Get the latest on what we've been developing in Amazon S3. In this session, we share best practices for performance optimization, security, data protection, storage management, and much more. We discuss ways to optimize key naming to increase throughput, apply the appropriate AWS Identity and Access Management (IAM) and encryption configurations, and take advantage of object tagging and other features to enhance security.
Using Amazon S3 and Amazon Glacier for Backup or Archive Storage (STG339) - A...Amazon Web Services
Whether you’re using Amazon S3 and Amazon Glacier as a backup target for database dumps, building a fully SEC-compliant archive, or something in between, AWS object storage offers a number of capabilities to ensure that your data stays retained, protected, and compliant with the rules of your business. This interactive session covers established best practices and new features to help you meet your retention requirements while minimizing storage costs.
Protect & Manage Amazon S3 & Amazon Glacier Objects at Scale (STG316-R1) - AW...Amazon Web Services
As your data repository grows on AWS using the object storage services Amazon S3 and Amazon Glacier, it becomes increasingly helpful to use particular features to help protect and manage your objects. In this chalk talk, you have the opportunity to speak directly with the AWS engineering team that builds and maintains features like Cross-Region Replication, S3 Storage Class Analysis, S3 Inventory, S3 Lifecycle, Amazon Glacier Vault Lock, and others. Bring your feedback, questions, and expertise to discuss innovative ways to protect data from corruption or malicious and accidental deletion, managing the data lifecycle to reduce costs, identifying wasted storage, and much more.
Optimizing Costs in Amazon S3 Creating Cost Efficiencies w/ Amazon S3 Storage...Amazon Web Services
Amazon S3 supports a wide range of storage classes to help you cost-effectively store your data. Each of the S3 Storage Classes is designed to support different use cases while reliably protecting your data. In this session, Amazon S3 experts will discuss the different S3 Storage Classes, their respective key features, and the unique use cases they support. We will then deep dive into S3’s newest storage class S3 Intelligent-Tiering—the first cloud storage class that automatically optimizes storage costs for data with changing access patterns. S3 Intelligent-Tiering moves data between two storage tiers based on changing access patterns of your objects and is ideal for data where customers don’t know or have a hard time learning how a data set is accessed over time. Attend this session to learn more about creating cost efficiencies with Amazon S3, when to use which storage class, and how S3 Intelligent-Tiering automates cost savings for you.
Deep Dive on Amazon S3: Manage Operations Across Amazon S3 Objects at Scale (...Amazon Web Services
As your data stores grow, managing and operating on your stored objects becomes increasingly difficult to scale. In this session, AWS experts demonstrate Amazon S3 features you can use to perform and manage operations across any number of objects, from hundreds to billions, stored in Amazon S3. Learn how to monitor performance, ensure compliance, automate actions, and optimize storage across all your Amazon S3 objects. We also provide relevant use cases that demonstrate the full range of Amazon S3 capabilities and options, such as copying objects across buckets to create development environments, restricting access to sensitive data, or restoring many objects from Amazon Glacier.
Get the latest on what we've been developing in Amazon S3. In this session, learn about new advances in S3 performance, security, data protection, storage management, and much more. We'll discuss how to apply the appropriate bucket policies and encryption configurations to enhance security, use S3 Select to accelerate queries, and take advantage of object tagging for data classification.
How to Build a Data Lake in Amazon S3 & Amazon Glacier - AWS Online Tech TalksAmazon Web Services
The document discusses how to build a data lake on Amazon S3 and Amazon Glacier. It defines a data lake as a centralized storage platform capable of handling heterogeneous data sets. It recommends Amazon S3 and Glacier for their scalability, security, and cost effectiveness. It provides examples of how to ingest, catalog, analyze, and query data in the data lake using services like AWS Glue, Athena, and Redshift Spectrum. It also discusses best practices for performance, security, and an example use case of an IoT sensor data pipeline.
The document introduces two new Amazon S3 features: Amazon S3 Select, which allows users to filter and analyze object data directly in S3 using standard SQL expressions, and Amazon S3 One Zone-IA storage class, which stores object data within a single availability zone at lower costs than S3 Standard storage. It provides overviews and demos of each feature.
How UCSD Simplified Data Protection with Rubrik and AWS (STG207-S) - AWS re:I...Amazon Web Services
Are you dealing with legacy system complexities when integrating your backup and recovery solution with the cloud? Rubrik can help you simplify data protection with its policy-based backup, recovery, and archival capabilities for hybrid applications. In this session, learn how University of California San Diego (UCSD) leverages Rubrik and AWS to help simplify data protection, achieve rapid data recovery, and scale for data growth. Join us to learn how UCSD replaced expensive and unreliable backup tapes with AWS storage, and how to move data to AWS and protect your cloud-native workloads running on AWS. This session is brought to you by AWS partner, Rubrik.
Using Amazon S3 and Amazon Glacier for Backup or Archive Storage (STG339) - A...Amazon Web Services
Whether you’re using Amazon S3 and Amazon Glacier as a backup target for database dumps, building a fully SEC-compliant archive, or something in between, AWS object storage offers a number of capabilities to ensure that your data stays retained, protected, and compliant with the rules of your business. This interactive session covers established best practices and new features to help you meet your retention requirements while minimizing storage costs.
Protect & Manage Amazon S3 & Amazon Glacier Objects at Scale (STG316-R1) - AW...Amazon Web Services
As your data repository grows on AWS using the object storage services Amazon S3 and Amazon Glacier, it becomes increasingly helpful to use particular features to help protect and manage your objects. In this chalk talk, you have the opportunity to speak directly with the AWS engineering team that builds and maintains features like Cross-Region Replication, S3 Storage Class Analysis, S3 Inventory, S3 Lifecycle, Amazon Glacier Vault Lock, and others. Bring your feedback, questions, and expertise to discuss innovative ways to protect data from corruption or malicious and accidental deletion, managing the data lifecycle to reduce costs, identifying wasted storage, and much more.
Optimizing Costs in Amazon S3 Creating Cost Efficiencies w/ Amazon S3 Storage...Amazon Web Services
Amazon S3 supports a wide range of storage classes to help you cost-effectively store your data. Each of the S3 Storage Classes is designed to support different use cases while reliably protecting your data. In this session, Amazon S3 experts will discuss the different S3 Storage Classes, their respective key features, and the unique use cases they support. We will then deep dive into S3’s newest storage class S3 Intelligent-Tiering—the first cloud storage class that automatically optimizes storage costs for data with changing access patterns. S3 Intelligent-Tiering moves data between two storage tiers based on changing access patterns of your objects and is ideal for data where customers don’t know or have a hard time learning how a data set is accessed over time. Attend this session to learn more about creating cost efficiencies with Amazon S3, when to use which storage class, and how S3 Intelligent-Tiering automates cost savings for you.
