Talk presented in the GDG Golang Berlin meetup group, about my current pet project. It is a tool designed to automate the use of AWS EC2 spot instances within an initially on-demand AutoScaling group.
Introduction of cloud HPC platform "Rescale", and demonstration of its new feature "Bring Your Own VPC"
Serverworks Lightning Talks Tournament, 7th July, 2017
See also https://youtu.be/IU8GxTzhPIs?t=24s
This document provides an overview of Netflix's API and how it fits into Netflix's systems and operations. The API enables innovation and insulation from failures by personalizing the user experience and enabling mid-tier services and UI scripts. It handles over 2 billion requests per day and is designed for automation, visibility, and balancing speed and quality. The API infrastructure includes load balancers, application clusters, services, and an API layer. Netflix uses tools like distributed tracing, automated canary analysis, deployment automation, and log streaming to operate and monitor the API at scale.
Custom SharePoint Integration - from zero to here in 60 minutesDelta-N
In this session we will build a custom SharePoint integration for CRM for scratch to a working version. I will build the following parts:
Custom workflow activity to call an Azure function
Workflow
A SharePoint model to create a SharePoint site using remote provisioning
Azure function to create a site on demand
The solution is is fully supported, easy to implement and after the custom creation run has taken place, only uses out of the box CRM components. All the great CRM document integration benefits and a decent SharePoint solution.
The document discusses Siebel eScript, a scripting language that can be used in Siebel applications. It provides two types of scripts: server scripts that run on the server and browser scripts that run in the browser. Siebel eScript allows access to system calls through objects and can be used for data validation, user interaction, and integration with external systems. The document provides guidelines and commands for using Siebel eScript and tips for optimizing scripts.
This document discusses how AWS services can help startups and developers achieve profitability. It provides an example of a company that was able to reduce costs and improve margins by 54% through optimizing its architecture on AWS. Key strategies discussed include leveraging reserved instances, spot pricing, cost-aware architecting techniques like caching with S3 and CloudFront, database optimizations, and rapid prototyping tools to reduce test/dev costs. The document emphasizes starting with understanding usage patterns, doing an apples-to-apples comparison of total costs, and continuously optimizing resources through pricing models and architectural improvements.
This document outlines the steps to deploy an Essbase cube for planning and reporting using Epma Studio. The key steps include using the same user and schema for interface tables, staging tables, and dimension tables to feed a fact table. The fact table then populates an Epma model and cube within Studio. Drill through reports are defined and the cube is deployed incrementally on the planning application.
The Microsoft Automated ML Service automates the machine learning process by using techniques like probabilistic matrix factorization to automatically train and deploy models for a given dataset with minimal coding. It handles tasks like feature engineering, model training, evaluation, and selection to build accurate machine learning models. The service is part of Azure Machine Learning and can be accessed through Azure Notebooks with sample projects provided to demonstrate its capabilities for automated machine learning.
Patterns and practices for real-world event-driven microservicesRachel Reese
Jet.com is an e-commerce startup competing with Amazon. We're heavy users of F#, and have based our architecture around Azure-based event-driven functional microservices. Over the last several months, we've schooled ourselves on what works and what doesn't for F# and microservices. This session will walk you through the lessons we have learned on our way to developing our platform.
Introduction of cloud HPC platform "Rescale", and demonstration of its new feature "Bring Your Own VPC"
Serverworks Lightning Talks Tournament, 7th July, 2017
See also https://youtu.be/IU8GxTzhPIs?t=24s
This document provides an overview of Netflix's API and how it fits into Netflix's systems and operations. The API enables innovation and insulation from failures by personalizing the user experience and enabling mid-tier services and UI scripts. It handles over 2 billion requests per day and is designed for automation, visibility, and balancing speed and quality. The API infrastructure includes load balancers, application clusters, services, and an API layer. Netflix uses tools like distributed tracing, automated canary analysis, deployment automation, and log streaming to operate and monitor the API at scale.
Custom SharePoint Integration - from zero to here in 60 minutesDelta-N
In this session we will build a custom SharePoint integration for CRM for scratch to a working version. I will build the following parts:
Custom workflow activity to call an Azure function
Workflow
A SharePoint model to create a SharePoint site using remote provisioning
Azure function to create a site on demand
The solution is is fully supported, easy to implement and after the custom creation run has taken place, only uses out of the box CRM components. All the great CRM document integration benefits and a decent SharePoint solution.
