This document discusses state transfer from an iPhone to an Apple Watch using Parallels Access. It describes the architecture goals of reducing dependencies and enabling delta updates. A key part of the architecture is a "live objects tree abstraction" that represents processes and machines in a synchronized tree structure. The document explains how watchOS 2 and Watch Connectivity APIs can improve synchronization by enabling file transfer and interactive messaging between devices.
An application designer usually has to choose where to trade flexibility for specificity (and thus usually performance); knowing when and where to do so is an art and requires experience. This talk will share over a decades worth of experience making these decisions and the learnings from developing Pivotal's successful Real Time Intelligence (RTI) product using the latest versions of Spring projects: Integration, Data, Boot, MVC/REST and XD. A walk through the RTI architecture will provide the base for an explanation about how Spring performs at hundreds (and millions) of events/operations per second and the techniques that you can use right now in your own Spring applications to minimise resource utilisation and gain performance.
Learn how to deploy your model to production in 30 minutes and..
• Reduce costs and man power with auto scaling
• Load balanced the traffic
• Natively monitored by Kubernetes
• Update your model continuously: canary deployments, blue/green deployments
Mariusz Richtscheid: Architektura typu serverless wraz z terminem "Function as a Service" zyskują coraz większą popularność. To całkiem odmienne podejście do tworzenia aplikacji oraz ich wdrażania ma wiele zalet, ale musimy być też świadomi problemów, jakie się z nim wiążą. W trakcie prezentacji pokażę, w jaki sposób można zmodyfikować istniejącą aplikację Node.js tak, by wykorzystać zalety tej architektury.
Setting up an ONAP development environment is not easy. Development tools and practices are not collected in a single place. This project pretends to collect and standardize that process.
The goal of data science teams are to build and deploy high impact models. Data scientists prefer to focus on building algorithms, while data engineers focus on performance and productionizing machine learning. Kubernetes is an orchestration platform that can be deployed anywhere and can serve any kind of machine and deep learning environment. Kubernetes is a great tool for data scientists to use to stay productive and for data engineers to get production-ready results. In this free workshop you’ll learn how to build your own Kubernetes to use in your next machine learning pipeline.
Watch all our webinars at https://cnvrg.io/webinars-and-workshops/
An application designer usually has to choose where to trade flexibility for specificity (and thus usually performance); knowing when and where to do so is an art and requires experience. This talk will share over a decades worth of experience making these decisions and the learnings from developing Pivotal's successful Real Time Intelligence (RTI) product using the latest versions of Spring projects: Integration, Data, Boot, MVC/REST and XD. A walk through the RTI architecture will provide the base for an explanation about how Spring performs at hundreds (and millions) of events/operations per second and the techniques that you can use right now in your own Spring applications to minimise resource utilisation and gain performance.
Learn how to deploy your model to production in 30 minutes and..
• Reduce costs and man power with auto scaling
• Load balanced the traffic
• Natively monitored by Kubernetes
• Update your model continuously: canary deployments, blue/green deployments
Mariusz Richtscheid: Architektura typu serverless wraz z terminem "Function as a Service" zyskują coraz większą popularność. To całkiem odmienne podejście do tworzenia aplikacji oraz ich wdrażania ma wiele zalet, ale musimy być też świadomi problemów, jakie się z nim wiążą. W trakcie prezentacji pokażę, w jaki sposób można zmodyfikować istniejącą aplikację Node.js tak, by wykorzystać zalety tej architektury.
Setting up an ONAP development environment is not easy. Development tools and practices are not collected in a single place. This project pretends to collect and standardize that process.
The goal of data science teams are to build and deploy high impact models. Data scientists prefer to focus on building algorithms, while data engineers focus on performance and productionizing machine learning. Kubernetes is an orchestration platform that can be deployed anywhere and can serve any kind of machine and deep learning environment. Kubernetes is a great tool for data scientists to use to stay productive and for data engineers to get production-ready results. In this free workshop you’ll learn how to build your own Kubernetes to use in your next machine learning pipeline.
