Learning Objectives:
- Choosing the right Elastic Load Balancer for your architecture
- How to use Network Load Balancer with Amazon ECS
- How to configure your tasks and services to take advantage of the Network Load Balancer
Docker Networking - Common Issues and Troubleshooting TechniquesSreenivas Makam
This document discusses Docker networking components and common issues. It covers Docker networking drivers like bridge, host, overlay, topics around Docker daemon access and configuration behind firewalls. It also discusses container networking best practices like using user-defined networks instead of links, connecting containers to multiple networks, and connecting managed services to unmanaged containers. The document is intended to help troubleshoot Docker networking issues.
1. Docker EE will include an unmodified Kubernetes distribution to provide orchestration capabilities alongside Docker Swarm.
2. When running mixed workloads across orchestrators, resource contention is a risk and it is recommended to separate workloads by orchestrator on each node for now.
3. Docker EE aims to address the shortcomings of running mixed workloads to better support this in the future.
Kubernetes advanced sheduling
- Taint and tolerant
- Affinity (Node & inter pod)
Learn how to place Pod like (same or different) node, rack, zone, region
Docker Swarm allows managing multiple Docker hosts as a single virtual Docker engine. The presenter demonstrates setting up a traditional Docker Swarm cluster with an external key-value store and load balancer. SwarmKit provides the core components of Docker Swarm as standalone binaries. Docker Swarm Mode is integrated directly into Docker Engine 1.12 and later, providing built-in orchestration without external components. The presenter then demonstrates a tutorial using Docker Swarm Mode to deploy a multi-container voting application across 3 Docker hosts and scale the service.
The document discusses different Docker networking drivers including null, host, bridge, overlay, and macvlan/ipvlan networks. It provides examples of creating networks with each driver and how containers on different networks will connect and obtain IPs. Specifically, it shows how the bridge driver sets up a private Docker bridge network (docker0 by default) and how overlay networks use VXLAN tunnels to connect containers across multiple Docker daemons.
This document provides an overview of Kubernetes including:
1) Kubernetes is an open-source platform for automating deployment, scaling, and operations of containerized applications. It provides container-centric infrastructure and allows for quickly deploying and scaling applications.
2) The main components of Kubernetes include Pods (groups of containers), Services (abstract access to pods), ReplicationControllers (maintain pod replicas), and a master node running key components like etcd, API server, scheduler, and controller manager.
3) The document demonstrates getting started with Kubernetes by enabling the master on one node and a worker on another node, then deploying and exposing a sample nginx application across the cluster.
Optimizing Kubernetes Resource Requests/Limits for Cost-Efficiency and Latenc...Henning Jacobs
Kubernetes has the concept of resource requests and limits. Pods get scheduled on the nodes based on their requests and optionally limited in how much of the resource they can consume. Understanding and optimizing resource requests/limits is crucial both for reducing resource "slack" and ensuring application performance/low-latency. This talk shows our approach to monitoring and optimizing Kubernetes resources for 80+ clusters to achieve cost-efficiency and reducing impact for latency-critical applications. All shown tools are Open Source and can be applied to most Kubernetes deployments.
This document provides an overview of Kubernetes, an open-source system for automating deployment, scaling, and management of containerized applications. It describes basic Kubernetes components like pods, replication controllers, services, deployments, and replica sets. It explains how Kubernetes is used to group and schedule containers, maintain desired pod counts, update applications seamlessly with rolling updates, and more. The document also notes Kubernetes was inspired by Google's internal container systems and can manage applications across cloud and bare-metal environments.
Docker Networking - Common Issues and Troubleshooting TechniquesSreenivas Makam
This document discusses Docker networking components and common issues. It covers Docker networking drivers like bridge, host, overlay, topics around Docker daemon access and configuration behind firewalls. It also discusses container networking best practices like using user-defined networks instead of links, connecting containers to multiple networks, and connecting managed services to unmanaged containers. The document is intended to help troubleshoot Docker networking issues.
1. Docker EE will include an unmodified Kubernetes distribution to provide orchestration capabilities alongside Docker Swarm.
2. When running mixed workloads across orchestrators, resource contention is a risk and it is recommended to separate workloads by orchestrator on each node for now.
3. Docker EE aims to address the shortcomings of running mixed workloads to better support this in the future.
Kubernetes advanced sheduling
- Taint and tolerant
- Affinity (Node & inter pod)
Learn how to place Pod like (same or different) node, rack, zone, region
Docker Swarm allows managing multiple Docker hosts as a single virtual Docker engine. The presenter demonstrates setting up a traditional Docker Swarm cluster with an external key-value store and load balancer. SwarmKit provides the core components of Docker Swarm as standalone binaries. Docker Swarm Mode is integrated directly into Docker Engine 1.12 and later, providing built-in orchestration without external components. The presenter then demonstrates a tutorial using Docker Swarm Mode to deploy a multi-container voting application across 3 Docker hosts and scale the service.