Deep Dive on Amazon S3: Manage Operations Across Amazon S3 Objects at Scale (...Amazon Web Services
As your data stores grow, managing and operating on your stored objects becomes increasingly difficult to scale. In this session, AWS experts demonstrate Amazon S3 features you can use to perform and manage operations across any number of objects, from hundreds to billions, stored in Amazon S3. Learn how to monitor performance, ensure compliance, automate actions, and optimize storage across all your Amazon S3 objects. We also provide relevant use cases that demonstrate the full range of Amazon S3 capabilities and options, such as copying objects across buckets to create development environments, restricting access to sensitive data, or restoring many objects from Amazon Glacier.
Get the latest on what we've been developing in Amazon S3. In this session, learn about new advances in S3 performance, security, data protection, storage management, and much more. We'll discuss how to apply the appropriate bucket policies and encryption configurations to enhance security, use S3 Select to accelerate queries, and take advantage of object tagging for data classification.
How to Build a Data Lake in Amazon S3 & Amazon Glacier - AWS Online Tech TalksAmazon Web Services
The document discusses how to build a data lake on Amazon S3 and Amazon Glacier. It defines a data lake as a centralized storage platform capable of handling heterogeneous data sets. It recommends Amazon S3 and Glacier for their scalability, security, and cost effectiveness. It provides examples of how to ingest, catalog, analyze, and query data in the data lake using services like AWS Glue, Athena, and Redshift Spectrum. It also discusses best practices for performance, security, and an example use case of an IoT sensor data pipeline.
The document introduces two new Amazon S3 features: Amazon S3 Select, which allows users to filter and analyze object data directly in S3 using standard SQL expressions, and Amazon S3 One Zone-IA storage class, which stores object data within a single availability zone at lower costs than S3 Standard storage. It provides overviews and demos of each feature.
How UCSD Simplified Data Protection with Rubrik and AWS (STG207-S) - AWS re:I...Amazon Web Services
Are you dealing with legacy system complexities when integrating your backup and recovery solution with the cloud? Rubrik can help you simplify data protection with its policy-based backup, recovery, and archival capabilities for hybrid applications. In this session, learn how University of California San Diego (UCSD) leverages Rubrik and AWS to help simplify data protection, achieve rapid data recovery, and scale for data growth. Join us to learn how UCSD replaced expensive and unreliable backup tapes with AWS storage, and how to move data to AWS and protect your cloud-native workloads running on AWS. This session is brought to you by AWS partner, Rubrik.
In this workshop, learn how to create a cloud-based business intelligence platform and deliver dynamic insights through a custom Alexa Skill. Together, we architect a data analytics platform using Amazon S3, Amazon Athena, Amazon QuickSight, Amazon DynamoDB, Amazon CloudWatch on the backend, and a voice-based user interface through a private Alexa Skill deployed via Alexa for Business on the front end.
One Data Lake, Many Uses: Enabling Multi-Tenant Analytics with Amazon EMR (AN...Amazon Web Services
One of the benefits of having a data lake is that same data can be consumed by multi-tenant groups—an efficient way to share a persistent Amazon EMR cluster. The same business data can be safely used for many different analytics and data processing needs. In this session, we discuss steps to make an Amazon EMR cluster multi-tenant for analytics, best practices for a multi-tenant cluster, and solutions to common challenges. We also address the security and governance aspects of a multi-tenant Amazon EMR cluster.
EFS Performance: Maximizing Performance for Linux/Unix File Systems (STG314-R...Amazon Web Services
Amazon EFS delivers highly available and highly durable file systems that are distributed across an unconstrained number of storage servers and enables massively parallel access. This means that highly parallelized workloads can drive high levels of aggregate throughput and operations per second. In this chalk talk, we diagram different architectures that leverage this distributed data storage design, and we share best practices around selecting the appropriate performance and throughput mode, configuring clients, ingesting data, and monitoring performance.
SRV302 Deep Dive: Hybrid Cloud Storage with AWS Storage GatewayAmazon Web Services
Enterprises of all sizes have the persistent storage challenges of data access, growth, and protection. Buying more storage stacks prolongs the pain of managing the storage lifecycle, which includes purchasing, ongoing operation, hardware failure, system retirement, and migration, yet it keeps on-premises datasets siloed from cloud workloads. In this session, learn how to use AWS Storage Gateway to connect your on-premises applications to AWS storage services by using standard storage protocols. Storage Gateway enables hybrid cloud storage solutions for file sharing, data lakes, big data analytics, backup and disaster recovery, and migration. We discuss best practices and new deployment approaches.
According to AWS, Amazon Aurora is the fastest growing service in the company’s history. Many businesses are looking for guidance on how to successfully move to and manage their data on Aurora. Do you know how to launch and configure a cluster on Aurora to ensure that your high-availability and performance requirements are met? Join Eric Johnson, AWS Evangelist at Rackspace, to discuss high availability and replication on Aurora, including extending the replication patterns to meet your application’s needs. He also covers how to choose the right endpoints to optimize writes and reads, as well as the future of Aurora. Spoiler: It’s serverless!
Querying Data in Place with AWS Object Storage Features and Analytics Tools (...Amazon Web Services
AWS offers tools and services that make analyzing and processing petabytes of data in the cloud faster, simpler, and more cost effective. In this chalk talk, AWS experts provide an overview of our querying data-in-place services, such as Amazon S3 Select, Amazon Glacier Select, Amazon Athena, and Amazon Redshift Spectrum. We explore best practices around using them with other analytics services (like Amazon EMR and AWS Glue) and third-party tools to build data lakes in Amazon S3 and Amazon Glacier and deploy other analytics solutions. Our AWS experts also provide sample use cases.
Containerize Legacy .NET Framework Web Apps for Cloud Migration Amazon Web Services
It can be daunting to migrate legacy .NET applications to the cloud. In this session, see how we use Microsoft Visual Studio and the AWS Management Console to demonstrate how to containerize a legacy .NET app with a SQL backend, and then deploy with Amazon ECS. We cover the Docker build and deployment process that are required to containerize the application, and we use Amazon EC2 Container Registry (Amazon ECR) to host the Docker image.
