Google Cloud Platform Blog: June 2014

All data is written locally first, then automatically synchronized in the background. The save, delete and query methods provide your basic CRUD operations while the requestSync method allows you to force a synchronization at any time.
On the backend the data is stored in Google Cloud Datastore which means you can access the raw data directly from a Google App Engine or Google Compute Engine instance using the existing Datastore API. Changes on the server will even be automatically synced back to client devices.
Importantly, this per-user data belongs to you, the developer, and stored in your own Google Cloud Datastore database.
Cloud Save (3).png

Google Cloud Save is currently in private beta and will be available for general use soon. If you’re interested in participating in the private beta, you can sign up here!

Cloud Tools for Android Studio
To simplify the process of adding an App Engine backend to your app, Android Studio now provides three App Engine backend module templates which you can add to your app:

App Engine Java Servlet Module - Minimal Backend

App Engine Java Endpoints Module - Basic Endpoint scaffolding

App Engine with Google Cloud Messaging - Push notification wireup

Built-in rich editing support for Google Cloud Endpoints
Once you have added the backend module to your Android application, you can use Google Cloud Endpoints to streamline the communication between your backend and your Android app. Cloud Endpoints automatically generates strongly-typed, mobile optimized client libraries from simple Java server-side API annotations, automates Java object marshalling to and from JSON, and provides built-in OAuth 2.0 support.
On deployment, this annotated Endpoints API definition class generates a RESTful API. You can explore this generated API (and even make calls to it) by navigating to Endpoints API explorer as shown in the image below:

To simplify calling this generated API from your Android app, Android Studio will automatically set up your project to include all compile dependencies and permissions required to consume Cloud Endpoints, and will re-generate strongly-typed client libraries if your backend changes. This means that you can start calling the client libraries from your Android app immediately after defining the server-side Endpoints API.
The underlying work-horses: Gradle, and Gradle plug-in for App Engine
Under the hood, Gradle is used to build both your app and your App Engine backend. In fact, when you add an App Engine backend to your Android app, the open-source App Engine plug-in for Gradle is automatically downloaded by Android Studio, and common App Engine tasks become available as Gradle targets. This allows you to use the same build system across your IDE, command-line or continuous integration environments.
Checkout more details on the new Cloud Endpoints features in Android Studio on the Android Developer Blog.

-Posted by Jason Polites, Product Manager

Sneak peek: Google Cloud Dataflow, a Cloud-native data processing service

Thursday, June 26, 2014

Google I/O

for data integration and preparation (e.g. in preparation for interactive SQL in BigQuery)

to examine a real-time stream of events for significant patterns and activities

to implement advanced, multi-step processing pipelines to extract deep insight from datasets of any size

MapReduceFlumeMillWheelCloud StorageBigQueryPub/SubIf you’d like to be notified of future updates about Cloud Dataflow, please join our Google Group.

Enabling developers to tame production systems in the cloud

Wednesday, June 25, 2014

Cloud Debugger Screen Shot 2014-06-19 at 10.34.21 AM.png

Cloud Tracecorrelates with end user satisfaction and retentionbatching them. Short Waterfall.png

Cloud Monitoring, Powered by Stackdriver

SSH to your VM instantly Screen Shot 2014-06-15 at 7.19.10 AM.png

Ready for a Spin?

Reimagining developer productivity and data analytics in the cloud - news from Google IO

Wednesday, June 25, 2014

Google I/OIntroducing Google Cloud DataflowFlumeMillWheelDebug, trace and monitor your application in production New features for mobile developmentSnapchatRising StarGoogle Cloud DatastoreGoogle App EngineGoogle Compute EngineDatastore APIAndroid StudioJava ServletJava EndpointsApp Engine backend with Google Cloud MessagingApp Engine plug-in for Gradle,*Apache, Nginx, MongoDB, MySQL, Tomcat, IIS, Redis, Elasticsearch and Cassandra are trademarks of their respective owners.

