What are the best services and tools for multicloud?

Multicloud is in. According to Pluralsight's latest State of Cloud report, 65% of organizations currently have a multicloud environment, with 20% actively investigating adding an additional cloud. If you’re considering such a shift, you might be wondering which services and tools will help you make the most of a multicloud infrastructure.

In this article, we provide a breakdown the preeminent multicloud-facing products you should consider.

1. AWS Systems Manager

AWS’ primary tool for managing its own resources, AWS Systems Manager, can also be applied to multicloud environments. Numerous components comprise the four main feature groups: Application Management, Change Management, Node Management, and Operations Management.

he Application Management group investigates and configures resources, then deploys application configurations. It does all this while managing both parameters and secrets.

It’s the Change Management group’s responsibility to safely implement updates and maintenance, while detecting schedule conflicts with important business events and automatically notifying impacted approvers.

The Node Management group allows you to remotely manage your complete compute infrastructure. The duties include checking the status of each server, device, or other resources; identifying any issues; and automatically remediate the problem or connect directly.

With the Operations Management group, you get a single pane of glass for monitoring your on-going applications health and performance. It also includes an incident manager for automatically texting or calling designated responders.

2. Azure Arc

The multicloud tool of choice for Azure is Azure Arc - it's a service specifically designed to apply Azure management to resources outside of Azure. In general, this is accomplished by installing an Arc agent on whatever resource you have, such as an AWS EC2 instance or a Google Cloud Kubernetes Engine cluster.

What benefits does Azure Arc bring to the multicloud table?

First, there’s consistent development and operations. Arc allows you to deploy data services—not just compute services—in their own environment. This centralized management enforces Azure security and governance.

For the multicloud service to be managed, a parallel Arc-enabled service must be running on Azure. As of this writing, there are five categories of Arc-enabled services: Servers, Data Services, Kubernetes, SQL Server, and Machine Learning.

Servers, as you might expect, are at the top of the list. This is compatible with any Linux and Windows virtual machines (VMs) and bare-metal servers allowing the same server management experience across environments. You can also search for servers that don’t comply with your Azure server policies.

Next is the general category of Data Services. This includes Managed SQL Server and PostgreSQL Server which both offer a full set of data management features—including provisioning, scaling, automated updates, high availability, backup, and monitoring.

Kubernetes on Azure is also an Arc-enabled service bringing centralized management to your clusters across the clouds.

And since it is Microsoft Azure, the is an Arc-enabled service for Microsoft SQL Server. Take this option for further customization and control over the Managed SQL Server alternative.

Finally, Azure Arc-enabled Machine Learning makes it possible to run your Azure Workloads on the Kubernetes clusters of your choice, enabling data scientists to distribute the model training across multiple cloud platforms.

3. Google Cloud's Anthos, BigQuery Omni, and Cross-Cloud Interconnect

From a multicloud perspective, Google Cloud presents a balanced offering in terms of both specific services and overall technological philosophy. The company has long been a supporter of - and an active participant in - the open-source community. Google has developed and released into open source some of the most impactful software in the industry including Kubernetes, the container orchestration system; TensorFlow, the machine learning platform; and Istio, the service mesh for microservices.

The first service to highlight is Anthos. Anthos delivers a central platform for managing Kubernetes clusters across the different cloud providers, as well as with hybrid cloud configurations.

Then there’s BigQuery Omni. BigQuery is Google Cloud’s recognized data analytic powerhouse. The Omni version of the service is a multi-cloud data warehouse that permits you to run BigQuery queries on data stored in Amazon S3, Azure Blob Storage, or Google Cloud Storage.

Recently, they introduced Cross-Cloud Interconnect, a companion to Dedicated Interconnect, the service that provides direct physical connections between your on-premises network and Google's network. Cross-Cloud Interconnect, on the other hand, provisions a dedicated physical connection between the Google network and that of another cloud service provider.

With Cross-Cloud Interconnect, you have a direct connection from Google Cloud to AWS, as well as to Azure, plus one to Oracle Cloud and another to Alibaba. But that’s not all. Not only does Cross-Cloud Interconnect bridge Google Cloud to these other cloud providers, but you can also use the service to join any of these other cloud providers to one another - without connecting to Google Cloud. For example, AWS can connect to Azure and Oracle Cloud can either communicate with Alibaba Cloud or with AWS, and services on Azure and Alibaba can be linked.

That’s pretty much the definition of multicloud.

If you want to learn more about the what, why, and how of multicloud environments, check out my Pluralsight course, "Multicloud Foundations." In this course, I explain the benefits and challenges of multicloud environments, as well as dive deeper into the various services available.