Watch all our webinars at https://cnvrg.io/webinars-and-workshops/
ASP.NET Core Quick Start covering Configuration, Logging, and .NET Framework versus .NET Core. Source code for the demos are on GitHub: https://github.com/ErikNoren/AspNetCoreDemos
Threading Made Easy! A Busy Developer’s Guide to Kotlin CoroutinesLauren Yew
Kotlin Coroutines is a powerful threading library for Kotlin, released by JetBrains in 2018. At The New York Times, we recently migrated our core libraries and parts of our News app from RxJava to Kotlin Coroutines. In this talk we’ll share lessons learned and best practices to understand, migrate to, and use Kotlin Coroutines & Flows.
In this presentation, you will learn:
What Coroutines are and how they function
How to use Kotlin Coroutines & Flows (with real world examples and demos)
Where and why you should use Coroutines & Flows in your app
How to avoid the pitfalls of Coroutines
Kotlin Coroutines vs. RxJava
Lessons learned from migrating to Kotlin Coroutines from RxJava in large legacy projects & libraries
By the end of this talk, you will be able to apply Kotlin Coroutines to your own app, run the provided sample code yourself, and convince your team to give Kotlin Coroutines a try!
Watch this talk here: http://videos.confluent.io/watch/Rgd5r8oV1ToDpcFfenMQrF
This session covers the patterns and techniques of using KSQL. Tim Berglund discusses the various building blocks that you can use in your own applications, starting with the language syntax itself and covering how and when to use its powerful capabilities like a pro. This is part 1 out of 3 in the Empowering Streams through KSQL series.
In this session, Nick Dearden covers the planning and operation of your KSQL deployment, including under-the-hood architectural details. You will learn about the various deployment models, how to track and monitor your KSQL applications, how to scale in and out and how to think about capacity planning. This is part 3 out of 3 in the Empowering Streams through KSQL series.
When running any amount of systems, gaining visibility into what they are doing can be a non-trivial matter. Starting on the path to monitoring can prove bumpy, and if you don’t measure, you don’t know. In this session, Michael Fiedler, Director of TechOps, will speak on personal experience with scalability, deployment, and monitoring challenges prior to using Datadog - and how that changed. He will cover how to get started, and examples of where monitoring the company's platform with Datadog provided the guiding light towards the team solving scalability problems.
Part 3 of the REAL Webinars on Oracle Cloud Native Application Development (J...Lucas Jellema
Continuing the discussion on Functions and API Gateway, combining several functions, API Gateway and Object Storage. Then introducing Streaming for Apache Kafka like messaging. Finally, Oracle NoSQL Database Cloud Service for relational as well as schemaless JSON persistence.
During this talk, speaker provided a detailed overview of the Elasticsearch search system, gave an insight into offline search tools, and suggested how to fine-tune Elasticsearch depending on specific goals.
This presentation by Mykhailo Brodskyi (Senior Software Engineer, Сonsultant, GlobalLogic, Kharkiv), was delivered at GlobalLogic Kharkiv Java Conference 2018 on June 10, 2018.
Continuous Intelligence - Streaming Apps That Are Always In Sync | Simon Cros...HostedbyConfluent
FREE NOW business is growing rapidly as a ride-hailing industry in general which creates a fair amount of technical challenges related to real-time data aggregation and processing. FREE NOW was a long-time user of Kafka and lately adopted Confluent Cloud as a mainstreaming data platform. We managed to scale it towards several hundreds of topics containing various information about the trip, location and business performance overall. This information is heavily utilized to create streaming applications like dynamic pricing computation, fraud detection as well as real-time analytics for marketing campaigns, and much more. We would like to share the details of the implementation for the real-time computation of the dynamic tour pricing which is based on more than 200 million events daily. Also, we would like to reflect on how Confluent helped us to address the development complexity and provide scalability options at the same time.
