Hybridity at the Edge: Introducing the AWS Greengrass on vSphere Preview

At VMworld 2017, we introduced the concept of serverless functions and functions as a service (FaaS) running on VMware vSphere®, noting that our strategy wasn’t just about FaaS, but most importantly focused on enabling organizations to run any application or service – including cloud services – anywhere. Today marks the first major step in that journey, and we are pleased to announce the AWS Greengrass on vSphere preview. Earlier this year, we announced VMware Cloud™ on AWS, which allows you to run VMware workloads in AWS data centers. AWS Greengrass on VMware vSphere takes hybridity in the other direction, allowing select AWS services to run on vSphere in the data center or at the edge. Business requirements – not artificial constraints – should determine where workloads execute, and it’s important for organizations to have a choice of running workloads in public clouds, private data centers, and at the edge. The majority of our customers have use cases that include cloud, data center, and edge scenarios, and it’s important for VMware to provide choice and consistency everywhere applications and services run.

Emerging Use Cases

The Internet of Things (IoT) has fueled a massive wave of emerging edge use cases. When it comes to mining intelligence from IoT sensor data, it is often more practical to move the compute capacity or cloud service nearer to where data is being created rather than moving the data itself. More specifically, the following requirements are driving the need for a rich set of intelligent services that execute at the edge:

  • Transaction execution time: Data and application services need to be near IoT sensors, consumers, data, and devices. For example, if a traditional cloud service takes 1 second or longer to complete a transaction (due to data, network, or latency constraints, for example), a given use case may require colocation of that service at the edge in order to reduce the overall transaction time to meet a particular SLA. That is especially true for common IoT use cases such as real-time analytics (e.g., smart surveillance) or factory automation. Emerging applications such as those that provide augmented reality also require that application components and intelligence be very near the consumption device in order to provide a rich user experience.
  • Data locale: Data sovereignty and data volume make it impossible to move many data sets to cloud services. It’s far more efficient to move the services to where the data physically resides, or to do some amount of local aggregation and consolidation prior to sending data to a public cloud.
  • Lower networking costs: Localized data processing and cloud service execution can significantly lower cloud networking costs.
  • Privacy: Many organizations want to take advantage of new services such as FaaS or serverless computing, but also require isolation and a full audit trail.
  • Always On: While many control and orchestration functions for edge devices can be managed from the public cloud, many real-time automation use cases require the required automation and intelligence to be adjacent to the data source.

AWS Greengrass Extends the AWS Cloud to the Edge

AWS Greengrass allows enterprises to run local cloud compute, messaging, data caching, sync capabilities, and AWS Lambda functions at the edge. With AWS Greengrass, connected devices can run AWS Lambda functions, keep device data in sync, and communicate with other devices securely – even when not connected to the Internet. Using AWS Lambda, Greengrass enables IoT devices to respond quickly to local events, operate with intermittent connections, and minimize the cost of transmitting IoT data to the cloud. AWS Greengrass seamlessly extends AWS to devices so they can act locally on the data they generate, while still using the cloud for management, analytics, and durable storage.

By running Greengrass on-premises on vSphere, organizations will be able to closely integrate Greengrass, using Lambda functions, with other applications and services already running on vSphere infrastructure at the edge. Placing cloud services in the same locations where devices reside and data is generated will give organizations even greater capabilities to innovate and build intelligent systems that surpass what’s possible in the cloud, data center, or edge alone. AWS Greengrass 1.3 can share common local resources with other VMs (such as a GPU or serial bus), and organizations are able to manage the Greengrass VM Appliance using familiar tools and platforms such as vCenter, VMware vRealize Operations, VMware vRealize Automation, and VMware NSX.

VMware’s Commitment to IoT and Edge Innovation

VMware is committed to delivering compelling IoT innovations for both information technology (IT) and operational technology (OT) users. We announced earlier this year, VMware Pulse, a new family of IoT solutions. The first solution – VMware Pulse IoT Center (beta) – offers comprehensive management, monitoring and security for IoT gateways and connected sensors. In addition, VMware infrastructure solutions at the edge (e.g., vSphere, vSAN and NSX managed by vRealize Suite) have long powered analytics and intelligence in factories, hospitals, oil rigs, and anywhere data is generated. In this new phase of our strategy, we are enabling organizations to deploy AWS Greengrass in order to run a select number AWS public cloud services (e.g., AWS Greengrass Lambda) at the edge on VMware infrastructure. The combined offerings will empower organizations to take IoT initiatives to new levels, with real-time automation driven by analytics at the edge, and backed by centralized infrastructure management and globally consistent infrastructure-as-code from VMware SDDCs. Our customers require heterogeneous solutions at the edge, and we are committed to making it simple for organizations to innovate across cloud services, open source projects, and traditional and cloud-native applications from a variety of vendors and service provider partners.

Here We Go!

The AWS Greengrass vSphere appliance will be packaged as an OVA, providing for easy import into VMware environments using vCenter. We will be publishing a download link in the very near future. If you would like early access to the VM appliance, please contact your local VMware account team.

The video below shows the overall import and deployment sequence, highlighting how simple it is to deploy and start AWS Greengrass Core on VMware vSphere.

The video shows the deployment as follows:

  1. The AWS Greengrass Core OVA file is imported to vCenter using the govc CLI.
  2. The new AWS Greengrass Core VM that was imported from the OVA file is now visible in the vSphere web client.
  3. The VM is started, which boots the Ubuntu 16.4.03 LTS guest OS.
  4. The admin logs in, applies the Greengrass core certificates/configuration, and starts up the core.
  5. Using the AWS console, the Greengrass group is deployed out to the new core.
  6. Utilizing the new features of Greengrass 1.3 (local device and volume access), a USB webcam is used to show local device support mapped in from the hypervisor through to the lambda function.
  7. A local MQTT capture event is sent to the Lambda to take the screen shot, and then stored into a locally mapped directory along with a resized image.

On Wednesday at AWS re:Invent, we will show the deployment process as well as VMs running AWS Greengrass Core interacting with physical devices locally connected to a VMware ESXi host. In addition, we will also show AWS Greengrass Lambda functions interacting with local storage in VMware VMs while fully disconnected from the public cloud. Beyond re:Invent, you will see additional posts from us in the coming weeks highlighting more use cases and including code samples. We have seen a tremendous amount of excitement from a variety of customers and we firmly believe that once you get AWS Greengrass Core on VMware vSphere out to your edge sites, you will be able to take IoT innovation and velocity to a whole new level.

Think about where we are going. We are reaching a time when the business requirements will be able to dictate a particular service’s physical location. We are expanding the boundaries of cloud data centers to anywhere data is created or consumed. Going forward, you will continue to see a variety of examples and use cases of AWS and other cloud services, along with open source FaaS, platform-as-a-service (PaaS), and container-as-a-service (CaaS) solutions interacting with applications on VMware infrastructure at the edge. If you have ideas or suggestions for AWS Greengrass or FaaS on vSphere, please reach out to us on Twitter (@cswolf and @markpeek).

For even more information on our IoT innovations, take a look at the VMware Internet of Things Solutions page.