Skip to main content

Instana Releases APM Integration with Humio and Splunk

Instana announced new capabilities that make it the only application management solution that can jump right into a log analysis tool with all context of the application and component under investigation.

“IT teams responsible for deploying and maintaining today’s mission critical applications must react quickly, especially when attacking service issues,” said Pete Abrams, Instana co-founder and COO. “it’s important to have tools that work together to optimize troubleshooting. Instana’s ability to kick off a log analysis solution, with a visualization of the exact logs needed for examination significantly reduces the time it takes to actually solve problems.”

The first log analysis tools for which Instana is rolling out its one-click integration are Splunk and Humio. The interaction is handled via built-in buttons in the Instana GUI on key component dashboards (such as Servers, Containers and Kubernetes). When the button is clicked, Instana starts up an instance of the log analysis tool, along with a pre-executed analysis filter into the exact logs of the application components and associated infrastructure needing examination. TIming is also synchronized, meaning users won’t have to search for the specific log or timeframe needed to solve problems.

“Log analysis is an important part of the troubleshooting process, especially when integrated with application performance management solutions like Instana. Humio’s unlimited plan enables users to log everything, giving them autonomy to correlate Instana metrics with relevant logs from their environment,” said Cinthia Portugal, VP of Marketing at Humio. “Humio’s one-click integration and simple query language makes it easy to get started. Our modern architecture runs real-time searches on millions of streaming events per second, and because Instana pulls the exact infrastructure logs associated with problem components, getting the root-cause analysis is fast and easy.”

Instana’s automated Application Performance Monitoring (APM) solution discovers all application service components and application infrastructure, including Cloud infrastructure such as Azure, orchestration infrastructure like Kubernetes and Docker, application services and DevOps processes. Instana automatically deploys monitoring sensors for each part of the application technology stack and traces all application requests – without requiring any human configuration or even application restarts. The solution detects application and infrastructure changes in real-time, adjusting its own models and visualizing the changes and impacts to performance in seconds.

The Latest

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

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 ...

Instana Releases APM Integration with Humio and Splunk

Instana announced new capabilities that make it the only application management solution that can jump right into a log analysis tool with all context of the application and component under investigation.

“IT teams responsible for deploying and maintaining today’s mission critical applications must react quickly, especially when attacking service issues,” said Pete Abrams, Instana co-founder and COO. “it’s important to have tools that work together to optimize troubleshooting. Instana’s ability to kick off a log analysis solution, with a visualization of the exact logs needed for examination significantly reduces the time it takes to actually solve problems.”

The first log analysis tools for which Instana is rolling out its one-click integration are Splunk and Humio. The interaction is handled via built-in buttons in the Instana GUI on key component dashboards (such as Servers, Containers and Kubernetes). When the button is clicked, Instana starts up an instance of the log analysis tool, along with a pre-executed analysis filter into the exact logs of the application components and associated infrastructure needing examination. TIming is also synchronized, meaning users won’t have to search for the specific log or timeframe needed to solve problems.

“Log analysis is an important part of the troubleshooting process, especially when integrated with application performance management solutions like Instana. Humio’s unlimited plan enables users to log everything, giving them autonomy to correlate Instana metrics with relevant logs from their environment,” said Cinthia Portugal, VP of Marketing at Humio. “Humio’s one-click integration and simple query language makes it easy to get started. Our modern architecture runs real-time searches on millions of streaming events per second, and because Instana pulls the exact infrastructure logs associated with problem components, getting the root-cause analysis is fast and easy.”

Instana’s automated Application Performance Monitoring (APM) solution discovers all application service components and application infrastructure, including Cloud infrastructure such as Azure, orchestration infrastructure like Kubernetes and Docker, application services and DevOps processes. Instana automatically deploys monitoring sensors for each part of the application technology stack and traces all application requests – without requiring any human configuration or even application restarts. The solution detects application and infrastructure changes in real-time, adjusting its own models and visualizing the changes and impacts to performance in seconds.

The Latest

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

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 ...