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, you will learn core concepts behind AWS Batch and details of how the service functions.
Amazon EC2 Spot instances provide acceleration, scale, and deep cost savings to run time-critical, hyper-scale workloads for rapid data analysis. In this session,you will learn best practices on how to scale big data workloads as well as process, store, and analyze big data securely and cost effectively.
Amazon EC2 provides you with the flexibility to cost optimize your computing portfolio through purchasing models that fit your business needs. With the flexibility of mix-and-match purchasing models, you can grow your compute capacity and throughput and enable new types of cloud computing applications with the lowest TCO. In this session, we will explore combining pay-as-you-go (On-Demand), reserve ahead of time for discounts (Reserved), and high-discount spare capacity (Spot) purchasing models to optimize costs while maintaining high performance and availability for your applications. Common application examples will be used to demonstrate how to best combine EC2’s purchasing models. You will leave the session with best practices you can immediately apply to your application portfolio.
Amazon EC2 changes the economics of computing and provides you with complete control of your computing resources. It is designed to make web-scale cloud computing easier for developers. In this session, we will take you on a journey, starting with the basics of key management and security groups and ending with an explanation of Auto Scaling and how you can use it to match capacity and costs to demand using dynamic policies. We will also discuss tools and best practices that will help you build failure resilient applications that take advantage of the scale and robustness of AWS regions.
Amazon EC2 allows you to bid for and run spare EC2 capacity, known as Spot instances, in a dynamically priced market. On average, customers save 80% to 90% compared to On Demand prices by using Spot instances. Achieving these savings has historically required time and effort to find the best deals while managing compute capacity as supply and demand fluctuate.
Intended for customers who have (or will have) thousands of instances on AWS, this session is about reducing the complexity of managing costs for these large fleets so they run efficiently. Attendees will learn about common roadblocks that prevent large customers from cost optimizing, tools they can use to efficiently remove those roadblocks, and techniques to monitor their rate of cost optimization. The session will include a case study that will talk in detail about the millions of dollars saved using these techniques. Customers will learn about a range of templates they can use to quickly implement these techniques, and also partners who can help them implement these templates.
Amazon EC2 Spot instances provide acceleration, scale, and deep cost savings to run time-critical, hyper-scale workloads for rapid data analysis. In this session,you will learn best practices on how to scale big data workloads as well as process, store, and analyze big data securely and cost effectively.
Amazon EC2 provides you with the flexibility to cost optimize your computing portfolio through purchasing models that fit your business needs. With the flexibility of mix-and-match purchasing models, you can grow your compute capacity and throughput and enable new types of cloud computing applications with the lowest TCO. In this session, we will explore combining pay-as-you-go (On-Demand), reserve ahead of time for discounts (Reserved), and high-discount spare capacity (Spot) purchasing models to optimize costs while maintaining high performance and availability for your applications. Common application examples will be used to demonstrate how to best combine EC2’s purchasing models. You will leave the session with best practices you can immediately apply to your application portfolio.
Amazon EC2 changes the economics of computing and provides you with complete control of your computing resources. It is designed to make web-scale cloud computing easier for developers. In this session, we will take you on a journey, starting with the basics of key management and security groups and ending with an explanation of Auto Scaling and how you can use it to match capacity and costs to demand using dynamic policies. We will also discuss tools and best practices that will help you build failure resilient applications that take advantage of the scale and robustness of AWS regions.
Amazon EC2 allows you to bid for and run spare EC2 capacity, known as Spot instances, in a dynamically priced market. On average, customers save 80% to 90% compared to On Demand prices by using Spot instances. Achieving these savings has historically required time and effort to find the best deals while managing compute capacity as supply and demand fluctuate.
Intended for customers who have (or will have) thousands of instances on AWS, this session is about reducing the complexity of managing costs for these large fleets so they run efficiently. Attendees will learn about common roadblocks that prevent large customers from cost optimizing, tools they can use to efficiently remove those roadblocks, and techniques to monitor their rate of cost optimization. The session will include a case study that will talk in detail about the millions of dollars saved using these techniques. Customers will learn about a range of templates they can use to quickly implement these techniques, and also partners who can help them implement these templates.
AWS Summit London 2014 | Introduction to Amazon EC2 (100)Amazon Web Services
This session will provide an overview of the Amazon Elastic Compute Cloud (EC2) service capability and help you understand the latest updates to the range of instances types, virtual private cloud (VPC) features. It will also help you to understand the broad range of pricing options that EC2 provides and how you can use these to make smart decisions that reduce your costs.