The document discusses different Docker networking drivers including null, host, bridge, overlay, and macvlan/ipvlan networks. It provides examples of creating networks with each driver and how containers on different networks will connect and obtain IPs. Specifically, it shows how the bridge driver sets up a private Docker bridge network (docker0 by default) and how overlay networks use VXLAN tunnels to connect containers across multiple Docker daemons.
This document provides an overview of Kubernetes including:
1) Kubernetes is an open-source platform for automating deployment, scaling, and operations of containerized applications. It provides container-centric infrastructure and allows for quickly deploying and scaling applications.
2) The main components of Kubernetes include Pods (groups of containers), Services (abstract access to pods), ReplicationControllers (maintain pod replicas), and a master node running key components like etcd, API server, scheduler, and controller manager.
3) The document demonstrates getting started with Kubernetes by enabling the master on one node and a worker on another node, then deploying and exposing a sample nginx application across the cluster.
Optimizing Kubernetes Resource Requests/Limits for Cost-Efficiency and Latenc...Henning Jacobs
Kubernetes has the concept of resource requests and limits. Pods get scheduled on the nodes based on their requests and optionally limited in how much of the resource they can consume. Understanding and optimizing resource requests/limits is crucial both for reducing resource "slack" and ensuring application performance/low-latency. This talk shows our approach to monitoring and optimizing Kubernetes resources for 80+ clusters to achieve cost-efficiency and reducing impact for latency-critical applications. All shown tools are Open Source and can be applied to most Kubernetes deployments.
This document provides an overview of Kubernetes, an open-source system for automating deployment, scaling, and management of containerized applications. It describes basic Kubernetes components like pods, replication controllers, services, deployments, and replica sets. It explains how Kubernetes is used to group and schedule containers, maintain desired pod counts, update applications seamlessly with rolling updates, and more. The document also notes Kubernetes was inspired by Google's internal container systems and can manage applications across cloud and bare-metal environments.
HAProxy TCP 모드에서 클라이언트의 Source IP를 내부 서버로 전달하는 방법을 알아봅니다.
* 중간에 오타가 있어서 수정본을 다시 업로드 하고자 했으나... SlideShare 측의 답변으로는 "Re-Upload 기능을 제거했다."라고 합니다. 부디 오타 등 부자연스러운 부분에 대해 너그럽게 이해를 부탁 드립니다.
Ceph is an open-source distributed storage platform that provides file, block, and object storage in a single unified system. It uses a distributed storage component called RADOS that provides reliable and scalable storage through data replication and erasure coding across commodity hardware. Higher-level services like RBD provide virtual block devices, RGW provides S3-compatible object storage, and CephFS provides a distributed file system.
This document provides instructions on installing and using Docker on Linux (Ubuntu) and Windows. It discusses installing Docker on Ubuntu, basic Docker commands like images, ps, pull, run options for ports, volumes, and other commands. For Windows, it recommends using Docker Toolbox which includes Docker Machine, Engine, Compose and Kitematic GUI. It also covers installing the newer Docker for Windows which requires Windows 10 Pro/Enterprise with Hyper-V enabled.
In this session, you'll learn how RBD works, including how it:
Uses RADOS classes to make access easier from user space and within the Linux kernel.
Implements thin provisioning.
Builds on RADOS self-managed snapshots for cloning and differential backups.
Increases performance with caching of various kinds.
Uses watch/notify RADOS primitives to handle online management operations.
Integrates with QEMU, libvirt, and OpenStack.
OpenStack 운영을 통해 얻은 교훈을 공유합니다.
목차
1. TOAST 클라우드 지금의 모습
2. OpenStack 선택의 이유
3. 구성의 어려움과 극복 사례
4. 활용 사례
5. 풀어야 할 문제들
대상
- TOAST 클라우드를 사용하고 싶은 분
- WMI를 처음 들어보시는 분
This document discusses Microservices and Docker Swarm. It begins by introducing the presenter and their background. It then defines what a microservice is and introduces Docker. Key concepts about Docker Swarm are explained such as swarm features, service discovery without an external database, and the swarm concept of managers, workers, services and tasks. It demonstrates how to build a swarm cluster and add nodes, and discusses security, routing mesh, scaling, reverse proxy, rolling updates and secrets. Finally it briefly mentions logging, metrics and dashboard tools to monitor Docker systems.
The document describes various API endpoints for managing organizations, projects, tasks, files, and other resources. It includes endpoints for creating, retrieving, updating, and deleting resources as well as examples of request and response payloads.
Docker allows building, shipping, and running applications in portable containers. It packages an application with all its dependencies into a standardized unit for software development. Major cloud providers and companies support and use Docker in production. Containers are more lightweight and efficient than virtual machines, providing faster launch times and allowing thousands to run simultaneously on the same server. Docker simplifies distributing applications and ensures a consistent environment.
The monolith to cloud-native, microservices evolution has driven a shift from monitoring to observability. OpenTelemetry, a merger of the OpenTracing and OpenCensus projects, is enabling Observability 2.0. This talk gives an overview of the OpenTelemetry project and then outlines some production-proven architectures for improving the observability of your applications and systems.
