cloud-test

Announcing the Google Cloud Platform Podcast

Wednesday, February 24, 2016

Google Cloud PlatformGoogle Cloud Platform Podcast—

Google Cloud Platform Developer Advocates (left to right) Mark Mandel and Francesc Campoy

Mark MandelFrancesc CampoyDeveloper Advocacy teamBig DataKubernetesHTTP/2— Ram RamanathanChris Sells—conversations with customers such as Shine TechnologiesRSSiTunesPosted by Mark Mandel, Developer Advocate and Francesc Campoy Flores, Developer Advocate

Spotify chooses Google Cloud Platform to power data infrastructure

Tuesday, February 23, 2016

Google Cloud Platform—

2 billion playlistsCompute EngineGoogle Cloud DatastoreGoogle Cloud BigtableDirect PeeringCloud VPNCloud RouterGoogle Cloud Pub/SubGoogle Cloud DataflowGoogle BigQueryGoogle Cloud DataprocJoin us for the GCP NEXT 2016 opening keynote, where we’ll feature a talk from Nicholas Harteau, VP of Engineering and Infrastructure at Spotify. You can also attend Spotify-led technical sessions where you can learn more about how they’re deploying Google Cloud BigQuery and Dataflow.
- Posted by Guillaume Leygues, Lead Sales Engineer, Google Cloud Platform

Google seeks new disks for data centers

Tuesday, February 23, 2016

2016 USENIX conference on File and Storage Technologies (FAST 2016white paperevery day

collection- Posted by Eric Brewer, VP Infrastructure, Google

Google Cloud Dataproc managed Spark and Hadoop service now GA

Monday, February 22, 2016

Google Cloud DataprocApache HadoopApache Spark———entered beta last yearDevelopers ConsoleGoogle Cloud SDKGoogle BigQueryGoogle Cloud BigtableGoogle Cloud StorageGoogle Cloud Dataflowproperty tuningcluster versioningcustom machine types

Cloud Dataproc tips the scale of running Spark and Hadoop in your favor by lowering cost and complexity while increasing scalability and productivity

—costcomplexity

Low-cost. We believe two things — using Spark and Hadoop should not break the bank and that you should pay for what you actually use. As a result, Cloud Dataproc is priced at only 1 cent per virtual CPU in your cluster per hour, on top of the other Cloud Platform resources you use. Moreover, with per-minute billing and a low 10-minute minimum, you pay for what you actually use, not a rounded (up) approximation.

Speed. With Cloud Dataproc, clusters do not take 10, 15, or more minutes to start or stop. On average, Cloud Dataproc start and stop operations take 90 seconds or less. This can be a 2-10x improvement over other on-premises and IaaS solutions. As a result, you spend less time waiting on clusters and more time hands-on with data.

Management. Cloud Dataproc clusters don't require specialized administrators or software products. Cloud Dataproc clusters are built on proven Cloud Platform services, such as Google Compute Engine, Google Coud Networking, and Google Cloud Logging to increase availability while eliminating the need for complicated hands-on cluster administration. Moreover, Cloud Dataproc supports cluster versioning, giving you access to modern, tested, and stable versions of Spark and Hadoop.

—scaleproductivity

Easy. You can create, monitor, and delete Cloud Dataproc clusters and jobs directly through Google Developers Console and Cloud SDK. For more advanced use cases, you can use the Cloud Dataproc REST API with a programming language, such as Python, to programmatically interact with Cloud Dataproc without hassle.

Modern. Cloud Dataproc is frequently updated with new image versions to support new software releases from the Spark and Hadoop ecosystem. This provides access to the latest stable releases while also ensuring backward compatibility. For general availability we're releasing image version 1.0.0 with support for Hadoop 2.7.2, Spark 1.6.0, Hive 1.2.1, and Pig 0.15.0. Support for other components, such as Apache Zeppelin (incubating) are provided in our GitHub repository for initialization actions.

Integrated. Cloud Dataproc has built-in integrations with other Cloud Platform services, such as BigQuery, Cloud Storage, Cloud Bigtable, and Google Cloud Logging so you have more than just a Spark or Hadoop cluster — you have a complete data platform. You can also use Cloud Dataproc initialization actions to extend the functionality of your clusters.

partner ecosystemArimoAttunityLookerWANdiscoZoomdataMoserPythianTectonic Cloud Dataproc sitegetting started guidepredict keno outcomes with Cloud DataprocStack OverflowPosted by James Malone, Product Manager

Sports Authority handles 2,000 transactions per second with Google Cloud Platform

Friday, February 19, 2016

Sports AuthorityGoogle Cloud Platformsportsauthority.com
Choosing the right cloud providerGoogle Apps for WorkGoogle Cloud PlatformGoogle App EngineGoogle Cloud DatastoreGoogle Cloud StorageSOAPUILOADUI

This screenshot shows what customers see when they shop for products on the website — a list of local stores, showing the availability of any given product in each store

In-store kioskGoogle Chromebox

This image shows the in-store kiosk that customers use to locate products available in other stores.

Internal store portalGoogle Custom SearchTempus Nova

This screenshot shows the internal store portal that employees use to monitor daily tasks.

Posted by Jon Byrum, Product Marketing Manager, Google Cloud Platform

Google Cloud Vision API enters Beta, open to all to try!

Thursday, February 18, 2016

Google Cloud Vision API—Google Cloud Storagepricing

Insights from your images: Powered by the same technologies behind Google Photos, Cloud Vision API detects broad sets of objects in your images — from flowers to popular landmarks

Inappropriate content detection: Powered by Google SafeSearch, Cloud Vision API moderates content from your crowd sourced images by detecting different types of inappropriate content.

Image sentiment analysis: Cloud Vision API can analyze emotional attributes of people in your images, like joy, sorrow and anger, along with detecting popular product logos.

Text extraction: Optical Character Recognition (OCR) enables you to detect text within your images, along with automatic language identification across a broad set of languages.

limited previewPhotoFyYik Yakdocumentation¹samplesGoogle Cloud Vision APIhere
We couldn't resist showing you our favorite robot again.

- Posted by Ram Ramanathan, Product Manager, Google Cloud Platform

1 Java is the registered trademark of Oracle and/or its affiliates.

Google and Red Hat announce cloud-based scalable file servers

Thursday, February 18, 2016

Google Cloud PlatformGoogle Cloud StorageDataStoreBigQueryPersistent Disksdisks of up to 64TB in sizewith up to 15,000 IOPS

here- Posted by Vic Iglesias, Cloud Solutions Architect

Google Cloud Platform Blog

Announcing the Google Cloud Platform Podcast

Spotify chooses Google Cloud Platform to power data infrastructure

Google seeks new disks for data centers

Google Cloud Dataproc managed Spark and Hadoop service now GA

Sports Authority handles 2,000 transactions per second with Google Cloud Platform

Google Cloud Vision API enters Beta, open to all to try!

Google and Red Hat announce cloud-based scalable file servers

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