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Gluware 5.6 Released

Gluware announced the release of Gluware 5.6, a transformative update designed to accelerate and refine network automation workflows. 

This launch builds on Gluware's momentum, enabling network automation builders to achieve unparalleled speed and efficiency. Further expanding Gluware's commitment to network automation without limits, this latest platform update delivers key integrations that enable NetDevOps and network automation engineers to accelerate automation, gain greater control, and extend automation capabilities across more vendors and devices.

"Gluware 5.6 is designed to remove the barriers that slow down network automation, giving network automation builders a comprehensive suite to work faster and more efficiently," said Michael Haugh, Vice President of Product Marketing at Gluware. "With new Git integration and expanded support for Arista, Cisco and HPE Aruba, we're making it easier for teams to automate large, complex multi-vendor networks and integrate with existing tools. With this update, we're helping customers reduce manual effort, accelerate project timelines, and achieve greater operational efficiency."

Gluware 5.6 provides network automation builders with several upgrades, including:

Enhanced Version Control with native Git Protocol integration with support for external repositories including GitHub and BitBucket: Seamlessly integrate Gluware with Git-based repositories including GitHub and BitBucket for enhanced transparency, version control and backup/restore of Gluware constructs including Audit Policies and Config Models. Commit updates to a local Git repository or effortlessly synchronize with external repositories.

Expanded Support for:

  • HPE Aruba EdgeConnect ECOS: Unlock key Gluware capabilities including Device Manager, Config Drift & Audit, Network RPA, and Topology.
  • Arista EOS Enhanced Discovery: Gluware discovery of Arista EOS-based devices now includes component-level information for lifecycle management and hardware inventory reports.
  • Meraki Device Filtering: Precisely control Gluware inventory using new filter mechanisms in Device Manager. Define user rules to exclude specific Meraki devices for focused automation.
  • Enhanced Switch Port Management: Leverage a new library within the Config Model Editor for streamlined and improved switch port configuration.
  • Cisco Catalyst 4500 ISSU Support: Benefit from In-Service Software Upgrade (ISSU) capabilities within OS Manager for uninterrupted operations on Cisco Catalyst 4500 switches.

Network RPA Template Builder: Accelerate automation workflows with real-time testing. Test and iterate variables and LiquidJS templates using live workflow context in the Network  RPA Template Builder. Define, load, build and edit until getting the desired outcome, then instantly sync the updated variable or template with your workflow.

Improved Platform Usability:

  • Intuitive Device Details Navigation: Clearly labeled sidebar tabs and an enhanced layout provide swift access to organized device sections with scrolling flexibility.
  • Centralized Third-Party Integrations: A unified tab simplifies management and configuration for Cisco API Services, Git repositories, NetBox, ServiceNow, and SMTP, improving visibility.

"The network is the vital backbone for enterprise innovation, and we see every day how network automation enables our customers to move faster and achieve more," said Ernest Lefner, Chief Product Officer at Gluware. "With Gluware 5.6, we make it even easier for network automation builders to overcome complexity and deliver results. We're committed to providing the tools and support that help our customers drive greater efficiency and innovation across their organizations."

Gluware 5.6 is available now. 

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

Gluware 5.6 Released

Gluware announced the release of Gluware 5.6, a transformative update designed to accelerate and refine network automation workflows. 

This launch builds on Gluware's momentum, enabling network automation builders to achieve unparalleled speed and efficiency. Further expanding Gluware's commitment to network automation without limits, this latest platform update delivers key integrations that enable NetDevOps and network automation engineers to accelerate automation, gain greater control, and extend automation capabilities across more vendors and devices.

"Gluware 5.6 is designed to remove the barriers that slow down network automation, giving network automation builders a comprehensive suite to work faster and more efficiently," said Michael Haugh, Vice President of Product Marketing at Gluware. "With new Git integration and expanded support for Arista, Cisco and HPE Aruba, we're making it easier for teams to automate large, complex multi-vendor networks and integrate with existing tools. With this update, we're helping customers reduce manual effort, accelerate project timelines, and achieve greater operational efficiency."

Gluware 5.6 provides network automation builders with several upgrades, including:

Enhanced Version Control with native Git Protocol integration with support for external repositories including GitHub and BitBucket: Seamlessly integrate Gluware with Git-based repositories including GitHub and BitBucket for enhanced transparency, version control and backup/restore of Gluware constructs including Audit Policies and Config Models. Commit updates to a local Git repository or effortlessly synchronize with external repositories.

Expanded Support for:

  • HPE Aruba EdgeConnect ECOS: Unlock key Gluware capabilities including Device Manager, Config Drift & Audit, Network RPA, and Topology.
  • Arista EOS Enhanced Discovery: Gluware discovery of Arista EOS-based devices now includes component-level information for lifecycle management and hardware inventory reports.
  • Meraki Device Filtering: Precisely control Gluware inventory using new filter mechanisms in Device Manager. Define user rules to exclude specific Meraki devices for focused automation.
  • Enhanced Switch Port Management: Leverage a new library within the Config Model Editor for streamlined and improved switch port configuration.
  • Cisco Catalyst 4500 ISSU Support: Benefit from In-Service Software Upgrade (ISSU) capabilities within OS Manager for uninterrupted operations on Cisco Catalyst 4500 switches.

Network RPA Template Builder: Accelerate automation workflows with real-time testing. Test and iterate variables and LiquidJS templates using live workflow context in the Network  RPA Template Builder. Define, load, build and edit until getting the desired outcome, then instantly sync the updated variable or template with your workflow.

Improved Platform Usability:

  • Intuitive Device Details Navigation: Clearly labeled sidebar tabs and an enhanced layout provide swift access to organized device sections with scrolling flexibility.
  • Centralized Third-Party Integrations: A unified tab simplifies management and configuration for Cisco API Services, Git repositories, NetBox, ServiceNow, and SMTP, improving visibility.

"The network is the vital backbone for enterprise innovation, and we see every day how network automation enables our customers to move faster and achieve more," said Ernest Lefner, Chief Product Officer at Gluware. "With Gluware 5.6, we make it even easier for network automation builders to overcome complexity and deliver results. We're committed to providing the tools and support that help our customers drive greater efficiency and innovation across their organizations."

Gluware 5.6 is available now. 

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.