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Transposit Unveils Next-Generation Platform for Engineering Operations

Transposit launched its next-generation platform for engineering operations that enables DevOps, site reliability engineers (SREs), and other on-call engineering teams to achieve greater velocity both during incidents and when operations are running smoothly.

Designed to address the challenges of modern stacks, Transposit’s new Mission Control is a centralized command center for operations and incidents that includes real-time visibility, streamlined communication, and stakeholder dashboards, as well as searchable documentation that is automatically generated. Knowledge Streams parse massive volumes of human-generated data and machine data to provide unified context across operations and incidents to drive root cause analysis during and after incident triage, dramatically cutting mean time to resolution (MTTR). By making it possible to take action from the command center or right within their communications tools, like Slack, engineers can move fast while preventing human error at scale. The platform logs all activities relating to operations and incidents, dynamically systematizes processes, and serves up interactive runbooks so that both new and experienced employees can access the latest best practices contextually – in real time – increasing productivity.

Transposit uses automation to bring order to incident response and troubleshooting, upleveling an existing ecosystem while keeping humans in the loop at key decision points to enhance stability and flexibility. By reducing the pain of on-call operations, engineering teams are freed to focus on innovation and evolving their technology stacks. The platform turns human activity into a data stream that can be processed alongside their automatically collected machine data streams. It enables users to automate repeatable tasks and provides a centralized place from which to act. Knowledge Streams drill into context with a holistic view across events, triggers, actions, and services, speeding up root cause analysis and eliminating silos. With Transposit’s Developer Console and integration platform, teams have quick access to shareable, sophisticated workflows and actions with infinite customization capabilities to achieve flexible, robust, and transparent automation. Workflows via interactive runbooks are now able to trigger multiple auto-actions at once. When a human takes a direct action command (such as ‘revert code commit’), multi-step automated workflows are initiated while maintaining full transparency for human operators.

“Automation is often sold as a panacea for managing today's complex stacks, but full automation takes a complete understanding of the system and all of its possible outcomes, which is a constantly moving target when you have high velocity of innovation. Teams who attempt to automate everything without a clear awareness of what is and isn’t appropriate to fully automate end up with either complex and brittle systems or missed opportunities,” said Tina Huang, founder and CTO, Transposit. “While some solutions take the human out of the picture, Transposit believes in a human-centric approach to automation. We believe it’s better to plan around the human and their intuition, letting them command and control when to apply various automations. This approach makes automation easier to build out and more reliable, so people are less afraid to use it. The path forward lies in having user friendly systems that are instrumented to collect data for both the human and machine process. Making this data accessible before, after, but most importantly, during an incident can drive strategic action seamlessly through the tech stack, with exceptional speed and transparency for all stakeholders.”

Traditionally the focus has been on the positives of agile development – transparency, improved product quality, and efficiency. However, there are downsides. According to IDC, “through 2022, the talent pool for emerging technologies will be inadequate to fill at least 30% of global demand and effective skills development and retention will become differentiating strategies.” Given the skills gap and difficulty in staffing DevOps roles, rapid agile development cycles, and the astronomical cost of downtime, the urgency of what it means to debug an incident has ballooned requiring engineers to support and debug against end users in real time.

With Transposit, engineers are able to reduce the stress of on-call life caused by the increased reliance on their support of production systems. Enterprises now have a single place for anyone to access key information on incidents. Engineers can more easily investigate, understand, and act on what is happening in production, both at the time of an incident and during post mortems. The only solution built on powerful bi-directional API integration technology, Transposit gathers semi-structured data from communications platforms such as Slack, continuous integration and continuous delivery solutions (CI/CD), application performance monitoring systems, and workflow management tools like Jira. These integrations provide better visibility into production systems so on-call engineers no longer need to spend countless hours communicating progress to stakeholders and can focus on keeping systems running smoothly and solving issues.

Key features of the Transposit platform:

- Incident Command Center provides real-time visibility to on-call engineers and stakeholders, enhancing collaboration and simplifying communication so that teams can focus on what matters most: resolution.

- Direct Action Commands (DACs) enable decisions to be carried from a communication platform, such as Transposit’s web interface or Slack, to a service, such as AWS ECS, with the touch of one button.

- Interactive runbooks guide engineers through human-in-the-loop automated workflows.

- Integration Hub manages identity and authentication and runs actions in Transposit’s serverless environment, serving as the “glue” that keeps the stack reliably connected as it evolves.

- The Developer Console enables infinite extensibility and customization, as developers are able to fork, copy and modify any workflow or integration with managed auth, identity management, and versioning with git.

- Self-documenting postmortems capture, annotate, and automatically document every action and event carried out on the Transposit platform and its connected systems.

“With cloud-native applications and ‘everything as a service' shaping the path forward for IT, technology and developer operations are ready for a revolution that keeps pace with digital transformation,” said Divanny Lamas, CEO, Transposit. “Offerings built before DevOps philosophy and cloud-native infrastructure existed fall short. They are too manual, segmented, and unfocused to provide the full value engineering teams need from ops management tools. With Transposit’s rich, bi-directional integration technology we enable unprecedented actionability, sustainable and secure connections between systems, collaboration, and multi-system event tracking. Our interactive runbooks, knowledge streams, and ability to automate actions while keeping the human in the loop allow teams to achieve well-functioning systems. Reliability of systems is all about having repeatable processes for humans and machines and our new platform brings our vision to life.”

Transposit also announced a $35 million Series B funding round led by Altimeter Capital with participation from existing investors Sutter Hill Ventures, SignalFire, and Unusual Ventures.

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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 ...

