2026 IT Reality Check: Rising Compute Costs, Rising Security Risk

Compute costs are rising, and memory and SSDs are the reason

For years, compute planning was CPU-centric: pick instance sizes, estimate utilization, then negotiate discounts. That logic is now incomplete. Modern workloads increasingly behave like this:

• Memory-bound: performance is limited by available RAM and memory bandwidth, not raw CPU cycles.
• Storage-dependent: fast SSD is required for caching, scratch, logs, analytics, and ML pipelines.
• Network-sensitive: east-west traffic between services becomes the bottleneck, raising both cost and security complexity.

AI makes this more extreme, but it is not only AI. Data platforms, real-time reporting, containerized apps, modern backup, and security telemetry all push in the same direction: more memory, more fast storage, more I/O.

What the market is telling us

Analysts tracking server and memory markets are pointing to sustained AI-driven demand. TrendForce expects global AI server shipments to grow by more than 28% year over year in 2026, with total server shipments up 12.8%. That demand concentrates on the same inputs that drive your costs: DRAM, high-bandwidth memory, and enterprise SSD supply.

TrendForce also notes a widening gap between DRAM and NAND revenue, reflecting how strongly demand is pulling DRAM capacity and pricing. When suppliers prioritize higher-margin server and AI products, “normal” enterprise purchasing often gets pushed into the leftovers lane. That is why even non-AI shops can see pricing pressure.

A real-world example: enterprise SSD pricing shock

Storage cost volatility is not theoretical. Recent reporting on enterprise SSD market conditions shows dramatic price jumps for high-capacity drives. Even if your organization is not buying 30TB data center SSDs, the same supply constraints ripple into mainstream SKUs through longer lead times and tighter discounts. When storage gets expensive, compute gets expensive too because storage is part of the performance envelope.

Key cost signals to watch in 2026

Budgeting based on 2023 to 2024 assumptions is risky

If your budget model still assumes that compute costs track mostly with vCPU, you will get surprised. The biggest “silent” drivers in 2026 are:

• Memory per workload: data platforms, security tools, and modern apps keep expanding their resident set size.
• SSD tiers and write amplification: caches and scratch volumes burn through high performance storage faster than expected.
• Telemetry growth: logs, metrics, traces, and endpoint data are exploding, especially with modern security stacks.
• Data movement: moving data between regions, clouds, and SaaS tools can quietly become a top-three cost.

Practical move: treat memory and storage as first-class budget line items, not a footnote under “servers” or “cloud.” Finance teams like clarity. Give them clarity.

On-prem and cloud: different wrappers, same physics

On-prem, rising component costs tend to show up as higher quotes, less discounting, and longer lead times. In the cloud, the same pressure can surface as fewer “sweet spot” instance options, changing reserved pricing dynamics, and a need to shift to right-sized memory-optimized families. The takeaway is not “cloud is bad” or “on-prem is bad.” The takeaway is: you need a plan that is cost-aware and portable. Lock-in is expensive when the price curve is moving.

FinOps in 2026: treat memory and storage as first-class citizens

Here is the uncomfortable truth: most “cloud optimization” projects are still doing 2019 math. They look at vCPU utilization, maybe commit to reserved instances, and call it a day. That is not enough in 2026, because the expensive parts of the bill are increasingly tied to RAM, storage tiering, IOPS, and data movement.

Seven levers that actually move the number

1. Right-size by memory, not just CPU: identify workloads that sit at 20% CPU but 85% RAM. Those are the bill-busters.
2. Engineer caching intentionally: unmanaged caches tend to sprawl and eat SSD. Manage cache size, eviction, and TTLs like you manage budget.
3. Tier storage aggressively: hot, warm, and cold tiers should have explicit policies. “Everything on the fastest disk” is a luxury tax.
4. Reduce I/O amplification: log storms, chatty microservices, and noisy jobs can turn storage into a furnace. Fixing the architecture is often cheaper than paying the meter.
5. Control data egress: data movement between clouds, regions, and SaaS tools is a silent cost center. If you cannot explain egress, you cannot control it.
6. Watch telemetry growth: observability is mandatory, but infinite retention is not. Set retention and sampling based on business needs.
7. Keep portability real: vendor lock-in is how repricing becomes a hostage situation. Design for clean exit paths and competitive pressure.

Architecture patterns that reduce cost without reducing capability

Cost control does not mean “do less.” It means do things on purpose. A few patterns that consistently help in 2026 environments:

• Data lifecycle by design: define what is hot, warm, and cold, and automate tiering. Storage is expensive when you keep everything on premium tiers forever.
• Cache discipline: set budgets for caches the same way you set budgets for ads. Caches grow if you let them. They behave if you govern them.
• Event-driven processing: stop polling and start reacting. Polling architectures generate predictable waste.
• Right-sized observability: collect what you need, retain what you must, and sample what you can. Observability should be a control system, not a data landfill.
• Hybrid by intent: place workloads where they are cheapest and safest to run, not where they landed historically.

Who owns which lever

None of these levers require magic. They require operating discipline. In 2026, that discipline is a competitive advantage.

If you only remember a few facts, remember these. They help executives understand why the cost curve is moving and why security posture has to keep up.

Security risk is escalating, and AI is speeding up attackers

Infrastructure costs get attention because they hit your P&L quickly. Security risk can be quieter until it is not. In 2026, the risk picture is intensifying for three reasons:

1. AI-enabled attacker workflows: threat actors can automate parts of the attack lifecycle, from reconnaissance to phishing and exploitation.
2. Distributed architecture reality: microservices, SaaS sprawl, and hybrid networks increase lateral movement opportunities.
3. Identity is the front door: stolen credentials remain a dominant driver in common breach patterns.

