The document discusses faбrik, an asynchronous messaging framework created by the NYT Infrastructure Group to enable communication between applications and devices. It provides decoupling of data producers from consumers, uses common messaging patterns like publish/subscribe, and scales across cloud infrastructure. The framework aims to simplify application development by handling complex distributed messaging requirements.
Cassandra Day NY 2014: Apache Cassandra & Python for the The New York Times ⨍...DataStax Academy
In this session, you’ll learn about how Apache Cassandra is used with Python in the NY Times ⨍aбrik messaging platform. Michael will start his talk off by diving into an overview of the NYT⨍aбrik global message bus platform and its “memory” features and then discuss their use of the open source Apache Cassandra Python driver by DataStax. Progressive benchmark to test features/performance will be presented: from naive and synchronous to asynchronous with multiple IO loops; these benchmarks tailored to usage at the NY Times. Code snippets, followed by beer, for those who survive. All code available on Github!
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Cassandra Day NY 2014: Apache Cassandra & Python for the The New York Times ⨍...DataStax Academy
In this session, you’ll learn about how Apache Cassandra is used with Python in the NY Times ⨍aбrik messaging platform. Michael will start his talk off by diving into an overview of the NYT⨍aбrik global message bus platform and its “memory” features and then discuss their use of the open source Apache Cassandra Python driver by DataStax. Progressive benchmark to test features/performance will be presented: from naive and synchronous to asynchronous with multiple IO loops; these benchmarks tailored to usage at the NY Times. Code snippets, followed by beer, for those who survive. All code available on Github!
Participation and Inclusion in Lifelong LearningRika Yorozu
Presented in the Training Workshop for Directors and Executives of Youth and Adult Education for Women in Saudi Arabia (Hamburg, 29 September – 10 October 2014)
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In this AE Foyer Glenn Dejaeger and Thomas Anciaux will focus on Trends and Aspects of front end engineering. When do you choose a native front end, when should you go web? What is a good front end architecture? How do you cover the design, development, test and lifecycle aspects of a professional front end? How to survive in the jungle of frameworks? What are the current insights and future directions in front end engineering? How do you deal with offline mobile? Do you need front end engineers?
What's next in digital communications for construction marketingpwcom.co.uk Ltd
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Making your Analytics Investment Pay Off - StampedeCon 2012StampedeCon
At StampedeCon 2012 in St. Louis, Bill Eldredge of Nokia presents: At Nokia, we expect to save millions on avoided license fees this year on a single “Big Data” project by creating a symbiotic relationship between our traditional RDBMS storage and our newer Hadoop cluster. Our hybrid approach to data enables us to manage the convergence of structured and unstructured data, and save money. In our case we use Hadoop to process and import data into traditional systems. We have found that this use of Hadoop as a preprocessing engine has enabled maximum value to be derived from our systems, our data and our people.
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IBM s'accocie à Crédit Agricole Immobilier, au CA Store et leurs partenaires pour vous présenter le Smart Home Challenge !
A travers ce challenge d’open innovation, IBM s’associe à Crédit Agricole Immobilier pour collaborer avec les startups pour concevoir et construire l’habitat connecté de demain.
Vous développez des produits et services dans le domaine de l’habitat, du bien-être, du développement durable, de l’IoT ? A vous de jouer !
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- les APIs Twitter, WeatherCompany,
- et 140 autres services BigData, Analytics, Mobilité, Sécurité, etc...
Co-développement, expérimentation, relation commerciale ou prises de participation minoritaires sont en jeu. Sans oublier la dotation "Go To Market" de 20 000€ à se partager pour les 3 lauréats.
Vous avez jusqu'au 24 janvier 2016 pour vous inscrire et déposer une présentation de votre concept.
www.smarthomechallenge.com
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Hadoop is becoming the well-known open source cloud computing technology developed by Apache community. It is very power tool for data mining. It had been used in Yahoo and Facebook production environment to provide cloud service model (2) — "Platform as a Service (PaaS)". It’s easy to setup single hadoop node but difficult to manage a hadoop cluster. In this talk, we will show you how DRBL can help on fast deployment and management.
Most bioinformatics applications are open source, such as R, Bioconductor, BLAST, Clustal, PipMaker, Phylip, etc. But it also require traditional cluster job submission. In this talk we will show you how DRBL can help to build a testbed of bioinformatics research and provide cloud service model (3) — "Software as a Service (SaaS)". In this talk, we will cover how to:
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- 2. Use DRBL to deploy Hadoop cluster (drbl-hadoop)
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A live demonstration about drbl-hadoop and drbl-biocluster will be done in the talk, too.
