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Multi-Tenancy in an APM Context

Ivar Sagemo

No topic in IT today is hotter than cloud computing. And I find it interesting how the rapid adoption of cloud platforms has led to a reinvention of how many IT applications and services work at a fairly deep level — certainly including those in my own area of APM.

Multi-tenancy, for instance, is a concept that has really come into vogue with the advent of public cloud platforms. A public cloud is by definition a shared architecture. This means an indefinite number of users (tenants) may be utilizing it at any given time. For all of those customers, the cloud provider wants to offer key services such as authentication, resource tracking, information management, policy creation, etc. It's only a question of what the most efficient way to accomplish this might be.

The most obvious idea would be to create a new instance of each service for each client. In this scenario, if the cloud has a thousand current clients, it also has a thousand iterations of a given service running simultaneously. Such an approach would be technically viable, but operationally wasteful — enormously complex, and therefore relatively slow and awkward to manage.

Multi-tenancy takes a different approach altogether. Instead of deploying new instances on a one-to-one basis with customers, the cloud host only needs to deploy one instance of a core application in total. That one instance, thanks to its sophisticated design, can then scale to support as many cloud customers as are necessary, logically sandboxing their data so as to keep them all completely separate from each other (even though the cloud architecture is in fact shared).

From the perspective of the cloud host, this approach is substantially superior. It is operationally much simpler to install, integrate, and manage one instance instead of many. And from the perspective of the cloud customer, the benefits are just as impressive. A customer who is interested in APM (Application Performance Management) capabilities, for example, can get them without ever having to worry about buying, deploying, or managing an actual APM solution. All that's required is contracting with a cloud provider who offers them.

Imagine an organization that manages a fleet of cruise ships. Each ship offers its own logical services, based on its own information; for each ship, separate APM considerations apply. Such an organization might solve that problem by purchasing, rolling out, and continually managing an APM solution in-house, but after all, IT infrastructure and IT service management isn't this organization's core strength; cruise ship management is. After all, APM on a moving target is tricky.

Now imagine that this organization discovers APM capabilities can be obtained from a trusted cloud provider, and that those capabilities will scale naturally to any number of ships. This may well prove the more attractive option of the two.

Setup time per server: roughly five minutes to install an agent. And because the cloud provider bills on a utility basis, the organization will only be charged in proportion to actual service usage. All the benefits of modern APM are thus achieved, yet the costs and complexity involved are relatively low.

Naturally, this does put a bit more burden on the APM solution developer! Re-coding an application to support multi-tenancy in cloud architecture is not a trivial feat of software engineering.

But for developers willing to put in the time, the benefits generated in the marketplace are clearly worth the effort:

• A broader range of service/software models, including both traditional and SaaS models, from which customers can easily choose to meet their needs

• A more direct focus on the core mission and less worry about IT infrastructure and overhead

• And for cloud hosts, simplified management, reduced costs and complexity, and a faster response to changing business conditions

For developer and organizations alike it’s a WIN-WIN situation.

Ivar Sagemo is CEO of AIMS Innovation.

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Multi-Tenancy in an APM Context

Ivar Sagemo

No topic in IT today is hotter than cloud computing. And I find it interesting how the rapid adoption of cloud platforms has led to a reinvention of how many IT applications and services work at a fairly deep level — certainly including those in my own area of APM.

Multi-tenancy, for instance, is a concept that has really come into vogue with the advent of public cloud platforms. A public cloud is by definition a shared architecture. This means an indefinite number of users (tenants) may be utilizing it at any given time. For all of those customers, the cloud provider wants to offer key services such as authentication, resource tracking, information management, policy creation, etc. It's only a question of what the most efficient way to accomplish this might be.

The most obvious idea would be to create a new instance of each service for each client. In this scenario, if the cloud has a thousand current clients, it also has a thousand iterations of a given service running simultaneously. Such an approach would be technically viable, but operationally wasteful — enormously complex, and therefore relatively slow and awkward to manage.

Multi-tenancy takes a different approach altogether. Instead of deploying new instances on a one-to-one basis with customers, the cloud host only needs to deploy one instance of a core application in total. That one instance, thanks to its sophisticated design, can then scale to support as many cloud customers as are necessary, logically sandboxing their data so as to keep them all completely separate from each other (even though the cloud architecture is in fact shared).

From the perspective of the cloud host, this approach is substantially superior. It is operationally much simpler to install, integrate, and manage one instance instead of many. And from the perspective of the cloud customer, the benefits are just as impressive. A customer who is interested in APM (Application Performance Management) capabilities, for example, can get them without ever having to worry about buying, deploying, or managing an actual APM solution. All that's required is contracting with a cloud provider who offers them.

Imagine an organization that manages a fleet of cruise ships. Each ship offers its own logical services, based on its own information; for each ship, separate APM considerations apply. Such an organization might solve that problem by purchasing, rolling out, and continually managing an APM solution in-house, but after all, IT infrastructure and IT service management isn't this organization's core strength; cruise ship management is. After all, APM on a moving target is tricky.

Now imagine that this organization discovers APM capabilities can be obtained from a trusted cloud provider, and that those capabilities will scale naturally to any number of ships. This may well prove the more attractive option of the two.

Setup time per server: roughly five minutes to install an agent. And because the cloud provider bills on a utility basis, the organization will only be charged in proportion to actual service usage. All the benefits of modern APM are thus achieved, yet the costs and complexity involved are relatively low.

Naturally, this does put a bit more burden on the APM solution developer! Re-coding an application to support multi-tenancy in cloud architecture is not a trivial feat of software engineering.

But for developers willing to put in the time, the benefits generated in the marketplace are clearly worth the effort:

• A broader range of service/software models, including both traditional and SaaS models, from which customers can easily choose to meet their needs

• A more direct focus on the core mission and less worry about IT infrastructure and overhead

• And for cloud hosts, simplified management, reduced costs and complexity, and a faster response to changing business conditions

For developer and organizations alike it’s a WIN-WIN situation.

Ivar Sagemo is CEO of AIMS Innovation.

Hot Topics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...