Running MongoDB on Google Compute Engine

Tuesday, June 24, 2014

virtual machine typespersistent disksGoogle Compute EngineMongoDBPuppet, Chef, Salt, and AnsibleMongoLabhttp://cloud.google.com/solutions/mongodbMongoDB on Google Compute Engine Put your MongoDB journal files and data files on the same disk It is a common recommendation to separate components onto different storage devices. However, persistent disk already stripes data across a very large number of volumes, so there is no need to do it yourself. MongoDB journal data is small and putting it on its own disk means either creating a small disk with insufficient performance or creating a large disk that goes mostly unused. Put your MongoDB journal files on the same disk as your data. Otherwise putting your MongoDB journal files on a small persistent disk will dramatically decrease performance of database writes.http://cloud.google.com/solutions/mongodbMongoDB, is registered trademarks of MongoDB, Inc. All other trademarks cited here are the property of their respective owners.

One click to deploy a RabbitMQ cluster handling over 1 million msg/sec

Monday, June 23, 2014

RabbitMQdedicated RabbitMQ cluster6 billion per day40 billion iMessages per dayGoogle and Pivotal BenchmarksPerfTestRabbitMQ clustering recommendations Screen Shot 2014-04-23 at 2.04.02 PM.png

Screen Shot 2014-04-23 at 2.04.02 PM.png

ConclusionPivotal benchmarksGoogle Developer Console Screen Shot 2014-06-19 at 10.13.59 AM copy.png

Screen Shot 2014-04-22 at 5.13.16 PM.png

CloudAMQP offering

Introducing Cloud Storage Online Cloud Import: One more way to efficiently import your data to Google Cloud Platform

Thursday, June 19, 2014

hereCloud Storage Offline Disk Importgsutil (now with rsync)sign up for Online Cloud Import

Announcing Limited Preview Of SSD persistent disk

Wednesday, June 18, 2014

Earlier this weekbest practices

You can run your databases and file servers on Google Cloud Platform faster than ever before and move ever more demanding applications into Google Cloud Platform.

You now have a simple and cost effective solution for handling small amounts of data that need high IO. When your application is I/O constrained, SSD persistent disk gives you up to 59% lower costs for read-heavy workloads, and up to 92% lower costs for write-heavy workloads.

This storage offering is targeted at highly transactional systems. Your MySQL, PostgreSQL, Mongo, Cassandra and Redis should work incredibly fast. But, this is not targeted at streaming large files sequentially. Use Standard persistent disk for bulk data or data that is read and written to in sequential streams and High IOPS PD for your heavily transactional storage with more random access.

High IOPS counts 16KB IOs and lower as 1 IO. Larger IO sizes will count as multiple IOs. For example, a 128KB IO will count as 8 IOs.

For larger volumes, VM IO capabilities will limit how much IO can be expected from the volume. VM limits today for the larger VMs are 10,000 read IOPS, 15,000 write IOPS, 180 MB/s read and 120 MB/s writes. These are numbers we are working hard to increase as we further optimize our infrastructure. Stay tuned for more here.

documentationheretechnical supportGooge Compute Engine Discussion mailing listGoogle Compute Engine Stack Overflow forum

Unveiling scalable HTTP load balancing across cloud regions

Tuesday, June 17, 2014

Editor’s note: This post is a follow-up to the announcements we made on 6/16/2014.serve 1 million requests per secondNetwork load balancingMondayHTTP Load Balancingsingle global external IP address

unified, region-free rates

documentationsign up

Introducing HTTP Load Balancing and SSD Persistent Disk on Google Cloud Platform

Monday, June 16, 2014

Google I/OHTTP Load BalancingSSD Persistent DiskSSD persistent diskLimited PreviewHTTP load balancing

CI&T uses Google Cloud Platform to power the Coca-Cola “Happiness Flag” unveiled on the pitch at the opening match of the 2014 FIFA World Cup™