Когда заходит речь о хранении данных .NET приложения, обычно вопросов не возникает. Конечно же это будет реляционная база. А в большинстве случаев — и вовсе MS SQL Server. Но что, если если мы скажем вам, что классический подход далеко не идеальный? Он требует дополнительных усилий, и практически всегда приводит к постоянной потере важных данных.
На этом докладе мы разберем основные проблемы и недостатки реляционной модели и рассмотрим как можно их избежать современным .NET разработчикам.
Akka A to Z: A Guide To The Industry’s Best Toolkit for Fast Data and Microse...Lightbend
Microservices. Streaming data. Event Sourcing and CQRS. Concurrency, routing, self-healing, persistence, clustering… You get the picture. The Akka toolkit makes all of this simple for Java and Scala developers at Amazon, LinkedIn, Starbucks, Verizon and others. So how does Akka provide all these features out of the box?
Join Hugh McKee, Akka expert and Developer Advocate at Lightbend, on an illustrated journey that goes deep into how Akka works–from individual Akka actors to fully distributed clusters across multiple datacenters.
Презентация директора по работе с партнерами Parallels в России, СНГ и странах Балтии Константина Анисимова. Доклад был представлен на выставке RIW2011 20 октября 2011, на секции "Хостинг".
ASP.NET Core Quick Start covering Configuration, Logging, and .NET Framework versus .NET Core. Source code for the demos are on GitHub: https://github.com/ErikNoren/AspNetCoreDemos
Threading Made Easy! A Busy Developer’s Guide to Kotlin CoroutinesLauren Yew
Kotlin Coroutines is a powerful threading library for Kotlin, released by JetBrains in 2018. At The New York Times, we recently migrated our core libraries and parts of our News app from RxJava to Kotlin Coroutines. In this talk we’ll share lessons learned and best practices to understand, migrate to, and use Kotlin Coroutines & Flows.
In this presentation, you will learn:
What Coroutines are and how they function
How to use Kotlin Coroutines & Flows (with real world examples and demos)
Where and why you should use Coroutines & Flows in your app
How to avoid the pitfalls of Coroutines
Kotlin Coroutines vs. RxJava
Lessons learned from migrating to Kotlin Coroutines from RxJava in large legacy projects & libraries
By the end of this talk, you will be able to apply Kotlin Coroutines to your own app, run the provided sample code yourself, and convince your team to give Kotlin Coroutines a try!
Watch this talk here: http://videos.confluent.io/watch/Rgd5r8oV1ToDpcFfenMQrF
This session covers the patterns and techniques of using KSQL. Tim Berglund discusses the various building blocks that you can use in your own applications, starting with the language syntax itself and covering how and when to use its powerful capabilities like a pro. This is part 1 out of 3 in the Empowering Streams through KSQL series.
In this session, Nick Dearden covers the planning and operation of your KSQL deployment, including under-the-hood architectural details. You will learn about the various deployment models, how to track and monitor your KSQL applications, how to scale in and out and how to think about capacity planning. This is part 3 out of 3 in the Empowering Streams through KSQL series.
When running any amount of systems, gaining visibility into what they are doing can be a non-trivial matter. Starting on the path to monitoring can prove bumpy, and if you don’t measure, you don’t know. In this session, Michael Fiedler, Director of TechOps, will speak on personal experience with scalability, deployment, and monitoring challenges prior to using Datadog - and how that changed. He will cover how to get started, and examples of where monitoring the company's platform with Datadog provided the guiding light towards the team solving scalability problems.
Part 3 of the REAL Webinars on Oracle Cloud Native Application Development (J...Lucas Jellema
Continuing the discussion on Functions and API Gateway, combining several functions, API Gateway and Object Storage. Then introducing Streaming for Apache Kafka like messaging. Finally, Oracle NoSQL Database Cloud Service for relational as well as schemaless JSON persistence.
During this talk, speaker provided a detailed overview of the Elasticsearch search system, gave an insight into offline search tools, and suggested how to fine-tune Elasticsearch depending on specific goals.
