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Keys to Building a Partner Ecosystem That Scales

Barb Huelskamp
SolarWinds

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.

The reality is that vendor offerings don't address modern complexity on their own, and enablement resources that don't map to real selling situations aren't resources at all. In a landscape that is evolving faster than most organizations can keep up with, surface-level channel programs will always fall short.

What the channel actually needs and what customers ultimately depend on is a partner ecosystem built to scale alongside that complexity. One that gives partners predictable frameworks, genuine specialization, and the kind of support that makes them more capable, not just more certified. Because when we get that right, partners don't just sell better. They deliver better outcomes for the customers who need them most.

Complexity Is Now the Persistent Reality

Current IT environments are completely different than they were just five years ago. Many IT teams must now manage hybrid architectures, multi-cloud developments, and edge infrastructure all at the same time. When you layer in a growing number of workloads that include AI, complexity becomes the baseline for modern IT architecture.

Ideally, partners should be absorbing this complexity for their clients. They should be helping them make sense of this new normal of distributed, hybrid environments, while limiting the noise that comes from monitoring, observability, and security platforms. But if partners are going to succeed, vendors need to look at things from a partner-first perspective and ask whether their program is removing complexity, or just adding to it.

Providing a Clear View of the Program

Providing enterprises with a single pane of glass has become a best practice for observability platforms, and modern partner programs can learn a lot from this. Partners need a clear view of where they stand: their tier, what they're earning, and where their growth opportunities are. Without that transparency, you get blind spots that slow deal-making and, ultimately, hurt customers.

Historically, this is an area where we, like many vendors, haven't always gotten it right. But it's something we're actively building toward. Our recent updates around structured, tier-based discounting are a step in that direction, giving partners a more consistent pricing framework they can count on when forecasting margins and co-selling, and we're expanding certifications and specialization tracks so partners have a concrete path to becoming genuine subject matter experts. 

We're working to make the everyday partner experience more seamless and role-based, and our goal is clear: partners should never have to guess how they can help customers achieve the outcomes they're looking for.

Enablement That Aligns with Partner Workflow

The best enablement programs provide more than deep learning opportunities because they match actual partner habits and workflows. Enablement is only as good as a partner's ability to access and leverage it in real time.

Flexibility and supporting different learning styles should always be top of mind. Instead of providing a certification and calling it a day, look at partners as an extension of the organization. When rolling out a new internal battle card, build a version for our partners online. In our case, we have introduced monthly webinars and newsletters to touch partners in different ways every month, as a means of giving them a differentiated story to take to market.

What I love about this approach is surrounding partners with whatever resources they need, whether that means looping in our sales, engineering, product, or marketing teams. When enablement is a true priority, it allows partners to build an expertise that sits right at the intersection of their customers' problems and the technical solutions needed to solve them.

Keeping the Customer at the Center

The North Star of any partner program must be customer success. We cannot run parallel paths or treat the partner like a barrier between us and the end user. It’s essential to get on a call with the partner and the customer together to deliver the right outcome.

When partners have clearer incentives, less friction, and attainable enablement opportunities, they can integrate technologies and deliver real customer outcomes. That is how you create a framework where every single part of the ecosystem wins together.

Barb Huelskamp is VP of Global Channel and Alliances at SolarWinds

Hot Topics

The Latest

For fifteen years, observability lived downstream of everything else. Code shipped, something broke, an engineer went to the dashboards. The job was forensic. The pillars we built, such as logs, metrics, and traces, were designed for that role: tell a human what just happened, fast enough that they can make it stop. That role has quietly ended ...

Hybrid IT has become the standard operating model for enterprises — but that companies are still looking for the right hybrid IT mix, according to the 2026 State of the Data Center Report from CoreSite. After years of cloud migration and hybrid adoption, organizations are shifting their focus from deciding whether to use cloud, colocation or on-premises infrastructure to determining which workloads belong in each environment ...

Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...

The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...

For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

The AI experimentation phase is over, and the private cloud is where enterprise AI workloads are being deployed for security and scale, according to Private Cloud Outlook 2026, a new report from Broadcom ... 2026 marks an acceleration into a full AI tipping point. The shift is being shaped by three forces — costs, complexity, and control — that public cloud environments are increasingly failing to address for production AI at scale. Key findings from the report include ...

44% of organizations have reported an outage in the past year tied to suppressed or ignored alerts, and 78% had at least one incident where no alert was fired at all ... Engineers learned about failures from customers. That gap between what our tools report and what our customers experience is the problem DevOps teams have been quietly solving with GenAI tooling, even as most enterprises continue to run their NOCs on manual alert triage ...