Saturday, June 14, 2014

Editor’s note: Today's guest post is from Daniel Viveiros, Head of Technology at CI&T, a Google Cloud Platform Partner of the Year LATAM 2013. In this post, Daniel describes how CI&T in partnership with Coca-Cola built the ‘Happiness Flag’ for the Coca-Cola 2014 FIFA World Cup™ campaign in Brazil. To learn more about the Happiness flag visit this website. Happiness Flag Coca-Cola Happiness Flag Live.png

Google Cloud Platform

Google App EngineGoogle Cloud StorageGoogle Compute EngineMemcacheDatastoreHappiness Flag

Achieve more with new Google Compute Engine command-line tool in Google Cloud SDK

Friday, June 13, 2014

tips and tricksGoogle Cloud SDKgcloudgcloudgcloud computeGoogle Compute Engine

Great Windows support out-of-the-boxGoogle Cloud SDK installergcloud computegcloud computegcloud compute ssh INSTANCE_NAME --zone=us-central1-a

--commandgcloud compute ssh INSTANCE_NAME --command="ps aux" --zone=us-central1-acopy-filesgcloud compute copy-files instance-1:file-1 instance-2:file-2 ... local-directory --zone=us-central1-a

gcloud compute copy-files file-1 file-2 ... instance:remote-directory --zone=us-central1-asshscpgcloud compute config-sshImproved scripting supportgcloud compute instances listgcloud compute instances delete my-old-vmgcloud compute instances delete $(gcloud compute instances list --zone=us-central1-b)Integrated documentation and command-line help-hgcloud compute instances list -h--helpman pageCloud SDK’s documentation page

Flexible output formattinggcloud compute instances list--format=json--format=textgcloud computegcloud compute firewall-rules list --format=textgcloud compute zones list --format=json--regexpmy-instance-1my-instance-2my-instance-3gcloud compute instances list --regexp my-instance-.* --fieldsgcloud compute instances list --fields name disks[].source disks[].modeCommand suggestion and autocompletiongcloudgcloud (e.g. type gcloud compute fi and press to have it expanded to gcloud compute firewall-rules). Similarly, you can type gcloud compute firewall-rules and press twice to see the operations which you can perform with firewall-rules. Also, if you mistype a command, gcloud will suggest a nearest match.

Screenz Real Time Platform powers ABC’s Rising Star in collaboration with Google Cloud Platform

Thursday, June 12, 2014

Today’s guest blog comes from Eli Uzan, CEO of Screenz. Screenz joined forces with Google to revolutionize the TV viewing experience. Their Real Time Platform is the state-of-the-art technology powering the upcoming ABC television show Rising Star.

Accelerating breakthroughs in understanding autism with Google Cloud Platform

Tuesday, June 10, 2014

Today’s guest blog is by Autism Speaks Chief Science Officer Robert Ring. As the world’s largest autism science and advocacy organization, Autism Speaks has committed more than $500 million to its mission, the majority in science and medical research. Google GenomicsGoogle BigQueryGoogle Compute Engine

An update on container support on Google Cloud Platform

Tuesday, June 10, 2014

Support for Docker images in Google App EngineCompute EngineManaged VMsvia this formKubernetes—an open source container managerOmegaGitHubmailing listContainer stack improvementscAdvisorA commitment to open container standards

Announcing Programmatic Access to Your Detailed Google Compute Engine Usage Data

Thursday, June 5, 2014

Google Compute EngineCompute Engine Usage ExportBilling Export

Report Date,MeasurementId,Quantity,Unit,Resource URI,ResourceId,Location 2014-05-01,com.google.cloud/services/compute-engine/VmimageN1Standard_1,86400,seconds,https://www.googleapis.com/compute/v1/projects/123456789/zones/us-central1-a/instances/testinstance1,13495613777116200000,us-central1-a 2014-05-01,com.google.cloud/services/compute-engine/VmimageN1Standard_1,86400,seconds,https://www.googleapis.com/compute/v1/projects/123456789/zones/us-central1-b/instances/testinstance2,17932867728944100000,us-central1-b Usage Export documentation