Docker allows users to package applications with all their dependencies into standardized units called containers that can run on any Linux server. Containers are more lightweight than virtual machines because they share the host operating system and only require the additional libraries and binaries needed to run the application rather than a full guest operating system. Docker uses containers and an image format to deploy applications in a consistent manner across development, testing, and production. The document provides examples of how to define a Dockerfile to build an image, run containers from images using docker-compose, and common Docker commands.
PerconaLive 2016 Santa Clara presentation on Hashicorp Vault with CTO Armon Dadger
https://www.percona.com/live/data-performance-conference-2016/sessions/using-vault-decouple-secrets-applications
Lambda is AWS's serverless compute service that allows you to run code without managing servers. With Lambda, you upload your code and AWS handles provisioning servers, scaling capacity automatically, and maintaining the servers. You are charged by the number of requests and amount of compute time used. Lambda functions can be triggered by various AWS services and events. It provides scaling and high availability without needing to manage servers or capacity planning.
Kafka Tutorial - Introduction to Apache Kafka (Part 1)Jean-Paul Azar
Why is Kafka so fast? Why is Kafka so popular? Why Kafka? This slide deck is a tutorial for the Kafka streaming platform. This slide deck covers Kafka Architecture with some small examples from the command line. Then we expand on this with a multi-server example to demonstrate failover of brokers as well as consumers. Then it goes through some simple Java client examples for a Kafka Producer and a Kafka Consumer. We have also expanded on the Kafka design section and added references. The tutorial covers Avro and the Schema Registry as well as advance Kafka Producers.
Everything You wanted to Know About Distributed TracingAmuhinda Hungai
In the age of microservices, understanding how applications are executing in a highly distributed environment can be complicated. Looking at log files only gives a snapshot of the whole story and looking at a single service in isolation simply does not give enough information. Each service is just one side of a bigger story. Distributed tracing has emerged as an invaluable technique that succeeds in summarizing all sides of the story into a shared timeline. Yet deploying it can be quite challenging, especially in the large scale, polyglot environments of modern companies that mix together many different technologies. During this session, we will take a look at patterns and means to implement Tracing for services. After introducing the basic concepts we will cover how the tracing model works, and how to safely use it in production to troubleshoot and diagnose issues.
Introducing KRaft: Kafka Without Zookeeper With Colin McCabe | Current 2022HostedbyConfluent
Introducing KRaft: Kafka Without Zookeeper With Colin McCabe | Current 2022
Apache Kafka without Zookeeper is now production ready! This talk is about how you can run without ZooKeeper, and why you should.
Kubernetes: A Short Introduction (2019)Megan O'Keefe
Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery called pods. Kubernetes can manage pods across a cluster of machines, providing scheduling, deployment, scaling, load balancing, volume mounting and networking. It is widely used by companies like Google, CERN and in large projects like processing images and analyzing particle interactions. Kubernetes is portable, can span multiple cloud providers, and continues growing to support new workloads and use cases.
Docker is an open platform for developing, shipping, and running distributed applications. It allows applications to be shipped and run in lightweight containers that can run on any Linux server. Docker uses operating-system-level virtualization and cgroups isolation to deliver lightweight containers quickly. Key features of Docker include portability, lightweight containers that share resources and isolate processes, and automated workflows.
During the Neos Conference 2024 I talked – again – about updating Neos. Next to why, when and how you should be updating I talked about going to Neos 9…
HAProxy TCP 모드에서 클라이언트의 Source IP를 내부 서버로 전달하는 방법을 알아봅니다.
* 중간에 오타가 있어서 수정본을 다시 업로드 하고자 했으나... SlideShare 측의 답변으로는 "Re-Upload 기능을 제거했다."라고 합니다. 부디 오타 등 부자연스러운 부분에 대해 너그럽게 이해를 부탁 드립니다.
Ceph is an open-source distributed storage platform that provides file, block, and object storage in a single unified system. It uses a distributed storage component called RADOS that provides reliable and scalable storage through data replication and erasure coding across commodity hardware. Higher-level services like RBD provide virtual block devices, RGW provides S3-compatible object storage, and CephFS provides a distributed file system.
This document provides instructions on installing and using Docker on Linux (Ubuntu) and Windows. It discusses installing Docker on Ubuntu, basic Docker commands like images, ps, pull, run options for ports, volumes, and other commands. For Windows, it recommends using Docker Toolbox which includes Docker Machine, Engine, Compose and Kitematic GUI. It also covers installing the newer Docker for Windows which requires Windows 10 Pro/Enterprise with Hyper-V enabled.
In this session, you'll learn how RBD works, including how it:
Uses RADOS classes to make access easier from user space and within the Linux kernel.
Implements thin provisioning.
Builds on RADOS self-managed snapshots for cloning and differential backups.
Increases performance with caching of various kinds.
Uses watch/notify RADOS primitives to handle online management operations.
Integrates with QEMU, libvirt, and OpenStack.
OpenStack 운영을 통해 얻은 교훈을 공유합니다.
