Multi-tenant cloud systems have long been a good option for various companies in the cloud space. However, many companies still don’t realize how a multi-tenant architecture can work to their benefit. Some companies have adopted a complex multi-tenant cloud system while unaware of the challenges this setup presents.

But what does multi-tenant mean in cloud environments, exactly? Here’s a brief guide explaining what multi-tenant cloud systems are, their benefits and challenges, and how Pepperdata can help.

What is Multi-Tenant Cloud?

Techtarget defines multi-tenant cloud as “a cloud computing architecture that allows customers to share computing resources in a public or private cloud.”

A multi-tenant cloud setup enables cloud services providers to make a greater pool of computing resources available to a bigger user group without compromising privacy and security or slowing down applications. Storage locations in the cloud are virtualized, which allows for flexibility and easy access by users from any location or device.

Multi-tenant cloud

What Does Multi-Tenant Mean in a Cloud Infrastructure Setting?

A simple analogy of this is an apartment building. Each individual owner has access to the unit they own, and only that unit. The owner of the building and other key personnel (housekeeper, electrician, etc.) can have access to all of the units. However, everyone in the same building still shares resources, like water and electricity.

A multi-tenant cloud architecture follows that apartment logic. It allows users individualized spaces to store their projects and data. In a cloud network, multi-tenant cloud systems include complex permissions that allow users access only to their data while keeping it secure from other tenants. Only through enabling certain cloud provider permissions can tenants access the data of others.

What is the Advantage of Using Multi-Tenant Cloud Services?

Many of the benefits of cloud computing are only possible because of multi-tenancy. Here are several crucial ways multi-tenancy improves cloud computing:

  • Better use of resources: One machine reserved for one tenant isn’t efficient, as that one tenant is not likely to use all of the machine’s computing power. By sharing machines among multiple tenants, the use of available resources is maximized.
    Lower costs: With multiple customers sharing resources, a cloud vendor can offer their services to many customers at a much lower cost than if each customer required their own dedicated infrastructure.
  • Easy Scaling and Maintenance. Fast and easy scalability in cloud computing is a notable benefit of multi-tenancy. Since new users can access the same resources and services as the original buyers, scaling doesn’t present problems. In addition, costs relating to maintenance and upgrades are usually included in the SaaS subscription fee, eliminating any surprise charges as well as the need for costly on-site technicians and updates.
  • Optimal Efficiency. Every user in the infrastructure receives the same level of service. This is because multi-tenant SaaS solutions utilize resources effectively and balance computing loads to achieve optimum efficiency and deliver greater flexibility to users.
  • Effortless Onboarding. Multi-tenant SaaS packages are designed to play right out of the box. These are made for immediate set-up and self-service configuration, making the entire onboarding process intuitive and user friendly. Most plans are easily configurable and integrations-ready, requiring little to none from the SaaS vendor.

Multi-tenant cloud networks give users bigger storage and enhanced access to resources as opposed to the limited access and security parameters single-tenancy clouds can deliver.

Moreover, multi-tenant cloud users can also enjoy a system they can scale on demand. Not having to manage software or infrastructure is an added bonus as well. This means tenants have more opportunities to focus on other important tasks.

What are the Drawbacks of Multi-Tenancy?

As with any system, multi-tenancy does have its own disadvantages, ranging from security flaws, poor performance, as well as business-IT misalignment in the cloud.

Possible Security Risks and Compliance Issues

Some companies may not be able to store data within shared infrastructure, no matter how secure, due to regulatory requirements. Additionally, security problems or corrupted data from one tenant could spread to other tenants on the same machine.

The “Bad Tenant” Effect

One tenant using an inordinate amount of computing power can cause scalability complications and other issues, resulting in slow performance for the other tenants. This could mean that at least one tenant is getting the “temporarily restricted” warning. Moreover, other instances of the bad tenant effect can include storage requirement issues in modern cloud hosting in addition to hypervisor and processor behavior that results in operations taking more time to complete.

How can Pepperdata Help in a Multi-Tenant Environment?

The bad tenant effect can be avoided if the cloud provider client knows precisely what workloads are being impacted and how. Case in point: Pepperdata Platform Spotlight helps with the quick diagnosis of performance issues and allows you to make resource decisions that eliminate this effect. A cluster performance monitoring solution that includes real-time and historical information about your clusters—like system demand, abusive users, and wasteful applications—will help you drill down into your system and big data applications. Thus, ensuring fair resource allocation and management among the tenants.

Cost savings is one of the most highlighted advantages of multi-tenant cloud computing. However, when left to run unoptimized, users are still at risk of experiencing performance issues. Resources are not properly utilized and allocated, which then leads to a significant, uncontrolled spike in costs.

Pepperdata Capacity Optimizer helps these multi-tenant users derive more value from their multi-tenant subscriptions by recapturing wasted capacity resources while improving autoscaling configurations. Utilizing machine learning (ML), Capacity Optimizer analyzes and automatically optimizes CPU, memory, and I/O resource usage—eliminating waste and increasing capacity. This enables the user to run more applications without consuming more resources.

Lower costs don’t always mean the best performance. But with Pepperdata, users enjoy superior visibility into their multi-tenant cloud environments, optimize their processes and resources using data-driven configurations, achieve better performance, and enjoy significant cost savings.

Find out more about our big data performance management solutions here. Or check out our other performance-related materials:

Pepperdata 2020 Big Data Performance Report 
Cloud Performance for Big Data Workloads
Advantages of Real-Time Performance Data
Integrated Performance into DevOps for Big Data 

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