Performance: Key Elements to Consider in the Cloud - RightScale Compute 2013

This presentation was given as part of a Dynatrace Lunch & Learn event. APM (=Application Performance Management) allows us to transform the way we develop, deploy and run software. Here are some ideas how APM can be (r)evolutionized

This document discusses common performance myths and challenges related to cloud migrations, SaaS deployments, and cloud native applications. It provides approaches to assess performance for each scenario. Some key points covered include: - Common myths like unlimited scaling without effort, cost savings from cloud alone, and SaaS vendors handling all performance. - Challenges for migrations include capacity planning, auto-scaling issues, and latency. For SaaS, risks include customization impacts and integration issues. Cloud native challenges are distributed architectures and configuration problems. - The document recommends approaches like baseline benchmarking, resilience testing, and 360-degree validation across user, cloud, data center and external layers to overcome myths and address challenges.

Believe it or not - 85% of mobile apps are removed after first usage! In this presentation - given at the APM Meetup in Singapore in April 2015 - I talked about the challenges, best practices and especially metrics to avoid this situation. Key Points of the Presentation The two key trends "Internet of Things" and "DevOps" play a big role in our life when we talk about User Experience and especially mobile user experience. In this presentation I tell you what metrics to use to make sure you deliver your ideas faster to your mobile end users but also ensuring the right quality and user experience so that your users stay loyal and dont delete the mobile app after first usage.

Slides used for https://www.devopsdays.org/events/2017-toronto/program/andreas-grabner/ In 2011 we delivered 2 major releases of our on premise enterprise software. Market, technology and customer requirements forced us to change that in order to remain competitive. Now – in 2017 - we are deploying and providing feature releases every 2 weeks for both our on premise and SaaS-based offering. We deploy 170 SaaS production changes per day and have a DevOps pipeline that allows us to deploy a code change within 1h if necessary. To increase quality, we built and provide a DevOps pipeline that currently executes 31000 Unit & Integration Tests per Hour as well as 60h UI Tests per Build. Our application teams are responsible end-to-end for their features and use production monitoring to validate their deployments which allows them to find 93% of bugs in production before it impacts our end users. In this session I explain how this transformation worked from both “Top Down” as well as “Bottom Up” in our organization. A key component was the 4 people strong DevOps Team who developed and “sell” their DevOps Pipeline to the globally distributed application teams. I will give insights into how our pipeline enables application teams to design, code, test and run a new feature for our user base. I will also talk about the “dark moments” as change is never without friction. Both internally as well as with our customers who also had to get used to more rapid changes.

Brian Frank, Sr. Manager of Technical Delivery at HOSTING, and Melissa Schultz, Project Manager at HOSTING, will be discussing why your organization needs to invest in disaster recovery solutions and how to do it. He will cover: -DR and business continuity -Key considerations for business continuity -Preparing for disasters -DR testing -How to implement your DR plan and run book

Talk about how we built and maintained a WebSockets platform on AWS infra. You can will learn insights about, * How to build and evovle a WebSockets platform on AWS * How we made the platform more resilient to failures known and unknown * How we saved costs by using right strategy for auto-scaling and load balancing * How to monitor a WebSockets platform

3 Tips to Deliver Fast Performance Across Mobile Web On-Demand Webinar Seems like everyone’s doing Responsive Web Design these days! Are you using React, Angular or others to create a mobile-friendly web experience? Newsflash: Mobile-friendly doesn’t always equal customer-friendly, when it comes to performance. We’re talking about 60% of your traffic—how do you avoid disaster? Learn the basics of high-performance mobile development through the examination of real-world, performance-killing code examples. You’ll also hear about: Why 4.5 seconds on Chrome can be 15 seconds on a Galaxy S5 Chromium How to identify major issues within mobile page construction Best practices for managing CSS and JavaScript Things to consider going global with your Web application Join web performance experts Klaus Enzenhofer and Stefan Baumgartner from Dynatrace to ensure your mobile properties are delighting your customers!

The concept of Reactive Streams (aka Reactive Extensions, Reactive Functional Programming, or simply Rx) has become increasingly popular recently, and with good reason. The Reactive Streams specification provides a universal abstraction for asynchronously processing data received across multiple sources (e.g. database, user input, third-party services), and includes mechanisms for controlling the rate at which data is received. This makes it a powerful tool within a Microservice platform. And did we mention that the Groovy lang community is quite involved? In this talk we’ll explore the various features and concepts of Reactive Streams. We’ll talk about some typical use cases for Rx and more importantly, how to implement them. We’ll focus primarily on RxGroovy and Ratpack, then provide example implementations that show you how to get started with this powerful technique.

A talk I gave at The API Architecture Summit hosted by Layer 7 on API design considerations for mobile devices and wearables

Subject to the CAP theorem, NoSQL distributed systems have mostly chosen availability over consistency. This has been changing, yet many famous databases are still AP only. This talk includes a theoretical overview, and a practical look at the tradeoffs for your application and data between AP and CP modes. Also, how do different levels of consistency actually matter? Distributed data stores are subject to the CAP theorem, and historically NoSQL distributed systems have chosen availability over consistency. This has been changing, yet many famous databases are still AP only. In Eric Brewer's 2012 follow-up article about the CAP theorem he stated: "Availability is obviously continuous from 0 to 100 percent, but there are also many levels of consistency, and even partitions have nuances, including disagreement within the system about whether a partition exists." This talk will include a theoretical overview, but focus on the practical aspects of the theorem. * What are the tradeoffs between AP and CP modes? * How do they affect your application and data? * How do different levels of consistency actually matter?

We'll discover the reasons why it is a risky bet to not *aim* to manage infrastructure and its configuration with idempotence and immutability at heart. Sharing real world experience, we'll see why configurations should not be done by humans (it's like playing Djenga), and why what may work at the beginning does not work over a long period of time or scale (pet vs cattle problem).

This is about leveling-up and REVOLUTIONIZING Testing as part of your Agile/DevOps Transformation. You can contribute more than testing functionality. You need to Level-Up your skill set by understanding the apps you are testing. # Images, # JS Files, # SQL Statements, Connection Pool Utilization and Garbage Collection Activity have to be added to your portfolio. Check these metrics when you do your functional testing and report regressions to your engineers even though the functionality is still good. But you just uncovered an Architectural regression that will lead to a scalabilty and performance problem. Finding these problems early will eliminate a lot of wasted and unplanned time later on in the lifecycle. that is your contribution to delivering software faster with better quality

This document discusses lessons learned from translating a book about agile practices using agile principles. It notes challenges with assumptions vs reality, communication visibility, planning and tracking, collaboration, quality, and work procedures. It provides recommendations such as using Kanban techniques like limiting work in process, visualizing work, and frequent checkpoints to improve synchronization and prevent delays. The key is to focus on communication, feedback, self-organization, and simple tools while inspecting and adapting practices.

This document provides advice on how to scale applications from Quentin Adam, who handles app uptime at Clever Cloud. It discusses two approaches for scaling - scaling up with a single large instance or scaling out across many smaller instances. Scaling out is recommended by splitting processes and storage, using statelessness, trusting middleware, and an event broker to modularize the app. Common mistakes to avoid include using the file system as a database, memory as a database, or dark magic. The key is to make small, modular codebases and services that can scale independently.

If you want to build the fastest WooCommerce store ever, then here is a checklist that you can review as you get started. It's the slide deck for my presentation in Grand Rapids this weekend.