Adapting the capacity of your compute infrastructure to the demands of your applications is the domain of Auto Scaling. Adding and removing Amazon EC2 instances is only part of the story, though – there is more to it than first meets the eye. This session introduces the basics of how to use Auto Scaling before moving on to more advanced topics such as mixing Spot and On-Demand instances to optimize cost or strategies for blue/green deployments. If you have used Auto Scaling before, you can learn about useful new features like lifecycle hooks and step scaling policies that make Auto Scaling even more widely applicable.
Amazon Elastic Compute Cloud (Amazon EC2) provides a broad selection of instance types to accommodate a diverse mix of workloads. In this technical session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations.
We dive into the current generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and GPU instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
Speaker:
Ian Massingham, AWS Technical Evangelist
AWS October Webinar Series - Using Spot Instances to Save up to 90% off Your ...Amazon Web Services
Amazon EC2 allows you to bid for and run spare EC2 capacity, known as Spot instances, in a dynamically priced market. On average, customers save 80% to 90% compared to On Demand prices by using Spot instances. Achieving these savings has historically required time and effort to find the best deals while managing compute capacity as supply and demand fluctuate.
In this webinar, we dive into best practices and new features that will help you realize immediate cost savings, maximize compute capacity within your budget, and maintain application availability and performance with less up-front or ongoing development effort. Attendees leave with practical knowledge of Spot bidding strategies, market trends, instance selection and benchmarking, and fault-tolerant architecture with examples taken from common Spot use cases such as web services, big data/analytics, media processing, and continuous integration workloads.
AWS Batch is a service that enables developers, scientists, and engineers to easily and efficiently run batch computing workloads at scale on AWS. AWS Batch automatically provisions compute resources and optimizes the workload distribution based on the quantity and scale of the workloads, allowing you to focus on analyzing results and solving problems.
In this session, led by the AWS Batch service team, you will learn core concepts behind AWS Batch and details of how the service functions. We will cover multiple patterns used by customers to leverage storage and GPUs as part of their batch workloads. We will also cover how to integrate AWS Batch with other services such as AWS Step Functions for decision based workloads or Amazon CloudWatch Events to trigger batch jobs based on events or schedules.
Using AWS Batch and AWS Step Functions to Design and Run High-Throughput Work...Amazon Web Services
Learning Objectives:
- How to simply scale out your batch workflows on AWS
- How to think about container/job management within managed, high-throughput workflows
- How to build a scalable orchestration framework within AWS Step Functions
Amazon Elastic Compute Cloud (Amazon EC2) provides a broad selection of instance types to accommodate a diverse mix of workloads. In this technical session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current-generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and GPU instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
AWS Summit London 2014 | Options for Hybrid Environments (200)Amazon Web Services
This session is recommended for anyone considering using the AWS Cloud to augment their current IT capabilities. Adoption of cloud computing provides access to the benefits of new deployment models. But for existing enterprises, in many cases, applications deployed to the cloud need to integrate with existing on-premises resources. This session outlines several key factors to consider from the point of view of a large-scale real IT shop executive. Since each company is unique, this session compares the strengths, weaknesses, opportunities, and risks of each model and then helps participants create new hybrid orchestration and deployment options for hybrid enterprise environments.
Nearly 1,000 takeaways ordered a minute from hungry consumers, with near real time confirmation from restaurants and delivery of their food just 45 minutes later is a hard technical challenge.
AWS allows the many small engineering teams at JUST EAT to take responsibility to meet that challenge, as they build and operate a platform that delivers a takeaway experience for consumers to love.
Learn how we migrated our e-commerce platform to AWS and organise both our platform and teams around the the twin goals of rapid change and high availability. Watch as during the session we deploy changes and break things live in production, and see how the JUST EAT platform is designed around AWS to recover quickly and automatically.
This mid-level technical session will help you choose among the AWS services that can help you deploy and run your applications more easily. You will learn how to get an application running using AWS OpsWorks and AWS Elastic Beanstalk and how to use AWS CloudFormation templates to document, version control, and share your application configuration
AWS Webcast - High Availability SQL Server with Amazon RDSAmazon Web Services
Amazon RDS for Microsoft SQL Server makes it easy to set up, operate, and scale SQL Server deployments in the cloud. Amazon RDS Multi-AZ deployments provide enhanced availability and durability, making them a natural fit for production database workloads.
Review this webinar to learn more about this easy way to achieve highly available operation of SQL Server. When you provision a Multi-AZ DB Instance, Amazon RDS automatically creates a primary DB Instance and synchronously replicates the data to a standby instance in a different Availability Zone (AZ). Each AZ runs on its own physically distinct, independent infrastructure, and is engineered to be highly reliable. Amazon RDS performs an automatic failover to the standby, with no administrator intervention required, so that your application can resume database operations as soon as the failover is complete.
