Architectures_Concepts
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DBMS Musings: Apache Arrow vs. Parquet and ORC: Do we really need a third Apache project for columnar data representation?

DBMS Musings: Apache Arrow vs. Parquet and ORC: Do we really need a third Apache project for columnar data representation? | Architectures_Concepts | Scoop.it
Apache Parquet and Apache ORC have become a popular file formats for storing data in the Hadoop ecosystem. Their primary value propositio
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SMACK stack for big data: Spark, Mesos, Akka, Cassandra, and Kafka | HPE™

SMACK stack for big data: Spark, Mesos, Akka, Cassandra, and Kafka | HPE™ | Architectures_Concepts | Scoop.it
Just as the LAMP stack revolutionized servers and web hosting, the SMACK stack has made Big Data applications viable and easier to develop. Want to come up to speed? Here’s the basics.
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How to design a serverless backend that scales with your apps success

Developing a small mobile app can be done very easily — although changing the underlying architecture after you’re up and running is difficult. Prior to launch, take the time to prepare your mobile…
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Hiding Images using AI — Deep Steganography –

Discussing the latest in Steganography using a Deep Learning approach
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How production engineers support global events on Facebook | Engineering Blog | Facebook Code | Facebook

How production engineers support global events on Facebook | Engineering Blog | Facebook Code | Facebook | Architectures_Concepts | Scoop.it
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Discovering issues in HTTP/2 with Chaos Testing

Discovering issues in HTTP/2 with Chaos Testing | Architectures_Concepts | Scoop.it
via Chaos Engineering we discovered that there are situations where HTTP/2 will perform worse than HTTP/1.
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Python’s Weak Performance Matters –

Python’s Weak Performance Matters – | Architectures_Concepts | Scoop.it
Here is an argument I used to make, but now disagree with: Just to add another perspective, I find many "performance" problems in the real world can often be attributed to factors other than the raw speed of the CPython interpreter. Yes, I'd love it if the interpreter were faster, but in my experience a…
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How we grew from 0 to 4 million women on our fashion app, with a vertical machine learning approach

Three years ago we launched Chicisimo, our goal was to offer automated outfit advice. Today, with over 4 million women on the app, we want to share how our data and machine learning approach helped…
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Hans Peter Luhn and the Birth of the Hashing Algorithm

Hans Peter Luhn and the Birth of the Hashing Algorithm | Architectures_Concepts | Scoop.it
The IBM engineer’s hashing algorithm gave computers a way to quickly search documents, DNA, and databases
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Container people, let’s talk about serverless – Paul Johnston – Medium

Can you run serverless on kubernetes?

Can you run your own private serverless?

There is a lot of conversation about containers at the moment with regards to serverless and whether some form of…
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Announcing the general availability of Azure Event Grid

Announcing the general availability of Azure Event Grid | Architectures_Concepts | Scoop.it
Modern applications are taking maximum advantage of the agility and flexibility of the cloud by moving away from monolithic architectures and instead using a set of distinct services, all working…
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NHS OKs offshoring patient data to cloud providers stateside

NHS OKs offshoring patient data to cloud providers stateside | Architectures_Concepts | Scoop.it
It's up to you but the fluffy stuff is awesome, beams guidance
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How we built a serverless digital archive with machine learning APIs, Cloud Pub/Sub and Cloud Functions

How we built a serverless digital archive with machine learning APIs, Cloud Pub/Sub and Cloud Functions | Architectures_Concepts | Scoop.it
By Kees van Bemmel, Managing Director, Incentro  [ Editor’s note : Today we hear from Incentro , a digital service provider and Googl
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Towards 3B time-series data points per day: Why DNSFilter replaced InfluxDB with TimescaleDB

DNSFilter (a Techstars Anywhere 2018 company) provides cloud-based content filtering and threat protection for IT Professionals. We accomplish this through DNS, and offer usage-based pricing. In the…
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Infinitely scalable machine learning with Amazon SageMaker - All Things Distributed