The document discusses Siebel eScript, a scripting language that can be used in Siebel applications. It provides two types of scripts: server scripts that run on the server and browser scripts that run in the browser. Siebel eScript allows access to system calls through objects and can be used for data validation, user interaction, and integration with external systems. The document provides guidelines and commands for using Siebel eScript and tips for optimizing scripts.
This document discusses how AWS services can help startups and developers achieve profitability. It provides an example of a company that was able to reduce costs and improve margins by 54% through optimizing its architecture on AWS. Key strategies discussed include leveraging reserved instances, spot pricing, cost-aware architecting techniques like caching with S3 and CloudFront, database optimizations, and rapid prototyping tools to reduce test/dev costs. The document emphasizes starting with understanding usage patterns, doing an apples-to-apples comparison of total costs, and continuously optimizing resources through pricing models and architectural improvements.
This document outlines the steps to deploy an Essbase cube for planning and reporting using Epma Studio. The key steps include using the same user and schema for interface tables, staging tables, and dimension tables to feed a fact table. The fact table then populates an Epma model and cube within Studio. Drill through reports are defined and the cube is deployed incrementally on the planning application.
The Microsoft Automated ML Service automates the machine learning process by using techniques like probabilistic matrix factorization to automatically train and deploy models for a given dataset with minimal coding. It handles tasks like feature engineering, model training, evaluation, and selection to build accurate machine learning models. The service is part of Azure Machine Learning and can be accessed through Azure Notebooks with sample projects provided to demonstrate its capabilities for automated machine learning.
Patterns and practices for real-world event-driven microservicesRachel Reese
Jet.com is an e-commerce startup competing with Amazon. We're heavy users of F#, and have based our architecture around Azure-based event-driven functional microservices. Over the last several months, we've schooled ourselves on what works and what doesn't for F# and microservices. This session will walk you through the lessons we have learned on our way to developing our platform.
Amazon cloud services have introduced a new feature called Spot Instances. When Amazon EC2 has unused capacity, it offers AWS Spot Instances at a low cost.
(CMP311) This One Weird API Request Will Save You ThousandsAmazon 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 session, 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."
Cloudreach Voices EC2 Making Sense of the Cost Options Cloudreach
This document discusses the various cost options for Amazon EC2 instances, including on-demand instances, reserved instances, spot instances, and dedicated instances. It provides details on the advantages and use cases for each option, and notes that the most cost-effective choice depends on factors like workload requirements and duration of usage. Reserved instances can offer significant savings but require capacity planning to avoid costs from unused reservations. Spot instances provide the lowest prices but exposures to termination risk.
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.
AWS Cost Opt Meetup 2 - News corp - Spot On deep divePeter Shi
1. The document discusses replacing reserved EC2 instances with Spot Instances to reduce costs and maximize unused AWS capacity. It outlines several challenges of using Spot Instances like instance termination and deregistration from load balancers.
2. The solutions proposed include using Lambda functions to deregister terminated instances from load balancers, pre-empting the Spot market by triggering autoscaling when Spot capacity is low, and automating the process through CloudFormation templates and stacks.
3. An automated deployment process is outlined using CloudFormation templates, Lambda functions to generate Spot Fleet configurations, and CloudWatch alarms and events to manage capacity and respond to market changes.
Cut AWS Costs: Using Spot Instances for More Than BatchRightScale
Think spot instances are only for batch jobs? It’s time to think again. In this webinar you will learn about new capabilities and techniques for using spot instances. Many AWS users are using spot for development, test, and even production applications. Learn about new spot capabilities from AWS and find out how Spotinst’s Elastigroup tool integrates with RightScale to help you save money.
An introduction to Spot Instances and AWS Fleet - WebinarCMPUTE
This document discusses AWS EC2 Spot Instances, which provide spare computing capacity on AWS at steep discounts compared to on-demand pricing. Spot Instances allow bidding on unused EC2 capacity and will remain running as long as the bid exceeds the current Spot price. The document outlines how Spot Instance pricing is determined by supply and demand, and how Spot Instances can be interrupted if prices rise. It also introduces Batchly, a service that automates provisioning of Spot Instances to optimize costs for batch jobs and data processing workloads.
