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ScienceLogic Acquires AppFirst

ScienceLogic has acquired AppFirst.

The acquisition included several patented technologies and scale-out data processing capability. Transaction terms were not disclosed.

ScienceLogic plans on releasing the industry’s first converged platform offering later this year. With newly added best in class agent-based analytics and sub-second application data collection, alongside ScienceLogic’s existing discovery and performance visibility, customers will benefit from an entirely new and better way to manage IT.

“We believe that application dependency discovery and management innovation will accelerate Hybrid Cloud production environments within the $23 billion cloud-computing market,” said Dave Link, CEO, ScienceLogic. “As we now embed deep application discovery and analytics capabilities into our Hybrid IT Monitoring platform, organizations for the first time can monitor all business-critical services, including deep application performance, fault and configuration analytics, across their Hybrid IT environments. Our acquisition of AppFirst represents a major leap in ScienceLogic’s sophisticated service assurance capabilities core to helping our customers run their businesses better.”

Customer benefits include:

- Real-time visibility: High Definition Monitoring enables detection of transient problems when they occur, enabling proactive monitoring and better availability. DevOps teams will appreciate enhanced support for dynamic workloads that live for minutes or even seconds covering application containers and virtual services.

- Scale-out architecture: Monitor any technology, any vendor, anywhere. Scale-out, microservices-based architecture ensures the business never misses a metric or log file.

- Enhanced Virtualized Systems support: Visibility across public clouds and converged compute private clouds, provides actionable analytics in environments that are more dynamic in nature

- SaaS enabled: Cloud-neutral and on-prem ready, ScienceLogic can be deployed anywhere and managed in one place. This reduces the cost of monitoring by giving customers the flexibility to determine where and how they wish to run their monitoring platform.

- Application-aware: Provides a complete view of Hybrid IT environments, from the business service down to the automatically correlated infrastructure elements. The result is higher quality service delivery at lower cost.

- Log and network layer analytics: Connecting real-time log and network performance data provides unprecedented visibility into potential service problems, resulting in faster root cause analysis and better proactive monitoring - enabling IT agility in solving problems before they impact the business.

- Automation: Enhanced automation actions from automated provisioning and discovery to corrective actions delivered via smart targeted runbook automation actions.

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ScienceLogic Acquires AppFirst

ScienceLogic has acquired AppFirst.

The acquisition included several patented technologies and scale-out data processing capability. Transaction terms were not disclosed.

ScienceLogic plans on releasing the industry’s first converged platform offering later this year. With newly added best in class agent-based analytics and sub-second application data collection, alongside ScienceLogic’s existing discovery and performance visibility, customers will benefit from an entirely new and better way to manage IT.

“We believe that application dependency discovery and management innovation will accelerate Hybrid Cloud production environments within the $23 billion cloud-computing market,” said Dave Link, CEO, ScienceLogic. “As we now embed deep application discovery and analytics capabilities into our Hybrid IT Monitoring platform, organizations for the first time can monitor all business-critical services, including deep application performance, fault and configuration analytics, across their Hybrid IT environments. Our acquisition of AppFirst represents a major leap in ScienceLogic’s sophisticated service assurance capabilities core to helping our customers run their businesses better.”

Customer benefits include:

- Real-time visibility: High Definition Monitoring enables detection of transient problems when they occur, enabling proactive monitoring and better availability. DevOps teams will appreciate enhanced support for dynamic workloads that live for minutes or even seconds covering application containers and virtual services.

- Scale-out architecture: Monitor any technology, any vendor, anywhere. Scale-out, microservices-based architecture ensures the business never misses a metric or log file.

- Enhanced Virtualized Systems support: Visibility across public clouds and converged compute private clouds, provides actionable analytics in environments that are more dynamic in nature

- SaaS enabled: Cloud-neutral and on-prem ready, ScienceLogic can be deployed anywhere and managed in one place. This reduces the cost of monitoring by giving customers the flexibility to determine where and how they wish to run their monitoring platform.

- Application-aware: Provides a complete view of Hybrid IT environments, from the business service down to the automatically correlated infrastructure elements. The result is higher quality service delivery at lower cost.

- Log and network layer analytics: Connecting real-time log and network performance data provides unprecedented visibility into potential service problems, resulting in faster root cause analysis and better proactive monitoring - enabling IT agility in solving problems before they impact the business.

- Automation: Enhanced automation actions from automated provisioning and discovery to corrective actions delivered via smart targeted runbook automation actions.

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64% of enterprise networking teams use internally developed software or scripts for network automation, but 61% of those teams spend six or more hours per week debugging and maintaining them, according to From Scripts to Platforms: Why Homegrown Tools Dominate Network Automation and How Vendors Can Help, my latest EMA report ...

Cloud computing has transformed how we build and scale software, but it has also quietly introduced one of the most persistent challenges in modern IT: cost visibility and control ... So why, after more than a decade of cloud adoption, are cloud costs still spiraling out of control? The answer lies not in tooling but in culture ...

CEOs are committed to advancing AI solutions across their organization even as they face challenges from accelerating technology adoption, according to the IBM CEO Study. The survey revealed that executive respondents expect the growth rate of AI investments to more than double in the next two years, and 61% confirm they are actively adopting AI agents today and preparing to implement them at scale ...

Image
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A major architectural shift is underway across enterprise networks, according to a new global study from Cisco. As AI assistants, agents, and data-driven workloads reshape how work gets done, they're creating faster, more dynamic, more latency-sensitive, and more complex network traffic. Combined with the ubiquity of connected devices, 24/7 uptime demands, and intensifying security threats, these shifts are driving infrastructure to adapt and evolve ...

Image
Cisco

The development of banking apps was supposed to provide users with convenience, control and piece of mind. However, for thousands of Halifax customers recently, a major mobile outage caused the exact opposite, leaving customers unable to check balances, or pay bills, sparking widespread frustration. This wasn't an isolated incident ... So why are these failures still happening? ...

Cyber threats are growing more sophisticated every day, and at their forefront are zero-day vulnerabilities. These elusive security gaps are exploited before a fix becomes available, making them among the most dangerous threats in today's digital landscape ... This guide will explore what these vulnerabilities are, how they work, why they pose such a significant threat, and how modern organizations can stay protected ...

The prevention of data center outages continues to be a strategic priority for data center owners and operators. Infrastructure equipment has improved, but the complexity of modern architectures and evolving external threats presents new risks that operators must actively manage, according to the Data Center Outage Analysis 2025 from Uptime Institute ...

As observability engineers, we navigate a sea of telemetry daily. We instrument our applications, configure collectors, and build dashboards, all in pursuit of understanding our complex distributed systems. Yet, amidst this flood of data, a critical question often remains unspoken, or at best, answered by gut feeling: "Is our telemetry actually good?" ... We're inviting you to participate in shaping a foundational element for better observability: the Instrumentation Score ...

We're inching ever closer toward a long-held goal: technology infrastructure that is so automated that it can protect itself. But as IT leaders aggressively employ automation across our enterprises, we need to continuously reassess what AI is ready to manage autonomously and what can not yet be trusted to algorithms ...

Much like a traditional factory turns raw materials into finished products, the AI factory turns vast datasets into actionable business outcomes through advanced models, inferences, and automation. From the earliest data inputs to the final token output, this process must be reliable, repeatable, and scalable. That requires industrializing the way AI is developed, deployed, and managed ...