Kentik launched The Cloud Latency Map, a free public tool that allows anyone to explore the latencies measured between 100 different cloud regions located around the world.
For the first time, users can identify recent changes in latencies globally between various public clouds and data center regions.
“The Cloud Latency Map benefits anyone trying to determine if there is a connectivity issue impacting the latencies to particular clouds and cloud regions,” said Doug Madory, Director of Internet Analysis at Kentik and the creator of The Cloud Latency Map. “And since the public clouds rely on the same physical infrastructure as the rest of the global Internet, the map can often pick up on the latency impacts of a variety of failures of core infrastructure, such as the loss of a major submarine cable.”
The Cloud Latency Map uses live measurement data generated by a full mesh of measurements between over 100 cloud agents hosted by Amazon Web Services (AWS), Microsoft Azure, Google Cloud (GCP), Oracle Cloud Infrastructure (OCI), and IBM. As an agnostic third party, Kentik is in a unique position to publish latency data across all major public clouds that has never been continuously available before. This newfound data can help digital businesses optimize their multi-cloud networks and identify impacts to cloud connectivity.
Kentik Cloud is also available for enterprises that want to go beyond the broad insights of The Cloud Latency Map. Kentik Cloud is a paid platform for enterprises with complex networks that need a best-in-class network observability platform with sophisticated insights into cloud performance. By connecting directly to an enterprise’s specific cloud setup, network teams are able to further optimize cost, performance, and security.
The Latest
Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...
For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...
Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...
Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...
For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...
New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...
Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...
In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ...
In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...
When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...