AWS re:Invent 2016: Auto Scaling – the Fleet Management Solution for Planet E...Amazon Web Services
Scaling allows cloud resources to scale automatically in reaction to the dynamic needs of customers. This session will show how Auto Scaling offers an advantage to everyone – whether it’s basic fleet management to keep instances healthy as an EC2 best practice, or dynamic scaling to manage “extremes”. We’ll share examples of how Auto Scaling is helping customers of all sizes and industries unlock use cases and value. We’ll also discuss how Auto Scaling is evolving to scaling different types of elastic AWS resources beyond EC2 instances. NASA Jet Propulsion Laboratory (JPL) / California Institute of Technology will share how Auto Scaling is used to scale science data processing of Interferometric Synthetic Aperture Radar (InSAR) data from earth-observing satellite missions, and reduce response times during hazard response events such as those from earthquakes, floods, and volcanoes. JPL will also discuss how they are integrating their science data systems with the AWS ecosystem to expand into NASA’s next two large-scale missions with remote-sensing radar-based observations. Learn how Auto Scaling is being used at a global scale – and beyond!
Automating Management of Amazon EC2 Instances with Auto Scaling - March 2017 ...Amazon Web Services
Automation is vital to efficient DevOps, and getting your fleets of EC2 instances to launch, provision software, and self-heal automatically is a key challenge. Auto Scaling provides essential features for each of these instance lifecycle automation steps, which are widely applicable to just about any type of application running on EC2. In this tech talk, you will learn about how to automate launches with Launch Configurations, configure the software environment before your instance accepts traffic using Lifecycle hooks, and how to create a resilient multi-AZ fleet to run your application with minimal effort.
Learning Objectives:
1. Learn how you can improve application availability and operational efficiency by automating fleet L10management for Amazon EC2 instances
2. Understand how Auto Scaling works and how easy it is to control the lifecycle of your fleet and the applications they run
3. Hear about recent developments in the Auto Scaling service how they provide an advantage to a wide variety of applications
Amazon EC2 provides a broad selection of instance types to accommodate a diverse mix of workloads. In this session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and GPU instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
As customers build and run production microservices architectures based on containers, having powerful tools to manage the placement and scheduling of these workloads is critical. Amazon ECS allows customers to focus on building their application and removes the need for managing the cluster management software entirely.
AWS Summit London 2014 | Introduction to Amazon EC2 (100)Amazon Web Services
This session will provide an overview of the Amazon Elastic Compute Cloud (EC2) service capability and help you understand the latest updates to the range of instances types, virtual private cloud (VPC) features. It will also help you to understand the broad range of pricing options that EC2 provides and how you can use these to make smart decisions that reduce your costs.
Adapting the capacity of your compute infrastructure to the demands of your applications is the domain of Auto Scaling. Adding and removing Amazon EC2 instances is only part of the story, though – there is more to it than first meets the eye. This session introduces the basics of how to use Auto Scaling before moving on to more advanced topics such as mixing Spot and On-Demand instances to optimize cost or strategies for blue/green deployments. If you have used Auto Scaling before, you can learn about useful new features like lifecycle hooks and step scaling policies that make Auto Scaling even more widely applicable.
Amazon Elastic Compute Cloud (Amazon EC2) provides a broad selection of instance types to accommodate a diverse mix of workloads. In this technical session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations.
We dive into the current generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and GPU instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
Speaker:
Ian Massingham, AWS Technical Evangelist
AWS October Webinar Series - Using Spot Instances to Save up to 90% off Your ...Amazon Web Services
Amazon EC2 allows you to bid for and run spare EC2 capacity, known as Spot instances, in a dynamically priced market. On average, customers save 80% to 90% compared to On Demand prices by using Spot instances. Achieving these savings has historically required time and effort to find the best deals while managing compute capacity as supply and demand fluctuate.
In this webinar, we dive into best practices and new features that will help you realize immediate cost savings, maximize compute capacity within your budget, and maintain application availability and performance with less up-front or ongoing development effort. Attendees leave with practical knowledge of Spot bidding strategies, market trends, instance selection and benchmarking, and fault-tolerant architecture with examples taken from common Spot use cases such as web services, big data/analytics, media processing, and continuous integration workloads.
AWS Batch is a service that enables developers, scientists, and engineers to easily and efficiently run batch computing workloads at scale on AWS. AWS Batch automatically provisions compute resources and optimizes the workload distribution based on the quantity and scale of the workloads, allowing you to focus on analyzing results and solving problems.
In this session, led by the AWS Batch service team, you will learn core concepts behind AWS Batch and details of how the service functions. We will cover multiple patterns used by customers to leverage storage and GPUs as part of their batch workloads. We will also cover how to integrate AWS Batch with other services such as AWS Step Functions for decision based workloads or Amazon CloudWatch Events to trigger batch jobs based on events or schedules.