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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 ...

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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.

Transposit Unveils Next-Generation Platform for Engineering Operations

Transposit launched its next-generation platform for engineering operations that enables DevOps, site reliability engineers (SREs), and other on-call engineering teams to achieve greater velocity both during incidents and when operations are running smoothly.

Designed to address the challenges of modern stacks, Transposit’s new Mission Control is a centralized command center for operations and incidents that includes real-time visibility, streamlined communication, and stakeholder dashboards, as well as searchable documentation that is automatically generated. Knowledge Streams parse massive volumes of human-generated data and machine data to provide unified context across operations and incidents to drive root cause analysis during and after incident triage, dramatically cutting mean time to resolution (MTTR). By making it possible to take action from the command center or right within their communications tools, like Slack, engineers can move fast while preventing human error at scale. The platform logs all activities relating to operations and incidents, dynamically systematizes processes, and serves up interactive runbooks so that both new and experienced employees can access the latest best practices contextually – in real time – increasing productivity.

Transposit uses automation to bring order to incident response and troubleshooting, upleveling an existing ecosystem while keeping humans in the loop at key decision points to enhance stability and flexibility. By reducing the pain of on-call operations, engineering teams are freed to focus on innovation and evolving their technology stacks. The platform turns human activity into a data stream that can be processed alongside their automatically collected machine data streams. It enables users to automate repeatable tasks and provides a centralized place from which to act. Knowledge Streams drill into context with a holistic view across events, triggers, actions, and services, speeding up root cause analysis and eliminating silos. With Transposit’s Developer Console and integration platform, teams have quick access to shareable, sophisticated workflows and actions with infinite customization capabilities to achieve flexible, robust, and transparent automation. Workflows via interactive runbooks are now able to trigger multiple auto-actions at once. When a human takes a direct action command (such as ‘revert code commit’), multi-step automated workflows are initiated while maintaining full transparency for human operators.

“Automation is often sold as a panacea for managing today's complex stacks, but full automation takes a complete understanding of the system and all of its possible outcomes, which is a constantly moving target when you have high velocity of innovation. Teams who attempt to automate everything without a clear awareness of what is and isn’t appropriate to fully automate end up with either complex and brittle systems or missed opportunities,” said Tina Huang, founder and CTO, Transposit. “While some solutions take the human out of the picture, Transposit believes in a human-centric approach to automation. We believe it’s better to plan around the human and their intuition, letting them command and control when to apply various automations. This approach makes automation easier to build out and more reliable, so people are less afraid to use it. The path forward lies in having user friendly systems that are instrumented to collect data for both the human and machine process. Making this data accessible before, after, but most importantly, during an incident can drive strategic action seamlessly through the tech stack, with exceptional speed and transparency for all stakeholders.”

Traditionally the focus has been on the positives of agile development – transparency, improved product quality, and efficiency. However, there are downsides. According to IDC, “through 2022, the talent pool for emerging technologies will be inadequate to fill at least 30% of global demand and effective skills development and retention will become differentiating strategies.” Given the skills gap and difficulty in staffing DevOps roles, rapid agile development cycles, and the astronomical cost of downtime, the urgency of what it means to debug an incident has ballooned requiring engineers to support and debug against end users in real time.

With Transposit, engineers are able to reduce the stress of on-call life caused by the increased reliance on their support of production systems. Enterprises now have a single place for anyone to access key information on incidents. Engineers can more easily investigate, understand, and act on what is happening in production, both at the time of an incident and during post mortems. The only solution built on powerful bi-directional API integration technology, Transposit gathers semi-structured data from communications platforms such as Slack, continuous integration and continuous delivery solutions (CI/CD), application performance monitoring systems, and workflow management tools like Jira. These integrations provide better visibility into production systems so on-call engineers no longer need to spend countless hours communicating progress to stakeholders and can focus on keeping systems running smoothly and solving issues.

Key features of the Transposit platform:

- Incident Command Center provides real-time visibility to on-call engineers and stakeholders, enhancing collaboration and simplifying communication so that teams can focus on what matters most: resolution.

- Direct Action Commands (DACs) enable decisions to be carried from a communication platform, such as Transposit’s web interface or Slack, to a service, such as AWS ECS, with the touch of one button.

- Interactive runbooks guide engineers through human-in-the-loop automated workflows.

- Integration Hub manages identity and authentication and runs actions in Transposit’s serverless environment, serving as the “glue” that keeps the stack reliably connected as it evolves.

- The Developer Console enables infinite extensibility and customization, as developers are able to fork, copy and modify any workflow or integration with managed auth, identity management, and versioning with git.

- Self-documenting postmortems capture, annotate, and automatically document every action and event carried out on the Transposit platform and its connected systems.

“With cloud-native applications and ‘everything as a service' shaping the path forward for IT, technology and developer operations are ready for a revolution that keeps pace with digital transformation,” said Divanny Lamas, CEO, Transposit. “Offerings built before DevOps philosophy and cloud-native infrastructure existed fall short. They are too manual, segmented, and unfocused to provide the full value engineering teams need from ops management tools. With Transposit’s rich, bi-directional integration technology we enable unprecedented actionability, sustainable and secure connections between systems, collaboration, and multi-system event tracking. Our interactive runbooks, knowledge streams, and ability to automate actions while keeping the human in the loop allow teams to achieve well-functioning systems. Reliability of systems is all about having repeatable processes for humans and machines and our new platform brings our vision to life.”

Transposit also announced a $35 million Series B funding round led by Altimeter Capital with participation from existing investors Sutter Hill Ventures, SignalFire, and Unusual Ventures.

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.