Get the Most out of Your Amazon Elasticsearch Service Domain (ANT334-R1) - AW...Amazon Web Services
The document discusses strategies for optimizing an Amazon Elasticsearch deployment to handle tenant data from a sports technology platform with thousands of organizations. It describes several iterations tried, including using a single index, separate indexes per tenant, and combining tenants into shared indexes. The final approach involved zero-downtime reindexing of tenant data to migrate organizations between indices in order to reduce shard counts and optimize performance and costs.
Build Your Own Log Analytics Solutions on AWS (ANT323-R) - AWS re:Invent 2018Amazon Web Services
With Amazon Elasticsearch Service's simplicity comes a multitude of opportunity to use it as a back end for real-time application and infrastructure monitoring. With this wealth of opportunities comes sprawl - developers in your organization are deploying Amazon Elasticsearch Service for many different workloads and many different purposes. Should you centralize into one Amazon Elasticsearch Service domain? What are the tradeoffs in scale and cost? How do you control access to the data and dashboards? How do you structure your indexes - single tenant or multi-tenant? In this session, we'll explore whether, when, and how to centralize logging across your organization to minimize cost and maximize value and learn how Autodesk has built a unified log analytics solution using Amazon Elasticsearch Service.
In this session, learn how AWS thinks about threat detection and remediation. We summarize the challenges of traditional threat detection efforts and explain how AWS helps address these challenges. We also provide an overview of key AWS services that detect and remediate threats to AWS. Finally, Terren Peterson, the VP of Software Engineering at Capital One, shares how his organization detects and remediates threats using Amazon GuardDuty and other AWS services.
Protecting Your Greatest Asset (Your Data): Security Best Practices on Dynamo...Amazon Web Services
This document discusses security best practices for Amazon DynamoDB. It covers encrypting data at rest with AWS Key Management Service (AWS KMS), monitoring access to data with AWS CloudTrail, and controlling access to data with Identity and Access Management (IAM) policies. The document provides examples of configuring encryption, viewing encryption settings and keys, and debugging access issues. It also discusses optimizing performance by enabling connection pooling in SDKs.
Build Your First Big Data Application on AWS (ANT213-R1) - AWS re:Invent 2018Amazon Web Services
Do you want to increase your knowledge of AWS big data web services and launch your first big data application on the cloud? In this session, we walk you through simplifying big data processing as a data bus comprising ingest, store, process, and visualize. You will build a big data application using AWS managed services, including Amazon Athena, Amazon Kinesis, Amazon DynamoDB, and Amazon S3. Along the way, we review architecture design patterns for big data applications and give you access to a take-home lab so you can rebuild and customize the application yourself. To get the most from this session, bring your own laptop and have some familiarity with AWS services.
Building Serverless Applications Using AWS AppSync and Amazon Neptune (SRV307...Amazon Web Services
In this session, learn how to build a data driven, serverless calorie tracker application with real-time, offline, and data syncing capabilities. The application provides an overview of your progress toward the calorie intake goal you've set, recommended intake remains, and breakdown of calories consumed. Use Amazon Cognito to build signup and sign-in capabilities as well as federated login to Facebook. The application integrates with AWS AppSync to provide real-time data from multiple data sources through GraphQL technology as well as offline capability. AWS AppSync makes it easy to access this data and provide the exact information your application needs. As a bonus, learn to use Amazon Neptune, a fully managed graph database, to build a personalized recommendation engine for calorie intake.
Bridgewater's Model-Based Verification of AWS Security Controls Amazon Web Services
Bridgewater Associates, the world’s largest hedge fund, operates a fleet of AWS accounts with different levels of information sensitivity and risk tolerance. To manage the risk these discrepancies introduce, Bridgewater developed an automated reasoning process that analyzes security policies and operationalizes them into an automated control validation and response system. In this talk, security leaders from Bridgewater describe the system they use to verify security controls. Learn about model-based verification approaches to security and how these approaches enable Bridgewater to confirm that security requirements are being met—an assurance previously unavailable by the conventional configuration checking and vulnerability scanning of other tools.
Lock It Down: Configure End-to-End Security & Access Control on Amazon EMR (A...Amazon Web Services
Amazon EMR helps you process all your data for analytics, but with great scale comes great responsibility—you need to make sure that data is secured by design. In this chalk talk, we walk through how to configure your environment to take full advantage of comprehensive security controls: including identifying sensitive data, encrypting data and managing keys, authenticating and authorizing users, utilizing fine-grained access controls, and using audit logs to demonstrate compliance.
Best Practices to Secure Data Lake on AWS (ANT327) - AWS re:Invent 2018Amazon Web Services
As customers are looking to build Data lakes to AWS, managing security, catalog and data quality becomes a challenge. Once data is put on Amazon S3, there are multiple processing engines to access it. This could be either through a SQL interface, programmatic, or using API. Customers require federated access to their data with strong controls around Authentication, Authorization, Encryption, and Audit. In this session, we explore the major AWS analytics services and platforms that customers can use to access data in the data Lake and provide best practices on securing them.
This document provides an overview of databases and Amazon Web Services database options. It discusses SQL and NoSQL databases, and covers Amazon RDS and DynamoDB in more detail. Amazon RDS is a relational database service that provides easy administration and scalability. DynamoDB is a fully managed NoSQL database with fast performance and seamless scalability. The document demonstrates how to choose between these and other database options based on needs.
Hybrid Cloud Storage for Recovery & Migration with AWS Storage Gateway (STG30...Amazon Web Services
In this workshop, we provide hands-on experience using the AWS Storage Gateway service to protect on-premises data in AWS, recover it locally or in the cloud in minutes, and migrate it when the time is right. You work with the File Gateway and Microsoft SQL Server native tools to back up to Amazon S3, and then recover or migrate that database in AWS rapidly. In addition, you use Volume Gateway and Amazon EBS Snapshots to protect and migrate block-based volumes. Use this session to hone your skills with backup and DR, and prepare for application migrations.
The Future of Enterprise Applications is Serverless (ENT314-R1) - AWS re:Inve...Amazon Web Services
The document discusses serverless computing and Amazon Web Services (AWS) serverless technologies. It provides an overview of AWS Lambda, API Gateway, Step Functions, and other services. It also shares experiences from Centrica, an energy company, in adopting a serverless approach for some of their applications and services. Centrica saw benefits from serverless including cost reduction, faster development cycles, and improved agility.