Using AWS Batch and AWS Step Functions to Design and Run High-Throughput Work...Amazon Web Services
Learning Objectives:
- How to simply scale out your batch workflows on AWS
- How to think about container/job management within managed, high-throughput workflows
- How to build a scalable orchestration framework within AWS Step Functions
Amazon Elastic Compute Cloud (Amazon EC2) provides a broad selection of instance types to accommodate a diverse mix of workloads. In this technical session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current-generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and GPU instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
AWS Summit London 2014 | Options for Hybrid Environments (200)Amazon Web Services
This session is recommended for anyone considering using the AWS Cloud to augment their current IT capabilities. Adoption of cloud computing provides access to the benefits of new deployment models. But for existing enterprises, in many cases, applications deployed to the cloud need to integrate with existing on-premises resources. This session outlines several key factors to consider from the point of view of a large-scale real IT shop executive. Since each company is unique, this session compares the strengths, weaknesses, opportunities, and risks of each model and then helps participants create new hybrid orchestration and deployment options for hybrid enterprise environments.
Nearly 1,000 takeaways ordered a minute from hungry consumers, with near real time confirmation from restaurants and delivery of their food just 45 minutes later is a hard technical challenge.
AWS allows the many small engineering teams at JUST EAT to take responsibility to meet that challenge, as they build and operate a platform that delivers a takeaway experience for consumers to love.
Learn how we migrated our e-commerce platform to AWS and organise both our platform and teams around the the twin goals of rapid change and high availability. Watch as during the session we deploy changes and break things live in production, and see how the JUST EAT platform is designed around AWS to recover quickly and automatically.
This mid-level technical session will help you choose among the AWS services that can help you deploy and run your applications more easily. You will learn how to get an application running using AWS OpsWorks and AWS Elastic Beanstalk and how to use AWS CloudFormation templates to document, version control, and share your application configuration
AWS Webcast - High Availability SQL Server with Amazon RDSAmazon Web Services
Amazon RDS for Microsoft SQL Server makes it easy to set up, operate, and scale SQL Server deployments in the cloud. Amazon RDS Multi-AZ deployments provide enhanced availability and durability, making them a natural fit for production database workloads.
Review this webinar to learn more about this easy way to achieve highly available operation of SQL Server. When you provision a Multi-AZ DB Instance, Amazon RDS automatically creates a primary DB Instance and synchronously replicates the data to a standby instance in a different Availability Zone (AZ). Each AZ runs on its own physically distinct, independent infrastructure, and is engineered to be highly reliable. Amazon RDS performs an automatic failover to the standby, with no administrator intervention required, so that your application can resume database operations as soon as the failover is complete.
AWS re:Invent 2016: Auto Scaling – the Fleet Management Solution for Planet E...Amazon Web Services
Scaling allows cloud resources to scale automatically in reaction to the dynamic needs of customers. This session will show how Auto Scaling offers an advantage to everyone – whether it’s basic fleet management to keep instances healthy as an EC2 best practice, or dynamic scaling to manage “extremes”. We’ll share examples of how Auto Scaling is helping customers of all sizes and industries unlock use cases and value. We’ll also discuss how Auto Scaling is evolving to scaling different types of elastic AWS resources beyond EC2 instances. NASA Jet Propulsion Laboratory (JPL) / California Institute of Technology will share how Auto Scaling is used to scale science data processing of Interferometric Synthetic Aperture Radar (InSAR) data from earth-observing satellite missions, and reduce response times during hazard response events such as those from earthquakes, floods, and volcanoes. JPL will also discuss how they are integrating their science data systems with the AWS ecosystem to expand into NASA’s next two large-scale missions with remote-sensing radar-based observations. Learn how Auto Scaling is being used at a global scale – and beyond!
Automating Management of Amazon EC2 Instances with Auto Scaling - March 2017 ...Amazon Web Services
Automation is vital to efficient DevOps, and getting your fleets of EC2 instances to launch, provision software, and self-heal automatically is a key challenge. Auto Scaling provides essential features for each of these instance lifecycle automation steps, which are widely applicable to just about any type of application running on EC2. In this tech talk, you will learn about how to automate launches with Launch Configurations, configure the software environment before your instance accepts traffic using Lifecycle hooks, and how to create a resilient multi-AZ fleet to run your application with minimal effort.
Learning Objectives:
1. Learn how you can improve application availability and operational efficiency by automating fleet L10management for Amazon EC2 instances
2. Understand how Auto Scaling works and how easy it is to control the lifecycle of your fleet and the applications they run
3. Hear about recent developments in the Auto Scaling service how they provide an advantage to a wide variety of applications
Amazon EC2 provides a broad selection of instance types to accommodate a diverse mix of workloads. In this session, we provide an overview of the Amazon EC2 instance platform, key platform features, and the concept of instance generations. We dive into the current generation design choices of the different instance families, including the General Purpose, Compute Optimized, Storage Optimized, Memory Optimized, and GPU instance families. We also detail best practices and share performance tips for getting the most out of your Amazon EC2 instances.
