What’s multi-cloud? And why should developers care?
Data sharing has been tough
It’s just been too difficult for developers to build and deploy across clouds. Data sharing has been almost impossible, which is why most developers haven’t jumped at the opportunity.
If they have chosen to do it, it hasn’t been easy. It’s meant:
The barriers between clouds have always been high. Devs have had to rewrite the majority of their application code for a second cloud, and even then they still had siloed data sets.
It’s true that portability for the application tier is getting easier. Kubernetes, orchestration solutions such as Terraform, and monitoring solutions like Datadog have made multi-cloud more manageable. But even in a world where stateless applications can be consistently managed across clouds, having both the data and operations management keep up has been a beast.
So who’s doing multi-cloud?
Still, business units are plowing ahead. More than half (55%) of organizations use multiple public clouds, with 21% using three or more,according to a recent IDG report.
TakePanoskinas an example.
Panoskin’s software allows users to develop custom VR tours of the world and upload them to Google Street View in minutes. The Chicago-based startup currently has 60+ million scenes in its platform across 100 countries, with ~18,000 photographers uploading 12,000 new tours monthly. The team uses a multi-cloud strategy across Google Cloud and AWS to deliver better scale and tools to its users.
Another example isTicketek. The company is Australia’s leading ticket distributor and can handle up to 300,000 ticket sales in less than 30 minutes. It also has data in various regions across AWS and Google Cloud, as well as a secondary ticketing platform that runs in Google Cloud’s Sydney region.
Advantages of “true” data sharing
Imagine if you could take modern applications like these one step further and deploy a single data layer across AWS and Google Cloud, or Google Cloud and Azure, or across all of the “big three” at the same time. All without the deployment and interoperability hassles.
That would give developers the flexibility to choose the best tools and cloud services for the apps they are building. In other words,use AWS Lambda, Google Cloud’s AI Platform, and Microsoft’s Azure DevOps Services within a unified console. That’s cool, right?
It’s now possible. You can operate seamlessly across clouds — AWS, Azure, and Google Cloud — with the new multi-cloud clusters capability onMongoDB Atlas.
Multi-cloud clusters let developers deploy data and apps across all of the different clouds at the same time, or seamlessly migrate from one cloud to the other without downtime. Here’s why you might want to do that:
Many developer teams are already using single-cloud clusters;multi-cloud clustersare what’s new. A single-cloud cluster enables continuous backups, automated data tiering, and workload isolation. Multi-cloud clusters on MongoDB Atlas do all that, plus data sharing and resiliency across clouds.
The secret ‘data sharing’ weapon
With multi-cloud clusters, there’s a tight organization between the various cloud platforms, so you can use the app-building tools you want and shift workloads as you see fit. And you can do that without adding data management complexity.
Maybe you don’t need to run workloads across multiple public clouds right now — not everyone does. But with multi-cloud clusters, you can rest easier knowing that cross-cloud migration is now a simple option if you need it. It’s only a matter of time before most devs do.
If you’re interested in getting up and running withmulti-cloud clusterson MongoDB Atlas, learn morehere.
Story byAndrew Davidson
Andrew Davidson is the Vice President of Cloud Products at MongoDB.Andrew Davidson is the Vice President of Cloud Products at MongoDB.
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