy it is to share it with colleagues and stakeholders in just a few seconds. And with SPICE – QuickSight’s in-memory calculation engine – you can go from data to insights, faster than ever.
Learn how you can point Amazon QuickSight to AWS data stores, flat files, or other third-party data sources and begin visualizing your data in minutes.
Amazon QuickSight is a fast, cloud-powered business intelligence (BI) service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data. In this session, we demonstrate how you can point Amazon QuickSight to AWS data stores, flat files, or other third-party data sources and begin visualizing your data in minutes. We also introduce you to SPICE - a Super-fast, Parallel, In-memory, Calculation Engine in Amazon QuickSight, which performs advanced calculations and render visualizations rapidly without requiring any additional infrastructure, SQL programming, or dimensional modeling, so you can seamlessly scale to hundreds of thousands of users and petabytes of data. Lastly, you will see how Amazon QuickSight provides you with smart visualizations and graphs that are optimized for your different data types, to ensure the most suitable and appropriate visualization to conduct your analysis, and how to share these visualization stories using the built-in collaboration tools.
Amazon QuickSight is a fast, cloud-powered business intelligence (BI) service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data. In this session, we demonstrate how you can point Amazon QuickSight to AWS data stores, flat files, or other third-party data sources and begin visualizing your data in minutes. We also introduce you to SPICE - a Super-fast, Parallel, In-memory, Calculation Engine in Amazon QuickSight, which performs advanced calculations and render visualizations rapidly without requiring any additional infrastructure, SQL programming, or dimensional modeling, so you can seamlessly scale to hundreds of thousands of users and petabytes of data. Lastly, you will see how Amazon QuickSight provides you with smart visualizations and graphs that are optimized for your different data types, to ensure the most suitable and appropriate visualization to conduct your analysis, and how to share these visualization stories using the built-in collaboration tools.
Amazon QuickSight is a fast BI service that makes it easy for you to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data. QuickSight is built to harness the power and scalability of the cloud, so you can easily run analysis on large datasets, and support hundreds of thousands of users. In this session, we’ll demonstrate how you can easily get started with Amazon QuickSight, uploading files, connecting to S3 and Redshift, and creating analyses from visualizations that are optimized based on the underlying data. Once we’ve built our analysis and dashboard, we’ll show you easy it is to share it with colleagues and stakeholders in just a few seconds.
By Leveraging AWS Cloud and its services it not only help in reducing the cost but also brings agility and innovation. One of such service BigData provides a paradigm shift by putting smart in everything we do today including smart home, smart city, smart health, smart campus and many more. We will talk about how AWS services can help in reducing the cost and bring agility by leveraging Big Data to bring in innovation to campus.
AWS October Webinar Series - Introducing Amazon QuickSightAmazon Web Services
Amazon QuickSight is a very fast, cloud-powered business intelligence (BI) service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data.
In this webinar, we will demonstrate how you can point Amazon QuickSight to AWS data stores, flat files, or other third-party data sources and begin visualizing your data in minutes. We will also introduce SPICE, a new Super-fast, Parallel, In-memory, Calculation Engine in Amazon QuickSight, which performs advanced calculations and renders visualizations rapidly without requiring any additional infrastructure, SQL programming, or dimensional modeling, so you can seamlessly scale to hundreds of thousands of users. Lastly, you will see how Amazon QuickSight provides you with smart visualizations and graphs that are optimized for your different data types, to ensure the most suitable and appropriate visualization to conduct your analysis, and how to share these visualization stories using the built-in collaboration tools.
AWS re:Invent 2016: Visualizing Big Data Insights with Amazon QuickSight (BDM...Amazon Web Services
Amazon QuickSight is a fast BI service that makes it easy for you to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data. QuickSight is built to harness the power and scalability of the cloud, so you can easily run analysis on large datasets, and support hundreds of thousands of users. In this session, we’ll demonstrate how you can easily get started with Amazon QuickSight, uploading files, connecting to S3 and Redshift and creating analyses from visualizations that are optimized based on the underlying data. Once we’ve built our analysis and dashboard, we’ll show you easy it is to share it with colleagues and stakeholders in just a few seconds. And with SPICE – QuckSight’s in-memory calculation engine – you can go from data to insights, faster than ever.