목차
1. TOAST 클라우드 지금의 모습
2. OpenStack 선택의 이유
3. 구성의 어려움과 극복 사례
4. 활용 사례
5. 풀어야 할 문제들
대상
- TOAST 클라우드를 사용하고 싶은 분
- WMI를 처음 들어보시는 분
This document discusses Microservices and Docker Swarm. It begins by introducing the presenter and their background. It then defines what a microservice is and introduces Docker. Key concepts about Docker Swarm are explained such as swarm features, service discovery without an external database, and the swarm concept of managers, workers, services and tasks. It demonstrates how to build a swarm cluster and add nodes, and discusses security, routing mesh, scaling, reverse proxy, rolling updates and secrets. Finally it briefly mentions logging, metrics and dashboard tools to monitor Docker systems.
The document describes various API endpoints for managing organizations, projects, tasks, files, and other resources. It includes endpoints for creating, retrieving, updating, and deleting resources as well as examples of request and response payloads.
Docker allows building, shipping, and running applications in portable containers. It packages an application with all its dependencies into a standardized unit for software development. Major cloud providers and companies support and use Docker in production. Containers are more lightweight and efficient than virtual machines, providing faster launch times and allowing thousands to run simultaneously on the same server. Docker simplifies distributing applications and ensures a consistent environment.
The monolith to cloud-native, microservices evolution has driven a shift from monitoring to observability. OpenTelemetry, a merger of the OpenTracing and OpenCensus projects, is enabling Observability 2.0. This talk gives an overview of the OpenTelemetry project and then outlines some production-proven architectures for improving the observability of your applications and systems.
Docker allows users to package applications with all their dependencies into standardized units called containers that can run on any Linux server. Containers are more lightweight than virtual machines because they share the host operating system and only require the additional libraries and binaries needed to run the application rather than a full guest operating system. Docker uses containers and an image format to deploy applications in a consistent manner across development, testing, and production. The document provides examples of how to define a Dockerfile to build an image, run containers from images using docker-compose, and common Docker commands.
PerconaLive 2016 Santa Clara presentation on Hashicorp Vault with CTO Armon Dadger
https://www.percona.com/live/data-performance-conference-2016/sessions/using-vault-decouple-secrets-applications
Lambda is AWS's serverless compute service that allows you to run code without managing servers. With Lambda, you upload your code and AWS handles provisioning servers, scaling capacity automatically, and maintaining the servers. You are charged by the number of requests and amount of compute time used. Lambda functions can be triggered by various AWS services and events. It provides scaling and high availability without needing to manage servers or capacity planning.
Kafka Tutorial - Introduction to Apache Kafka (Part 1)Jean-Paul Azar
Why is Kafka so fast? Why is Kafka so popular? Why Kafka? This slide deck is a tutorial for the Kafka streaming platform. This slide deck covers Kafka Architecture with some small examples from the command line. Then we expand on this with a multi-server example to demonstrate failover of brokers as well as consumers. Then it goes through some simple Java client examples for a Kafka Producer and a Kafka Consumer. We have also expanded on the Kafka design section and added references. The tutorial covers Avro and the Schema Registry as well as advance Kafka Producers.
Everything You wanted to Know About Distributed TracingAmuhinda Hungai
In the age of microservices, understanding how applications are executing in a highly distributed environment can be complicated. Looking at log files only gives a snapshot of the whole story and looking at a single service in isolation simply does not give enough information. Each service is just one side of a bigger story. Distributed tracing has emerged as an invaluable technique that succeeds in summarizing all sides of the story into a shared timeline. Yet deploying it can be quite challenging, especially in the large scale, polyglot environments of modern companies that mix together many different technologies. During this session, we will take a look at patterns and means to implement Tracing for services. After introducing the basic concepts we will cover how the tracing model works, and how to safely use it in production to troubleshoot and diagnose issues.
Introducing KRaft: Kafka Without Zookeeper With Colin McCabe | Current 2022HostedbyConfluent
Introducing KRaft: Kafka Without Zookeeper With Colin McCabe | Current 2022
Apache Kafka without Zookeeper is now production ready! This talk is about how you can run without ZooKeeper, and why you should.
Kubernetes: A Short Introduction (2019)Megan O'Keefe
Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery called pods. Kubernetes can manage pods across a cluster of machines, providing scheduling, deployment, scaling, load balancing, volume mounting and networking. It is widely used by companies like Google, CERN and in large projects like processing images and analyzing particle interactions. Kubernetes is portable, can span multiple cloud providers, and continues growing to support new workloads and use cases.
Docker is an open platform for developing, shipping, and running distributed applications. It allows applications to be shipped and run in lightweight containers that can run on any Linux server. Docker uses operating-system-level virtualization and cgroups isolation to deliver lightweight containers quickly. Key features of Docker include portability, lightweight containers that share resources and isolate processes, and automated workflows.