Power up Your AWS Data Lake and Warehouse with Trusted Data (Sponsored by Tal...Amazon Web Services
Do data quality issues, demanding business needs and increasingly stringent regulations sound familiar? You may have moved your data to a data lake on Amazon S3 or a data warehouse on Amazon Redshift, but how do you deliver the ‘single source of trust’ needed to make decisions with scale and speed? We will share best practices that have helped our customers overcome these challenges. Betfair Pty Ltd, the world’s largest online betting exchange, will also share their experience using Talend and Redshift in enabling a analytics data warehouse with strong data quality and light governance practices.
Amazon S3: Updates and Best Practices - SRV301 - Chicago AWS SummitAmazon Web Services
Get the latest on what we've been developing in Amazon S3. In this session, learn about new advances in Amazon S3 performance, security, data protection, storage management, and much more. We discuss how to apply the appropriate bucket policies and encryption configurations to enhance security. We also explain how to use Amazon S3 Select to accelerate queries and take advantage of object tagging for data classification.
Best Practices for Amazon S3 and Amazon Glacier (STG203-R2) - AWS re:Invent 2018Amazon Web Services
Learn best practices for Amazon S3 performance optimization, security, data protection, storage management, and much more. In this session, we look at common Amazon S3 use cases and ways to manage large volumes of data within Amazon S3. We discuss the latest performance improvements and how they impact previous guidance. We also talk about the Amazon S3 data resilience model and how architecture for the AWS Regions and Availability Zones impact architecture for fault tolerance.
In this workshop, learn how to create a cloud-based business intelligence platform and deliver dynamic insights through a custom Alexa Skill. Together, we architect a data analytics platform using Amazon S3, Amazon Athena, Amazon QuickSight, Amazon DynamoDB, Amazon CloudWatch on the backend, and a voice-based user interface through a private Alexa Skill deployed via Alexa for Business on the front end.
One Data Lake, Many Uses: Enabling Multi-Tenant Analytics with Amazon EMR (AN...Amazon Web Services
One of the benefits of having a data lake is that same data can be consumed by multi-tenant groups—an efficient way to share a persistent Amazon EMR cluster. The same business data can be safely used for many different analytics and data processing needs. In this session, we discuss steps to make an Amazon EMR cluster multi-tenant for analytics, best practices for a multi-tenant cluster, and solutions to common challenges. We also address the security and governance aspects of a multi-tenant Amazon EMR cluster.
EFS Performance: Maximizing Performance for Linux/Unix File Systems (STG314-R...Amazon Web Services
Amazon EFS delivers highly available and highly durable file systems that are distributed across an unconstrained number of storage servers and enables massively parallel access. This means that highly parallelized workloads can drive high levels of aggregate throughput and operations per second. In this chalk talk, we diagram different architectures that leverage this distributed data storage design, and we share best practices around selecting the appropriate performance and throughput mode, configuring clients, ingesting data, and monitoring performance.
SRV302 Deep Dive: Hybrid Cloud Storage with AWS Storage GatewayAmazon Web Services
Enterprises of all sizes have the persistent storage challenges of data access, growth, and protection. Buying more storage stacks prolongs the pain of managing the storage lifecycle, which includes purchasing, ongoing operation, hardware failure, system retirement, and migration, yet it keeps on-premises datasets siloed from cloud workloads. In this session, learn how to use AWS Storage Gateway to connect your on-premises applications to AWS storage services by using standard storage protocols. Storage Gateway enables hybrid cloud storage solutions for file sharing, data lakes, big data analytics, backup and disaster recovery, and migration. We discuss best practices and new deployment approaches.
According to AWS, Amazon Aurora is the fastest growing service in the company’s history. Many businesses are looking for guidance on how to successfully move to and manage their data on Aurora. Do you know how to launch and configure a cluster on Aurora to ensure that your high-availability and performance requirements are met? Join Eric Johnson, AWS Evangelist at Rackspace, to discuss high availability and replication on Aurora, including extending the replication patterns to meet your application’s needs. He also covers how to choose the right endpoints to optimize writes and reads, as well as the future of Aurora. Spoiler: It’s serverless!
Querying Data in Place with AWS Object Storage Features and Analytics Tools (...Amazon Web Services
AWS offers tools and services that make analyzing and processing petabytes of data in the cloud faster, simpler, and more cost effective. In this chalk talk, AWS experts provide an overview of our querying data-in-place services, such as Amazon S3 Select, Amazon Glacier Select, Amazon Athena, and Amazon Redshift Spectrum. We explore best practices around using them with other analytics services (like Amazon EMR and AWS Glue) and third-party tools to build data lakes in Amazon S3 and Amazon Glacier and deploy other analytics solutions. Our AWS experts also provide sample use cases.
Containerize Legacy .NET Framework Web Apps for Cloud Migration Amazon Web Services
It can be daunting to migrate legacy .NET applications to the cloud. In this session, see how we use Microsoft Visual Studio and the AWS Management Console to demonstrate how to containerize a legacy .NET app with a SQL backend, and then deploy with Amazon ECS. We cover the Docker build and deployment process that are required to containerize the application, and we use Amazon EC2 Container Registry (Amazon ECR) to host the Docker image.
Get the Most out of Your Amazon Elasticsearch Service Domain (ANT334-R1) - AW...Amazon Web Services
The document discusses strategies for optimizing an Amazon Elasticsearch deployment to handle tenant data from a sports technology platform with thousands of organizations. It describes several iterations tried, including using a single index, separate indexes per tenant, and combining tenants into shared indexes. The final approach involved zero-downtime reindexing of tenant data to migrate organizations between indices in order to reduce shard counts and optimize performance and costs.
Build Your Own Log Analytics Solutions on AWS (ANT323-R) - AWS re:Invent 2018Amazon Web Services
With Amazon Elasticsearch Service's simplicity comes a multitude of opportunity to use it as a back end for real-time application and infrastructure monitoring. With this wealth of opportunities comes sprawl - developers in your organization are deploying Amazon Elasticsearch Service for many different workloads and many different purposes. Should you centralize into one Amazon Elasticsearch Service domain? What are the tradeoffs in scale and cost? How do you control access to the data and dashboards? How do you structure your indexes - single tenant or multi-tenant? In this session, we'll explore whether, when, and how to centralize logging across your organization to minimize cost and maximize value and learn how Autodesk has built a unified log analytics solution using Amazon Elasticsearch Service.
In this session, learn how AWS thinks about threat detection and remediation. We summarize the challenges of traditional threat detection efforts and explain how AWS helps address these challenges. We also provide an overview of key AWS services that detect and remediate threats to AWS. Finally, Terren Peterson, the VP of Software Engineering at Capital One, shares how his organization detects and remediates threats using Amazon GuardDuty and other AWS services.
