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Tigera Releases Calico Enterprise 3.5

Tigera announced the latest release of Calico Enterprise, version 3.5, that adds Kubernetes-native full-stack observability capabilities that DevOps, site reliability engineers (SREs), and platform owners can use to observe and monitor microservices interaction to quickly troubleshoot issues while avoiding business disruption in cloud-native applications typically deployed with Kubernetes.

Building on Calico’s Kubernetes networking and security capabilities, now Calico Enterprise 3.5 delivers full-stack observability across the entire Kubernetes stack starting from application layer to networking layer. Calico Enterprise delivers an easy-to-understand and action-oriented view that is otherwise extremely difficult and time-consuming to come by, due to the abstracted, ephemeral, and distributed nature of Kubernetes infrastructure. At the same time, Calico Enterprise maintains the correlations at the service, deployment, container, node, pod, network, and packet levels. Otherwise, as the application grows and the volume of interactions increases, these correlations become increasingly unwieldy to manage and complicated to troubleshoot.

“We are providing full-stack observability for cloud-native applications in the Kubernetes environment,” said Ratan Tipirneni, CEO of Tigera. “Now users can get a live, high-fidelity view of microservices and workload interactions in their environment right at their fingertips with the ability to take corrective actions in real time.”

Calico keeps the Kubernetes context intact for developers, DevOps, SREs, and platform owners to do easy filtering and subsequent analysis of traffic payloads from their perspective providing the following.

- Dynamic Service Graph: A point-to-point topographical representation of traffic between namespaces, microservices, and deployments that speeds problem identification and troubleshooting.

- Application-Level Observability: Detect and prevent anomalous behaviors such as attempts to access applications, restricted URLs, and scans for particular URLs.

- Domain Name System (DNS) Dashboard: With an interactive display that shows DNS information categorized by microservices and workloads, determine whether DNS is the root cause for application connectivity issues.

- Dynamic Packet Capture: Automatically retrieve pcap files, with the ability to customize the duration and packet size for packet capture, to help reduce the time for addressing performance hotspots and troubleshooting connectivity issues.

- Multi-Cloud: Works across multi-cloud and hybrid clouds with any Kubernetes distribution or combination of Kubernetes distributions.

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Tigera Releases Calico Enterprise 3.5

Tigera announced the latest release of Calico Enterprise, version 3.5, that adds Kubernetes-native full-stack observability capabilities that DevOps, site reliability engineers (SREs), and platform owners can use to observe and monitor microservices interaction to quickly troubleshoot issues while avoiding business disruption in cloud-native applications typically deployed with Kubernetes.

Building on Calico’s Kubernetes networking and security capabilities, now Calico Enterprise 3.5 delivers full-stack observability across the entire Kubernetes stack starting from application layer to networking layer. Calico Enterprise delivers an easy-to-understand and action-oriented view that is otherwise extremely difficult and time-consuming to come by, due to the abstracted, ephemeral, and distributed nature of Kubernetes infrastructure. At the same time, Calico Enterprise maintains the correlations at the service, deployment, container, node, pod, network, and packet levels. Otherwise, as the application grows and the volume of interactions increases, these correlations become increasingly unwieldy to manage and complicated to troubleshoot.

“We are providing full-stack observability for cloud-native applications in the Kubernetes environment,” said Ratan Tipirneni, CEO of Tigera. “Now users can get a live, high-fidelity view of microservices and workload interactions in their environment right at their fingertips with the ability to take corrective actions in real time.”

Calico keeps the Kubernetes context intact for developers, DevOps, SREs, and platform owners to do easy filtering and subsequent analysis of traffic payloads from their perspective providing the following.

- Dynamic Service Graph: A point-to-point topographical representation of traffic between namespaces, microservices, and deployments that speeds problem identification and troubleshooting.

- Application-Level Observability: Detect and prevent anomalous behaviors such as attempts to access applications, restricted URLs, and scans for particular URLs.

- Domain Name System (DNS) Dashboard: With an interactive display that shows DNS information categorized by microservices and workloads, determine whether DNS is the root cause for application connectivity issues.

- Dynamic Packet Capture: Automatically retrieve pcap files, with the ability to customize the duration and packet size for packet capture, to help reduce the time for addressing performance hotspots and troubleshooting connectivity issues.

- Multi-Cloud: Works across multi-cloud and hybrid clouds with any Kubernetes distribution or combination of Kubernetes distributions.

The Latest

For many B2B and B2C enterprise brands, technology isn't a core strength. Relying on overly complex architectures (like those that follow a pure MACH doctrine) has been flagged by industry leaders as a source of operational slowdown, creating bottlenecks that limit agility in volatile market conditions ...

FinOps champions crucial cross-departmental collaboration, uniting business, finance, technology and engineering leaders to demystify cloud expenses. Yet, too often, critical cost issues are softened into mere "recommendations" or "insights" — easy to ignore. But what if we adopted security's battle-tested strategy and reframed these as the urgent risks they truly are, demanding immediate action? ...

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 ...