Skip to main content

Correlsense Releases SharePath Version 2.5

Correlsense, a provider of transaction management solutions, announced the availability of SharePath 2.5, the latest version of its application performance management platform.

This updated version includes deeper visibility for code in production environments, broader views across the IT infrastructure, user interface enhancements, and greater analytical capabilities. These improvements allow users to more efficiently isolate the cause of slowdowns, improve end-user experiences, and monitor applications for better service level management.

The new code level visibility in SharePath 2.5 provides application support and development teams with deeper data about production failures and bottlenecks, along with the transaction flow and user request context. This enhancement gives the complete platform the broadest visibility for transaction flows across components, as well as deepest views into production code. Sharepath’s lightweight agent technology adds very little overhead and can be easily installed, deployed, and configured with little direct code knowledge.

“The new code level visibility means that SharePath now meets the complete needs of today’s increasingly application-centric IT operations. Infrastructure and applications support professionals who are looking for a comprehensive APM solution can benefit from using SharePath to manage complex service-oriented environments,” said Oren Elias, CEO of Correlsense.

Additionally, users can now leverage SharePath’s updated analytic capabilities to significantly reduce time-to-isolation.

A new application dashboard provides a focused view of trends along with contextual drill downs.

The weekly application performance report gives both IT and business stakeholders an intuitive view of real-time and historical trends. This report is easily exportable as a CSV file or Excel spreadsheet.

Finally, new change analysis features allow users to compare the time frames before and after bottlenecks have been eliminated, adding another level of assurance.

Updated data center intelligence features improve usability and help users understand real-time trend data and performance metrics. New response time and volume graphs are now correlated with a breakdown graph, making performance monitoring much easier. Data may also be displayed as processing time per transaction, allowing a quick understanding of how different tiers affect user response times.

Using patent-pending transaction tracking technology, SharePath offers advanced behavior modeling, real user monitoring, code level visibility, and advanced analytics in a single platform.

The Latest

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Correlsense Releases SharePath Version 2.5

Correlsense, a provider of transaction management solutions, announced the availability of SharePath 2.5, the latest version of its application performance management platform.

This updated version includes deeper visibility for code in production environments, broader views across the IT infrastructure, user interface enhancements, and greater analytical capabilities. These improvements allow users to more efficiently isolate the cause of slowdowns, improve end-user experiences, and monitor applications for better service level management.

The new code level visibility in SharePath 2.5 provides application support and development teams with deeper data about production failures and bottlenecks, along with the transaction flow and user request context. This enhancement gives the complete platform the broadest visibility for transaction flows across components, as well as deepest views into production code. Sharepath’s lightweight agent technology adds very little overhead and can be easily installed, deployed, and configured with little direct code knowledge.

“The new code level visibility means that SharePath now meets the complete needs of today’s increasingly application-centric IT operations. Infrastructure and applications support professionals who are looking for a comprehensive APM solution can benefit from using SharePath to manage complex service-oriented environments,” said Oren Elias, CEO of Correlsense.

Additionally, users can now leverage SharePath’s updated analytic capabilities to significantly reduce time-to-isolation.

A new application dashboard provides a focused view of trends along with contextual drill downs.

The weekly application performance report gives both IT and business stakeholders an intuitive view of real-time and historical trends. This report is easily exportable as a CSV file or Excel spreadsheet.

Finally, new change analysis features allow users to compare the time frames before and after bottlenecks have been eliminated, adding another level of assurance.

Updated data center intelligence features improve usability and help users understand real-time trend data and performance metrics. New response time and volume graphs are now correlated with a breakdown graph, making performance monitoring much easier. Data may also be displayed as processing time per transaction, allowing a quick understanding of how different tiers affect user response times.

Using patent-pending transaction tracking technology, SharePath offers advanced behavior modeling, real user monitoring, code level visibility, and advanced analytics in a single platform.

The Latest

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...