This presentation by Mykhailo Brodskyi (Senior Software Engineer, Сonsultant, GlobalLogic, Kharkiv), was delivered at GlobalLogic Kharkiv Java Conference 2018 on June 10, 2018.
Continuous Intelligence - Streaming Apps That Are Always In Sync | Simon Cros...HostedbyConfluent
FREE NOW business is growing rapidly as a ride-hailing industry in general which creates a fair amount of technical challenges related to real-time data aggregation and processing. FREE NOW was a long-time user of Kafka and lately adopted Confluent Cloud as a mainstreaming data platform. We managed to scale it towards several hundreds of topics containing various information about the trip, location and business performance overall. This information is heavily utilized to create streaming applications like dynamic pricing computation, fraud detection as well as real-time analytics for marketing campaigns, and much more. We would like to share the details of the implementation for the real-time computation of the dynamic tour pricing which is based on more than 200 million events daily. Also, we would like to reflect on how Confluent helped us to address the development complexity and provide scalability options at the same time.
Когда заходит речь о хранении данных .NET приложения, обычно вопросов не возникает. Конечно же это будет реляционная база. А в большинстве случаев — и вовсе MS SQL Server. Но что, если если мы скажем вам, что классический подход далеко не идеальный? Он требует дополнительных усилий, и практически всегда приводит к постоянной потере важных данных.
На этом докладе мы разберем основные проблемы и недостатки реляционной модели и рассмотрим как можно их избежать современным .NET разработчикам.
Akka A to Z: A Guide To The Industry’s Best Toolkit for Fast Data and Microse...Lightbend
Microservices. Streaming data. Event Sourcing and CQRS. Concurrency, routing, self-healing, persistence, clustering… You get the picture. The Akka toolkit makes all of this simple for Java and Scala developers at Amazon, LinkedIn, Starbucks, Verizon and others. So how does Akka provide all these features out of the box?
Join Hugh McKee, Akka expert and Developer Advocate at Lightbend, on an illustrated journey that goes deep into how Akka works–from individual Akka actors to fully distributed clusters across multiple datacenters.
Презентация директора по работе с партнерами Parallels в России, СНГ и странах Балтии Константина Анисимова. Доклад был представлен на выставке RIW2011 20 октября 2011, на секции "Хостинг".
Laying the Foundation for Ionic Platform Insights on SparkIonic Security
The Ionic Analytics team shares insights about the system they built using Spark and Databricks to enable low cost, flexible reporting and lay a foundation for advanced analytics.
These slides were originally presented at the Databricks Data+ML Workshop entitled "Unify Data Pipelines with Machine Learning" on Tuesday September 11 2018 in Atlanta, GA.
Monitoring microservices: Docker, Mesos and Kubernetes visibility at scaleAlessandro Gallotta
Microservices and containers are revolutionizing the way we deploy applications and maintain infrastructure. But as many have found containers still have a key problem: monitoring and troubleshooting them can be impractical, painful, and sometimes impossible. With the rise of microservice based architectures and orchestration tools such as Kubernetes and Mesos, managing this has become even harder.
Using real tools, in live environments, Alessandro Gallotta will walk through various hands-on scenarios including how to:
-visualize physical vs logical architectures of Kubernetes/Mesos deployments
-understand performance at the microservice/app level for orchestrated systems
-identify & surface system activity of individual Docker containers
-extract process & app-level metrics inside containers with non-intrusive methods
-troubleshoot detailed network activity in distributed containers
DevOpsDays Houston 2019 - Shaun Ladewig, Robert Stone - From OverTheWallOps t...DevOpsDays Houston
Is your organization suffering from “Over the Wall Ops?” The road to production is fraught with danger and risks, learn how Endurance is tackling the problem, lowering risk, and speeding up launches by having Development and Operations work hand in hand leveraging OpenShift! Join us for a real-world case study from both sides, Shaun Ladewig (System Architect) presents lessons learned in understanding, deploying, and managing an OpenShift cluster while Robert Stone (Principal Software Engineer) outlines how that cluster is used to stand up, deploy, and re-tool our monoliths to fit a more container-based architecture.
