65% of enterprises say storage costs bite into their IT budget more than expected — a number that alters procurement decisions overnight.

We set the scene for Australian decision-makers comparing modern storage options for business-critical workloads. Our aim is clear: help you weigh architecture, integration and whole-of-life cost under real operational pressures.

Both platforms deliver enterprise-grade performance and resilience, but they follow different design philosophies. One is hypervisor-native and policy-driven, streamlining virtualisation and compute stacks. The other is a unified block, file and object system that rewards teams prepared for distributed systems work.

We highlight the practical trade-offs — licensing, hardware sizing, networking and day‑two operations — so you can align a solution to strategy rather than fitting strategy to a product. Expect concrete use cases, capacity and performance notes, and an Australian data‑centre lens on 10–100G networks and common backup patterns.

Key Takeaways

• We compare architecture, integration and operational impact for business storage choices.
• Policy-driven options suit VMware-centric estates; unified systems suit diverse environments.
• Consider lifecycle cost, skills and networking before choosing for performance and scale.
• Local context matters — Australian 10–100G networks and common backup flows influence design.
• We provide pragmatic guidance so you can map a storage strategy to your roadmap.

Why Ceph and vSAN matter now for Australian organisations

Australian IT teams face a pivotal choice as software-first storage reshapes data operations. Traditional arrays no longer fit the pace of cloud-style delivery, rapid data growth and platform consolidation.

vSAN offers native vSphere integration and policy-driven provisioning, which simplifies VM lifecycle management. That tight integration reduces operational friction across compute and management planes and helps teams deliver predictable performance.

By contrast, Ceph delivers unified block, file and object services and scales storage independently of compute. That flexibility suits mixed environments—OpenStack, Kubernetes and vSphere—where different workloads need varied storage behaviours.

• Network readiness: 10–100G fabrics in Australian data centres unlock consistent results for either approach.
• Costs and skills: licensing visibility for vSAN versus open-source economics demands lifecycle analysis.
• Scalability and devices: NVMe tiers, SSD choices and NICs directly influence performance and capacity planning.

In short, choose on time‑to‑value, total risk and the management model that matches your environment today and tomorrow.

Ceph vs vSAN: core architectures and how they deliver storage

We compare the internal building blocks that make each platform behave in production — and what that means for operations, resilience and cost.

Ceph building blocks

MON, OSD, MDS and Mgr form the control and data planes. MONs keep cluster maps, OSDs hold and replicate data, MDS handles CephFS metadata and Mgr provides monitoring and management. CRUSH maps place data across the cluster so there is no single point of failure.

Hypervisor‑native virtual SAN

vSAN sits inside the ESXi hypervisor and uses policy-driven classes of service. Admins set availability, performance and dedupe/compression through the vSphere client. Scale is linear as hosts and disk groups are added.

Service breadth and performance

Ceph natively serves block, file and object workloads. That flexibility suits mixed environments. vSAN remains block-centric and is optimised for VM performance via hypervisor data paths.

• Configuration domains: CRUSH and pools on one side; policies and disk groups on the other.
• Devices: NVMe/SSD roles differ — journals/WAL/DB versus cache/capacity tiers — impacting latency and throughput.

Integration paths: VMware, Kubernetes, OpenStack and beyond

Integration choices shape how storage delivers value across virtual and cloud platforms. We focus on how native hooks, drivers and APIs affect operations and performance in Australian data centres.

vSAN’s native vSphere experience for virtual machines

vSAN integrates directly into the vSphere Client for provisioning, policy and health checks. Admins manage virtual machines and storage policies in one place — reducing operational friction and simplifying lifecycle tasks.

Ceph with vSphere via RBD/NFS, plus Kubernetes and OpenStack

Ceph connects to vSphere through RBD or NFS and also serves Kubernetes PVs and OpenStack services such as Cinder, Glance and Swift. It exposes APIs and CSI drivers so diverse workloads can share a single storage fabric.