During the Neos Conference 2024 I talked – again – about updating Neos. Next to why, when and how you should be updating I talked about going to Neos 9…
With more than 140 million users, KakaoTalk is the most popular mobile messaging platform in South Korea. The team at daumkakao has been using OpenStack with the intention for tranforming the current legacy infrastructure into scale out based cloud to build and offer new services for its users. In this session, we'd like to share our experiences with the OpenStack community, specifically in regards to meeting our needs for networking with Neutron.OpenStack Neutron offers a lot of methods to implement networking for VMs and containers. For production operations, VM migration can be a common activity to manage resources and improve uptime. It's not hard using shared storage like Ceph, but network settings, such as IP addresses need to be preserved. With a shared storage environment, an image can be attached anywhere inside of a data center, but a service IP for a virtual machine is different story. And when you don't use the floating IPs, keeping the same IP across a data center-wide set of VLANs is hard job.To maintain a virtual machine's IP settings and balance IPs between VLANS, we tried several options including overlay, SDN, and NFV technologies. In the end we came to use a route-only network for our virtual machine networks, leveraging technology like Quagga for RIP, OSPF BGP integrated with Neutron.
This document provides instructions for transferring data from an older version of the uniCenta oPOS database to the current version 4.5 database format. The transfer process involves 3 main steps:
1. Creating a new database schema and configuring the new uniCenta oPOS version to use it.
2. Connecting the transfer tool to the source database, selecting the database to transfer from.
3. Starting the transfer process, which outputs progress information and status updates. The transferred data is then available in the new database schema.
The document discusses container scheduling and placement in Amazon ECS. It explains that container scheduling determines where containers run on instances in a cluster. As the number of containers grows, scheduling them effectively becomes more difficult. The ECS scheduling engine and placement engine work together to place containers based on constraints and strategies while ensuring resources are available. It provides examples of placement strategies like binpacking and spread to distribute containers across instances and availability zones.
The technical level of this document is 300.
This article requires knowledge about Microsoft Performance Monitor, Lync Monitoring, Hardware SPEC’s and Consulting.
Building the Test User Scenario, requires full understand of each Lync feature and how user will utilize those feature. Please also carefully understand the Lync PSTN Gateway Simulator. The Simulator must be provide with correct Dial-Plans, Voice Policy and Voice Routes.
You also need to understand the Lync User Provisioning Tool and how to design the Stress Test Scenarios.
Note:
This document is neither a sizing nor a configuration guide. You should use this document only for your environment planning’s purposes and security considerations. In lager environments you should spend some time to evaluate the optimal path of your Lync deployment.
Table of Content:
Introduction 4
The Calculation Process (I can recommend to you): 6
Build the Stress Test Lab 7
The Stress Test Process: 9
The Validation Process: 11
User Provisioning Tool 12
Setup User Provisioning Tool 13
User Creation 13
Contacts Creation 14
Distribution List Creation 15
Location Info Service Config 16
Run Configuration Scripts 18
Stress Test Simulations 20
User Profile Generator 20
Common Configuration 21
General Scenario 23
Voice Scenario 34
Reach Scenario 49
Mobility Scenario 52
Summary (Important User Load definition) 54
Table of Figures 58
Author: Thomas Poett MVP, Managing Consultant Microsoft Unified Communication
Monitoring Large-scale Cloud Infrastructures with OpenNebulaNETWAYS
Efficient monitoring is crucial when managing your Cloud infrastructure. The metrics collected by OpenNebula can be used to trigger automatic scaling, or quickly detect failures to automatically restart virtual machines. During this talk, I will show how OpenNebula can be used to efficiently monitor thousands of virtual machines at sub-1 minute interval. I will show how OpenNebula can be enhanced and optimized, and how different metrics collection tools such as Ganglia and Host-sFlow can be used with OpenNebula to monitor large-scale Cloud infrastructures.
OpenNebulaConf 2013 - Monitoring Large-scale Cloud Infrastructures with OpenN...OpenNebula Project
Efficient monitoring is crucial when managing your Cloud infrastructure. The metrics collected by OpenNebula can be used to trigger automatic scaling, or quickly detect failures to automatically restart virtual machines. During this talk, I will show how OpenNebula can be used to efficiently monitor thousands of virtual machines at sub-1 minute interval. I will show how OpenNebula can be enhanced and optimized, and how different metrics collection tools such as Ganglia and Host-sFlow can be used with OpenNebula to monitor large-scale Cloud infrastructures.
Bio:
Simon Boulet is an Entrepreneur and an IT Consultant from Montreal, Canada. He has worked on various Cloud infrastructure projects, including projects for the CBC/Radio-Canada public television that had important scaling needs for hosting online interactive TV shows. Prior to becoming an IT Consultant, Simon was IT Director at iWeb, Canada’s largest Web Hosting company, where he led iWeb’s first steps into Cloud Computing with the development of the Smart Servers. Simon is also an active and frequent contributor to OpenNebula, with a deep understanding of OpenNebula internals, and has contributed several enhancements and bug fixes that made it through the official releases of OpenNebula.
Scaling Django Apps using AWS Elastic BeanstalkLushen Wu
• What is AWS Elastic Beanstalk (EB)?
• What are the advantages of using EB over managing EC2 instances / Load-balancing / Auto-scaling myself?
• What are some common issues I might run into when deploying my Django app to EB?
This document outlines a project to create a single installer ISO that delivers a functional Xen hypervisor on CentOS without requiring a preexisting CentOS installation. The ISO would upgrade the kernel to match Xen repositories and configure networking and storage, allowing Xen to run out of the box. It would provide options for self-hosted or bridged networking and file-backed or LVM storage. The goal is to facilitate easy consumption of Xen and extensions like OpenStack or OpenNebula.