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

Keys to Building a Partner Ecosystem That Scales

Barb Huelskamp
SolarWinds

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.

The reality is that vendor offerings don't address modern complexity on their own, and enablement resources that don't map to real selling situations aren't resources at all. In a landscape that is evolving faster than most organizations can keep up with, surface-level channel programs will always fall short.

What the channel actually needs and what customers ultimately depend on is a partner ecosystem built to scale alongside that complexity. One that gives partners predictable frameworks, genuine specialization, and the kind of support that makes them more capable, not just more certified. Because when we get that right, partners don't just sell better. They deliver better outcomes for the customers who need them most.

Complexity Is Now the Persistent Reality

Current IT environments are completely different than they were just five years ago. Many IT teams must now manage hybrid architectures, multi-cloud developments, and edge infrastructure all at the same time. When you layer in a growing number of workloads that include AI, complexity becomes the baseline for modern IT architecture.

Ideally, partners should be absorbing this complexity for their clients. They should be helping them make sense of this new normal of distributed, hybrid environments, while limiting the noise that comes from monitoring, observability, and security platforms. But if partners are going to succeed, vendors need to look at things from a partner-first perspective and ask whether their program is removing complexity, or just adding to it.

Providing a Clear View of the Program

Providing enterprises with a single pane of glass has become a best practice for observability platforms, and modern partner programs can learn a lot from this. Partners need a clear view of where they stand: their tier, what they're earning, and where their growth opportunities are. Without that transparency, you get blind spots that slow deal-making and, ultimately, hurt customers.

Historically, this is an area where we, like many vendors, haven't always gotten it right. But it's something we're actively building toward. Our recent updates around structured, tier-based discounting are a step in that direction, giving partners a more consistent pricing framework they can count on when forecasting margins and co-selling, and we're expanding certifications and specialization tracks so partners have a concrete path to becoming genuine subject matter experts. 

We're working to make the everyday partner experience more seamless and role-based, and our goal is clear: partners should never have to guess how they can help customers achieve the outcomes they're looking for.

Enablement That Aligns with Partner Workflow

The best enablement programs provide more than deep learning opportunities because they match actual partner habits and workflows. Enablement is only as good as a partner's ability to access and leverage it in real time.

Flexibility and supporting different learning styles should always be top of mind. Instead of providing a certification and calling it a day, look at partners as an extension of the organization. When rolling out a new internal battle card, build a version for our partners online. In our case, we have introduced monthly webinars and newsletters to touch partners in different ways every month, as a means of giving them a differentiated story to take to market.

What I love about this approach is surrounding partners with whatever resources they need, whether that means looping in our sales, engineering, product, or marketing teams. When enablement is a true priority, it allows partners to build an expertise that sits right at the intersection of their customers' problems and the technical solutions needed to solve them.

Keeping the Customer at the Center

The North Star of any partner program must be customer success. We cannot run parallel paths or treat the partner like a barrier between us and the end user. It’s essential to get on a call with the partner and the customer together to deliver the right outcome.

When partners have clearer incentives, less friction, and attainable enablement opportunities, they can integrate technologies and deliver real customer outcomes. That is how you create a framework where every single part of the ecosystem wins together.

Barb Huelskamp is VP of Global Channel and Alliances at SolarWinds

Hot Topics

The Latest

For fifteen years, observability lived downstream of everything else. Code shipped, something broke, an engineer went to the dashboards. The job was forensic. The pillars we built, such as logs, metrics, and traces, were designed for that role: tell a human what just happened, fast enough that they can make it stop. That role has quietly ended ...

Hybrid IT has become the standard operating model for enterprises — but that companies are still looking for the right hybrid IT mix, according to the 2026 State of the Data Center Report from CoreSite. After years of cloud migration and hybrid adoption, organizations are shifting their focus from deciding whether to use cloud, colocation or on-premises infrastructure to determining which workloads belong in each environment ...

Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...

The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...

For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

The AI experimentation phase is over, and the private cloud is where enterprise AI workloads are being deployed for security and scale, according to Private Cloud Outlook 2026, a new report from Broadcom ... 2026 marks an acceleration into a full AI tipping point. The shift is being shaped by three forces — costs, complexity, and control — that public cloud environments are increasingly failing to address for production AI at scale. Key findings from the report include ...

44% of organizations have reported an outage in the past year tied to suppressed or ignored alerts, and 78% had at least one incident where no alert was fired at all ... Engineers learned about failures from customers. That gap between what our tools report and what our customers experience is the problem DevOps teams have been quietly solving with GenAI tooling, even as most enterprises continue to run their NOCs on manual alert triage ...

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...