Google Cloud Platform Blog
Reimagining developer productivity and data analytics in the cloud - news from Google IO
Wednesday, June 25, 2014
Today at
Google I/O
, we are introducing new services that help developers build and optimize data pipelines, create mobile applications, and debug, trace, and monitor their cloud applications in production.
Introducing Google Cloud Dataflow
A decade ago, Google invented MapReduce to process massive datasets using distributed computing. Since then, more devices and information require more capable analytics pipelines — though they are difficult to create and maintain.
Today at Google I/O, we are demonstrating Google Cloud Dataflow for the first time. Cloud Dataflow is a fully managed service for creating data pipelines that ingest, transform and analyze data in both batch and streaming modes. Cloud Dataflow is a successor to MapReduce, and is based on our internal technologies like
Flume
and
MillWheel
.
Cloud Dataflow makes it easy for you to get actionable insights from your data while lowering operational costs without the hassles of deploying, maintaining or scaling infrastructure. You can use Cloud Dataflow for use cases like ETL, batch data processing and streaming analytics, and it will automatically optimize, deploy and manage the code and resources required.
Debug, trace and monitor your application in production
We are also introducing several new Cloud Platform tools that let developers understand, diagnose and improve systems in production.
Google Cloud Monitoring is designed to help you find and fix unusual behavior across your application stack. Based on technology from our recent acquisition of Stackdriver, Cloud Monitoring provides rich metrics, dashboards and alerting for Cloud Platform, as well as more than a dozen popular open source apps, including Apache, Nginx, MongoDB, MySQL, Tomcat, IIS, Redis, Elasticsearch and more. For example, you can use Cloud Monitoring to identify and troubleshoot cases where users are experiencing increased error rates connecting from an App Engine module or slow query times from a Cassandra database with minimal configuration.
We know that it can be difficult to isolate the root cause of performance bottlenecks. Cloud Trace helps you visualize and understand time spent by your application for request processing. In addition, you can compare performance between various releases of your application using latency distributions.
Finally, we’re introducing Cloud Debugger, a new tool to help you debug your applications in production with effectively no performance overhead. Cloud Debugger gives you a full stack trace and snapshots of all local variables for any watchpoint that you set in your code while your application continues to run undisturbed in production. This brings modern debugging to cloud-based applications.
New features for mobile development
With rapid autoscaling, caching and other mobile friendly capabilities, many apps like
Snapchat
or
Rising Star
have built and run on Cloud Platform. We’re adding new features that make building a mobile app using Cloud Platform even better.
Today, we’re demonstrating a new version of Google Cloud Save, which gives you a simple API for saving, retrieving, and synchronizing user data to the cloud and across devices without needing to code up the backend. Data is stored in
Google Cloud Datastore
, making the data accessible from
Google App Engine
or
Google Compute Engine
using the existing
Datastore API
. Google Cloud Save is currently in private beta and will be available for general use soon.
We’ve also added tooling to
Android Studio
, which simplifies the process of adding an App Engine backend to your mobile app. In particular, Android Studio now has three built-in App Engine backend module templates, including
Java Servlet
,
Java Endpoints
and an
App Engine backend with Google Cloud Messaging
. Since this functionality is powered by the open-source
App Engine plug-in for Gradle,
you can use the same build configuration for both your app and your backend across IDE, CLI and Continuous Integration environments.
We’ll be doing more detailed follow-up posts about these announcements in the coming days, so stay tuned.
-Posted by Greg DeMichillie, Director of Product Management
*Apache, Nginx, MongoDB, MySQL, Tomcat, IIS, Redis, Elasticsearch and Cassandra are trademarks of their respective owners.
No comments :
Post a Comment
Don't Miss Next '17
Use promo code NEXT1720 to save $300 off general admission
REGISTER NOW
Free Trial
GCP Blogs
Big Data & Machine Learning
Kubernetes
GCP Japan Blog
Labels
Announcements
56
Big Data & Machine Learning
91
Compute
156
Containers & Kubernetes
36
CRE
7
Customers
90
Developer Tools & Insights
80
Events
34
Infrastructure
24
Management Tools
39
Networking
18
Open Source
105
Partners
63
Pricing
24
Security & Identity
23
Solutions
16
Stackdriver
19
Storage & Databases
111
Weekly Roundups
16
Archive
2017
Feb
Jan
2016
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2015
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2014
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2013
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2012
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2011
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2010
Dec
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2009
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2008
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Feed
Subscribe by email
Technical questions? Check us out on
Stack Overflow
.
Subscribe to
our monthly newsletter
.
Google
on
Follow @googlecloud
Follow
Follow
Follow
No comments :
Post a Comment