Real-Time Communications between MicroservicesSolace
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------------
Learn the advantages of enabling communications between applications using open APIs and protocols like AMQP, JMS, MQTT, Qpid, Paho, REST and WebSockets. Mark Spielman demonstrates how easily you can enable real-time communications between microservices with the new Solace Messaging Tile for Pivotal Cloud Foundry. We’ll then discuss the architecture and code that makes it all possible.
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Demian Neidetcher's presentation to the Denver Open Source Users Group on the Android mobile phone platform. Full details and source code available at http://neidetcher.com/android.html
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Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
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IBM s'accocie à Crédit Agricole Immobilier, au CA Store et leurs partenaires pour vous présenter le Smart Home Challenge !
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Vous développez des produits et services dans le domaine de l’habitat, du bien-être, du développement durable, de l’IoT ? A vous de jouer !
IBM met à a disposition des participants les plus disruptifs sa Plate-forme d'Innovation Digitale IBM Bluemix et ses nombreux services :
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Co-développement, expérimentation, relation commerciale ou prises de participation minoritaires sont en jeu. Sans oublier la dotation "Go To Market" de 20 000€ à se partager pour les 3 lauréats.
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www.smarthomechallenge.com
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In short, Diskless Remote Boot in Linux (DRBL) provides a diskless or systemless environment for client machines. It works on Debian, Ubuntu, Mandriva, Red Hat, Fedora, CentOS and SuSE. DRBL uses distributed hardware resources and makes it possible for clients to fully access local hardware.
Xen is one of open source hypervisor for linux kernel. It had been used in Amazon EC2 production environment to provide cloud service model (1) — "Infrastructure as a Service (IaaS)". In this talk, we will show you how DRBL can help on fast deployment of Xen playground in classroom.
Hadoop is becoming the well-known open source cloud computing technology developed by Apache community. It is very power tool for data mining. It had been used in Yahoo and Facebook production environment to provide cloud service model (2) — "Platform as a Service (PaaS)". It’s easy to setup single hadoop node but difficult to manage a hadoop cluster. In this talk, we will show you how DRBL can help on fast deployment and management.
Most bioinformatics applications are open source, such as R, Bioconductor, BLAST, Clustal, PipMaker, Phylip, etc. But it also require traditional cluster job submission. In this talk we will show you how DRBL can help to build a testbed of bioinformatics research and provide cloud service model (3) — "Software as a Service (SaaS)". In this talk, we will cover how to:
- 1. Use DRBL to deploy Xen virtual cluster (drbl-xen)
- 2. Use DRBL to deploy Hadoop cluster (drbl-hadoop)
- 3. Use DRBL to deploy bioinformatics cluster (drbl-biocluster)
A live demonstration about drbl-hadoop and drbl-biocluster will be done in the talk, too.
Real-Time Communications between MicroservicesSolace
This presentation is from the Pivotal Cloud Foundry meetup in Columbus, Ohio, on February 23, 2017.
------------
Learn the advantages of enabling communications between applications using open APIs and protocols like AMQP, JMS, MQTT, Qpid, Paho, REST and WebSockets. Mark Spielman demonstrates how easily you can enable real-time communications between microservices with the new Solace Messaging Tile for Pivotal Cloud Foundry. We’ll then discuss the architecture and code that makes it all possible.
Join us to learn how you can improve the way your applications exchange information both within Pivotal Cloud Foundry and across clouds.
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In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
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4. Takeaways
Application Developer
– Demand „events‟ (no polling, no thanks, been there, done that)
– Demand infrastructure that scales and you don‟t have to worry about
Infrastructure Engineer
– Decouple, flatten, simplify
– Outsource complexity
4
5. The Story: Harvard U, 1986+
Bad:
– No Internet (pre-web)
– data locked in mainframe
– large central clerical staff
– monolithic central systems
Good:
– Vision of an Information Utility
– desire to innovate
– lots of desktop computers (30,000)
– email everywhere although over diverse networks and technologies
5
6. The Story: Harvard U, 1986+
Solution:
– Relational database (decouple data from application)
– Email backbone (decouple producers from consumers)
– Event-driven desktop applications (flatten)
– Identical code on mainframe (simplify)
Result:
– Data warehouse unlocked (before the term was coined)
– Central clerical staff functions upgraded/dispersed
– Old central systems replaceable and, ultimately, replaced
– Happy users!