Protecting Your Greatest Asset (Your Data): Security Best Practices on Dynamo...Amazon Web Services
This document discusses security best practices for Amazon DynamoDB. It covers encrypting data at rest with AWS Key Management Service (AWS KMS), monitoring access to data with AWS CloudTrail, and controlling access to data with Identity and Access Management (IAM) policies. The document provides examples of configuring encryption, viewing encryption settings and keys, and debugging access issues. It also discusses optimizing performance by enabling connection pooling in SDKs.
Build Your First Big Data Application on AWS (ANT213-R1) - AWS re:Invent 2018Amazon Web Services
Do you want to increase your knowledge of AWS big data web services and launch your first big data application on the cloud? In this session, we walk you through simplifying big data processing as a data bus comprising ingest, store, process, and visualize. You will build a big data application using AWS managed services, including Amazon Athena, Amazon Kinesis, Amazon DynamoDB, and Amazon S3. Along the way, we review architecture design patterns for big data applications and give you access to a take-home lab so you can rebuild and customize the application yourself. To get the most from this session, bring your own laptop and have some familiarity with AWS services.
Building Serverless Applications Using AWS AppSync and Amazon Neptune (SRV307...Amazon Web Services
In this session, learn how to build a data driven, serverless calorie tracker application with real-time, offline, and data syncing capabilities. The application provides an overview of your progress toward the calorie intake goal you've set, recommended intake remains, and breakdown of calories consumed. Use Amazon Cognito to build signup and sign-in capabilities as well as federated login to Facebook. The application integrates with AWS AppSync to provide real-time data from multiple data sources through GraphQL technology as well as offline capability. AWS AppSync makes it easy to access this data and provide the exact information your application needs. As a bonus, learn to use Amazon Neptune, a fully managed graph database, to build a personalized recommendation engine for calorie intake.
Bridgewater's Model-Based Verification of AWS Security Controls Amazon Web Services
Bridgewater Associates, the world’s largest hedge fund, operates a fleet of AWS accounts with different levels of information sensitivity and risk tolerance. To manage the risk these discrepancies introduce, Bridgewater developed an automated reasoning process that analyzes security policies and operationalizes them into an automated control validation and response system. In this talk, security leaders from Bridgewater describe the system they use to verify security controls. Learn about model-based verification approaches to security and how these approaches enable Bridgewater to confirm that security requirements are being met—an assurance previously unavailable by the conventional configuration checking and vulnerability scanning of other tools.
Lock It Down: Configure End-to-End Security & Access Control on Amazon EMR (A...Amazon Web Services
Amazon EMR helps you process all your data for analytics, but with great scale comes great responsibility—you need to make sure that data is secured by design. In this chalk talk, we walk through how to configure your environment to take full advantage of comprehensive security controls: including identifying sensitive data, encrypting data and managing keys, authenticating and authorizing users, utilizing fine-grained access controls, and using audit logs to demonstrate compliance.
Best Practices to Secure Data Lake on AWS (ANT327) - AWS re:Invent 2018Amazon Web Services
As customers are looking to build Data lakes to AWS, managing security, catalog and data quality becomes a challenge. Once data is put on Amazon S3, there are multiple processing engines to access it. This could be either through a SQL interface, programmatic, or using API. Customers require federated access to their data with strong controls around Authentication, Authorization, Encryption, and Audit. In this session, we explore the major AWS analytics services and platforms that customers can use to access data in the data Lake and provide best practices on securing them.
This document provides an overview of databases and Amazon Web Services database options. It discusses SQL and NoSQL databases, and covers Amazon RDS and DynamoDB in more detail. Amazon RDS is a relational database service that provides easy administration and scalability. DynamoDB is a fully managed NoSQL database with fast performance and seamless scalability. The document demonstrates how to choose between these and other database options based on needs.
Hybrid Cloud Storage for Recovery & Migration with AWS Storage Gateway (STG30...Amazon Web Services
In this workshop, we provide hands-on experience using the AWS Storage Gateway service to protect on-premises data in AWS, recover it locally or in the cloud in minutes, and migrate it when the time is right. You work with the File Gateway and Microsoft SQL Server native tools to back up to Amazon S3, and then recover or migrate that database in AWS rapidly. In addition, you use Volume Gateway and Amazon EBS Snapshots to protect and migrate block-based volumes. Use this session to hone your skills with backup and DR, and prepare for application migrations.
The Future of Enterprise Applications is Serverless (ENT314-R1) - AWS re:Inve...Amazon Web Services
The document discusses serverless computing and Amazon Web Services (AWS) serverless technologies. It provides an overview of AWS Lambda, API Gateway, Step Functions, and other services. It also shares experiences from Centrica, an energy company, in adopting a serverless approach for some of their applications and services. Centrica saw benefits from serverless including cost reduction, faster development cycles, and improved agility.
Power up Your AWS Data Lake and Warehouse with Trusted Data (Sponsored by Tal...Amazon Web Services
Do data quality issues, demanding business needs and increasingly stringent regulations sound familiar? You may have moved your data to a data lake on Amazon S3 or a data warehouse on Amazon Redshift, but how do you deliver the ‘single source of trust’ needed to make decisions with scale and speed? We will share best practices that have helped our customers overcome these challenges. Betfair Pty Ltd, the world’s largest online betting exchange, will also share their experience using Talend and Redshift in enabling a analytics data warehouse with strong data quality and light governance practices.
Amazon S3: Updates and Best Practices - SRV301 - Chicago AWS SummitAmazon Web Services
Get the latest on what we've been developing in Amazon S3. In this session, learn about new advances in Amazon S3 performance, security, data protection, storage management, and much more. We discuss how to apply the appropriate bucket policies and encryption configurations to enhance security. We also explain how to use Amazon S3 Select to accelerate queries and take advantage of object tagging for data classification.
Best Practices for Amazon S3 and Amazon Glacier (STG203-R2) - AWS re:Invent 2018Amazon Web Services
Learn best practices for Amazon S3 performance optimization, security, data protection, storage management, and much more. In this session, we look at common Amazon S3 use cases and ways to manage large volumes of data within Amazon S3. We discuss the latest performance improvements and how they impact previous guidance. We also talk about the Amazon S3 data resilience model and how architecture for the AWS Regions and Availability Zones impact architecture for fault tolerance.