Mathew Beane discusses strategies for optimizing and scaling Magento applications on clustered infrastructure. Some key points include:
- Using Puppetmaster to build out clusters with standard webnodes and database configurations.
- Magento supports huge stores and is very flexible and scalable. Redis is preferred over Memcache for caching.
- Important to have application optimization, testing protocols and deployment pipelines in place before scaling.
- Common components for scaling include load balancers, proxying web traffic, clustering Redis with Sentinel and Twemproxy, adding read servers and auto-scaling.
Dark launching with Consul at Hootsuite - Bill MonkmanAmbassador Labs
Dark Launching (A.K.A. Feature Flagging) is a technique and mindset that has truly shaped the way we write, test, and deploy code at Hootsuite. It gives our team realtime, fine-grained control over our production systems which helps to prevent issues from reaching users, and build developer confidence in a culture of pushing code many times per day.
In this presentation I will go over how the system helps us both in the context of microservices and monoliths, and how we made use of Consul, Hashicorp's HA service discovery / KV store, to make it more resilient and performant at scale.
Using DC/OS for Continuous Delivery - DevPulseCon 2017pleia2
The document discusses new features in DC/OS 1.9 including improved operations through remote container shells, unified logging and metrics, deployment failure debugging, and upgrades/configuration updates. It also covers new workload features such as pods for co-locating containers and GPU-based scheduling. A variety of data services are now available in the DC/OS ecosystem.
Netty @Apple: Large Scale Deployment/ConnectivityC4Media
Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/1SIYyxQ.
Norman Maurer presents how Apple uses Netty for its Java based services and the challenges of doing so, including how they enhanced performance by participating in the Netty open source community. Maurer takes a deep dive into advanced topics like JNI, JVM internals, and others. Filmed at qconsf.com.
Norman Maurer is one of the core developers of Netty, a member of the Apache Software Foundation and a contributor to many Open Source Projects. He's a Senior Software Engineer for Apple, where he works on Netty and other projects.
The document discusses Docker usage in production at a large company with high traffic and fast growth. It outlines the tools used to deploy Docker containers at scale, including an internal deployment tool called Santa, Consul for configuration, Mesos for clustering, Marathon as the Mesos API, and custom AWS Docker images. It also describes internal tools developed for logging, metrics, and protection. The presentation will demonstrate the deployment flow from code to production using these tools and discuss best practices, failures encountered, and how they were addressed.
TechWiseTV Workshop: Open NX-OS and Devops with Puppet LabsRobb Boyd
Two incredible engineers: Shane Corban from Cisco and Carl Caum from Puppet Labs came together to be our guest experts for this workshop. See the demos in the replay at bit.ly/1lJQm3A
The document discusses applying OpenStack at iNET, an IT company in Vietnam. It introduces the author who is leading OpenStack deployment and operations. It then outlines iNET's architecture which uses Mitaka OpenStack with bonded network and Ceph storage. Their plans are to migrate more servers and all customer VPS to OpenStack. Key challenges discussed are selecting an OpenStack version, covering all components, and testing performance with limited lab devices.
JavaScript news in December 2017 edition:
+ Kill Internet Explorer
+ Google Chrome 63 Released
+ How to Cancel Your Promise
+ Parcel
+ Turbo
+ Average Page Load Times for 2018
+ Vulnerable JavaScript Libraries
+ New theming API in Firefox
+ Bower is dead
+ Extension Tree Style Tab: Reborn
+ React v16.2.0
+ WebStorm 2017.3.1
+ The Best JavaScript and CSS Libraries for 2017
Similar to Using the New Network Load Balancer with Amazon ECS - AWS Online Tech Talks (20)
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Amazon Web Services
Il Forecasting è un processo importante per tantissime aziende e viene utilizzato in vari ambiti per cercare di prevedere in modo accurato la crescita e distribuzione di un prodotto, l’utilizzo delle risorse necessarie nelle linee produttive, presentazioni finanziarie e tanto altro. Amazon utilizza delle tecniche avanzate di forecasting, in parte questi servizi sono stati messi a disposizione di tutti i clienti AWS.
In questa sessione illustreremo come pre-processare i dati che contengono una componente temporale e successivamente utilizzare un algoritmo che a partire dal tipo di dato analizzato produce un forecasting accurato.
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Amazon Web Services
La varietà e la quantità di dati che si crea ogni giorno accelera sempre più velocemente e rappresenta una opportunità irripetibile per innovare e creare nuove startup.
Tuttavia gestire grandi quantità di dati può apparire complesso: creare cluster Big Data su larga scala sembra essere un investimento accessibile solo ad aziende consolidate. Ma l’elasticità del Cloud e, in particolare, i servizi Serverless ci permettono di rompere questi limiti.
Vediamo quindi come è possibile sviluppare applicazioni Big Data rapidamente, senza preoccuparci dell’infrastruttura, ma dedicando tutte le risorse allo sviluppo delle nostre le nostre idee per creare prodotti innovativi.