Operating a High Velocity Large Organization with Spring Cloud MicroservicesNoriaki Tatsumi
Noriaki Tatsumi prepares you to build a microservices architecture that's not only reliable, resilient, and scalable but also addresses the challenges large organizations typically face. He dives into the technical details on how Spring Cloud empowers developers to build the patterns and components of microservices foundation quickly.
Based on experience with hundreds of customers, here's a set of best practices for monitoring Kubernetes and monitoring your applications running inside docker containers.
Docker in Production: How RightScale Delivers Cloud ApplicationsRightScale
Combining Docker, cloud infrastructure, and continuous integration and delivery practices can create a highly automated and efficient way to get new applications and features to market. The RightScale development team has been using Docker from development to continuous integration, and now the operations team has taken Docker into the production environment.
The Docker in Production: How RightScale Delivers Cloud Applications webinar will cover:
Approach and use case for adopting Docker
How RightScale has adopted Docker for development, CI, and production
Overcoming technical and process challenges
The RightScale process before and after Docker
Benefits for both developers and operations teams
Introduction to Module Development with Appcelerator TitaniumAaron Saunders
VIDEO: http://bit.ly/P1UlGr starts at 1:13
Overview of creating modules with Appcelerator Titanium. We integrate SkyhookWireless location SDK and Card.io mobile card sdk
Source:
Source code for ios cardio module presented at @codestrong http://bit.ly/PQlsW9
Source code for android skyhookwireless module presented at @codestrong http://bit.ly/z4zfdl
This guide will help you get started with Innoslate, the full lifecycle systems engineering tool. It will take you through developing your requirements, creating model, simulating your models, and keeping traceability through the entire project.
Microservices: How loose is loosely coupled?John Rofrano
Microservice architecture is a popular design pattern for DevOps deployments of cloud native applications. It's single purpose, loosely coupled, bounded context design lends itself to the independent life cycle required to quickly deploy and scale in the cloud. Docker containerization of these services further aids in the zero down-time deployments of these horizontally scalable services. But how do you keep them loosely coupled? How do they communicate without knowing about each other? and how do you keep all of those containers patched from new vulnerabilities that are being discovered every day?
This talk discusses the implementation of a Container Vulnerability Remediation Services that itself is designed as a collection of loosely coupled microservices that communicate via publish/subscribe messaging model using Kafka, Cloud Functions (OpenWhisk), and REST APIs implemented in Python Flask. This design keeps each microservice independent and replaceable, while enabling expandability for new services to participate in business functions without any pre-determined knowledge of the business workflow.
A list of action items you want to keep in mind when you're devsecops'ing for your cloudnative environments. Given as a part of a talk on the Modern Security series (
https://info.signalsciences.com/securing-cloud-native-ten-tips-better-container-security).
Introduction to angular with a simple but complete projectJadson Santos
A simple front end project with angular. Its show how to create your first components, include bootstrap templates, create routes and build the project to production.
24. NSFileCoordinator
• Initialized for each file operation
• Coordinates file reading and writing
• Not async
• Contains list of coordination methods
24
28. File Wrappers + File Presenter
<host id>.paxhost
hostInfo.plist
img.png
• File Presenter can present directory
• The same callbacks:
presentedItem -> presentedSubitem
• All callbacks in one place
• Diminishes the need to merge changes
28
29. Things to consider
• Requires minimum 3 queues
• System holds strong references to file presenters
• Memory limit for extension is ~10 MB
29
30. watchOS 2
Watch Connectivity
Parent Application
extension
• WCSession with the Delegate
• File Transfer
• Application context
• Interactive Messaging
• User info
30
31. Other uses of approach
• The same mechanism with WCSession’s file transfer
• Sync state between
• iOS devices and Macs via iCloud
• iOS application and extension
• 2 iOS applications
• 2 different Mac applications
31
32. State transfer from iPhone to Apple Watch
Artemiy Sobolev
asobolev@parallels.com
Software Developer, Parallels Inc. c
32