AWS re:Invent 2016: Dollars and Sense: Technical Tips for Continual Cost Opti...Amazon Web Services
In this session, we explore techniques, tools, and partner solutions that provide a framework for monitoring, analyzing, and automating cost savings. We look at several case studies and real world examples where our customers have realized significant savings. Some of the specific topics covered are: migration cost management; cost-effective hybrid architectures; saving money with microservices; serverless computing with AWS Lambda, and Amazon EC2; using fungible components to drive down costs over time; cost vs. performance vs. value; AWS purchasing strategies (On-Demand, Reserved Instances, and the Spot Market), tools and services from both AWS (AWS Trusted Advisor, Amazon CloudWatch, etc.) and our partner solutions that can help with cost optimization. Finally, we roll all of these into an automated process for continuous optimization.
Coding Apps in the Cloud to reduce costs up to 90% - September 2016 Webinar S...Amazon Web Services
Think differently when building apps in the cloud: heterogeneous environments, microservices, and disposable nodes are key components to building robust, deployment, and automated server management.
In this session, we will investigate patterns for engineering scalable stateless systems, indentifying anti-patterns to avoid, and show how you can save 90% on your overall compute costs. When engineered for cloud, you will never worry about the uptime of a node again.
We will 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 and ongoing development effort. Attendees leave with practical knowledge of Spot bidding strategies, Spot market price trends, instance selection, and fault-tolerant architectures for web services.
Learning Objectives:
• Learn more about EC2 Spot and how you can use it to save 90% off your EC2 bill
• Learn how to effective use Spot in production workloads by incorporating new Auto Scaling features
• Learn best practices on bidding and choosing Spot instances
Who Should Attend:
• Customers who are familiar with Amazon EC2, or customers who want to understand how they can use Spot to run applications in the cloud.
AWS EMEA Online Summit - Blending Spot and On-Demand instances to optimizing ...Cobus Bernard
This document discusses optimizing costs and capacity on Amazon EC2. It provides an overview of AWS global infrastructure including 23 regions and 216 CloudFront points of presence. It then discusses Amazon EC2 instance types and characteristics, and how customers can optimize costs through purchase options like Reserved Instances (RIs), Savings Plans, and Spot Instances. The document also discusses how to configure Auto Scaling groups to use different purchase options together to further optimize costs.
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. Lunch will be provided.
The document provides an overview of Amazon EC2 Spot Instances. It discusses what Spot Instances are, the simple rules that govern them, best practices for using them including fault tolerance and diversification, tools for managing Spot Instances like Spot Fleet and the Spot console, and examples of how customers like Guttman Lab and Yelp have used Spot Instances.
The document discusses cloud cost optimization strategies. It identifies key pillars for cost optimization including right-sizing resources, leveraging different pricing models, using appropriate storage classes, measuring usage, and designing architectures for cost efficiency. The optimization process involves monitoring usage and costs, identifying unnecessary resources, and establishing a tagging strategy. Key recommendations include turning off idle instances, deleting unused volumes, stopping paid services when not in use, using consolidated billing for discounts, and automating processes. Latest trends discussed are 1ms billing granularity for Lambda and independent provisioning of performance and capacity for EBS volumes.
Getting Started with EC2 Spot - November 2016 Webinar SeriesAmazon Web Services
This document discusses how to save up to 90% on EC2 costs by using Spot Instances. It provides an overview of AWS EC2 pricing models including On-Demand, Reserved, and Spot Instances. It then focuses on best practices for using Spot Instances, such as using the Spot Bid Advisor, diversifying Spot Fleets across instance types and Availability Zones, and leveraging the two minute warning for Spot termination. Examples are given of customers saving 75-87% on their EC2 costs by using Spot Instances for batch processing, continuous integration, and real-time ad delivery workloads.
AWS re:Invent 2016: Save up to 90% and Run Production Workloads on Spot - Fea...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 session, we dive into how customers who have designed scalable, cloud friendly application architectures can leverage new Spot features to realize immediate cost savings while maintaining availability. Attendees will leave with practical knowledge of how, via well architected applications, they can run production services on the Spot instances just like IFTTT and Mapbox.
