Welcome!

@CloudExpo Authors: Yeshim Deniz, Elizabeth White, Liz McMillan, Zakia Bouachraoui, Pat Romanski

Related Topics: Release Management , Agile Computing

Release Management : Article

Gmail Inches Toward Offline Support

Google calls the feature “early experimental”

Eighteen months or so after Google Gears debuted, a period of time scarred by several major Gmail outages, Google’s cloud-accessible-only e-mail is finally getting invested with offline support.

English-speaking US and UK Gmail users who want to test the new skill can now catch up with the rest of the world.

Google calls the feature “early experimental,” but then Gmail is still in beta two years after its general release.

Although Google has been using the widgetry internally “for quite a while,” it warns that there still may be “some kinks that haven’t been completely ironed out yet.” It’s looking for feedback.

Once the feature is turned on, Gmail uses Gears to download a local cache of the user’s mail. As long as a connection to the network is maintained, that cache is synchronized with Gmail’s servers. When Internet connection is lost, Gmail automatically switches to offline mode and uses the data stored on the user’s hard drive instead of sending the messages across the network.

Any messages a user sends while offline go to his outbox and get sent when Gmail detects a connection. There’s a “flaky connection mode” for when the user’s on an unreliable or slow connection. Google says it uses the local cache as if you were disconnected, but still synchronizes your mail with the server in the background. It’s striving for the same user experience on- and offline.

More Stories By Maureen O'Gara

Maureen O'Gara the most read technology reporter for the past 20 years, is the Cloud Computing and Virtualization News Desk editor of SYS-CON Media. She is the publisher of famous "Billygrams" and the editor-in-chief of "Client/Server News" for more than a decade. One of the most respected technology reporters in the business, Maureen can be reached by email at maureen(at)sys-con.com or paperboy(at)g2news.com, and by phone at 516 759-7025. Twitter: @MaureenOGara

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


CloudEXPO Stories
Even if your IT and support staff are well versed in agility and cloud technologies, it can be an uphill battle to establish a DevOps style culture - one where continuous improvement of both products and service delivery is expected and respected and all departments work together throughout a client or service engagement. As a service-oriented provider of cloud and data center technology, Green House Data sought to create more of a culture of innovation and continuous improvement, from our helpdesk on to our product development and cloud service teams. Learn how the Chief Executive team helped guide managers and staff towards this goal with metrics to measure progress, staff hiring or realignment, and new technologies and certifications.
Technology has changed tremendously in the last 20 years. From onion architectures to APIs to microservices to cloud and containers, the technology artifacts shipped by teams has changed. And that's not all - roles have changed too. Functional silos have been replaced by cross-functional teams, the skill sets people need to have has been redefined and the tools and approaches for how software is developed and delivered has transformed. When we move from highly defined rigid roles and systems to more fluid ones, we gain agility at the cost of control. But where do we want to keep control? How do we take advantage of all these new changes without losing the ability to efficiently develop and ship great software? And how should program and project managers adapt?
When Enterprises started adopting Hadoop-based Big Data environments over the last ten years, they were mainly on-premise deployments. Organizations would spin up and manage large Hadoop clusters, where they would funnel exabytes or petabytes of unstructured data.However, over the last few years the economics of maintaining this enormous infrastructure compared with the elastic scalability of viable cloud options has changed this equation. The growth of cloud storage, cloud-managed big data environments, and cloud data warehouses like Snowflake, Redshift, BigQuery and Azure SQL DW, have given the cloud its own gravity - pulling data from existing environments. In this presentation we will discuss this transition, describe the challenges and solutions for creating the data flows necessary to move to cloud analytics, and provide real-world use-cases and benefits obtained through adop...
Docker and Kubernetes are key elements of modern cloud native deployment automations. After building your microservices, common practice is to create docker images and create YAML files to automate the deployment with Docker and Kubernetes. Writing these YAMLs, Dockerfile descriptors are really painful and error prone.Ballerina is a new cloud-native programing language which understands the architecture around it - the compiler is environment aware of microservices directly deployable into infrastructures like Docker and Kubernetes.
Your applications have evolved, your computing needs are changing, and your servers have become more and more dense. But your data center hasn't changed so you can't get the benefits of cheaper, better, smaller, faster... until now. Colovore is Silicon Valley's premier provider of high-density colocation solutions that are a perfect fit for companies operating modern, high-performance hardware. No other Bay Area colo provider can match our density, operating efficiency, and ease of scalability.