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ScienceLogic Adds New Elite MSP Tier to ChannelLogic Partner Program

ScienceLogic announced a new Elite MSP tier for its ChannelLogic partner program.

Elite MSP is a new program that includes joint marketing activities with top-tier MSP partners, helping them deliver advanced business-centric managed services based on the ScienceLogic SL1 platform.

The first round of MSPs to join the program, including ePLUS, Flexential, HOSTING, and TierPoint, are each enabled through the new, automated AIOps platform to offer a range of advanced services to customers. With the SL1 platform, MSPs can create new offerings that manage business services and applications, rather than focusing on infrastructure alone. MSPs are encouraged to join the program with the intent of creating services within their existing portfolio that include advanced offerings such as Managed AWS, Managed Azure and Monitoring-as-a-Service for multi-cloud and hybrid IT. ScienceLogic will feature these services on the ScienceLogic website and will also contribute to members marketing support and sponsorships at customer events, joint webinars and sales trainings.

“Our goal is to provide actionable insights for MSP operations teams, which in turn helps them transform their offerings with compelling new business-centric and application-centric managed services.” said ScienceLogic CEO Dave Link. “These are great opportunities for our partners and the Elite program helps them accelerate the introduction of these new services based around our platform.”

The Elite MSP designation is the top tier of the ScienceLogic ChannelLogic program, which authorizes solution providers to resell the new, industry-defining ScienceLogic platform. Elite MSPs can also resell to those customers who prefer to stand up and run their own ScienceLogic system. All ScienceLogic MSPs can also benefit from the existing MSP JumpStart program that helps MSPs define, deploy, market and sell new managed services based on the ScienceLogic platform.

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ScienceLogic Adds New Elite MSP Tier to ChannelLogic Partner Program

ScienceLogic announced a new Elite MSP tier for its ChannelLogic partner program.

Elite MSP is a new program that includes joint marketing activities with top-tier MSP partners, helping them deliver advanced business-centric managed services based on the ScienceLogic SL1 platform.

The first round of MSPs to join the program, including ePLUS, Flexential, HOSTING, and TierPoint, are each enabled through the new, automated AIOps platform to offer a range of advanced services to customers. With the SL1 platform, MSPs can create new offerings that manage business services and applications, rather than focusing on infrastructure alone. MSPs are encouraged to join the program with the intent of creating services within their existing portfolio that include advanced offerings such as Managed AWS, Managed Azure and Monitoring-as-a-Service for multi-cloud and hybrid IT. ScienceLogic will feature these services on the ScienceLogic website and will also contribute to members marketing support and sponsorships at customer events, joint webinars and sales trainings.

“Our goal is to provide actionable insights for MSP operations teams, which in turn helps them transform their offerings with compelling new business-centric and application-centric managed services.” said ScienceLogic CEO Dave Link. “These are great opportunities for our partners and the Elite program helps them accelerate the introduction of these new services based around our platform.”

The Elite MSP designation is the top tier of the ScienceLogic ChannelLogic program, which authorizes solution providers to resell the new, industry-defining ScienceLogic platform. Elite MSPs can also resell to those customers who prefer to stand up and run their own ScienceLogic system. All ScienceLogic MSPs can also benefit from the existing MSP JumpStart program that helps MSPs define, deploy, market and sell new managed services based on the ScienceLogic platform.

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 ...