Skip to main content

Kemp Enhances Availability and Performance of Scality’s Object Storage

Kemp announced a technology integration with Scality, a provider of software solutions for distributed file and object storage.

By combining Kemp LoadMaster load balancer and Scality RING, customers will benefit from added security, availability and optimization for their cloud storage and unstructured data management needs.

As enterprises adopt cloud-first narrative to become more agile, they also need an easily manageable cloud storage that ensures smooth delivery of applications’ content. Scality RING is a scale-out object storage that delivers petabyte-scale software-defined storage designed to support cloud native mobile apps, edge cloud portals and SaaS offerings.

"Our integration with Scality enables joint customers to achieve highly scalable storage environments to support availability, security and compliance for critical application data. When deployed along with Scality RING software-defined storage, Kemp load balancers simplify SLA satisfaction, minimize downtime and maximize scalability," says Jason Dover, VP of Product Strategy at Kemp.

Kemp LoadMaster, deployed in front of Scality RING, provides a key connection point and load balancing functions for applications and users. It intelligently distributes traffic across the nodes to ensure efficient use of RING resources. Also, by using advanced health-checking, should any node go offline due to maintenance or outage, Kemp intelligently redistributes traffic enabling an always-on application experience.

Kemp LoadMaster provides Scality RING customers with:

- High Availability - LoadMaster delivers uninterrupted access to data stored on Scality RING. Advanced application-level health checking features ensure the Scality nodes are healthy and ready to accept connections.

- Site Resilience - Global Server Load Balancing (GEO) ensures traffic is intelligently distributed based on proximity which reduces latency and provides better performance. In the event of a complete site failure, LoadMaster directs all traffic to a healthy datacenter.

- Greater Performance - SSL/TLS offloading increases performance by terminating secure connections on the Kemp LoadMaster and sending traffic back to Scality unencrypted. This configuration eliminates the encryption processing overhead on the Scality nodes by transferring it onto the Kemp LoadMaster, which is optimized to handle this traffic.

- Quality of Service - LoadMaster includes Quality of Service (QoS) controls to rate limit connections to Scality RING providing full control over fair and balanced allocation of services for applications and users.

The Latest

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

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 ...

Kemp Enhances Availability and Performance of Scality’s Object Storage

Kemp announced a technology integration with Scality, a provider of software solutions for distributed file and object storage.

By combining Kemp LoadMaster load balancer and Scality RING, customers will benefit from added security, availability and optimization for their cloud storage and unstructured data management needs.

As enterprises adopt cloud-first narrative to become more agile, they also need an easily manageable cloud storage that ensures smooth delivery of applications’ content. Scality RING is a scale-out object storage that delivers petabyte-scale software-defined storage designed to support cloud native mobile apps, edge cloud portals and SaaS offerings.

"Our integration with Scality enables joint customers to achieve highly scalable storage environments to support availability, security and compliance for critical application data. When deployed along with Scality RING software-defined storage, Kemp load balancers simplify SLA satisfaction, minimize downtime and maximize scalability," says Jason Dover, VP of Product Strategy at Kemp.

Kemp LoadMaster, deployed in front of Scality RING, provides a key connection point and load balancing functions for applications and users. It intelligently distributes traffic across the nodes to ensure efficient use of RING resources. Also, by using advanced health-checking, should any node go offline due to maintenance or outage, Kemp intelligently redistributes traffic enabling an always-on application experience.

Kemp LoadMaster provides Scality RING customers with:

- High Availability - LoadMaster delivers uninterrupted access to data stored on Scality RING. Advanced application-level health checking features ensure the Scality nodes are healthy and ready to accept connections.

- Site Resilience - Global Server Load Balancing (GEO) ensures traffic is intelligently distributed based on proximity which reduces latency and provides better performance. In the event of a complete site failure, LoadMaster directs all traffic to a healthy datacenter.

- Greater Performance - SSL/TLS offloading increases performance by terminating secure connections on the Kemp LoadMaster and sending traffic back to Scality unencrypted. This configuration eliminates the encryption processing overhead on the Scality nodes by transferring it onto the Kemp LoadMaster, which is optimized to handle this traffic.

- Quality of Service - LoadMaster includes Quality of Service (QoS) controls to rate limit connections to Scality RING providing full control over fair and balanced allocation of services for applications and users.

The Latest

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

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 ...