Infinitely scalable machine learning with Amazon SageMaker - All Things Distributed | Architectures_Concepts | Scoop.it
Amazon SageMaker offers production-ready, infinitely scalable algorithms such as: Linear Learner Factorization Machines Neural Topic Modeling Principal Component Analysis (PCA) K-Means clustering DeepAR forecasting
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Open-sourcing a 10x reduction in Apache Cassandra tail latency

At Instagram, we have one of the world’s largest deployments of the Apache Cassandra database. We began using Cassandra in 2012 to replace Redis and support product use cases like fraud detection…
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Migrating Batch ETL to Stream Processing: A Netflix Case Study with Kafka and Flink

Migrating Batch ETL to Stream Processing: A Netflix Case Study with Kafka and Flink | Architectures_Concepts | Scoop.it
At QCon New York, Shriya Arora presented “Personalising Netflix with Streaming Datasets” and discussed the trials and tribulations of a recent migration of a Netflix data processing job from the traditional approach of batch-style ETL to stream processing using Apache Flink.
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Serverless Databases: The Future of Event-Driven Architecture

Serverless Databases: The Future of Event-Driven Architecture | Architectures_Concepts | Scoop.it
Serverless Databases | How it Works? | Benefits & Key Features | Pricing Comparison | Firebase | FaunaDB | Aurora Serverless | CosmosDB
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Reflecting on Wayfair’s Conversion to React and Redux | Wayfair Technology Blog

Reflecting on Wayfair’s Conversion to React and Redux | Wayfair Technology Blog | Architectures_Concepts | Scoop.it
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Russell Cohen | Maximize Cache Performance with this One Weird Trick: An Introduction to Cache-Oblivious Data Structures

Russell Cohen | Maximize Cache Performance with this One Weird Trick: An Introduction to Cache-Oblivious Data Structures | Architectures_Concepts | Scoop.it
If you read my recent post about Postgres you may have noted that Postgres operates primarily with fixed-size blocks of memory called “pages.” By default, Postgres pages are 8KB. This number is tuned to match operating system page sizes which are tuned to match hardware cache sizes. If you were to run Postgres on hardware with different cache sizes than Postgres was tuned for, you may be able to pick a better page size.
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You're the IT worker in charge of securing the cloud for your company. Welcome to Hell

You're the IT worker in charge of securing the cloud for your company. Welcome to Hell | Architectures_Concepts | Scoop.it
How'd data leave country? Yep, control-V'd into a rando app the user set up
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A scalable Keras + deep learning REST API - PyImageSearch

A scalable Keras + deep learning REST API - PyImageSearch | Architectures_Concepts | Scoop.it
In today's tutorial you'll learn how to build a scalable deep learning REST API using Keras, Flask, Redis, and message queuing/message brokers.
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ISP Column - January 2018

ISP Column - January 2018 | Architectures_Concepts | Scoop.it
Geoff Huston : "Time for another annual roundup from the world of IP addresses. Let's see what has changed in the past 12 months in addressing the Internet and look at how IP address allocation information can inform us of the changing nature of the network itself."
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Build a multi-region, multi-master application with Serverless and DynamoDB Global Tables

Build a multi-region, multi-master application with Serverless and DynamoDB Global Tables | Architectures_Concepts | Scoop.it
We're going to create a multi-region, multi-master, geo-routed application—all in about 30 minutes.
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Running Dedicated Game Servers in Kubernetes Engine  |  Solutions  |  Google Cloud Platform

Running Dedicated Game Servers in Kubernetes Engine  |  Solutions        |  Google Cloud Platform | Architectures_Concepts | Scoop.it
This tutorial describes an expandable architecture for running real-time, session-based multiplayer dedicated game servers on Kubernetes Engine. A scaling manager process automatically starts and stops virtual machine instances as needed. Configuration of the machines as Kubernetes nodes is handled automatically by managed instance groups.
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