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Moogsoft Partners with Alesia Labs

Moogsoft announced a partnership with AI observability solutions Alesia Labs (Activesec).

Through this partnership, Moogsoft will enhance Alesia’s observability portfolio with AIOps capabilities, such as noise reduction, anomaly detection and insight enrichment.

Alesia Labs provides full-stack observability solutions that deliver real-time alerting, reporting and troubleshooting for top business process visibility. As Alesia expands its international footprint into Latin America (LATAM) and Europe, the company is broadening its AIOps service offerings through its partnership with Moogsoft.

Alesia Labs’s solutions portfolio was designed in response to the increasing complexity in observability platforms. The partnership between Alesia Labs and Moogsoft provides a robust intelligent observability platform that helps customers provide outstanding UX to their customers.

“After many years of working with Application Performance Monitoring solutions, our team felt it was time to help customers achieve a higher Observability Maturity Level,” said Jorge De Buono, Co-founding Director at Alesia Labs. “Now we are taking our customers’ capabilities a step further by partnering with Moogsoft that can jump in and provide AIOps and observability capabilities. With Moogsoft, we can add correlation and noise reduction, thus reducing mean time to resolve incidents, faster root cause analysis and higher availability.”

Beyond noise reduction, anomaly detection and enrichment of ingested alerts, the Moogsoft observability platform provides features such as connections between data, custom integration to any data source and collaboration across teams. These Moogsoft solutions assist DevOps and SRE teams to improve the customer experience by ensuring systems are operating optimally.

“...The Alesia Labs team has demonstrated a deep understanding of AIOps and observability...” said Mike Silvey, Executive VP at Moogsoft.

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Moogsoft Partners with Alesia Labs

Moogsoft announced a partnership with AI observability solutions Alesia Labs (Activesec).

Through this partnership, Moogsoft will enhance Alesia’s observability portfolio with AIOps capabilities, such as noise reduction, anomaly detection and insight enrichment.

Alesia Labs provides full-stack observability solutions that deliver real-time alerting, reporting and troubleshooting for top business process visibility. As Alesia expands its international footprint into Latin America (LATAM) and Europe, the company is broadening its AIOps service offerings through its partnership with Moogsoft.

Alesia Labs’s solutions portfolio was designed in response to the increasing complexity in observability platforms. The partnership between Alesia Labs and Moogsoft provides a robust intelligent observability platform that helps customers provide outstanding UX to their customers.

“After many years of working with Application Performance Monitoring solutions, our team felt it was time to help customers achieve a higher Observability Maturity Level,” said Jorge De Buono, Co-founding Director at Alesia Labs. “Now we are taking our customers’ capabilities a step further by partnering with Moogsoft that can jump in and provide AIOps and observability capabilities. With Moogsoft, we can add correlation and noise reduction, thus reducing mean time to resolve incidents, faster root cause analysis and higher availability.”

Beyond noise reduction, anomaly detection and enrichment of ingested alerts, the Moogsoft observability platform provides features such as connections between data, custom integration to any data source and collaboration across teams. These Moogsoft solutions assist DevOps and SRE teams to improve the customer experience by ensuring systems are operating optimally.

“...The Alesia Labs team has demonstrated a deep understanding of AIOps and observability...” said Mike Silvey, Executive VP at Moogsoft.

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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 ...