Building Hybrid Cloud Storage Architectures with AWS @scaleAmazon Web Services
The document discusses building hybrid cloud storage architectures with AWS. It provides an overview of AWS storage services including Amazon S3, Glacier, EBS, and EFS. It also describes the AWS Storage Gateway family of on-premises appliances that enable hybrid storage between on-premises and AWS cloud storage. Specifically, it covers the File Gateway for accessing S3 storage as files, Volume Gateway for iSCSI volumes, and Tape Gateway for migrating tape backups to S3.
Learn best practices for Amazon Simple Storage Service (Amazon S3) performance optimization, security, data protection, storage management, and much more. Learn how to optimize key naming to increase throughput, apply the appropriate AWS Identity and Access Management (IAM) and encryption configurations, and leverage object tagging and other features to enhance security.
Public sector teams with on-prem applications face many problems managing storage arrays throughout their short lifecycle: guessing at capacity needs, waiting for procurement cycles, recruiting staff with specialized hardware skills, etc. AWS Storage Gateway helps reduce these pains by providing a way to start using Amazon S3, Amazon Glacier and Amazon EBS in hybrid architectures for traditional and cutting-edge workloads, from backup to big data analytics. Storage Gateway connects local applications to AWS storage with familiar block and file protocols, and local caching for performance. In this session, learn how you can use these AWS Storage services with Storage Gateway for backup, content storage, data lakes, disaster recovery, data migration and more.
Stevan Beara, Solutions Architect, Amazon Web Services
Matt Campbell, Engineering Director, D2L
Cost efficiencies and security best practices with Amazon S3 storage - STG301...Amazon Web Services
Join us to learn best practices for Amazon S3 cost optimization and security. Amazon S3 supports various storage classes to help you cost-effectively store data. In this session, Amazon S3 experts discuss these storage classes, their key features, and the use cases that they support. We examine the newest storage classes, S3 Intelligent-Tiering and S3 Glacier Deep Archive. Learn about Amazon S3 access control policies, encryption, and security monitoring. Also, learn how to use S3 Block Public Access, a feature that helps you enforce a no public access policy for an individual bucket, a group of buckets, or an entire account.
On premises compliance archival systems are expensive to maintain, are isolated IT silos, have very inefficient utilization, and are poorly protected from disaster. In AWS, we provide better infrastructure durability, better physical security, lower cost, and richer features for data access. Consider that many data lakes contain medical records, trading records, and other regulated content. The industry now has the opportunity to execute rich analytics against their data while retaining regulatory compliance.
Learn from our engineering experts how we've designed Amazon S3 and Amazon Glacier to be durable, available, and massively scalable. Hear how Sprinklr architected their environment for the ultimate in high availability for their mission-critical applications. In this session, we'll discuss AWS Region and Availability Zone architecture, storage classes, built-in and on-demand data replication, and much more.
Amazon S3 and Amazon Glacier provide developers and IT teams with secure, durable, highly-scalable object storage with no minimum fees or setup costs. In this webcast, we will provide an introduction to each service, dive deep into key features of Amazon S3 and Amazon Glacier, and explore different use cases that these services optimize.
Learning Objectives:
• Business value of Amazon S3 and Amazon Glacier
• Leveraging S3 for web applications, media delivery, big data analytics and backup
• Leveraging Amazon Glacier to build cost effective archives
• Understand the life cycle management of AWS’s storage services
Who Should Attend:
• Developers, DevOps Engineers, Engineers and System Administrators
by Robbie Wright, HEad of Amazon S3 & Amazon Glacier Product Marketing, AWS
Learn from AWS on how we've designed S3 and Glacier to be durable, available, and massively scalable. Hear how customers are using these services to enhance the accessibility and usability of their data. We will also dive into the benefits of object storage, its applications, and some best practices to follow.
Data Lake Implementation: Processing and Querying Data in Place (STG204-R1) -...Amazon Web Services
Flexibility is key when building and scaling a data lake. The analytics solutions you use in the future will almost certainly be different from the ones you use today, and choosing the right storage architecture gives you the agility to quickly experiment and migrate with the latest analytics solutions. In this session, we explore best practices for building a data lake in Amazon S3 and Amazon Glacier for leveraging an entire array of AWS, open source, and third-party analytics tools. We explore use cases for traditional analytics tools, including Amazon EMR and AWS Glue, as well as query-in-place tools like Amazon Athena, Amazon Redshift Spectrum, Amazon S3 Select, and Amazon Glacier Select.
The document provides an overview of Amazon Web Services storage and content delivery services, including Amazon Simple Storage Service (S3), Amazon Elastic Block Store (EBS), Amazon Import/Export Snowball, and Amazon CloudFront. It describes the core capabilities and use cases for each service. Specifically, it notes that S3 provides scalable object storage, EBS offers persistent block storage volumes, Snowball enables petabyte-scale data transport, and CloudFront helps distribute content globally for low latency. The document also includes pricing, performance, and architectural details for each service.
Modern data is massive, quickly evolving, unstructured, and increasingly hard to catalog and understand from multiple consumers and applications. This presentation will guide you though the best practices for designing a robust data architecture, highlightning the benefits and typical challenges of data lakes and data warehouses. We will build a scalable solution based on managed services such as Amazon Athena, AWS Glue, and AWS Lake Formation.
The document discusses Amazon S3 and how it is used by many large companies to store massive amounts of data. It outlines key features of S3 including different storage classes, cross region replication, lifecycle policies, and analytics capabilities. The document also discusses using S3 for website hosting, big data analytics, backup/disaster recovery, and event-driven architectures with AWS Lambda. Overall, the document shows how Amazon S3 has become a fundamental service for storing and analyzing large scale data across a wide variety of use cases.
The document discusses AWS analytics services that can be used to build better data lakes. It describes how customers are moving to data lake architectures that bring together the benefits of data warehouses and data lakes. The document then summarizes various AWS analytics services like Amazon S3, AWS Glue, Lake Formation, Amazon Redshift, Amazon EMR, Amazon Athena, Amazon Elasticsearch Service, Amazon SageMaker, Amazon QuickSight, and AWS Data Exchange that can be used for different types of analytics on the data lake including data warehousing, big data processing, interactive querying, operational analytics, real-time analytics, predictive analytics, and visualizations.
This document provides an overview of Amazon Web Services storage and content delivery services, including Amazon Simple Storage Service (S3), Amazon Elastic Block Store (EBS), and Amazon CloudFront. It describes the core capabilities and use cases for each service. The key points are:
S3 provides scalable object storage and retrieval online. It can store unlimited objects with 99.999999999% durability. EBS offers persistent block storage volumes for EC2 instances with consistent performance. Snapshots of EBS volumes are stored in S3. CloudFront is a content delivery network (CDN) that caches content at edge locations for low-latency access. It can deliver entire websites, applications and APIs to users.
