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Kentik Map for Azure Released

Kentik announced general availability of Kentik Map for Azure and extensive support for Microsoft Azure infrastructure in Kentik Cloud.

With this release, Kentik provides comprehensive network observability across all multi-cloud deployments, and gives network, cloud, and infrastructure engineers the context to rapidly answer any question about their networks.

Enterprises use Kentik Cloud to optimize performance, resolve network incidents, reduce cloud costs, and maximize ROI of migrations to Azure, Google Cloud, and AWS. These latest Azure enhancements follow the recently announced release of Kentik Map for Google Cloud, underscoring Kentik's command of network observability for hybrid and multi-cloud environments.

Kentik Map for Azure visualizes Azure infrastructure in an interactive, data- and context-rich map that highlights how Azure resources nest within each other and connect to on-prem environments. Additionally, Kentik now collects, analyzes, and contextualizes traffic flow and performance data from Microsoft Azure along with data from on-prem, Google Cloud, and AWS services, enriching all network telemetry with deep application, business, and security context to provide actionable observability across all hybrid and multi-cloud environments. Organizations can now:

- Reference live visualizations of Azure infrastructure topology in Kentik Map for Azure, with both current and historical views of paths and detailed metadata

- Quickly understand path and performance details of traffic routes that connect Microsoft Azure workloads to data centers across Azure Express Routes

- Visualize and interrogate traffic across Azure Firewalls, Load Balancers, Application Gateways, and other network infrastructure

- Visualize and interrogate all branch, VPN, private cloud, and intra-cloud connectivity that is connected with Azure VWAN

- Drill into the impact of NSG (Network Security Group) configuration on security and productivity with live traffic data

- Use custom tags to add any custom context to Microsoft Azure data along with pre-built Azure-native attributes sourced from Azure APIs

- Create custom dashboards with configurable pre-built widgets to visualize important Azure cost and performance trends

"Legacy NPM and observability tools are simply not able to provide the visibility that enterprises need to understand the impact of traffic flows and performance on customer experiences," said Christoph Pfister, Chief Product Officer, Kentik. "By unifying all network telemetry, across all clouds and data centers, Kentik's latest advancements enable enterprises to make data-driven decisions, optimize resource utilization, and achieve peak performance and security for their hybrid and multi-cloud infrastructure."

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Kentik Map for Azure Released

Kentik announced general availability of Kentik Map for Azure and extensive support for Microsoft Azure infrastructure in Kentik Cloud.

With this release, Kentik provides comprehensive network observability across all multi-cloud deployments, and gives network, cloud, and infrastructure engineers the context to rapidly answer any question about their networks.

Enterprises use Kentik Cloud to optimize performance, resolve network incidents, reduce cloud costs, and maximize ROI of migrations to Azure, Google Cloud, and AWS. These latest Azure enhancements follow the recently announced release of Kentik Map for Google Cloud, underscoring Kentik's command of network observability for hybrid and multi-cloud environments.

Kentik Map for Azure visualizes Azure infrastructure in an interactive, data- and context-rich map that highlights how Azure resources nest within each other and connect to on-prem environments. Additionally, Kentik now collects, analyzes, and contextualizes traffic flow and performance data from Microsoft Azure along with data from on-prem, Google Cloud, and AWS services, enriching all network telemetry with deep application, business, and security context to provide actionable observability across all hybrid and multi-cloud environments. Organizations can now:

- Reference live visualizations of Azure infrastructure topology in Kentik Map for Azure, with both current and historical views of paths and detailed metadata

- Quickly understand path and performance details of traffic routes that connect Microsoft Azure workloads to data centers across Azure Express Routes

- Visualize and interrogate traffic across Azure Firewalls, Load Balancers, Application Gateways, and other network infrastructure

- Visualize and interrogate all branch, VPN, private cloud, and intra-cloud connectivity that is connected with Azure VWAN

- Drill into the impact of NSG (Network Security Group) configuration on security and productivity with live traffic data

- Use custom tags to add any custom context to Microsoft Azure data along with pre-built Azure-native attributes sourced from Azure APIs

- Create custom dashboards with configurable pre-built widgets to visualize important Azure cost and performance trends

"Legacy NPM and observability tools are simply not able to provide the visibility that enterprises need to understand the impact of traffic flows and performance on customer experiences," said Christoph Pfister, Chief Product Officer, Kentik. "By unifying all network telemetry, across all clouds and data centers, Kentik's latest advancements enable enterprises to make data-driven decisions, optimize resource utilization, and achieve peak performance and security for their hybrid and multi-cloud infrastructure."

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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 ...