6
8. NYT Mission
Enhance society by creating, collecting and
distributing high quality news, information and
entertainment
- Distributing: publish / subscribe
- Collecting: gather / analyze
- High Quality: fast, reliable, accurate
8
9. faбrik
Asynchronous Messaging Framework
For client devices as well as our apps
Enabled by:
– Websockets
– Robust message handling software
– Amazon Web Services
Focusing on simple, common services
9
GE225 – also analog computersHarvard: Milly Koss – beginning in 1950 Hopper, Mawkley – computer pioneersTech: Managing hardware/software companies in Venezuela & AustraliaUN: slow to change
Picture: Not really Harvard - Central message switch for London’s pneumatic tube system – 50 miles of tubes – ca 1930 – 1870’s thru the 30’s
Learning points:. When you touch some data, take it all. Keep the lowest level of detail
Events – like email but fasterBig deal – extended to client devices – takes some effort as I’ll describe in a few slidesMessaging Infrastructure used to be expensiveIn combination, we can:. Outsource a lot of complexity. Decouple and flatten by using messaging everywhereSo we can focus on doing the simple things well, e.g.:. Publish/Subscribe. Persisting data. Gathering data for analysis
I’ve been in ‘infrastructure’ mode – switching back to a developer’s point of viewWe’ll look later at some code that does just thatMeanwhile we’ll dive back into the innards of the fabrik
Message Broker: . Routes and load balances – simple and complex topologies. ResilientHorizontalDecouples:. Different technologies. Different rates – buffers, queues
Outsource complexity to Amazon Web Services
2 levelsWholesale Message Broker extends throughout the fabrik – think of it as encircling the world – components are pretty stable – doesn’t fail, although components mightRetail Message Broker is a “spur” – supports an app buddy and a collection of service buddies – spurs are added/subtracted as needed and may fail
We’ve got a little ruby in there tooA bit about nodejs and python: (since I am the “meat – or maybe the ham” in this evening’s lineup re node). a plus for node is that asynch programming is natural and consistent – and with coffeescript it’s actually fun – in python you have to “do” something – and your support modules may have chosen to “do” something else!. However for our purposes, some of the nodejs support modules are not as mature or robust – so we have had to “fix” them. In particular, for the most critical high-performance components, we’re likely to use python for now, though nodejs is strategic for us, because javascript is so important to our community of clients
Zooming up – and leaving out some detail – here’s an illustration of one way we are tying to create “non-stop” servicesThe red dot indicates clustering between virtual machine instances, each running in a separate zone – think datacenter – in an AWS regionMy 2 service buddies each perform the same service, and the broker load balances work to them, so they are each active
If one of the service buddies goes down, or a broker instance goes down, or a zone goes down, the other broker adjusts and requeues work to the survivorMeanwhile, we will automatically be adding more resources to compensate, and possibly shunting work away from this region until it is fully healthy againNow lets zoom up again and take a global view
These are the Amazon regions, and the zonesExcept a 3rd zone has now been added both to Northern California and Tokyo, so there are 20 zones availableEach zone has independent power and independent communications infrastructure – so think of them as datacentersOne of our goal is to be able to balance across all the zones, optimizing service and cost
Logically, the wholesale layer is unified in each region The retail layer is autoscaled based upon demand and “health” – remember the retail components are “spurs” off the cluster, sharing nothing
The regions are federated in a complete networkLet’s take another perspective on pretty much the same information
I’ve pulled the regional clusters together in this view
So that is the wholesale layer
The our own apps – publishers or analyzers or whatever – connect via load balancers
The retail layer connects via load balancer tooEach instance in this layer has an app buddy, a local broker, and service buddies, hence the “blend” of red and blue
Finally the external clients coming thru Route 53 and via another layer of load balancers into our retail layer
Every layer is supported by AWSNow let’s take a look at how we can use the fabrikOur initial target is to support the “publish/subscribe” pattern
Nothing too radical here – classic Pub/SubExcept:. One machine image. Small systems software complement. 10-20 small, testable, tunable apps in a different languages. Decoupled, simple, flat. Global, fast, resilient, autoscaled – complexity outsourcedDevelopers – the real payoff is for you which I’ll try to illustrate with code in a few minutes
Wholesale layer does not scale to the degree necessary to directly handle all retail eventsKill a couple birds at once by using AWS DynamoDB. Persist data immediately. Use dynamo to assemble detail from many sources in near real time
That’s enough of an overview of the fabrik – let’s see a demo and look at some code
Specifically we’ll look at some html that runs the demoThe publishing app is written in coffeescript and pretty simple too – anyone who’s interested can see me after and we’ll take a lookFirst the demo