This document provides an overview of Amazon Web Services storage and content delivery services, including Amazon Simple Storage Service (S3), Amazon Elastic Block Store (EBS), and Amazon CloudFront. It describes the core capabilities and use cases for each service. The key points are:
S3 provides scalable object storage and retrieval online. It has unlimited storage capacity and high durability. EBS offers persistent block level storage volumes for EC2 instances with consistent performance. CloudFront is a content delivery network (CDN) that caches and delivers content globally for websites and applications.
As the volume and types of data continues to grow, customers often have valuable data that is not easily discoverable and available for analytics. A common challenge for data engineering teams is architecting a data lake that can cater to the needs of diverse users - from developers to business analysts to data scientists. In this session, dive deep into building a data lake using Amazon S3, Amazon Kinesis, Amazon Athena and AWS Glue. Learn how AWS Glue crawlers can automatically discover your data, extracting and cataloguing relevant metadata to reduce operations in preparing your data for downstream consumers.
Storage Data Management: Tools and Templates to Seamlessly Automate and Optim...Amazon Web Services
This document discusses storage management strategies for Amazon S3 and Amazon Glacier. It provides an overview of S3 architecture and storage classes. It also describes tools for organizing, monitoring, securing, and taking action on stored data using object tagging, inventory, metrics, lifecycle policies, cross-region replication, encryption, and event notifications. The document aims to help users understand their stored data and automate storage management.
Similar to SRV301 Latest Updates & Best Practices for Amazon S3 (20)
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Amazon Web Services
Il Forecasting è un processo importante per tantissime aziende e viene utilizzato in vari ambiti per cercare di prevedere in modo accurato la crescita e distribuzione di un prodotto, l’utilizzo delle risorse necessarie nelle linee produttive, presentazioni finanziarie e tanto altro. Amazon utilizza delle tecniche avanzate di forecasting, in parte questi servizi sono stati messi a disposizione di tutti i clienti AWS.
In questa sessione illustreremo come pre-processare i dati che contengono una componente temporale e successivamente utilizzare un algoritmo che a partire dal tipo di dato analizzato produce un forecasting accurato.
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Amazon Web Services
La varietà e la quantità di dati che si crea ogni giorno accelera sempre più velocemente e rappresenta una opportunità irripetibile per innovare e creare nuove startup.
Tuttavia gestire grandi quantità di dati può apparire complesso: creare cluster Big Data su larga scala sembra essere un investimento accessibile solo ad aziende consolidate. Ma l’elasticità del Cloud e, in particolare, i servizi Serverless ci permettono di rompere questi limiti.
Vediamo quindi come è possibile sviluppare applicazioni Big Data rapidamente, senza preoccuparci dell’infrastruttura, ma dedicando tutte le risorse allo sviluppo delle nostre le nostre idee per creare prodotti innovativi.
Ora puoi utilizzare Amazon Elastic Kubernetes Service (EKS) per eseguire pod Kubernetes su AWS Fargate, il motore di elaborazione serverless creato per container su AWS. Questo rende più semplice che mai costruire ed eseguire le tue applicazioni Kubernetes nel cloud AWS.In questa sessione presenteremo le caratteristiche principali del servizio e come distribuire la tua applicazione in pochi passaggi
Vent'anni fa Amazon ha attraversato una trasformazione radicale con l'obiettivo di aumentare il ritmo dell'innovazione. In questo periodo abbiamo imparato come cambiare il nostro approccio allo sviluppo delle applicazioni ci ha permesso di aumentare notevolmente l'agilità, la velocità di rilascio e, in definitiva, ci ha consentito di creare applicazioni più affidabili e scalabili. In questa sessione illustreremo come definiamo le applicazioni moderne e come la creazione di app moderne influisce non solo sull'architettura dell'applicazione, ma sulla struttura organizzativa, sulle pipeline di rilascio dello sviluppo e persino sul modello operativo. Descriveremo anche approcci comuni alla modernizzazione, compreso l'approccio utilizzato dalla stessa Amazon.com.
Come spendere fino al 90% in meno con i container e le istanze spot Amazon Web Services
L’utilizzo dei container è in continua crescita.
Se correttamente disegnate, le applicazioni basate su Container sono molto spesso stateless e flessibili.
I servizi AWS ECS, EKS e Kubernetes su EC2 possono sfruttare le istanze Spot, portando ad un risparmio medio del 70% rispetto alle istanze On Demand. In questa sessione scopriremo insieme quali sono le caratteristiche delle istanze Spot e come possono essere utilizzate facilmente su AWS. Impareremo inoltre come Spreaker sfrutta le istanze spot per eseguire applicazioni di diverso tipo, in produzione, ad una frazione del costo on-demand!
In recent months, many customers have been asking us the question – how to monetise Open APIs, simplify Fintech integrations and accelerate adoption of various Open Banking business models. Therefore, AWS and FinConecta would like to invite you to Open Finance marketplace presentation on October 20th.
Event Agenda :
Open banking so far (short recap)
• PSD2, OB UK, OB Australia, OB LATAM, OB Israel
Intro to Open Finance marketplace
• Scope
• Features
• Tech overview and Demo
The role of the Cloud
The Future of APIs
• Complying with regulation
• Monetizing data / APIs
• Business models
• Time to market
One platform for all: a Strategic approach
Q&A
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Amazon Web Services
Per creare valore e costruire una propria offerta differenziante e riconoscibile, le startup di successo sanno come combinare tecnologie consolidate con componenti innovativi creati ad hoc.
AWS fornisce servizi pronti all'utilizzo e, allo stesso tempo, permette di personalizzare e creare gli elementi differenzianti della propria offerta.
Concentrandoci sulle tecnologie di Machine Learning, vedremo come selezionare i servizi di intelligenza artificiale offerti da AWS e, anche attraverso una demo, come costruire modelli di Machine Learning personalizzati utilizzando SageMaker Studio.
OpsWorks Configuration Management: automatizza la gestione e i deployment del...Amazon Web Services
Con l'approccio tradizionale al mondo IT per molti anni è stato difficile implementare tecniche di DevOps, che finora spesso hanno previsto attività manuali portando di tanto in tanto a dei downtime degli applicativi interrompendo l'operatività dell'utente. Con l'avvento del cloud, le tecniche di DevOps sono ormai a portata di tutti a basso costo per qualsiasi genere di workload, garantendo maggiore affidabilità del sistema e risultando in dei significativi miglioramenti della business continuity.