Network and driver paths shape performance. Tight integration gives faster provisioning and simpler management. Broad protocol support unlocks multi‑platform capabilities and flexible data services.

• Operational boundary: centralised management vs a separate storage system to observe and patch.
• Governance: clear role separation and change control when two control planes exist.
• Interoperability: validate driver and CSI versions to avoid disruptions.

Performance and hardware sizing: CPU, RAM, disks and NVMe

Right‑sizing hardware hinges on clear workload metrics — IOPS, throughput, latency and growth. We start with those profiles to pick CPU, RAM and media that meet service targets. This approach keeps cost and risk aligned with expected demand.

Ceph tuning essentials

OSD daemons typically need ~4 GB of ram each. Placing journals, WAL or DB on NVMe drives materially reduces write latency and tail amplification.

Balance CPU cores between OSDs, recovery tasks and client IO. Use 10 Gbps or higher networks and tune NUMA/IRQ to feed disks at line rate.

vSAN policies and host configuration

Virtual san uses cache and capacity tiers; policies control FTT, stripe width and RAID choices. Enable dedupe and compression only after validating CPU headroom — these services increase cpu use.

For Australian builds, three all‑flash HCI hosts (dual‑socket, 1 TB ram, ~60 TB per host) with 100G switching give ample headroom for growth.

• Check drive endurance (DWPD) and thermal profiles.
• Keep firmware, drivers and BIOS uniform for predictable IO behaviour.
• Set realistic linear scaling expectations as nodes and media are added.

Networking considerations: from 10GbE to 100G in Australian data centres

Network design is the single biggest determinant of steady‑state storage performance at scale. We focus on practical checks that stop silent bottlenecks and speed recovery when a node or device fails.

Separate storage networks and MTU alignment

Use dedicated storage VLANs or physical separation to protect throughput and isolate broadcast domains. Consistent MTU end‑to‑end matters — jumbo frames reduce CPU load and increase effective throughput.

East‑west traffic, latency and scaling

Both ceph and vSAN depend on low‑latency, high‑bandwidth east‑west links during resyncs and rebuilds. Australian sites commonly use 100G core/leaf fabrics for HCI and SDS backplanes to avoid hotspots.

“Misaligned MTU or hashing anomalies can silently halve effective throughput — validate at switch and host.”

• Tune queue depths, RSS and NUMA locality to lower tail latency.
• Apply DCB/QoS in multi‑tenant fabrics and monitor packet loss closely.
• Set Grafana/Prometheus alerts for latency variance and >0.1% packet loss thresholds.

Network readiness checklist: validate MTU, LACP hashing, buffer profiles, and end‑to‑end path. Test rebuild traffic to size uplinks and set QoS. Do this before production data lands on the cluster.

Data protection, fault tolerance and recovery models

Protecting business data starts with a clear recovery model tailored to real operational failure modes. We compare replication, coding and policy approaches so you can choose pragmatically for your environment.

Replication, erasure coding and failure domains

Replication defaults to a factor of three in many systems, giving simple, fast recovery with predictable performance and strong fault tolerance.

Erasure coding reduces capacity overhead but adds CPU and network cost during writes and rebuilds. Model trade-offs for your workload mix — capacity‑heavy archives differ from latency‑sensitive VMs.

Use placement maps to encode racks, rooms and sites. Mapping physical failure domains prevents correlated losses and keeps rebuilds local where possible.

Policy-driven tolerance, self‑healing and rebuild behaviour

Hypervisor storage policies express FTT and RAID choices. These policies control how object components are placed and how self‑healing runs after a fault.

Recovery kinetics depend on available bandwidth, queue depths and background IO throttling. Throttle too little and foreground IO suffers; throttle too much and restores take longer.

• Block-level rebuilds increase write amplification and can raise tail latency — monitor closely.
• Maintain ~20% capacity headroom so objects remain compliant after a failure without cascading risk.
• Test with disk pulls, node isolation and planned maintenance to validate tolerance assumptions in real cases.