This document discusses how to reduce spending on AWS through various techniques:
1. Paying for cloud resources only when they are used through the pay-as-you-go model avoids upfront costs and allows turning off unused capacity.
2. Using reserved instances when capacity needs are predictable provides significant discounts compared to on-demand pricing.
3. Architecting applications in a "cost aware" manner, such as leveraging caching, auto-scaling, managed services, and right-sizing instances can optimize costs.
4. Taking advantage of AWS's economies of scale through consolidated billing and free services helps lower overall spend. Planning workload usage of spot instances can achieve up to 85% savings.
AWS has different pricing models to match your needs. One example is the different instance types available such as On-Demand, Reserved and Spot Instances. Customers can develop cost-saving strategies based upon their usage patterns, models and growth expectations. In some cases, a set of larger instances can be cheaper than multiple small instances. Learn how to size your AWS applications to maximize your use and minimize your spend. Companies such as Pinterest take very active roles to constantly reduce their spend; learn how they do it and develop your own cost-saving approaches.
This session is a deep dive into techniques used by successful customers who optimized their use of AWS. Learn tricks and hear tips you can implement right away to reduce waste, choose the most efficient instance, and fine-tune your spending; often with improved performance and a better end-customer experience. We showcase innovative approaches and demonstrate easily applicable methods to save you time and money with Amazon EC2, Amazon S3, and a host of other services.
Workshop; Deploy a Deep Learning Framework on Amazon ECS and Spot InstancesAmazon Web Services
This document provides an overview of a workshop on deploying a deep learning framework on Amazon ECS and Spot Instances. The workshop will introduce MXNet, containers, Amazon ECS, Amazon ECR, AWS CloudFormation, Amazon EC2 Spot Fleet and Spot Instances. It will include hands-on labs to build an MXNet Docker image, deploy an MXNet container with ECS, and run an image classification demo using a Spot Fleet on ECS. The overall goal is to learn how to cost-effectively run deep learning workloads on AWS.
This document provides an overview of Amazon EC2 and autoscaling. It discusses EC2 basics like instance lifecycle, types, and using Amazon Machine Images. It also covers bootstrapping EC2 instances using metadata and user data. Monitoring EC2 with CloudWatch and different types of autoscaling like vertical, horizontal, and using Auto Scaling groups are explained. Autoscaling helps ensure applications have the correct resources to handle varying load and reduces manual scaling efforts.
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
More Related Content
Similar to Autospoting - an automated EC2 spot market bidder
Amazon cloud services have introduced a new feature called Spot Instances. When Amazon EC2 has unused capacity, it offers AWS Spot Instances at a low cost.
(CMP311) This One Weird API Request Will Save You ThousandsAmazon 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 session, 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."
Cloudreach Voices EC2 Making Sense of the Cost Options Cloudreach
This document discusses the various cost options for Amazon EC2 instances, including on-demand instances, reserved instances, spot instances, and dedicated instances. It provides details on the advantages and use cases for each option, and notes that the most cost-effective choice depends on factors like workload requirements and duration of usage. Reserved instances can offer significant savings but require capacity planning to avoid costs from unused reservations. Spot instances provide the lowest prices but exposures to termination risk.
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.
AWS Cost Opt Meetup 2 - News corp - Spot On deep divePeter Shi
1. The document discusses replacing reserved EC2 instances with Spot Instances to reduce costs and maximize unused AWS capacity. It outlines several challenges of using Spot Instances like instance termination and deregistration from load balancers.
2. The solutions proposed include using Lambda functions to deregister terminated instances from load balancers, pre-empting the Spot market by triggering autoscaling when Spot capacity is low, and automating the process through CloudFormation templates and stacks.
3. An automated deployment process is outlined using CloudFormation templates, Lambda functions to generate Spot Fleet configurations, and CloudWatch alarms and events to manage capacity and respond to market changes.
Cut AWS Costs: Using Spot Instances for More Than BatchRightScale
Think spot instances are only for batch jobs? It’s time to think again. In this webinar you will learn about new capabilities and techniques for using spot instances. Many AWS users are using spot for development, test, and even production applications. Learn about new spot capabilities from AWS and find out how Spotinst’s Elastigroup tool integrates with RightScale to help you save money.
