All change! How the new Economics of Cloud will make you think differently about Java - Chris Bailey, Steve Poole

The document discusses how to build trust in cloud computing. It recommends a four-layer approach: 1) Educate yourself on cloud terms and security measures; 2) Monitor cloud services and infrastructure for issues; 3) Establish processes for training, escalation, and documentation; 4) Practice failover procedures by backing up data and testing backup systems. Following these steps can help address common concerns about lack of control, visibility and reliability in cloud computing.

The document discusses optimizing mobile web apps for performance and battery life. It outlines 5 tips: 1) Don't rely too heavily on network access due to high latency and battery drain. 2) Show content while loading to improve the user experience. 3) Leverage HTML5 features like localStorage, app caching, and web workers. 4) Offload animations and rendering to the GPU using CSS transforms where possible. 5) Keep the DOM simple and use event listeners carefully to improve efficiency. The document provides examples and recommendations for optimizing images, JavaScript, rendering, and the development process for better mobile web optimization.

The document discusses strategies for successful implementation of hybrid cloud environments at both the organizational and application levels. At the organizational level, key strategies include defining the cloud model for the organization, enabling users to transition workloads between clouds, and providing incentives for users to place workloads where costs are lowest. At the application level, important strategies involve understanding infrastructure differences between clouds, being aware of limitations of abstraction layers, and avoiding vendor lock-in through use of open source software. The document provides examples and considerations for hybrid cloud adoption from various companies.

How do organizations ensure that they maintain control over their costs when adopting Cloud? Ultimately, the key to controlling cost for cloud infrastructure is to ensure that the organization has visibility over resources that are being provisioned — a task that is easier said than done when developers can provision resources in a single API Call. This talk was presented at the 2014 OpenStack Summit in Atlanta.

Are you planning to deploy Web applications in the cloud? Will their performance be acceptable? What will you do to make sure? There are a lot of good reasons to deploy applications in a cloud environment — but they are all forgotten if your application is slow or has poor availability. Poor performance results in unhappy, lost customers. Traditional data center techniques for monitoring, measuring, and optimizing Web application performance won’t work in the cloud. There are a new set of best practices that you need to learn to optimize the performance of your cloud-based Web applications.

Today, a web page can be delivered to a desktop computer, a television, or a handheld device like a tablet or a phone. While a technique like responsive design helps ensure that our web sites look good across that spectrum of screen sizes we may forget our web sites should also be able to perform equally well across that same spectrum. While more and more of our users are shifting their Internet usage to these more varied platforms and connection speeds our development practices might not be keeping up.In this session we’ll review why optimizing web performance should be an important step in the development of responsive websites. We’ll look at the tools that can help you understand and measure the performance of those sites as well as discuss front-end and server-side techniques that can be used to help you improve their performance. Finally, since the best way to test your site is to have real devices in hand, we’ll share “lessons learned” so you can set-up your own device lab similar to what we have at West Virginia University.This presentation builds upon Dave’s “Optimization for Mobile” chapter in Smashing Magazine’s “The Mobile Book.”

Once you are at scale, it is even more important to focus on costs and run lean on AWS. This talk with explain the various purchasing models available, and will then address how to size your application for AWS. We will take you through various architectural best practices, such as auto-scaling, caching etc. to save costs and run lean by making the best decisions.

We all know Mobile is different, but by how much? This presentation attempts to quantify the difference between mobile and non-mobile, focusing on CPU, network and browser differences.

Choosing your mobile design paradigm is hard, and performance is an often overlooked parameter in this decision process. This presentation discusses the top performance concerns for the top mobile design paradigms - Dedicated Sites (mdot) and Responsive Web Design (RWD). Presented at Breaking Dev (bdconf) in April, 2012.

Leveraging the AWS Cloud can help you further lower your overall IT costs and avoid fixed, upfront IT investments. Learning how to right-size your environments can help you to go from capacity guessing to meeting QoE targets for your customers. The session will also cover best practices on how to Architect for Cost from real world customer use cases and ultimately how the AWS Cloud can help you increase revenue by focusing on Innovation and Return on Agility. Key takeaways - Replace up-front capital expenses with low variable costs - Outsource undifferentiated IT tasks to useful services - Evaluate the total Cost of (Non) Ownership - Build Cost-aware architectures - AWS features that help you reduce your spend - Different purchasing options available with AWS Who should attend - Technical Users: Developers, engineers, system administrators and architects - Decision Makers: IT Managers, directors and business leaders

This document discusses how cloud computing on Amazon Web Services (AWS) has impacted startups and venture capital. It notes that AWS allows startups to focus on innovation rather than infrastructure, developing faster at lower costs. This has led to more experimentation and new companies. It also discusses how AWS has changed the venture capital model by enabling startups to scale more quickly with lower costs. As a result, VCs now see more deals, faster growth, and higher valuations from portfolio companies using AWS.