As customers build and run production microservices architectures based on containers, having powerful tools to manage the placement and scheduling of these workloads is critical. Amazon ECS allows customers to focus on building their application and removes the need for managing the cluster management software entirely.
AWS is an elastic, secure, flexible, and developer-centric ecosystem that serves as an ideal platform for Docker deployments. AWS offers the scalable infrastructure, APIs, and SDKs that integrate tightly into a development lifecycle and accentuate the benefits of the lightweight and portable containers that Docker offers to its users. This session familiarizes you with the benefits of containers, introduce Amazon EC2 Container Service, and demonstrates how to use Amazon ECS to run containerized applications at scale in production.
Modern data architectures for real time analytics and engagementAmazon Web Services
The AWS Workshop Series Online is a series of live webinars designed for IT professionals who are looking to leverage the AWS Cloud to build and transform their business, are new to the AWS Cloud or looking to further expand their skills and expertise. In this series, we will cover:" Modern Data Architectures for Real-time Analytics and Engagement'.
AWS X-Ray helps developers analyze and debug production, distributed applications, such as those built using a microservices architecture. With X-Ray, you can understand how your application and its underlying services are performing to identify and troubleshoot the root cause of performance issues and errors. X-Ray provides an end-to-end view of requests as they travel through your application, and shows a map of your application’s underlying components. Learn how to use X-Ray to analyze both applications in development and in production, from simple three-tier applications to complex microservices applications consisting of thousands of services.
In this session you will hear how Amazon Web Services (AWS) operates at scale and services over 1 Million customers, which maps to even more API calls every single second. Come and hear about how they deal with APIs, operate at scale and help to create lego block services that helps them to be customer obsessed.
The AWS Workshop Series Online is a series of live webinars designed for IT professionals who are looking to leverage the AWS Cloud to build and transform their business, are new to the AWS Cloud or looking to further expand their skills and expertise. In this series, we will cover : "Build a Website on AWS for Your First 10 Million Users".
Amazon Lightsail is the latest addition to the AWS family of compute services and the fastest way to get your next cloud server up and running. For a low price that starts at $5/month, Lightsail offers a bundle of resources and services that let you jumpstart your cloud project in a few clicks. The new, intuitive Lightsail console makes it simple to manage your virtual resources, letting you focus on code, not system administration. Learn how Lightsail can get you started on AWS quickly and efficiently.
Learn how to monitor and manage your serverless APIs in production. We show you how to set up Amazon CloudWatch alarms, interpret CloudWatch logs for Amazon API Gateway and AWS Lambda, and automate common maintenance and management tasks on your service.
Introducing Amazon Lex – A Service for Building Voice or Text Chatbots - Marc...Amazon Web Services
Amazon Lex is a service for building conversational interfaces into any application using voice and text. Lex provides the advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU) to recognize the intent of the text, to enable you to build applications with highly engaging user experiences and lifelike conversational interactions.
Learning Objectives:
• Learn about the capabilities and features of Amazon Lex
• Learn about the benefits of Amazon Lex
• Learn about the different use cases
• Learn how to get started using Amazon Lex
In this session, you'll learn what’s new and hot with AWS Lambda. Come learn about what we’ve been working on and what we are planning for the future. You'll get a hands-on demonstration of some our newest features.
With distributed frameworks like Hadoop and Kafka, it is essential to deploy the right environment to successfully support these workloads. Learn about the different block storage options from AWS and walk through with our experts on how to select the best option for your big data analytic workloads. We will demonstrate how to setup, select, and modify volume types to right size your environment needs.
AWS Step Functions is a new, fully-managed service that makes it easy to coordinate the components of distributed applications and microservices using visual workflows. Step Functions is a reliable way to connect and step through a series of AWS Lambda functions so that you can build and run multi-step applications in a matter of minutes. This session shows how to use AWS Step Functions to create, run, and debug cloud state machines to execute parallel, sequential, and branching steps of your application, with automatic catch and retry conditions.
Real-time data processing serverless architecture can eliminate the need to provision and manage servers required to process files or streaming data in real time. In this session, we will cover the fundamentals of using AWS Lambda to process data in real-time from push sources such as AWS Iot and pull sources such as Amazon DynamoDB Streams or Amazon Kinesis. We'll also discuss best practices and do a deep dive into AWS Lambda real-time stream processing.