Codify runbooks that assign roles, priorities and configuration flags for fast, repeatable response. Combine those runbooks with governance reviews so protection intent keeps pace with hardware and topology changes.

Scalability and growth: nodes, clusters and multi‑site options

Scaling storage is more than adding disks — it changes networking, cooling and operational practices. We look at how growth patterns affect cluster design, predictable performance and ongoing costs for Australian sites.

Scale models differ: one approach adds OSD nodes to grow capacity independently. The other grows as you add ESXi hosts to the same vSphere cluster and supports stretched configurations for site resilience.

Plan by number: define failure domains, rack counts and growth cadence to avoid painful rebalances. More nodes increase parallelism and improve throughput — but they add power, cooling and cabling needs.

• Multi‑site: design latency budgets, quorum and inter‑site links before any data lands.
• Performance guardrails: set east‑west bandwidth per node and decide when to move to 25/40/100G backbones.
• Maintenance: use rolling upgrades, drain/rebuild policies and workload placement to limit disruption.

In short, choose the model that matches your workload and skillset — massive petabyte growth favours independent scale‑out, while virtualised estates gain predictable scaling inside vSphere. This gives clear paths for sustainable performance and cost control.

Operational complexity and day‑two management

How teams run, observe and patch storage after deployment determines real business value more than initial performance numbers.

Operational management is about predictable routines: alerts, upgrades and capacity planning. Complexity increases with scale and mixed workloads. We focus on practical controls that lower risk for Australian sites.

Monitoring with Dashboard, Prometheus and Grafana

Dashboard plus Prometheus and Grafana provides deep telemetry and flexible dashboards. This stack exposes latency, backlog and rebuild metrics so teams can act quickly.

Automation via Ansible or Terraform reduces manual steps for lifecycle tasks. Track cpu and memory overhead for telemetry and data services before enabling heavy features.

vSAN workflows and operational simplicity

The vSphere Client keeps provisioning, policy and health in one pane. This reduces cognitive load for small teams and speeds common tasks like policy changes and capacity checks.

PowerCLI and integrated tooling help automate routine work and lock down configuration drift. That lowers the risk of ad‑hoc changes that create outages.

• Plan maintenance: schedule windows for rebalances and upgrades; track cpu and IO during restores.
• Governance: define who owns policies, pool design and patch orchestration.
• Runbooks & KPIs: time to restore redundancy, backlog burn rate and change failure rate.
• Automation: Ansible/Terraform for lifecycle tasks; PowerCLI for vSphere automation.

Choosing storage solutions is a management decision: convenience and speed favour vSAN while separate telemetry and broader features favour the flexible option. Align roles, document runbooks and measure KPIs to reach production maturity.

Costs, licensing and total cost of ownership in Australia

A realistic TCO view combines upfront hardware outlay with ongoing support, networking and skills.

We compare licensing models so you can see real cost drivers. Proprietary licences and support for vsan add predictable fees and vendor SLAs. Open‑source software like ceph avoids licence costs but shifts spend to staff and enterprise support contracts.

Hardware, networking and skills as part of TCO

Major TCO items are obvious: servers, disks, switches and high‑speed network fabric. An Australian HCI example (three dual‑socket, 1 TB RAM, all‑flash 60 TB hosts with 100G switching) sits near AU$180k — before backup targets and replication.

Operational costs matter: cpu and RAM for data services, staff training, and support subscriptions. Backup infrastructure — Veeam to TrueNAS and dark fibre replication — increases resilience and recurring costs.

• Procurement levers: standardise BOMs, align warranties with refresh cycles.
• Scalability economics: adding hosts or OSD nodes changes marginal cost per usable TB.
• Configuration impact: dedupe/compression, replication factors and erasure coding each alter usable capacity and performance.

In practice, VMware‑centric estates often favour virtual san for lower operational overhead. Large, diverse deployments favour open options when teams can absorb hardware and networking costs. We recommend modelling both scenarios against local Australian prices and your expected growth number to find the true payback period.

Ceph vs vSAN: use cases and real‑world scenarios

Different workloads demand distinct storage patterns — we map practical use cases to infrastructure choices for Australian sites.