One of the biggest tradeoffs customers usually make when deploying BI solutions at scale is agility versus governance. Large-scale BI implementations with the right governance structure can take months to design and deploy. In this session, learn how you can avoid making this tradeoff using Amazon QuickSight. Learn how to easily deploy Amazon QuickSight to thousands of users using Active Directory and Federated SSO, while securely accessing your data sources in Amazon VPCs or on-premises. We also cover how to control access to your datasets, implement row-level security, create scheduled email reports, and audit access to your data.
Using AWS to design and build your data architecture has never been easier to gain insights and uncover new opportunities to scale and grow your business. Join this workshop to learn how you can gain insights at scale with the right big data applications.
Using AWS to design and build your data architecture has never been easier to gain insights and uncover new opportunities to scale and grow your business. Join this workshop to learn how you can gain insights at scale with the right big data applications.
By using a Data Lake, you no longer need to worry about structuring or transforming data before storing it. A Data Lake on AWS enables your organization to more rapidly analyze data, helping you quickly discover new business insights. Join us for our webinar to learn about the benefits of building a Data Lake on AWS and how your organization can begin reaping their rewards. In this webinar, select APN Partners will share their specific methodology for implementing a Data Lake on AWS and best practices for getting the most from your Data Lake.
Creating a Data Driven Culture with Amazon QuickSight - Technical 201Amazon Web Services
Data drives good business decisions and a data-driven culture can help organisations increase profitability and reduce costs.
Amazon QuickSight is a very fast, cloud-powered Business Intelligence (BI) service that makes it easy for all employees to build visualisations, perform ad-hoc analysis, and quickly get business insights from their data.
Speaker: David McAmis, Consultant, Amazon Web Services
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.
ABD202_Best Practices for Building Serverless Big Data ApplicationsAmazon Web Services
Serverless technologies let you build and scale applications and services rapidly without the need to provision or manage servers. In this session, we show you how to incorporate serverless concepts into your big data architectures. We explore the concepts behind and benefits of serverless architectures for big data, looking at design patterns to ingest, store, process, and visualize your data. Along the way, we explain when and how you can use serverless technologies to streamline data processing, minimize infrastructure management, and improve agility and robustness and share a reference architecture using a combination of cloud and open source technologies to solve your big data problems. Topics include: use cases and best practices for serverless big data applications; leveraging AWS technologies such as Amazon DynamoDB, Amazon S3, Amazon Kinesis, AWS Lambda, Amazon Athena, and Amazon EMR; and serverless ETL, event processing, ad hoc analysis, and real-time analytics.
MSC203_How Citrix Uses AWS Marketplace Solutions To Accelerate Analytic Workl...Amazon Web Services
Find out how Citrix built a solution using Matillion ETL for Amazon Redshift from AWS Marketplace to load all data into an Amazon Redshift cluster, allowing them to do their analytics on the entire environment at a single time. We’ll discuss the transition made to consolidate multiple disparate databases in order to run analytic workloads, get a holistic view of all their data sources, and prevent inconsistent data from being captured.
How Citrix Uses AWS Marketplace Solutions to Accelerate Analytic Workloads on...Amazon Web Services
Find out how Citrix built a solution using Matillion ETL for Amazon Redshift from AWS Marketplace to load all data into an Amazon Redshift cluster, allowing them to do their analytics on the entire environment at a single time. We’ll discuss the transition made to consolidate multiple disparate databases in order to run analytic workloads, get a holistic view of all their data sources, and prevent inconsistent data from being captured.