Ora puoi utilizzare Amazon Elastic Kubernetes Service (EKS) per eseguire pod Kubernetes su AWS Fargate, il motore di elaborazione serverless creato per container su AWS. Questo rende più semplice che mai costruire ed eseguire le tue applicazioni Kubernetes nel cloud AWS.In questa sessione presenteremo le caratteristiche principali del servizio e come distribuire la tua applicazione in pochi passaggi
Vent'anni fa Amazon ha attraversato una trasformazione radicale con l'obiettivo di aumentare il ritmo dell'innovazione. In questo periodo abbiamo imparato come cambiare il nostro approccio allo sviluppo delle applicazioni ci ha permesso di aumentare notevolmente l'agilità, la velocità di rilascio e, in definitiva, ci ha consentito di creare applicazioni più affidabili e scalabili. In questa sessione illustreremo come definiamo le applicazioni moderne e come la creazione di app moderne influisce non solo sull'architettura dell'applicazione, ma sulla struttura organizzativa, sulle pipeline di rilascio dello sviluppo e persino sul modello operativo. Descriveremo anche approcci comuni alla modernizzazione, compreso l'approccio utilizzato dalla stessa Amazon.com.
Come spendere fino al 90% in meno con i container e le istanze spot Amazon Web Services
L’utilizzo dei container è in continua crescita.
Se correttamente disegnate, le applicazioni basate su Container sono molto spesso stateless e flessibili.
I servizi AWS ECS, EKS e Kubernetes su EC2 possono sfruttare le istanze Spot, portando ad un risparmio medio del 70% rispetto alle istanze On Demand. In questa sessione scopriremo insieme quali sono le caratteristiche delle istanze Spot e come possono essere utilizzate facilmente su AWS. Impareremo inoltre come Spreaker sfrutta le istanze spot per eseguire applicazioni di diverso tipo, in produzione, ad una frazione del costo on-demand!
In recent months, many customers have been asking us the question – how to monetise Open APIs, simplify Fintech integrations and accelerate adoption of various Open Banking business models. Therefore, AWS and FinConecta would like to invite you to Open Finance marketplace presentation on October 20th.
Event Agenda :
Open banking so far (short recap)
• PSD2, OB UK, OB Australia, OB LATAM, OB Israel
Intro to Open Finance marketplace
• Scope
• Features
• Tech overview and Demo
The role of the Cloud
The Future of APIs
• Complying with regulation
• Monetizing data / APIs
• Business models
• Time to market
One platform for all: a Strategic approach
Q&A
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Amazon Web Services
Per creare valore e costruire una propria offerta differenziante e riconoscibile, le startup di successo sanno come combinare tecnologie consolidate con componenti innovativi creati ad hoc.
AWS fornisce servizi pronti all'utilizzo e, allo stesso tempo, permette di personalizzare e creare gli elementi differenzianti della propria offerta.
Concentrandoci sulle tecnologie di Machine Learning, vedremo come selezionare i servizi di intelligenza artificiale offerti da AWS e, anche attraverso una demo, come costruire modelli di Machine Learning personalizzati utilizzando SageMaker Studio.
OpsWorks Configuration Management: automatizza la gestione e i deployment del...Amazon Web Services
Con l'approccio tradizionale al mondo IT per molti anni è stato difficile implementare tecniche di DevOps, che finora spesso hanno previsto attività manuali portando di tanto in tanto a dei downtime degli applicativi interrompendo l'operatività dell'utente. Con l'avvento del cloud, le tecniche di DevOps sono ormai a portata di tutti a basso costo per qualsiasi genere di workload, garantendo maggiore affidabilità del sistema e risultando in dei significativi miglioramenti della business continuity.
AWS mette a disposizione AWS OpsWork come strumento di Configuration Management che mira ad automatizzare e semplificare la gestione e i deployment delle istanze EC2 per mezzo di workload Chef e Puppet.
Scopri come sfruttare AWS OpsWork a garanzia e affidabilità del tuo applicativo installato su Instanze EC2.
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsAmazon Web Services
Vuoi conoscere le opzioni per eseguire Microsoft Active Directory su AWS? Quando si spostano carichi di lavoro Microsoft in AWS, è importante considerare come distribuire Microsoft Active Directory per supportare la gestione, l'autenticazione e l'autorizzazione dei criteri di gruppo. In questa sessione, discuteremo le opzioni per la distribuzione di Microsoft Active Directory su AWS, incluso AWS Directory Service per Microsoft Active Directory e la distribuzione di Active Directory su Windows su Amazon Elastic Compute Cloud (Amazon EC2). Trattiamo argomenti quali l'integrazione del tuo ambiente Microsoft Active Directory locale nel cloud e l'utilizzo di applicazioni SaaS, come Office 365, con AWS Single Sign-On.
Dal riconoscimento facciale al riconoscimento di frodi o difetti di fabbricazione, l'analisi di immagini e video che sfruttano tecniche di intelligenza artificiale, si stanno evolvendo e raffinando a ritmi elevati. In questo webinar esploreremo le possibilità messe a disposizione dai servizi AWS per applicare lo stato dell'arte delle tecniche di computer vision a scenari reali.