An introduction to Spot Instances and AWS Fleet - WebinarCMPUTE
This document discusses AWS EC2 Spot Instances, which provide spare computing capacity on AWS at steep discounts compared to on-demand pricing. Spot Instances allow bidding on unused EC2 capacity and will remain running as long as the bid exceeds the current Spot price. The document outlines how Spot Instance pricing is determined by supply and demand, and how Spot Instances can be interrupted if prices rise. It also introduces Batchly, a service that automates provisioning of Spot Instances to optimize costs for batch jobs and data processing workloads.
AWS re:Invent 2016: Dollars and Sense: Technical Tips for Continual Cost Opti...Amazon Web Services
In this session, we explore techniques, tools, and partner solutions that provide a framework for monitoring, analyzing, and automating cost savings. We look at several case studies and real world examples where our customers have realized significant savings. Some of the specific topics covered are: migration cost management; cost-effective hybrid architectures; saving money with microservices; serverless computing with AWS Lambda, and Amazon EC2; using fungible components to drive down costs over time; cost vs. performance vs. value; AWS purchasing strategies (On-Demand, Reserved Instances, and the Spot Market), tools and services from both AWS (AWS Trusted Advisor, Amazon CloudWatch, etc.) and our partner solutions that can help with cost optimization. Finally, we roll all of these into an automated process for continuous optimization.
Coding Apps in the Cloud to reduce costs up to 90% - September 2016 Webinar S...Amazon Web Services
Think differently when building apps in the cloud: heterogeneous environments, microservices, and disposable nodes are key components to building robust, deployment, and automated server management.
In this session, we will investigate patterns for engineering scalable stateless systems, indentifying anti-patterns to avoid, and show how you can save 90% on your overall compute costs. When engineered for cloud, you will never worry about the uptime of a node again.
We will 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 and ongoing development effort. Attendees leave with practical knowledge of Spot bidding strategies, Spot market price trends, instance selection, and fault-tolerant architectures for web services.
Learning Objectives:
• Learn more about EC2 Spot and how you can use it to save 90% off your EC2 bill
• Learn how to effective use Spot in production workloads by incorporating new Auto Scaling features
• Learn best practices on bidding and choosing Spot instances
Who Should Attend:
• Customers who are familiar with Amazon EC2, or customers who want to understand how they can use Spot to run applications in the cloud.
AWS EMEA Online Summit - Blending Spot and On-Demand instances to optimizing ...Cobus Bernard
This document discusses optimizing costs and capacity on Amazon EC2. It provides an overview of AWS global infrastructure including 23 regions and 216 CloudFront points of presence. It then discusses Amazon EC2 instance types and characteristics, and how customers can optimize costs through purchase options like Reserved Instances (RIs), Savings Plans, and Spot Instances. The document also discusses how to configure Auto Scaling groups to use different purchase options together to further optimize costs.
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. Lunch will be provided.
The document provides an overview of Amazon EC2 Spot Instances. It discusses what Spot Instances are, the simple rules that govern them, best practices for using them including fault tolerance and diversification, tools for managing Spot Instances like Spot Fleet and the Spot console, and examples of how customers like Guttman Lab and Yelp have used Spot Instances.
The document discusses cloud cost optimization strategies. It identifies key pillars for cost optimization including right-sizing resources, leveraging different pricing models, using appropriate storage classes, measuring usage, and designing architectures for cost efficiency. The optimization process involves monitoring usage and costs, identifying unnecessary resources, and establishing a tagging strategy. Key recommendations include turning off idle instances, deleting unused volumes, stopping paid services when not in use, using consolidated billing for discounts, and automating processes. Latest trends discussed are 1ms billing granularity for Lambda and independent provisioning of performance and capacity for EBS volumes.
Getting Started with EC2 Spot - November 2016 Webinar SeriesAmazon Web Services
This document discusses how to save up to 90% on EC2 costs by using Spot Instances. It provides an overview of AWS EC2 pricing models including On-Demand, Reserved, and Spot Instances. It then focuses on best practices for using Spot Instances, such as using the Spot Bid Advisor, diversifying Spot Fleets across instance types and Availability Zones, and leveraging the two minute warning for Spot termination. Examples are given of customers saving 75-87% on their EC2 costs by using Spot Instances for batch processing, continuous integration, and real-time ad delivery workloads.