A modern Big Data architecture involves extending your on-premises data management to AWS, implementing a data pipeline to stream real-time data into cloud data warehouse Amazon Redshift, perform data transformation, discovery, predictive analytics through machine learning, visualize complex information and be notified to respond to business events. This session is for APN Consulting Partners and organizations looking for ways to accelerate and modernize their Big Data projects. You will learn how to deploy and integrate AWS Services with Third-party Solutions in AWS Marketplace. Reduce your time to market by combining AWS services, open source software and ready-to-run on AWS solutions. Familiarity with Database technologies required. The session includes demonstrations and cooperative learning group activities.
Comprehensive Big Data Analytics Architecture Made Easy - The AWS Marketplace...Amazon Web Services
A modern Big Data architecture involves extending your on-premises data management to AWS, implementing a data pipeline to stream real-time data into cloud data warehouse Amazon Redshift, perform data transformation, discovery, predictive analytics through machine learning, visualize complex information and be notified to respond to business events. This session is for APN Consulting Partners and organizations looking for ways to accelerate and modernize their Big Data projects. You will learn how to deploy and integrate AWS Services with Third-party Solutions in AWS Marketplace. Reduce your time to market by combining AWS services, open source software and ready-to-run on AWS solutions. Familiarity with Database technologies required. The session includes demonstrations and cooperative learning group activities.
Think of big data as all data, no matter what the volume, velocity, or variety. The simple truth is a traditional on-prem data warehouse will not handle big data. So what is Microsoft’s strategy for building a big data solution? And why is it best to have this solution in the cloud? That is what this presentation will cover. Be prepared to discover all the various Microsoft technologies and products from collecting data, transforming it, storing it, to visualizing it. My goal is to help you not only understand each product but understand how they all fit together, so you can be the hero who builds your companies big data solution.
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.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
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/
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
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.
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.
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.
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.
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.
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.
2. What to expect from the session
• Overview of big data and analytics strategy
• Challenges our customers face in big data analytics
• Amazon QuickSight Introduction
• DEMO
4. We start with the customer
We take on the big challenges they have
We innovate
5. We start with the customer… and innovate
Customers told us… We created…
Managing databases is painful and difficult
SQL databases do not perform well at scale
Hadoop is difficult to deploy and manage
Data warehouses are complex, costly, and slow
Commercial DBs are punitive and expensive
Streaming data is difficult to capture and analyze
Amazon RDS
Amazon DynamoDB
Amazon EMR
Amazon Redshift
Amazon Aurora
Amazon Kinesis
8. Old-guard BI
Costs too much
Pay $ million before seeing first analysis
3 year TCO $150 to $250 per user per month
Takes too long
Spend 6 to 12 months of consulting
and software implementation time
9. Can’t handle NoSQL, streaming data
Time
Cost
Pay $ millions for license and hardware
Requires 6 to 12 months of consulting
Slower performance at scale
Doesn’t deliver fast query performance
Extra $$ for mobile and sharing
Extra $$ for IoT dashboards
Old-guard BI
14. Business Professionals
Data Consumers
Data
Professionals
Who Is QuickSight For?
QuickSight is designed to give
everyday business users the
flexibility to do easy, self serve
analysis on their data.
QuickSight is also perfect for
delivering published dashboards
throughout the organization.
CMO
Sales Managers
Product Managers
CEOs
Procurement
AWS Ops
Sales Reps
Store Managers
CEOs Warehouse Managers
Support Reps
15. Fast, Easy Ad-Hoc Analytics for
End Users
QuickSight combines an elegant, easy to
use interface with blazing fast performance
powered by SPICE to get users from data to
insights faster than ever before.
17. Business User
QuickSight API
Data prep Metadata SuggestionsConnectors SPICE
Business User
QuickSight UI
Mobile devices Web browsers
Amazon
S3
Amazon
Kinesis
Amazon
DynamoDB
Amazon
EMR
Amazon
Redshift
Amazon RDSFiles Apps
Direct connect
JDBC/ODBC
On-premises data
Partner BI products
18. I have multiple datasets both on-premises and on
AWS from different sources, and I need to make
data available and enable access by using
Amazon QuickSight.
How do I do this?
19. Deeply Integrated
QuickSight is deeply integrated with
AWS data sources like Redshift,
RDS, S3 and others, as well as third
party sources like Excel, Salesforce
as well as on-premise databases.