This talk will be a 2-300 level discussion on Serverless Architectures on AWS. We’ll first explore the Serverless ecosystem on AWS, looking at some particular use cases for Serverless. Looking through the lens of AWS customers, we’ll look at the typical Serverless journey, as well some of the key emerging patterns and benefits of Serverless Architectures. We’ll also touch some of the key challenges in a distributed environment and some potential solutions and tools that customers might want to consider.
Announcing AWS Batch - Run Batch Jobs At Scale - December 2016 Monthly Webina...Amazon Web Services
AWS Batch enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. AWS Batch dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted. With AWS Batch, there is no need to install and manage batch computing software or server clusters that you use to run your jobs, allowing you to focus on analyzing results and solving problems.
Learning Objectives:
• Learn about the capabilities and features of AWS Batch
• Learn about the benefits of AWS Batch
• Learn about the different use cases
• Learn how to get started using AWS Batch
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.
NEW LAUNCH! Introducing AWS Batch: Easy and efficient batch computing on Amaz...Amazon 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.
Docker enables you to create highly customized images that are used to execute your jobs. These images allow you to easily share complex applications between teams and even organizations
AWS Batch: Simplifying batch computing in the cloudAdrian Hornsby
Docker enables you to create highly customized images that are used to execute your jobs. These images allow you to easily share complex applications between teams and even organizations. However, sometimes you might just need to run a script! This talk walk you through the steps to create and run a simple “fetch & run” job in AWS Batch. AWS Batch executes jobs as Docker containers using Amazon ECS. You build a simple Docker image containing a helper application that can download your script or even a zip file from Amazon S3. AWS Batch then launches an instance of your container image to retrieve your script and run your job.
CMP323_AWS Batch Easy & Efficient Batch Computing on Amazon Web ServicesAmazon Web Services
AWS Batch is a fully managed service that enables developers to easily and efficiently run batch computing workloads of any scale on AWS. AWS Batch automatically provisions the right quantity and type of compute resources needed to run your jobs. With AWS Batch, you don't need to install or manage batch computing software, so you can focus on analyzing results and solving problems. In this session, the principal product manager for AWS Batch, Jamie Kinney, describes the core concepts behind AWS Batch and details of how the service functions. The presenter then demonstrates the latest features of AWS Batch with relevant use cases and sample code before describing some of the upcoming features for the service. Finally, hear from AWS Batch customers as they describe why and how they are using AWS Batch. This portion of the talk is delivered by representatives from the University of Utah, Autodesk, and AdRoll.
Batch Processing with Containers on AWS - CON304 - re:Invent 2017Amazon Web Services
Batch processing is useful to analyze large amounts of data. But configuring and scaling a cluster of virtual machines to process complex batch jobs can be difficult.
In this talk, we'll show how to use containers on AWS for batch processing jobs that can scale quickly and cost-effectively. We will also discuss AWS Batch, our fully managed batch-processing service. You'll also hear from GoPro and Here about how they use AWS to run batch processing jobs at scale including best practices for ensuring efficient scheduling, fine-grained monitoring, compute resource automatic scaling, and security for your batch jobs.
Batch computing is a common way to run a series of programs, called batch jobs, on a large pool of shared compute resources, such as servers, virtual machines, and containers. But running batch workloads at scale is a challenging task, configuring and scaling a cluster of virtual machines to process complex batch jobs is difficult and resource intensive. In this session, we’ll discuss options and best practices for running batch jobs on AWS including AWS Batch, a fully managed batch-processing service, and building batch processing architectures with the Amazon EC2 Container Service. We’ll also discuss best practices for ensuring efficient and opportunistic scheduling, fine-grained monitoring, compute resource auto-scaling, and security for batch jobs.
Batch Processing with Containers on AWS - June 2017 AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Learn about the options for running batch workloads on AWS
- Learn how to architect a containerized batch processing service on Amazon ECS
- Learn best practices for optimizing and scaling complex batch workload requirements
Batch processing is useful when you need to periodically analyze large amounts of data, but configuring and scaling a cluster of virtual machines to process complex batch jobs can be difficult. Containers provide a great solution for running batch jobs by providing easily managed, scalable, and portable code environments.
In this tech talk, we’ll show you how to use containers on AWS for batch processing jobs that can scale quickly and cost-effectively. We’ll discuss AWS Batch, our fully managed batch-processing service, and show you how to architect your own batch processing service using the Amazon EC2 Container Service. We’ll also discuss best practices for ensuring efficient and opportunistic scheduling, fine-grained monitoring, compute resource auto-scaling, and security for your batch jobs.
by Harrell Stiles, Sr. Consultant, AWS ProServe
Batch computing is a common way to run a series of programs, called batch jobs, on a large pool of shared compute resources, such as servers, virtual machines, and containers. But running batch workloads at scale is a challenging task, configuring and scaling a cluster of virtual machines to process complex batch jobs is difficult and resource intensive. In this session, we’ll discuss options and best practices for running batch jobs on AWS including AWS Batch, a fully managed batch-processing service, and building batch processing architectures with the Amazon EC2 Container Service. We’ll also discuss best practices for ensuring efficient and opportunistic scheduling, fine-grained monitoring, compute resource auto-scaling, and security for batch jobs. Level 200
Docker containers have become a key component of modern application design. Increasingly, developers are breaking their applications apart into smaller components and distributing them across a pool of compute resources.