AWS re:Invent 2016: Save up to 90% and Run Production Workloads on Spot - Fea...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 session, we dive into how customers who have designed scalable, cloud friendly application architectures can leverage new Spot features to realize immediate cost savings while maintaining availability. Attendees will leave with practical knowledge of how, via well architected applications, they can run production services on the Spot instances just like IFTTT and Mapbox.
This document discusses how to reduce spending on AWS through various techniques:
1. Paying for cloud resources only when they are used through the pay-as-you-go model avoids upfront costs and allows turning off unused capacity.
2. Using reserved instances when capacity needs are predictable provides significant discounts compared to on-demand pricing.
3. Architecting applications in a "cost aware" manner, such as leveraging caching, auto-scaling, managed services, and right-sizing instances can optimize costs.
4. Taking advantage of AWS's economies of scale through consolidated billing and free services helps lower overall spend. Planning workload usage of spot instances can achieve up to 85% savings.
AWS has different pricing models to match your needs. One example is the different instance types available such as On-Demand, Reserved and Spot Instances. Customers can develop cost-saving strategies based upon their usage patterns, models and growth expectations. In some cases, a set of larger instances can be cheaper than multiple small instances. Learn how to size your AWS applications to maximize your use and minimize your spend. Companies such as Pinterest take very active roles to constantly reduce their spend; learn how they do it and develop your own cost-saving approaches.
This session is a deep dive into techniques used by successful customers who optimized their use of AWS. Learn tricks and hear tips you can implement right away to reduce waste, choose the most efficient instance, and fine-tune your spending; often with improved performance and a better end-customer experience. We showcase innovative approaches and demonstrate easily applicable methods to save you time and money with Amazon EC2, Amazon S3, and a host of other services.
Workshop; Deploy a Deep Learning Framework on Amazon ECS and Spot InstancesAmazon Web Services
This document provides an overview of a workshop on deploying a deep learning framework on Amazon ECS and Spot Instances. The workshop will introduce MXNet, containers, Amazon ECS, Amazon ECR, AWS CloudFormation, Amazon EC2 Spot Fleet and Spot Instances. It will include hands-on labs to build an MXNet Docker image, deploy an MXNet container with ECS, and run an image classification demo using a Spot Fleet on ECS. The overall goal is to learn how to cost-effectively run deep learning workloads on AWS.
This document provides an overview of Amazon EC2 and autoscaling. It discusses EC2 basics like instance lifecycle, types, and using Amazon Machine Images. It also covers bootstrapping EC2 instances using metadata and user data. Monitoring EC2 with CloudWatch and different types of autoscaling like vertical, horizontal, and using Auto Scaling groups are explained. Autoscaling helps ensure applications have the correct resources to handle varying load and reduces manual scaling efforts.
Similar to Autospoting - an automated EC2 spot market bidder (20)
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
Must Know Postgres Extension for DBA and Developer during MigrationMydbops
Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
Abstract: Discover how PostgreSQL extensions can be your secret weapon! This talk explores how key extensions enhance database capabilities and streamline the migration process for users moving from other relational databases like Oracle.
Key Takeaways:
* Learn about crucial extensions like oracle_fdw, pgtt, and pg_audit that ease migration complexities.
* Gain valuable strategies for implementing these extensions in PostgreSQL to achieve license freedom.
* Discover how these key extensions can empower both developers and DBAs during the migration process.
* Don't miss this chance to gain practical knowledge from an industry expert and stay updated on the latest open-source database trends.
Mydbops Managed Services specializes in taking the pain out of database management while optimizing performance. Since 2015, we have been providing top-notch support and assistance for the top three open-source databases: MySQL, MongoDB, and PostgreSQL.
Our team offers a wide range of services, including assistance, support, consulting, 24/7 operations, and expertise in all relevant technologies. We help organizations improve their database's performance, scalability, efficiency, and availability.
Contact us: info@mydbops.com
Visit: https://www.mydbops.com/
Follow us on LinkedIn: https://in.linkedin.com/company/mydbops
For more details and updates, please follow up the below links.
Meetup Page : https://www.meetup.com/mydbops-databa...
