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ITinvolve Introduces New Agility Manager and Drift Manager to Accelerate DevOps Transformation

ITinvolve announced Spring '14 with new ITinvolve Agility Manager and ITinvolve Drift Manager offerings that improve development and operations (DevOps) work coordination and collaboration; manage business initiatives from requirements to deployment; and improve drift visibility, remediation, and prevention.

The announcement was made at Interop Las Vegas at the Mandalay Bay Convention Center.

ITinvolve represents a new way of working between business, development and operations that enables DevOps and brings greater agility while also ensuring operational stability and quality. ITinvolve provides the actionable information IT professionals need by uniting scattered sources of information and tribal knowledge, by delivering unparalleled risk and impact analysis, and by breaking down silos of disconnected teams, tools, and processes.

"Spring '14 fills the collaboration and transparency gaps that are so critical for DevOps success," said ITinvolve co-founder and CTO Rob Reiner. "With modern visualizations and automatic involvement of the right team members, IT now has a single application to orchestrate the complete development lifecycle from business goals and requirements, to managing projects and releases, to having complete visibility across environments in order to avoid problems during deployment."

ITinvolve Agility Manager was developed with extensive input from DevOps practitioners and ITinvolve's own experience with disconnected development and operations tools in the market. Agility Manager helps organizations improve project delivery times and release quality by facilitating DevOps with greater collaboration and enhanced operations across the development lifecycle:

- Eliminates communication handoff gaps and risk of information distortion.

- Aligns business goals, requirements, projects, and releases.

- Communicates changing requirements with downstream impact to those who need to know.

- Manages development iterations, assigns and tracks tasks, and facilitates cross-team collaboration and daily standups.

- Provides full transparency into project and release status including work in process and bottlenecks.

- Keeps environments in sync between pre-production and production.

ITinvolve Drift Manager was developed in response to ongoing enterprise drift management challenges that persist despite investments in automation tools. Drift Manager helps organizations improve service stability and deployment success rates by visualizing, identifying, and correcting configuration drift:

- Centralizes and visualizes existing script and automation information, configuration files, binary files, system-level attributes, and product version data.

- Provides interactive dashboards that compare current state against expected with the ability to drill-down into granular settings across the entire stack and all tiers.

- Generates incidents when drift is detected and provides the ability to "snooze" drift issues if they are expected.

- Ensures everyone who needs to know is aware of existing scripts and automations so configuration changes are always made with this information in mind.

Both ITinvolve Agility Manager and ITinvolve Drift Manager work with existing project management and automation tool investments and are available as add-on modules to ITinvolve's core product offering. ITinvolve also provides ITinvolve Service Manager which supports incident, problem, request, and change management along with a service catalog and self-service portal.

The company also announced it has received an additional equity investment from Austin Ventures. Proceeds of the investment will be used to expand sales and marketing as well as further product innovations.

The Latest

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.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

ITinvolve Introduces New Agility Manager and Drift Manager to Accelerate DevOps Transformation

ITinvolve announced Spring '14 with new ITinvolve Agility Manager and ITinvolve Drift Manager offerings that improve development and operations (DevOps) work coordination and collaboration; manage business initiatives from requirements to deployment; and improve drift visibility, remediation, and prevention.

The announcement was made at Interop Las Vegas at the Mandalay Bay Convention Center.

ITinvolve represents a new way of working between business, development and operations that enables DevOps and brings greater agility while also ensuring operational stability and quality. ITinvolve provides the actionable information IT professionals need by uniting scattered sources of information and tribal knowledge, by delivering unparalleled risk and impact analysis, and by breaking down silos of disconnected teams, tools, and processes.

"Spring '14 fills the collaboration and transparency gaps that are so critical for DevOps success," said ITinvolve co-founder and CTO Rob Reiner. "With modern visualizations and automatic involvement of the right team members, IT now has a single application to orchestrate the complete development lifecycle from business goals and requirements, to managing projects and releases, to having complete visibility across environments in order to avoid problems during deployment."

ITinvolve Agility Manager was developed with extensive input from DevOps practitioners and ITinvolve's own experience with disconnected development and operations tools in the market. Agility Manager helps organizations improve project delivery times and release quality by facilitating DevOps with greater collaboration and enhanced operations across the development lifecycle:

- Eliminates communication handoff gaps and risk of information distortion.

- Aligns business goals, requirements, projects, and releases.

- Communicates changing requirements with downstream impact to those who need to know.

- Manages development iterations, assigns and tracks tasks, and facilitates cross-team collaboration and daily standups.

- Provides full transparency into project and release status including work in process and bottlenecks.

- Keeps environments in sync between pre-production and production.

ITinvolve Drift Manager was developed in response to ongoing enterprise drift management challenges that persist despite investments in automation tools. Drift Manager helps organizations improve service stability and deployment success rates by visualizing, identifying, and correcting configuration drift:

- Centralizes and visualizes existing script and automation information, configuration files, binary files, system-level attributes, and product version data.

- Provides interactive dashboards that compare current state against expected with the ability to drill-down into granular settings across the entire stack and all tiers.

- Generates incidents when drift is detected and provides the ability to "snooze" drift issues if they are expected.

- Ensures everyone who needs to know is aware of existing scripts and automations so configuration changes are always made with this information in mind.

Both ITinvolve Agility Manager and ITinvolve Drift Manager work with existing project management and automation tool investments and are available as add-on modules to ITinvolve's core product offering. ITinvolve also provides ITinvolve Service Manager which supports incident, problem, request, and change management along with a service catalog and self-service portal.

The company also announced it has received an additional equity investment from Austin Ventures. Proceeds of the investment will be used to expand sales and marketing as well as further product innovations.

The Latest

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.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...