Amazon Web Services e VMware organizzano un evento virtuale gratuito il prossimo mercoledì 14 Ottobre dalle 12:00 alle 13:00 dedicato a VMware Cloud ™ on AWS, il servizio on demand che consente di eseguire applicazioni in ambienti cloud basati su VMware vSphere® e di accedere ad una vasta gamma di servizi AWS, sfruttando a pieno le potenzialità del cloud AWS e tutelando gli investimenti VMware esistenti.
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
Crea la tua prima serverless ledger-based app con QLDB e NodeJSAmazon Web Services
Molte aziende oggi, costruiscono applicazioni con funzionalità di tipo ledger ad esempio per verificare lo storico di accrediti o addebiti nelle transazioni bancarie o ancora per tenere traccia del flusso supply chain dei propri prodotti.
Alla base di queste soluzioni ci sono i database ledger che permettono di avere un log delle transazioni trasparente, immutabile e crittograficamente verificabile, ma sono strumenti complessi e onerosi da gestire.
Amazon QLDB elimina la necessità di costruire sistemi personalizzati e complessi fornendo un database ledger serverless completamente gestito.
In questa sessione scopriremo come realizzare un'applicazione serverless completa che utilizzi le funzionalità di QLDB.
Con l’ascesa delle architetture di microservizi e delle ricche applicazioni mobili e Web, le API sono più importanti che mai per offrire agli utenti finali una user experience eccezionale. In questa sessione impareremo come affrontare le moderne sfide di progettazione delle API con GraphQL, un linguaggio di query API open source utilizzato da Facebook, Amazon e altro e come utilizzare AWS AppSync, un servizio GraphQL serverless gestito su AWS. Approfondiremo diversi scenari, comprendendo come AppSync può aiutare a risolvere questi casi d’uso creando API moderne con funzionalità di aggiornamento dati in tempo reale e offline.
Inoltre, impareremo come Sky Italia utilizza AWS AppSync per fornire aggiornamenti sportivi in tempo reale agli utenti del proprio portale web.
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareAmazon Web Services
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
In queste slide, gli esperti AWS e VMware presentano semplici e pratici accorgimenti per facilitare e semplificare la migrazione dei carichi di lavoro Oracle accelerando la trasformazione verso il cloud, approfondiranno l’architettura e dimostreranno come sfruttare a pieno le potenzialità di VMware Cloud ™ on AWS.
1) The document discusses building a minimum viable product (MVP) using Amazon Web Services (AWS).
2) It provides an example of an MVP for an omni-channel messenger platform that was built from 2017 to connect ecommerce stores to customers via web chat, Facebook Messenger, WhatsApp, and other channels.
3) The founder discusses how they started with an MVP in 2017 with 200 ecommerce stores in Hong Kong and Taiwan, and have since expanded to over 5000 clients across Southeast Asia using AWS for scaling.
This document discusses pitch decks and fundraising materials. It explains that venture capitalists will typically spend only 3 minutes and 44 seconds reviewing a pitch deck. Therefore, the deck needs to tell a compelling story to grab their attention. It also provides tips on tailoring different types of decks for different purposes, such as creating a concise 1-2 page teaser, a presentation deck for pitching in-person, and a more detailed read-only or fundraising deck. The document stresses the importance of including key information like the problem, solution, product, traction, market size, plans, team, and ask.
This document discusses building serverless web applications using AWS services like API Gateway, Lambda, DynamoDB, S3 and Amplify. It provides an overview of each service and how they can work together to create a scalable, secure and cost-effective serverless application stack without having to manage servers or infrastructure. Key services covered include API Gateway for hosting APIs, Lambda for backend logic, DynamoDB for database needs, S3 for static content, and Amplify for frontend hosting and continuous deployment.
This document provides tips for fundraising from startup founders Roland Yau and Sze Lok Chan. It discusses generating competition to create urgency for investors, fundraising in parallel rather than sequentially, having a clear fundraising narrative focused on what you do and why it's compelling, and prioritizing relationships with people over firms. It also notes how the pandemic has changed fundraising, with examples of deals done virtually during this time. The tips emphasize being fully prepared before fundraising and cultivating connections with investors in advance.
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...Amazon Web Services
This document discusses Amazon's machine learning services for building conversational interfaces and extracting insights from unstructured text and audio. It describes Amazon Lex for creating chatbots, Amazon Comprehend for natural language processing tasks like entity extraction and sentiment analysis, and how they can be used together for applications like intelligent call centers and content analysis. Pre-trained APIs simplify adding machine learning to apps without requiring ML expertise.
Amazon Elastic Container Service (Amazon ECS) è un servizio di gestione dei container altamente scalabile, che semplifica la gestione dei contenitori Docker attraverso un layer di orchestrazione per il controllo del deployment e del relativo lifecycle. In questa sessione presenteremo le principali caratteristiche del servizio, le architetture di riferimento per i differenti carichi di lavoro e i semplici passi necessari per poter velocemente migrare uno o più dei tuo container.