Twitter: https://twitter.com/mydbopsofficial
Blogs: https://www.mydbops.com/blog/
Facebook(Meta): https://www.facebook.com/mydbops/
Discover the Unseen: Tailored Recommendation of Unwatched ContentScyllaDB
The session shares how JioCinema approaches ""watch discounting."" This capability ensures that if a user watched a certain amount of a show/movie, the platform no longer recommends that particular content to the user. Flawless operation of this feature promotes the discover of new content, improving the overall user experience.
JioCinema is an Indian over-the-top media streaming service owned by Viacom18.
Northern Engraving | Modern Metal Trim, Nameplates and Appliance PanelsNorthern Engraving
What began over 115 years ago as a supplier of precision gauges to the automotive industry has evolved into being an industry leader in the manufacture of product branding, automotive cockpit trim and decorative appliance trim. Value-added services include in-house Design, Engineering, Program Management, Test Lab and Tool Shops.
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
Introducing BoxLang : A new JVM language for productivity and modularity!Ortus Solutions, Corp
Just like life, our code must adapt to the ever changing world we live in. From one day coding for the web, to the next for our tablets or APIs or for running serverless applications. Multi-runtime development is the future of coding, the future is to be dynamic. Let us introduce you to BoxLang.
Dynamic. Modular. Productive.
BoxLang redefines development with its dynamic nature, empowering developers to craft expressive and functional code effortlessly. Its modular architecture prioritizes flexibility, allowing for seamless integration into existing ecosystems.
Interoperability at its Core
With 100% interoperability with Java, BoxLang seamlessly bridges the gap between traditional and modern development paradigms, unlocking new possibilities for innovation and collaboration.
Multi-Runtime
From the tiny 2m operating system binary to running on our pure Java web server, CommandBox, Jakarta EE, AWS Lambda, Microsoft Functions, Web Assembly, Android and more. BoxLang has been designed to enhance and adapt according to it's runnable runtime.
The Fusion of Modernity and Tradition
Experience the fusion of modern features inspired by CFML, Node, Ruby, Kotlin, Java, and Clojure, combined with the familiarity of Java bytecode compilation, making BoxLang a language of choice for forward-thinking developers.
Empowering Transition with Transpiler Support
Transitioning from CFML to BoxLang is seamless with our JIT transpiler, facilitating smooth migration and preserving existing code investments.
Unlocking Creativity with IDE Tools
Unleash your creativity with powerful IDE tools tailored for BoxLang, providing an intuitive development experience and streamlining your workflow. Join us as we embark on a journey to redefine JVM development. Welcome to the era of BoxLang.
AI in the Workplace Reskilling, Upskilling, and Future Work.pptxSunil Jagani
Discover how AI is transforming the workplace and learn strategies for reskilling and upskilling employees to stay ahead. This comprehensive guide covers the impact of AI on jobs, essential skills for the future, and successful case studies from industry leaders. Embrace AI-driven changes, foster continuous learning, and build a future-ready workforce.
Read More - https://bit.ly/3VKly70
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsDianaGray10
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
seamless data management.
Speakers:
Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
"What does it really mean for your system to be available, or how to define w...Fwdays
We will talk about system monitoring from a few different angles. We will start by covering the basics, then discuss SLOs, how to define them, and why understanding the business well is crucial for success in this exercise.
This talk will cover ScyllaDB Architecture from the cluster-level view and zoom in on data distribution and internal node architecture. In the process, we will learn the secret sauce used to get ScyllaDB's high availability and superior performance. We will also touch on the upcoming changes to ScyllaDB architecture, moving to strongly consistent metadata and tablets.
GlobalLogic Java Community Webinar #18 “How to Improve Web Application Perfor...GlobalLogic Ukraine
Під час доповіді відповімо на питання, навіщо потрібно підвищувати продуктивність аплікації і які є найефективніші способи для цього. А також поговоримо про те, що таке кеш, які його види бувають та, основне — як знайти performance bottleneck?
Відео та деталі заходу: https://bit.ly/45tILxj
"Scaling RAG Applications to serve millions of users", Kevin GoedeckeFwdays
How we managed to grow and scale a RAG application from zero to thousands of users in 7 months. Lessons from technical challenges around managing high load for LLMs, RAGs and Vector databases.