Amazon S3
Amazon RDS, Aurora Amazon Redshift
Flat
Files
20. 1. Data made available in “data lakes” using Amazon S3 or
Amazon Redshift
2. Data access managed with bucket- or schema-level policies
3. Data enabled by using Amazon QuickSight
21. Amazon EMR
or Apache
Hadoop
Log files,
application API
extracts
On-premises data
Amazon
Redshift
Amazon
DynamoDB or EC2
based MongoDB,
Cassandra
Amazon
S3
Data made
available in
data lakes
QuickSight
Mobile devices Web browsers
Bucket- or
schema-level
permissions by
user and data
access needs
Data access
managed at
the data lake
Data enabled
by user
in data marts
22. Super-Fast Performance with SPICE
QuickSight is powered by SPICE, a super-fast
calculation engine that delivers unprecedented
performance and scale delivering insights at the speed
of thought.
• Super-fast, Parallel, In-memory optimized,
Calculation Engine
• 2x to 4x compression columnar data
• Compiled queries with machine code generation
• Rich calculations
• SQL-like syntax
• Very fast response time to queries
• Fully managed—no hardware or software to
license
23. Intuitive visualizations with AutoGraph
• Automatic detection of data types
• Optimal query generation
• Appropriate graph type selection
• Ability to customize the graph type
• Very fast response
24. Collaborate, Share and Publish
QuickSight let’s users create and share Data Sets, collaborate on your live Analyses, and share,
read only Dashboards and Storyboards that can be accessed on any device, anytime, anywhere.
Analyses
Analyses are visual explorations of your data.
Multiple users can collaborate on an analyses with
the ability to modify and change them in any way.
Dashboards
You can share your analyses as read only
dashboards. Viewers can interact with and
filter the visualizations without modifying them.
StoryBoards
Let you combine visualizations into a
guided tour that you can share with
other users.
25. Tell a story with your data
• Capture the critical snapshot of analysis
• Build a sequence of analysis
• Share it securely
• Enable interactive exploration
• Very fast response
26. Native mobile experience
•iOS, Android
•Full experience on tablets
•Consumption experience on smart phones
•Very fast response
28. Secure Sharing
Hosted content created in QS is shared with
secure links preventing loose files from falling
into the wrong hands, as well as keeping out
of date versions of reports and dashboards
from staying in circulation.
29. End User Flexibility WITH
Centralized Control
QuickSight gives end users the ability to
easily perform self-serve data-discovery with
the centralized control companies need to
guarantee a single source of the truth.
• Create and syndicate managed Data Sets
• Assign or revoke Data Set access
• Governed Data Sources (coming soon)
30. User Management and AD
Integration
QuickSight has admin and users roles to
make sure you have the control you need
over your account.
QuickSight Enterprise Edition can connect
to both your hosted and on-premise Active
Directories via AWS Directory Services
31. Partners
QuickSight has a strong network of ETL
partners to help get your data into
QuickSight. Check out the complete list at
http://quicksight.aws
34. Individual Standard Edition
(60 Day Free Trial)
Enterprise Edition
(60 Day Free Trial)
Price per user per month Free $9
(Annual)
$12
(Mont to Month)
$18
(Annual)
$24
(Mont to Month)
Number of Users 1 2+ 2+ 2+ 2+
SPICE Capacity (GB)* 10 10 10 10 10
Additional SPICE
GB-month
$0.25 $0.25 $0.38
As an AWS service, QuickSight is a cost effective solution
whether you’re deploying to 10 users or 10,000
36. Secure, Scalable, Cloud
As a native cloud service, QuickSight combines the speed, scalability, and security that our customers
have come to depend on with the value and cost effectiveness you expect from AWS.
• Native AWS Cloud Service
• Secure
• No Server Licensing
• No Infrastructure or Maintenance Costs
• No Deployment, Sign Up and Go!
• Designed to Scale
• Simple, Intuitive UX
• Subscription Model