Speed changes everything

When attack speed increases, your response model has to change. The question stops being “can we block everything?” and becomes “can we detect and contain fast enough to keep impact small?” That is why continuous monitoring, strong identity controls, and tested recovery plans matter more than a one-time security audit.

Identity is still the main event

Verizon’s DBIR keeps reinforcing an unglamorous truth: credential abuse sits near the center of many breaches, especially web application attacks. If your identity controls are average, your risk is above average. Practical improvements that move the needle include phishing-resistant MFA where possible, conditional access, privileged access management, and reducing long-lived credentials.

East-west traffic: the attack surface you do not see

Modern environments are chatty. Services talk to services. Containers talk to APIs. SaaS talks to identity. That east-west traffic is a productivity win, but it is also a visibility and segmentation challenge. If you cannot see it, you cannot protect it. And if you cannot protect it, attackers will move through it.

Zero Trust is not a buzzword in 2026

Zero Trust is a practical response to distributed reality. NIST’s Zero Trust Architecture guidance frames the shift away from static network perimeters toward continuous verification, least privilege, and strong identity controls. CISA’s Zero Trust Maturity Model provides a structured way to evaluate and plan improvements across core pillars.

Canada-specific context for SMB leaders

If you operate in Canada, the National Cyber Threat Assessment 2025 to 2026 from the Canadian Centre for Cyber Security is worth reading as a leadership team. It highlights the evolving threat environment and underscores why cyber risk is a business risk, not just an IT concern. Even if you do not have a dedicated security team, you can still implement the foundational controls that reduce real-world risk.

Shadow AI: the new shadow IT, but with higher stakes

Shadow IT used to mean “someone bought a SaaS tool.” Shadow AI can mean “someone pasted sensitive data into an AI tool” or “a team deployed an AI agent with access it did not earn.” Governance bodies and industry groups have been warning that unauthorized AI usage introduces data leakage, compliance exposure, and audit headaches.

Managing this does not require banning AI. It requires treating AI usage as a governed capability, like payments processing or customer data handling.

A practical governance checklist

• Approved tools list: define which AI tools are permitted for work use, and under what conditions.
• Data classification rules: specify which data classes can be used with AI tools (and which cannot).
• Logging and monitoring: track AI tool usage, especially where sensitive data could be exposed.
• User training: explain safe prompts, unsafe prompts, and common data leakage patterns.
• Vendor review: evaluate retention, training, and data handling practices for any AI vendor you approve.
• Incident process: define what to do if sensitive data is shared with an unapproved tool.

For structure, align your approach to a recognized framework like the NIST AI Risk Management Framework. The goal is not paperwork. The goal is predictable behavior and audit-ready decisions.

The MASP communication gap is an operational liability

Many Managed Application Service Providers are still running an uptime-era playbook: tickets, patching, backups, and vague “security.” That is table stakes. In 2026, you need your provider to be your early warning system. If you are not getting proactive briefings on cost drivers and risk drivers, you are paying for silence.

What you should expect from any serious provider in 2026

A quick self-check

If your provider cannot answer those questions with evidence, not opinions, you have a planning problem. And planning problems become budget problems. In 2026, that is a painful and avoidable loop.

DiskIT’s approach: visibility first, then optimization

DiskIT helps SMBs and partners navigate 2026 with one principle: decisions are only good when they are informed. That means combining FinOps discipline with security architecture, and translating both into executive-ready reporting.

30 days: stabilize visibility

• Baseline cloud and on-prem run-rate, including memory and storage drivers.
• Inventory data flows, including SaaS and AI tooling usage.
• Identify the highest risk identity paths (privileged accounts, MFA gaps, legacy authentication).
• Confirm backup integrity and recovery time objectives through testing, not hope.

90 days: reduce exposure and avoid waste

• Right-size memory and storage allocations based on measured demand.
• Implement Zero Trust building blocks: stronger identity, segmentation, device posture, continuous monitoring.
• Harden web-facing services and reduce credential risk with conditional access and least privilege.
• Establish cost guardrails: budgets, alerts, and tagging that tie spend to owners.

180 days: build for the long game

• Modernize architectures for portability: hybrid patterns, vendor-agnostic tooling, and clean exit paths.
• Adopt AI governance aligned to NIST AI RMF, including policies for data classes and model usage.
• Establish quarterly forecasting and scenario planning for compute and storage volatility.
• Run tabletop incident exercises so executives and IT operate from the same script under pressure.

What you get at the end of the process

• A cost model that reflects 2026 reality, including memory, storage, and data movement drivers.
• A security posture that reduces credential risk and lateral movement opportunities.
• Visibility: dashboards and executive summaries that translate technical choices into business outcomes.

The takeaway

In 2026, compute is getting more expensive, and security risk is rising. The organizations that win will be the ones with visibility and forecasting, not the ones reacting to surprises. If your provider is not preparing you for AI-driven infrastructure economics and an accelerating threat landscape, it is time to upgrade the partnership.

Ready for clarity? DiskIT can help you build a cost-aware modernization plan and a security-first architecture that supports growth without chaos. Explore Managed IT services in Toronto and request an executive readiness review.

References

1. TrendForce: Global AI Server Shipments Forecast to Grow Over 28% YoY in 2026
2. TrendForce: AI Architecture Evolution Set to Drive Memory Market
3. Financial Times: Chip shortages and memory pressure (HBM and DRAM)
4. Tom’s Hardware: Enterprise SSD price shock linked to NAND shortage
5. Microsoft Digital Defense Report 2025
6. Verizon 2025 Data Breach Investigations Report
7. NIST SP 800-207: Zero Trust Architecture
8. CISA: Zero Trust Maturity Model v2.0
9. NIST AI RMF 1.0
10. Canadian Centre for Cyber Security: National Cyber Threat Assessment 2025-2026