Talk @ CodeMotion Berlin, 12/10/2017 Amazon AI Amazon Polly Amazon Rekognition Apache MXNet Raspberry Pi robot

The document discusses how cloud computing has changed the game by allowing for innovation, scale, cost savings, and global reach. It outlines four key areas of change enabled by cloud computing: innovation through rapid experimentation, global scale through multiple regions and edge locations, cost optimization by paying for only what is used, and the ability to go global easily. Examples are given of companies innovating faster and scaling globally using AWS cloud services like EC2, S3, DynamoDB, and others.

Machine Learning (ML) works by using powerful algorithms to discover patterns in data, and constructing complex mathematical models using these patterns. Once a model is built, you perform inference by applying data to the trained model to make predictions for your application. Building and training ML models requires massive computing resources so it is a natural fit for the cloud. But, inference takes a lot less computing power and is typically done in real-time when new data is available, so getting inference results with very low latency is important to making sure your applications can respond quickly to local events. AWS Greengrass ML inference gives you the best of both worlds. You use ML models that are built and trained in the cloud, and you deploy and run ML inference locally on connected devices. For example, autonomous cars need to identify road signs in real time; and drones need to recognize objects with or without network connectivity.

This document summarizes an opening presentation about startups using AWS cloud services. The summary includes: 1) The presentation discusses how AWS has enabled startups and companies like Dropbox, Instagram, and Pinterest to develop and scale their applications quickly and affordably. 2) Examples are given of how these companies leveraged AWS services like auto-scaling, reserved instances, and global infrastructure to lower costs and handle growth. 3) The presentation announces a new AWS Activate program that provides benefits and support packages to help startups get started and grow using AWS.

In this session we will show the agility gained by developing on AWS, so you can focus on your app, not your infrastructure. It starts with some key concepts around automation and managed services, and will then go into a live demo that brings a concept into production in 40 minutes, on a highly available, scalable, secure architecture.

Deskdoo is a cloud-based operating system that allows users to access applications and resources from any device without needing to install anything. It was founded in 2014 by Adam Adamczyk, Dawid Krawczykiewicz, and Robert Pasternak after an earlier startup failed in 2001 due to limitations of technology and experience. Deskdoo provides a unified interface for accessing tools like Google Apps, Adobe Photo Editor, and users' disk drives from any browser. It uses a freemium business model where basic services are free and premium applications and services can be paid for on a per-usage basis. The company aims to create a new ecosystem and revenue model for IT services hosted in the cloud.

This document discusses how the economics of cloud computing will change how Java applications are developed. Cloud providers charge for computing resources on an hourly basis (e.g. $ per GB per hour), which means applications need to use resources efficiently. Java applications generally use more memory and have longer startup times than other languages. To be cost effective in the cloud, Java applications will need to reduce their memory footprint, decrease startup times, and be designed to fail and recover gracefully. The rise of APIs and microservices also requires changes to make Java more modular and efficient in constrained environments.

How far have you got with learning about Cloud? Got your head around Platform as a Service? Understand what IaaS means? Can spell Docker? Working in a DevOps mode? It’s easy to focus on learning new technology but it’s time to take a step back and look at what the technical implications are when an application is heading to the cloud. In the world of the cloud the benefits are high but the economics (financial and technical) can be radically different. Learn more about these new realities and how they can change application design, deployment and support. The introduction of Cloud technologies and its rapid adoption creates new opportunities and challenges. Whether designer, developer or tester, this talk will help you to start thinking differently about Java and the Cloud. Presented at JAX DE, 2016

Presented at JAX London 2013 Per-tenant resource management can help ensure that collocated tenants peacefully share computational resources based on individual quotas. This session begins with a comparison of deployment models (shared: hardware, OS, middleware, everything) to motivate the multitenant approach. The main topic is an exploration of experimental data isolation and resource management primitives in IBM’s JDK that combine to help make multitenant applications smaller and more predictable.

Everyone is talking about building “cloud native” Java applications—and taking advantage of microservice architecture, containers, and orchestration/PaaS platforms—but there is surprisingly little discussion of migrating existing legacy (moneymaking) applications. This session aims to address this, and, using lessons learned from several real-world examples, it covers topics such when to rewrite applications (if at all), modeling/extracting business domains, applying the “application strangler” pattern, common misconceptions with “12-factor” application design, and the benefits/drawbacks of container technology.

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.

So you get DevOps. You like the idea and think it’s important. The trouble is that others in your team don’t. This session will help you understand how to convince your team of the benefits of DevOps. Packed with facts and figures, the presentation works through the common challenges Java teams face when moving to a DevOps model and outlines how to address them. It also shows you how to balance evangelism against pragmatism when championing DevOps in your organization. You’ll learn how others have made the transition to DevOps and understand what mistakes to avoid when doing so. Whether you need to know how to be a DevOps evangelist or simply want to understand why DevOps is important, this session is for you.