AWS mette a disposizione AWS OpsWork come strumento di Configuration Management che mira ad automatizzare e semplificare la gestione e i deployment delle istanze EC2 per mezzo di workload Chef e Puppet.
Scopri come sfruttare AWS OpsWork a garanzia e affidabilità del tuo applicativo installato su Instanze EC2.
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsAmazon Web Services
Vuoi conoscere le opzioni per eseguire Microsoft Active Directory su AWS? Quando si spostano carichi di lavoro Microsoft in AWS, è importante considerare come distribuire Microsoft Active Directory per supportare la gestione, l'autenticazione e l'autorizzazione dei criteri di gruppo. In questa sessione, discuteremo le opzioni per la distribuzione di Microsoft Active Directory su AWS, incluso AWS Directory Service per Microsoft Active Directory e la distribuzione di Active Directory su Windows su Amazon Elastic Compute Cloud (Amazon EC2). Trattiamo argomenti quali l'integrazione del tuo ambiente Microsoft Active Directory locale nel cloud e l'utilizzo di applicazioni SaaS, come Office 365, con AWS Single Sign-On.
Dal riconoscimento facciale al riconoscimento di frodi o difetti di fabbricazione, l'analisi di immagini e video che sfruttano tecniche di intelligenza artificiale, si stanno evolvendo e raffinando a ritmi elevati. In questo webinar esploreremo le possibilità messe a disposizione dai servizi AWS per applicare lo stato dell'arte delle tecniche di computer vision a scenari reali.
Amazon Web Services e VMware organizzano un evento virtuale gratuito il prossimo mercoledì 14 Ottobre dalle 12:00 alle 13:00 dedicato a VMware Cloud ™ on AWS, il servizio on demand che consente di eseguire applicazioni in ambienti cloud basati su VMware vSphere® e di accedere ad una vasta gamma di servizi AWS, sfruttando a pieno le potenzialità del cloud AWS e tutelando gli investimenti VMware esistenti.
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
Crea la tua prima serverless ledger-based app con QLDB e NodeJSAmazon Web Services
Molte aziende oggi, costruiscono applicazioni con funzionalità di tipo ledger ad esempio per verificare lo storico di accrediti o addebiti nelle transazioni bancarie o ancora per tenere traccia del flusso supply chain dei propri prodotti.
Alla base di queste soluzioni ci sono i database ledger che permettono di avere un log delle transazioni trasparente, immutabile e crittograficamente verificabile, ma sono strumenti complessi e onerosi da gestire.
Amazon QLDB elimina la necessità di costruire sistemi personalizzati e complessi fornendo un database ledger serverless completamente gestito.
In questa sessione scopriremo come realizzare un'applicazione serverless completa che utilizzi le funzionalità di QLDB.
Con l’ascesa delle architetture di microservizi e delle ricche applicazioni mobili e Web, le API sono più importanti che mai per offrire agli utenti finali una user experience eccezionale. In questa sessione impareremo come affrontare le moderne sfide di progettazione delle API con GraphQL, un linguaggio di query API open source utilizzato da Facebook, Amazon e altro e come utilizzare AWS AppSync, un servizio GraphQL serverless gestito su AWS. Approfondiremo diversi scenari, comprendendo come AppSync può aiutare a risolvere questi casi d’uso creando API moderne con funzionalità di aggiornamento dati in tempo reale e offline.
Inoltre, impareremo come Sky Italia utilizza AWS AppSync per fornire aggiornamenti sportivi in tempo reale agli utenti del proprio portale web.
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareAmazon Web Services
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
In queste slide, gli esperti AWS e VMware presentano semplici e pratici accorgimenti per facilitare e semplificare la migrazione dei carichi di lavoro Oracle accelerando la trasformazione verso il cloud, approfondiranno l’architettura e dimostreranno come sfruttare a pieno le potenzialità di VMware Cloud ™ on AWS.
1) The document discusses building a minimum viable product (MVP) using Amazon Web Services (AWS).
2) It provides an example of an MVP for an omni-channel messenger platform that was built from 2017 to connect ecommerce stores to customers via web chat, Facebook Messenger, WhatsApp, and other channels.
3) The founder discusses how they started with an MVP in 2017 with 200 ecommerce stores in Hong Kong and Taiwan, and have since expanded to over 5000 clients across Southeast Asia using AWS for scaling.
This document discusses pitch decks and fundraising materials. It explains that venture capitalists will typically spend only 3 minutes and 44 seconds reviewing a pitch deck. Therefore, the deck needs to tell a compelling story to grab their attention. It also provides tips on tailoring different types of decks for different purposes, such as creating a concise 1-2 page teaser, a presentation deck for pitching in-person, and a more detailed read-only or fundraising deck. The document stresses the importance of including key information like the problem, solution, product, traction, market size, plans, team, and ask.
This document discusses building serverless web applications using AWS services like API Gateway, Lambda, DynamoDB, S3 and Amplify. It provides an overview of each service and how they can work together to create a scalable, secure and cost-effective serverless application stack without having to manage servers or infrastructure. Key services covered include API Gateway for hosting APIs, Lambda for backend logic, DynamoDB for database needs, S3 for static content, and Amplify for frontend hosting and continuous deployment.
This document provides tips for fundraising from startup founders Roland Yau and Sze Lok Chan. It discusses generating competition to create urgency for investors, fundraising in parallel rather than sequentially, having a clear fundraising narrative focused on what you do and why it's compelling, and prioritizing relationships with people over firms. It also notes how the pandemic has changed fundraising, with examples of deals done virtually during this time. The tips emphasize being fully prepared before fundraising and cultivating connections with investors in advance.
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...Amazon Web Services
This document discusses Amazon's machine learning services for building conversational interfaces and extracting insights from unstructured text and audio. It describes Amazon Lex for creating chatbots, Amazon Comprehend for natural language processing tasks like entity extraction and sentiment analysis, and how they can be used together for applications like intelligent call centers and content analysis. Pre-trained APIs simplify adding machine learning to apps without requiring ML expertise.
Amazon Elastic Container Service (Amazon ECS) è un servizio di gestione dei container altamente scalabile, che semplifica la gestione dei contenitori Docker attraverso un layer di orchestrazione per il controllo del deployment e del relativo lifecycle. In questa sessione presenteremo le principali caratteristiche del servizio, le architetture di riferimento per i differenti carichi di lavoro e i semplici passi necessari per poter velocemente migrare uno o più dei tuo container.