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ngrok Launches Global Server Load Balancing

ngrok announced the launch of ngrok Global Server Load Balancing (GSLB).

The ngrok GSLB distributes traffic across connected servers in multiple geographies to enhance application performance and resiliency without adding any overhead to ITOps.

Without a GSLB, application performance can experience high latency due to ineffective traffic routing through suboptimal regions and long client-to-TLS termination point distances. Additionally, if a point of presence (PoP) shuts down, there is no failover to reroute client traffic to an operational PoP, causing service disruptions.

The ngrok GSLB optimizes application performance and improves resiliency and high availability. It intelligently routes client and agent traffic to the PoP with the lowest latency and terminates TLS connections at ngrok edges closest to the client. If an entire PoP is unavailable, the ngrok GSLB provides geo-aware load balancing and failover capabilities that reroute traffic to another operational PoP.

“The launch of ngrok Global Server Load Balancing sets a new standard for application performance and resilience,” said Alan Shreve, founder and CEO of ngrok. “The ngrok GSLB reflects our commitment to delivering solutions that simplify complex networking challenges and improve application delivery across every stage of the development life cycle, from dev and test to production environments.”

Additional benefits of the ngrok GSLB include:

- Reduced Operational Overhead: Traditional appliance-based GSLB demands substantial resources from NetOps teams due to the complexity of deployment and ongoing maintenance. The ngrok GSLB is an out-of-the-box, hosted solution that’s active by default and requires no additional configuration.

- Simplified Application Delivery: Now, ITOps teams can use ngrok as their GSLB, firewall and reverse proxy to reduce tool sprawl.

- Instant Availability of New Locations: When a service is added in a new region or a configuration change is made at the edge, it immediately becomes available across the ngrok Global Network.

- Origin Network Protection: With the ngrok GSLB, there is no need to create a demilitarized zone (DMZ) to secure apps. ngrok enforces security policies at the edge, ensuring unauthorized requests are instantly blocked and only valid requests are sent to services.

To further boost performance and improve resiliency for applications and APIs delivered by ngrok, the company has also expanded its Global Network with a new PoP on the West Coast of the U.S.

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ngrok Launches Global Server Load Balancing

ngrok announced the launch of ngrok Global Server Load Balancing (GSLB).

The ngrok GSLB distributes traffic across connected servers in multiple geographies to enhance application performance and resiliency without adding any overhead to ITOps.

Without a GSLB, application performance can experience high latency due to ineffective traffic routing through suboptimal regions and long client-to-TLS termination point distances. Additionally, if a point of presence (PoP) shuts down, there is no failover to reroute client traffic to an operational PoP, causing service disruptions.

The ngrok GSLB optimizes application performance and improves resiliency and high availability. It intelligently routes client and agent traffic to the PoP with the lowest latency and terminates TLS connections at ngrok edges closest to the client. If an entire PoP is unavailable, the ngrok GSLB provides geo-aware load balancing and failover capabilities that reroute traffic to another operational PoP.

“The launch of ngrok Global Server Load Balancing sets a new standard for application performance and resilience,” said Alan Shreve, founder and CEO of ngrok. “The ngrok GSLB reflects our commitment to delivering solutions that simplify complex networking challenges and improve application delivery across every stage of the development life cycle, from dev and test to production environments.”

Additional benefits of the ngrok GSLB include:

- Reduced Operational Overhead: Traditional appliance-based GSLB demands substantial resources from NetOps teams due to the complexity of deployment and ongoing maintenance. The ngrok GSLB is an out-of-the-box, hosted solution that’s active by default and requires no additional configuration.

- Simplified Application Delivery: Now, ITOps teams can use ngrok as their GSLB, firewall and reverse proxy to reduce tool sprawl.

- Instant Availability of New Locations: When a service is added in a new region or a configuration change is made at the edge, it immediately becomes available across the ngrok Global Network.

- Origin Network Protection: With the ngrok GSLB, there is no need to create a demilitarized zone (DMZ) to secure apps. ngrok enforces security policies at the edge, ensuring unauthorized requests are instantly blocked and only valid requests are sent to services.

To further boost performance and improve resiliency for applications and APIs delivered by ngrok, the company has also expanded its Global Network with a new PoP on the West Coast of the U.S.

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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 ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.