Cloud computing is an information technology paradigm that enables ubiquitous access to shared pools of configurable system resources and higher-level services that can be rapidly provisioned with minimal management effort, often over the Internet.
Enterprises need to grow and manage their global computing infrastructures rapidly and efficiently while simultaneously optimizing and managing capital costs and expenses. Amazon Web Services (AWS) and Elastic Compute Cloud (EC2) computing and storage services meet the needs of the most demanding Caché based application by providing a highly robust global computing infrastructure.
This article provides a reference architecture as a sample for providing robust performing and highly available applications based on InterSystems Technologies that are applicable to Caché, Ensemble, HealthShare, TrakCare, and associated embedded technologies such as DeepSee, iKnow, Zen and Zen Mojo.
Azure has two different deployment models for creating and working with resources: Azure Classic and Azure Resource Manager. The information detailed in this article is based on the Azure Resource Manager model (ARM).
Let assume you have a infinitely scaling algorithm implemented in your application, using replication, ECP, or any other means of horizontal scaling, and let assume you know how to run your system under any volume of requests, the trick is to deploy required number of computing nodes in the cluster. If we are talking about cluster of 2-4 nodes your administrator (or as they call it today "devops engineer") will install anything manually. Probably he will easily handle 5 nodes configuration in the cluster.
Presenter: Tony Pepper Task: Host an application based on InterSystems’ technology in a public cloud environment Approach: Provide a checklist of things to think about before you deploy
Are you looking at hosting your applications in the public cloud? This talk will highlight what you need to think about when deploying InterSystems technology in any public cloud environment.
Content related to this session, including slides, video and additional learning content can be found here.
Presenter: Mark Bolinsky Task: Provide failover for distributed systems without using a VIP Approach: Demonstrate using InterSystems’ database mirroring with external traffic managers such as F5 LTM/GTM
With distributed environments and even public cloud environments, the use of a VIP sometimes is not desirable or even possible given network topology or deployment. The session will demonstrate integrating database mirroring with external traffic managers such F5 LTM/GTM using API based triggers in InterSystems products to interface with the F5 appliances. This not only presents automated redirection for the local mirror members, but also provided automated client redirection to asynchronous DR mirror members.
Content related to this session, including slides, video and additional learning content can be found here.
Presenter: Luca Ravazzolo Task: Define, provision, and configure a cloud infrastructure Approach: Use open-source tools for DevOps automation
This session demonstrates how a cloud infrastructure of clustered servers can be defined, provisioned and configured efficiently with a simple yet powerful provisioning technology.
Content related to this session, including slides, video and additional learning content can be found here.
Whichever way you want to look at it, their numbers are impressive... growing revenue year-on-year of 69% is amazing... and now they are opening DCs in Canada and India...
Can a Cache Mirror be used in the cloud ? (ie stand up a Primary and Backup member instances in a High Availability Cache Mirroring configuration)
I'm investigating the validity of this configuration, because I was of the understanding that this may not possible due to these cloud servers not (typically) having fixed ip addresses, which interferes with the Virtual IP settings for the mirror set.
Is this correct, and if there are workarounds (like Load Balancing ?) can I have details on how this should be configured ?
RESTful API Call From Cache to Particle.io Electron
Tom Fitzgibbon | Multidata | 212-967-6700 x537 | tom@mul.com
Summary: Simple Blink Tutorial for Particle.io Electron Device from Cache
Electron device is a tiny ARM processor ($40-$60) that connects to Particle’s world wide leased 2G/3G network (about $3/mo) and runs off an included LiPo battery. Using Cache’s %Net.HttpRequest you can send/receive data, control hardware and read sensors.
I was wondering, what is your favourite public cloud provider?
What is your level of engagement with the cloud provider? Are you testing their infrastructure? In which case I'd expect you being progressing a parallel test with at least a second provider ;-) Or, are you already running a production environment?
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OK, so, let me be the first one to share my experience with one specific cloud provider.
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