SIOS sets 2026 vision for clustering in hybrid AI IT

SIOS Technology has outlined a set of 2026 IT predictions that place high availability clustering at the centre of security resilience, hybrid cloud operations and AI reliability.

Cassius Rhue, Vice President of Customer Experience at SIOS Technology, said organisations now expect more from high availability and disaster recovery than uptime alone. He pointed to changes in infrastructure strategy, threat conditions and application design.

"By 2026, IT admins will require clustering tools for high availability and disaster recovery that provide far greater visibility and control across increasingly complex environments," said Cassius Rhue, Vice President of Customer Experience, SIOS Technology.

SIOS Technology sells high availability and disaster recovery software for Windows and Linux applications. The company positions clustering as a common approach for handling local failures and regional outages across physical, virtual and cloud environments.

Rhue described high availability and disaster recovery as moving closer to the day-to-day operating model for IT teams. He said demands now include visibility, automation and simpler management as estates spread across more platforms and teams take on broader responsibilities.

Hybrid momentum

One prediction focuses on the continued adoption of hybrid and multicloud strategies. Rhue said organisations use these approaches to balance performance, cost and resilience. He also said they use them to reduce reliance on a single vendor.

The shift increases pressure on operational tools to work across different infrastructure types. Rhue said high availability solutions that run across diverse environments will become a common expectation in modern IT strategies.

Security pressures

Rhue also linked high availability more closely with cybersecurity needs. He said enterprises will treat clustering as part of the response to an expanding threat landscape.

In his predictions, high availability sits alongside patching and update practices. He said organisations will use clusters for rapid patching with lower risk. He also said IT teams will aim to keep systems available while they apply changes intended to address emerging threats.

Ease of use

Another theme in the predictions covers the changing profile of the IT staff responsible for high availability. Rhue said more administrators and generalists now manage complex application environments. He predicted demand will rise for tools that reduce the need for specialist clustering skills.

He said IT teams will favour platforms that limit manual configuration. He also said guided workflows and automation will become more important in vendor product decisions as organisations seek to simplify cluster management.

DevOps planning

Rhue predicted DevOps teams will integrate high availability clustering earlier in application planning. He said this approach changes how teams manage deployment risk.

In the predictions, clustering tools need robust APIs and automation hooks. Rhue also highlighted real-time observability. He said engineers will use clusters to test patches against active workloads and reduce the scale of changes introduced into production.

AI availability

Rhue said AI and machine learning workloads will run more frequently on distributed clusters and GPU-intensive systems. He described downtime as more costly in those environments due to disruption and complexity.

He predicted IT administrators will demand high availability tools that simplify AI stacks. He also said they will want full visibility into data, storage and node health. Rhue framed continuous availability as a prerequisite for trust and reliability in AI operations.

Observability focus

Observability also features prominently in the predictions. Rhue said IT infrastructures now span on-premises environments, public cloud, hybrid and multicloud estates. He said that mix increases the importance of visibility into application health, performance and dependencies across the stack.

He predicted observability will become a key differentiator for high availability solutions. He said platforms that provide insight from hardware through the application layer will stand out as IT teams seek earlier detection and faster resolution of issues that might affect uptime.

Virtual consolidation

Rhue also pointed to consolidation in virtual application environments. He said enterprises continue to concentrate more workloads per host as they standardise on virtualised platforms.

In his predictions, high availability clustering becomes more central as density rises. He said clustering will provide automated failover across hypervisors. He also said security pressures will increase the use of cluster-based patch automation across larger pools of virtual machines.

Disaster recovery automation

Rhue predicted stronger expectations for automated disaster recovery. He said IT teams will want clustering tools that handle disaster recovery locations with automated failover and replication integrity checks.

He also said administrators will expect visibility across the full application stack, including networking, storage and cloud resources. Rhue linked this to cyber incidents and the need for faster recovery cycles.

"Hybrid cloud, cybersecurity pressures, and AI-driven workloads are fundamentally reshaping what organizations expect from HA and DR platforms," said Rhue.