VM workloads, VDI and private clouds

vSAN is ideal for virtual machines and VDI. It gives policy‑based provisioning and fast provisioning in vSphere.

That case suits teams that need predictable performance and simplified lifecycle operations.

Kubernetes, AI/ML, big data and object storage

We position ceph for mixed workloads — block for VM disks, file for shared content and object for analytics and backups.

Large pipelines benefit from high throughput across many devices and nodes. These setups need extra cpu, RAM and network headroom for steady performance.

Backup and DR targets

Common patterns pair Veeam to S3‑compatible RGW or CephFS shares. Australian teams often mirror TrueNAS offsite for DR over dark fibre.

Practical adoption tip: start with object backups on the flexible platform while keeping core VM workloads on vSphere to de‑risk change.

Best‑practice deployment checklists and configuration tips

A disciplined configuration process turns a fast build into a reliable, repeatable deployment. Below we list practical checks for cluster configuration, network readiness and operational management before production cutover.

Ceph: pool, replication and OSD layout

Pool design: set quotas, choose replication factor 3 for most pools and use erasure coding for archive pools where capacity matters over write latency.

CRUSH and failure domains: map failuresets to racks and rooms so rebuilds stay local when possible.

OSD layout: place journals/WAL/DB on NVMe, give each OSD adequate ram and reserve cpu for recovery jobs.

vSAN: policies, host uniformity and health

Policy baselines: define FTT, RAID and stripe width in policy templates and test their impact in staging.

Host builds: keep drives, firmware and BIOS identical across nodes and maintain disk group symmetry for predictable performance.

Health checks: schedule daily checks and automate proactive remediation via the management plane.

Networking, observability and runbooks

• MTU consistency and QoS for storage VLANs — validate jumbo frames end‑to‑end.
• Redundant fabrics and failover tests for each node and uplink.
• Exporters, Prometheus/Grafana dashboards and alerts for latency percentiles, resync debt and capacity burn.
• Runbooks: node evacuation, rolling upgrades and emergency rebuild throttling.

“Validate configuration with a pre‑production soak and mixed read/write profiles before the cutover.”

Acceptance criteria: successful soak test, runbooks verified, RBAC and audit trails in place, and management alerts green. Only then move to production.

Ceph vs vSAN: which solution fits your environment?

A practical decision balances immediate platform fit with long‑term scale and management overhead.

We focus on how each solution aligns to current platform choices and future ambitions. For a vSphere‑first estate, the hypervisor‑native path delivers tight policy control and lower day‑two overhead.

For multi‑platform environments that need block, file and object, the unified fabric favours scale‑out throughput and protocol breadth. That option asks for more operational skills and network planning.

• Workload fit: latency‑sensitive VMs => hypervisor policy model; analytics and object stores => distributed fabric.
• Management: single‑pane policies reduce toil; separate clusters give deeper control over data services.
• Scale & topology: consider number of racks, failure domains and how a cluster grows.
• Procurement: count hosts, licences and support models when you cost both solutions.

Recommendation: choose the solution that maps to your dominant workloads and skills. If you standardise on vSphere, favour the hypervisor path. If you must serve containers, analytics and object targets at scale, favour the unified fabric and plan for the operational lift.

Conclusion

The right storage approach lets you balance predictable performance with flexible scale.

For VMware‑centric estates we recommend the hypervisor path—vSAN delivers tight policy control, low‑latency data paths and simpler day‑two operations. That path reduces toil and gives predictable performance for VM fleets.

For mixed platforms we recommend the unified fabric—Ceph offers block, file and object from one cluster and scales across multiple workloads. Use that option where flexibility and growth are priorities.

Clusters, node design and network choices remain the top levers to meet SLAs. Run a proof‑of‑value: measure latency, throughput and rebuild behaviour under realistic load before committing.

Next steps: uplift skills, test a reference architecture and codify runbooks so your storage, data and network choices deliver reliable outcomes at scale.