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.
Have you ever wondered how search works while visiting an e-commerce site, internal website, or searching through other types of online resources? Look no further than this informative session on the ways that taxonomies help end-users navigate the internet! Hear from taxonomists and other information professionals who have first-hand experience creating and working with taxonomies that aid in navigation, search, and discovery across a range of disciplines.
This presentation by Morris Kleiner (University of Minnesota), was made during the discussion “Competition and Regulation in Professions and Occupations” held at the Working Party No. 2 on Competition and Regulation on 10 June 2024. More papers and presentations on the topic can be found out at oe.cd/crps.
This presentation was uploaded with the author’s consent.
This presentation, created by Syed Faiz ul Hassan, explores the profound influence of media on public perception and behavior. It delves into the evolution of media from oral traditions to modern digital and social media platforms. Key topics include the role of media in information propagation, socialization, crisis awareness, globalization, and education. The presentation also examines media influence through agenda setting, propaganda, and manipulative techniques used by advertisers and marketers. Furthermore, it highlights the impact of surveillance enabled by media technologies on personal behavior and preferences. Through this comprehensive overview, the presentation aims to shed light on how media shapes collective consciousness and public opinion.
0x01 - Newton's Third Law: Static vs. Dynamic AbusersOWASP Beja
f you offer a service on the web, odds are that someone will abuse it. Be it an API, a SaaS, a PaaS, or even a static website, someone somewhere will try to figure out a way to use it to their own needs. In this talk we'll compare measures that are effective against static attackers and how to battle a dynamic attacker who adapts to your counter-measures.
About the Speaker
===============
Diogo Sousa, Engineering Manager @ Canonical
An opinionated individual with an interest in cryptography and its intersection with secure software development.
Acorn Recovery: Restore IT infra within minutesIP ServerOne
Introducing Acorn Recovery as a Service, a simple, fast, and secure managed disaster recovery (DRaaS) by IP ServerOne. A DR solution that helps restore your IT infra within minutes.
Sharpen existing tools or get a new toolbox? Contemporary cluster initiatives...Orkestra
UIIN Conference, Madrid, 27-29 May 2024
James Wilson, Orkestra and Deusto Business School
Emily Wise, Lund University
Madeline Smith, The Glasgow School of Art
2. Agenda
• A brief history of batch computing
• AWS Batch overview and concepts
• Use cases
• Let’s take it for a spin!
• Q&A
3. What is batch computing?
Run jobs asynchronously and automatically across one or
more computers.
Jobs may dependencies, making the sequencing and
scheduling of multiple jobs complex and challenging.
6. CRAY-1: 1976
• First commercial
supercomputer
• 167 millions
calculations/second
• USD$8.86 million
($7.9 million plus
$1 million for disk)
CRAY-1 on display in the hallways of the EPFL in Lausanne. https://commons.wikimedia.org/wiki/File:Cray_1_IMG_9126.jpg
7. Early Batch on AWS: NY Times TimesMachine
aws.amazon.com/blogs/aws/new-york-times/
In 2007 the New York Times
processed 130 years of archives in
36 hours.
11 million articles & 4TB of data
AWS services used:
Amazon S3, SQS, EC2, and EMR
Total cost (in 2007): $890
$240 compute + $650 storage
http://open.blogs.nytimes.com/2007/11/01/self-service-
prorated-super-computing-fun/
14. However, batch computing could be easier…
AWS
Components:
• EC2
• Spot Fleet
• Auto-Scaling
• SNS
• SQS
• CloudWatch
• AWS Lambda
• S3
• DynamoDB
• API Gateway
• …
15. Introducing AWS Batch
Fully Managed
No software to install or
servers to manage. AWS
Batch provisions,
manages, and scales your
infrastructure
Integrated with AWS
Natively integrated with the
AWS Platform, AWS Batch
jobs can easily and securely
interact with services such as
Amazon S3, DynamoDB, and
Rekognition
Cost-optimized
Resource Provisioning
AWS Batch automatically
provisions compute
resources tailored to the
needs of your jobs using
Amazon EC2 and EC2 Spot
16. Introducing AWS Batch
• Fully-managed batch primitives
• Focus on your applications (shell scripts,
Linux executables, Docker images) and
their resource requirements
• We take care of the rest!
