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Instana Improves Visibility of Kubernetes Application and System Performance

Instana announced further enhancements to the company’s automatic application monitoring solution for containerized applications. The new capabilities center around Instana’s Application Perspectives, a way to group and analyze all performance metrics and traces from specific application components.

“While Kubernetes-based orchestration allows DevOps to keep applications operating properly most of the time, it’s quite challenging to understand what is happening,” said Pete Abrams, Instana co-founder and COO. “To help developers quickly and easily understand how their application code is behaving within a Kubernetes environment, Instana has connected Kubernetes and Kubernetes Service monitoring directly to application performance metrics and traces. This happens completely automatically.”

Instana’s Application Perspectives changes the way in which IT organizations, especially development teams, use APM solutions for monitoring and troubleshooting their distributed microservice applications. Using operational tags or allowing real-time ad hoc definitions, Instana’s Application Perspectives gather all the metrics and traces that are related to specific applications, filtering out the noise from other distributed systems.

“DevOps and Site Reliability Engineers are important, but they aren’t the only application performance stakeholders,” Abrams continued. “Developers are also involved in performance tuning and troubleshooting containerized microservice applications. That’s why Instana has created an entire User Experience specifically for the developer community.”

Instana’s automatic APM solution for dynamic applications is unique in its ability to automate every step of the application monitoring lifecycle, from monitoring deployment to application discovery and monitoring. Instana automatically consumes any source of performance and tracing information, including popular open source solutions like Jaeger and Zipkin. Like other Instana APM capabilities, the new Kubernetes monitoring occurs automatically, making it a quick and easy way to monitor Kubernetes applications and assure their performance.

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Instana Improves Visibility of Kubernetes Application and System Performance

Instana announced further enhancements to the company’s automatic application monitoring solution for containerized applications. The new capabilities center around Instana’s Application Perspectives, a way to group and analyze all performance metrics and traces from specific application components.

“While Kubernetes-based orchestration allows DevOps to keep applications operating properly most of the time, it’s quite challenging to understand what is happening,” said Pete Abrams, Instana co-founder and COO. “To help developers quickly and easily understand how their application code is behaving within a Kubernetes environment, Instana has connected Kubernetes and Kubernetes Service monitoring directly to application performance metrics and traces. This happens completely automatically.”

Instana’s Application Perspectives changes the way in which IT organizations, especially development teams, use APM solutions for monitoring and troubleshooting their distributed microservice applications. Using operational tags or allowing real-time ad hoc definitions, Instana’s Application Perspectives gather all the metrics and traces that are related to specific applications, filtering out the noise from other distributed systems.

“DevOps and Site Reliability Engineers are important, but they aren’t the only application performance stakeholders,” Abrams continued. “Developers are also involved in performance tuning and troubleshooting containerized microservice applications. That’s why Instana has created an entire User Experience specifically for the developer community.”

Instana’s automatic APM solution for dynamic applications is unique in its ability to automate every step of the application monitoring lifecycle, from monitoring deployment to application discovery and monitoring. Instana automatically consumes any source of performance and tracing information, including popular open source solutions like Jaeger and Zipkin. Like other Instana APM capabilities, the new Kubernetes monitoring occurs automatically, making it a quick and easy way to monitor Kubernetes applications and assure their performance.

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Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...

While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...

A perfect storm is brewing in cybersecurity — certificate lifespans shrinking to just 47 days while quantum computing threatens today's encryption. Organizations must embrace ephemeral trust and crypto-agility to survive this dual challenge ...

In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability... 

While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...