A workshop held in StartIT as part of Catena Media learning sessions. We aim to dispel the notion that large PHP applications tend to be sluggish, resource-intensive and slow compared to what the likes of Python, Erlang or even Node can do. The issue is not with optimising PHP internals - it's the lack of proper introspection tools and getting them into our every day workflow that counts! In this workshop we will talk about our struggles with whipping PHP Applications into shape, as well as work together on some of the more interesting examples of CPU or IO drain.

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 document discusses how integrating cloud services can help solve technology issues and reduce costs compared to building infrastructure from scratch. It provides 10 ways to utilize the cloud, including content delivery, CMS asset hosting, forms, backups, media streaming, development sandboxes, and encoding/processing large amounts of data. Examples are given of colleges that saved money by using cloud services for video hosting, CMS testing, and project development. Potential cloud providers like Amazon, Rackspace, and Mechanical Turk are also mentioned.

This slide contains a brief presentation of how Organizations can leverage Cloud to virtualize functional/performance testing and cost benefit from investing in hardware.

A introductory discussion of cloud computing and capacity planning implications is followed by a step by step guide to running a Hadoop job in EMR, and finally a discussion of how to write your own Hadoop queries.

This document provides an overview and summary of key points from a presentation on designing virtual infrastructures and hypervisors. It discusses pre-requisites, assessing which servers are good candidates for virtualization, measuring server performance, determining the right amount of RAM for virtual machines, different types of virtualization technologies, high availability options, and live migration capabilities.

This document discusses building a full-stack application called MemeMail using Golang and Google Cloud Platform within one week. It describes choosing Google Cloud over other cloud providers for its ease of use. It then discusses the frontend implementation using Vue.js with a simple state mutation approach. The backend is built with Golang on App Engine using Cloud services like Datastore and Cloud Build for CI/CD. It emphasizes keeping the architecture simple rather than over-engineering for an MVP within a tight deadline.

The document discusses how Lenddo, a financial technology company, has used AWS to scale its operations in a cost-effective manner. It provides details on: 1) How Lenddo started in 2011 in the Philippines and has since expanded to other countries, processing over 50k loan applications for 400k members. 2) How Lenddo's usage of AWS grew significantly from 2011 to 2013 as the company expanded. 3) The various AWS services Lenddo utilizes, including EC2, S3, DynamoDB, RDS, and others, to build its infrastructure in a flexible and scalable way. 4) How using AWS has helped Lenddo focus on coding and

The document discusses issues with memory and garbage collection in Java applications. It notes that the practical heap size for most Java applications has stagnated at around 2GB for the past decade, due to garbage collection pauses above this size. The document introduces Azul Systems and their Zing virtualization platform, which aims to eliminate garbage collection as a limiting factor through techniques like concurrent and parallel garbage collection that can support heaps up to 100GB without long pauses. It discusses various performance aspects of concurrent garbage collection like sensitivity to workload, heap population, and mutation rate.

This document provides information about cloud computing and Drupal cloud hosting providers. It discusses traditional hosting limitations like high costs, difficulty maintaining servers, and downtime issues. Cloud computing evolved to address these through virtualization, pay-as-you-go models, and automatic scaling. The document then compares top Drupal cloud providers Acquia, Pantheon, and Platform.sh based on their base cloud provider, uptime SLAs, pricing, support offerings, development environments, and other features. It concludes that while each provider has pros and cons, budget and client requirements should determine the best choice for a given project.

When we talk about prices, we often only talk about Lambda costs. In our applications, however, we rarely use only Lambda. Usually we have other building blocks like API Gateway, data sources like SNS, SQS or Kinesis. We also store our data either in S3 or in serverless databases like DynamoDB or recently in Aurora Serverless. All of these AWS services have their own pricing models to look out for. In this talk, we will draw a complete picture of the total cost of ownership in serverless applications and present a decision-making list for determining if and whether to rely on serverless paradigm in your project. In doing so, we look at the cost aspects as well as other aspects such as understanding application lifecycle, software architecture, platform limitations, organizational knowledge and plattform and tooling maturity. We will also discuss current challenges adopting serverless such as lack of high latency ephemeral storage, unsufficient network performance and missing security features.

This document discusses analyzing and optimizing costs when using AWS. It begins by addressing common misconceptions about AWS costs, such as that hardware costs are always cheaper than AWS or that cloud is not cost-effective for steady workloads. It then examines the total cost of ownership for on-premises infrastructure versus AWS, considering various fixed costs like hardware, software, facilities, administration, etc. The document provides examples of how tools like reserved instances, spot instances, and Trusted Advisor can help optimize costs over time. It emphasizes that AWS allows customers to scale resources up and down as needed to match actual demand.