18. Jobs
Jobs are the unit of work executed by AWS Batch as containerized
applications running on Amazon EC2.
Containerized jobs can reference a container image, command, and
parameters or users can simply provide a .zip containing their
application and we will run it on a default Amazon Linux container.
$ aws batch submit-job --job-name variant-calling
--job-definition gatk --job-queue genomics
19. Easily run massively parallel jobs
Today, users can submit a large number of independent “simple jobs.”
Soon, we will add support for “array jobs” that run many copies of an
application against an array of elements.
Array jobs are an efficient way to run:
• Parametric sweeps
• Monte Carlo simulations
• Processing a large collection of objects
These use-cases are still possibly today. Simply submit more jobs.
21. Workflows, Pipelines, and Job Dependencies
Jobs can express a dependency on the successful
completion of other jobs or specific elements of an
array job.
Use your preferred workflow engine and language to
submit jobs. Flow-based systems simply submit jobs
serially, while DAG-based systems submit many jobs
at once, identifying inter-job dependencies.
$ aws batch submit-job –depends-on 606b3ad1-aa31-48d8-92ec-f154bfc8215f ...
22. Job Definitions
Similar to ECS Task Definitions, AWS Batch Job Definitions specify how
jobs are to be run. While each job must reference a job definition, many
parameters can be overridden.
Some of the attributes specified in a job definition:
• IAM role associated with the job
• vCPU and memory requirements
• Mount points
• Container properties
• Environment variables
$ aws batch register-job-definition --job-definition-name gatk
--container-properties ...
23. Job Queues
Jobs are submitted to a Job Queue, where they reside until they are
able to be scheduled to a compute resource. Information related to
completed jobs persists in the queue for 24 hours.
$ aws batch create-job-queue --job-queue-name genomics
--priority 500 --compute-environment-order ...
24. Compute Environments
Job queues are mapped to one or more Compute Environments
containing the EC2 instances used to run containerized batch jobs.
Managed compute environments enable you to describe your business
requirements (instance types, min/max/desired vCPUs, and EC2 Spot bid
as a % of On-Demand) and we launch and scale resources on your behalf.
You can choose specific instance types (e.g. c4.8xlarge), instance families
(e.g. C4, M4, R3), or simply choose “optimal” and AWS Batch will launch
appropriately sized instances from our more-modern instance families.
25. Compute Environments
Alternatively, you can launch and manage your own resources within an
Unmanaged compute environment. Your instances need to include the
ECS agent and run supported versions of Linux and Docker.
AWS Batch will then create an Amazon ECS cluster which can accept the
instances you launch. Jobs can be scheduled to your Compute
Environment as soon as your instances are healthy and register with the
ECS Agent.
$ aws batch create-compute-environment --compute-
environment-name unmanagedce --type UNMANAGED ...
26. AWS Batch Concepts
The Scheduler evaluates when, where, and
how to run jobs that have been submitted to
a job queue.
Jobs run in approximately the order in which
they are submitted as long as all
dependencies on other jobs have been met.
27. Job States
Jobs submitted to a queue can have the following states:
SUBMITTED: Accepted into the queue, but not yet evaluated for execution
PENDING: Your job has dependencies on other jobs which have not yet completed
RUNNABLE: Your job has been evaluated by the scheduler and is ready to run
STARTING: Your job is in the process of being scheduled to a compute resource
RUNNING: Your job is currently running
SUCCEEDED: Your job has finished with exit code 0
FAILED: Your job finished with a non-zero exit code or was cancelled or
terminated.
29. AWS Batch Actions
CancelJob: Marks jobs that are not yet STARTING as FAILED.
TerminateJob: Cancels jobs that are currently waiting in the
queue. Stops jobs that are in a STARTING or RUNNING state
and transitions them to FAILED.
Requires a “reason” which is viewable via DescribeJobs
$ aws batch cancel-job --reason “Submitted to wrong queue”
--jobId= 8a767ac8-e28a-4c97-875b-e5c0bcf49eb8
30. AWS Batch Pricing
There is no charge for AWS Batch; you only pay for the
underlying resources that you consume!
31. AWS Batch Availability
• AWS Batch is GA in the US East (Northern Virginia) Region
• Support for Array Jobs and jobs executed as AWS Lambda
functions coming soon!
32. Use the Right Tool for the Job
Not all batch workloads are the same…
ETL and Big Data processing/analytics?
Consider EMR, Data Pipeline, Redshift, and related services.
Lots of small Cron jobs? AWS Batch is a great way to execute these jobs, but
you will likely want a workflow or job-scheduling system to orchestrate job
submissions.
Efficiently run lots of big and small compute jobs on heterogeneous
compute resources? That’s why we’re here!