Archives

google cloud

Google makes it easier to migrate VMware environments to its cloud

Google Cloud today announced the next step in its partnership with VMware: the Google Cloud VMware Engine. This fully managed service provides businesses with a full VMware Cloud Foundation stack on Google Cloud to help businesses easily migrate their existing VMware-based environments to Google’s infrastructure. Cloud Foundation is VMware’s stack for hybrid and private cloud deployments

Given Google Cloud’s focus on enterprise customers, it’s no surprise that the company continues to bet on partnerships with the likes of VMware to attract more of these companies’ workloads. Less than a year ago, Google announced that VMware Cloud Foundation would come to Google Cloud and that it would start supporting VMware workloads. Then, last November, Google Cloud acquired CloudSimple, a company that specialized in running VMware environments and that Google had already partnered with for its original VMware deployments. The company describes today’s announcement as the third step in this journey.

VMware Engine provides users with all of the standard Cloud Foundation components: vSphere, vCenter, vSAN, NSX-T and HCX. With this, Google Cloud General Manager June Yang notes in today’s announcement, businesses can quickly stand up their own software-defined data center in the Google Cloud.

“Google Cloud VMware Engine is designed to minimize your operational burden, so you can focus on your business,” she notes. “We take care of the lifecycle of the VMware software stack and manage all related infrastructure and upgrades. Customers can continue to leverage IT management tools and third-party services consistent with their on-premises environment.”

Google is also working with third-party providers like NetApp, Veeam, Zerto, Cohesity and Dell Technologies to ensure that their solutions work on Google’s platform, too.

“As customers look to simplify their cloud migration journey, we’re committed to build cloud services to help customers benefit from the increased agility and efficiency of running VMware workloads on Google Cloud,” said Bob Black, Dell Technologies Global Lead Alliance Principal at Deloitte Consulting. “By combining Google Cloud’s technology and Deloitte’s business transformation experience, we can enable our joint customers to accelerate their cloud migration, unify operations, and benefit from innovative Google Cloud services as they look to modernize applications.””

Microsoft partners with Redis Labs to improve its Azure Cache for Redis

For a few years now, Microsoft has offered Azure Cache for Redis, a fully managed caching solution built on top of the open-source Redis project. Today, it is expanding this service by adding Redis Enterprise, Redis Lab’s commercial offering, to its platform. It’s doing so in partnership with Redis Labs and while Microsoft will offer some basic support for the service, Redis Labs will handle most of the software support itself.

Julia Liuson, Microsoft’s corporate VP of its developer tools division, told me that the company wants to be seen as a partner to open-source companies like Redis Labs, which was among the first companies to change its license to prevent cloud vendors from commercializing and repackaging their free code without contributing back to the community. Last year, Redis Labs partnered with Google Cloud to bring its own fully managed service to its platform and so maybe it’s no surprise that we are now seeing Microsoft make a similar move.

Liuson tells me that with this new tier for Azure Cache for Redis, users will get a single bill and native Azure management, as well as the option to deploy natively on SSD flash storage. The native Azure integration should also make it easier for developers on Azure to integrate Redis Enterprise into their applications.

It’s also worth noting that Microsoft will support Redis Labs’ own Redis modules, including RediSearch, a Redis-powered search engine, as well as RedisBloom and RedisTimeSeries, which provide support for new datatypes in Redis.

“For years, developers have utilized the speed and throughput of Redis to produce unbeatable responsiveness and scale in their applications,” says Liuson. “We’ve seen tremendous adoption of Azure Cache for Redis, our managed solution built on open source Redis, as Azure customers have leveraged Redis performance as a distributed cache, session store, and message broker. The incorporation of the Redis Labs Redis Enterprise technology extends the range of use cases in which developers can utilize Redis, while providing enhanced operational resiliency and security.”

Google Cloud’s fully-managed Anthos is now generally available for AWS

A year ago, back in the days of in-person conferences, Google officially announced the launch of its Anthos multi-cloud application modernization platform at its Cloud Next conference. The promise of Anthos was always that it would allow enterprises to write their applications once, package them into containers and then manage their multi-cloud deployments across GCP, AWS, Azure and their on-prem data centers.

Until now, support for AWS and Azure was only available in preview, but today, the company is making support for AWS and on-premises generally available. Microsoft Azure support remains in preview, though.

“As an AWS customer now, or a GCP customer, or a multi-cloud customer, […] you can now run Anthos on those environments in a consistent way, so you don’t have to learn any proprietary APIs and be locked in,” Eyal Manor, the VP of engineering in charge of Anthos, told me. “And for the first time, we enable the portability between different infrastructure environments as opposed to what has happened in the past where you were locked into a set of API’s.”

Manor stressed that Anthos was designed to be multi-cloud from day one. As for why AWS support is launching ahead of Azure, Manor said that there was simply more demand for it. “We surveyed the customers and they said, hey, we want, in addition to GCP, we want AWS,” he said. But support for Azure will come later this year and the company already has a number of preview customers for it. In addition, Anthos will also come to bare metal servers in the future.

Looking even further ahead, Manor also noted that better support for machine learning workloads in on the way. Many businesses, after all, want to be able to update and run their models right where their data resides, no matter what cloud that may be. There, too, the promise of Anthos is that developers can write the application once and then run it anywhere.

“I think a lot of the initial response and excitement was from the developer audiences,” Jennifer Lin, Google Cloud’s VP of product management, told me. “Eric Brewer had led a white paper that we did to say that a lot of the Anthos architecture sort of decouples the developer and the operator stakeholder concerns. There hadn’t been a multi-cloud shared software architecture where we could do that and still drive emerging and existing applications with a common shared software stack.”

She also noted that a lot of Google Cloud’s ecosystem partners endorsed the overall Anthos architecture early on because they, too, wanted to be able to write once and run anywhere — and so do their customers.

Plaid is one of the launch partners for these new capabilities. “Our customers rely on us to be always available and as a result we have very high reliability requirements,” said Naohiko Takemura, Plaid’s head of engineering. “We pursued a multi-cloud strategy to ensure redundancy for our critical KARTE service. Google Cloud’s Anthos works seamlessly across GCP and our other cloud providers preventing any business disruption. Thanks to Anthos, we prevent vendor lock-in, avoid managing cloud-specific infrastructure, and our developers are not constrained by cloud providers.”

With this release, Google Cloud is also bringing deeper support for virtual machines to Anthos, as well as improved policy and configuration management.

Over the next few months, the Anthos Service Mesh will also add support for applications that run in traditional virtual machines. As Lin told me, “a lot of this is is about driving better agility and talking the complexity out of it so that we have abstractions that work across any environment, whether it’s legacy or new or on-prem or AWS or GCP.”