"Choosing proper type of scaling", Olena SyrotaFwdays
Imagine an IoT processing system that is already quite mature and production-ready and for which client coverage is growing and scaling and performance aspects are life and death questions. The system has Redis, MongoDB, and stream processing based on ksqldb. In this talk, firstly, we will analyze scaling approaches and then select the proper ones for our system.
1. AutoSpoting - an automated EC2
spot market bidder
GDG Berlin Golang - Clowdy Gophers
30 May 2016
Cristian Măgherușan-Stanciu
HERE Maps, Berlin
2. About me
SysAdmin at HERE Maps, Berlin, supporting maps.here.com(https://maps.here.com)
Background: networking, Linux, AWS, C/Shell/Perl/Ruby/Python
Passionate about automation
Spare-time gopher for a few months now, and I love it
5. AWS Spot Market Automation
Needed a non-trivial problem for learning Go in my spare time
First discussed on an AWS Berlin meet-up
Interesting, it got me thinking
Decided to 'go build' it in my spare time
6. AutoSpoting
Simple solution to reliably use the AWS spot market, for production use-cases
Easy to use
Simple design and implementation
Maximize cost savings without sacri cing high availability
7. AWS Spot Market - Intro
Unused EC2 capacity sold to the highest paying bidders
Prices based on supply/demand
Considerable variation per region, instance type and even availability zone
Not all of them are available on the market
8. AWS Spot Market - Typical Prices, Savings and Risks
Starts from 10% the on-demand price, peaks as high as 10x
Savings >80% of on-demand are common, or ~5x capacity for the same costs
But spot instances are terminated with a 2 minute notice when outbid!!!
m3.large in Virginia, last 30 days
9. AWS Spot Market - Challenges
Instances could be terminated at any time
The application must be designed with this in mind
Not applicable for everything
Rewards cloud'y designs
10. AWS Spot Market - Achieving High Availability with Manual Bidding
Place large bids and hope for the best
Spread over multiple pricing zones
Carefully pick region, instance type and availability zone
AWS o ers helper tools
AWS Spot Bid Advisor
11. AWS Spot Market - Automation Bidding Solutions
AWS o ers just building blocks
AutoScaling native integration - supports a single instance type
SpotFleet - entirely di erent API, has some limitations (scaling, ELB...)
Also there are many 3rd party & custom tools
12. My Solution - AutoSpoting
Leverage recent autoscaling features to replace on-demand instances with spot
equivalents
Spread over multiple instance types in each availability zone
AutoScaling handles instance terminations and ELB integration for the spot
instances
Easy to install and con gure against existing AutoScaling groups
Serverless and low overhead
22. Algorithm details
The Lambda JavaScript shim automatically updates to the latest released binary
that is implementing all the logic and runs it
The Go program downloads data describing instance specs and on-demand
pricing (compiled by ec2instances.info)
Goroutines are then processing in parallel all the regions and enabled groups
The spot instance type and bid price are determined for each group, based on the
on-demand running instances and current spot prices
Instance replacement is performed as described in the work ow
23. High Availability
Spot instance termination, when outbid
Handled by AutoScaling like any instance failure
AutoScaling will launch on-demand instances to compensate for lost capacity
Those will in turn be replaced with spot instances later, as per the work ow
Low likelihood of service downtime, with enough pricing zones and redundancy
24. Installation details
Easy deployment via CloudFormation stack
Enable/disable per AutoScaling group using a custom tag, o by default
Have a look on my my blog(http://mcristi.wordpress.com)for detailed installation instructions
26. Challenges
Needs automated testing, currently I mostly do it manually
Automated testing needs some internal redesign (WIP)
Still trying to gure out testing with the AWS SDK for Go
How to do table-structured tests with big/mocked data structures
27. Future Plans
Finish preparing for automated testing
Write tests
Use information about termination likelihood from the Spot Bid Advisor
Make some parameters of the algorithm con gurable
React on the 2min termination notice, with code running on spot instances
Allow keeping some on-demand capacity if con gured
Open source the code
32. Thank you
Cristian Măgherușan-Stanciu
HERE Maps, Berlin
cristian.magherusan-stanciu@here.com(mailto:cristian.magherusan-stanciu@here.com)
https://mcristi.wordpress.com(https://mcristi.wordpress.com)
@magheru_san(http://twitter.com/magheru_san)