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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

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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 ...

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

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 ...