RSAM — Resource Allocation Module
Architecture:
VEGA™ — Value Execution Governance Architecture
Parent Standard:
Resource Governance Standard (RGS)
Category:
Governance & Enforcement
Subcategory:
Value Execution Governance
Type: Core Module
Governed Space:
Execution Resource Allocation
Module ID: VEGA-RGS-RSAM-002
Origin ID: OOF.CM.VEGA.04.02.01
Version: 1.0
Status: Canonical · Open Standard
Effective Date: 28 September 2026
Compatibility: OOF® Methodology OS™ · Modular OOF® Architecture Ecosystem
AI-Readable: Yes
Authority: OOF® — OriginOpen® Foundation
Protection:
MIP® — Methodological Intellectual Property
Canonical Language:
English (UCL™)
1. Canonical Definition
The Resource Allocation Module (RSAM) governs how identified execution resources are assigned to an intelligence execution in quantities, capacities, durations, and configurations proportionate to the Operational Requirement and applicable governed constraints.
RSAM converts the Governed Execution Resource Inventory established by RIM into an explicit Governed Resource Allocation State.
It determines which identified resources should be allocated, how much should be allocated, to which execution object, for what operational purpose, for what duration, and under what allocation conditions.
RSAM prevents resource availability, historical provisioning, technical capacity, or maximum possible demand from automatically becoming resource allocation.
Its principal output is:
Governed Resource Allocation State
Its foundational distinction is:
Available Capacity ≠ Required Allocation.
2. Operational Role
The operational role of RSAM is:
to translate identified execution resource requirements into explicit, proportionate, bounded, and evidence- supported resource allocations.
RIM establishes what resources belong to the execution resource system.
RSAM determines what portion of those resources should actually be assigned to the execution.
3. Position in the RGS Internal Flow
The RGS internal module progression is:
Resource Identification → Resource Allocation → Dynamic Reallocation → Resource Constraint → Consumption Traceability
RSAM governs:
Resource Allocation
Its principal input is:
Governed Execution Resource Inventory
Its principal output is:
Governed Resource Allocation State
That output proceeds to:
DRRM — Dynamic Resource Reallocation Module
4. Central Operational Question
Which identified resources should be allocated to the intelligence execution, in what quantity, for what purpose, and for how long?
5. Allocation Object
Every allocation should identify the execution object receiving the resource.
An Allocation Object may be:
a model execution,
agent,
multi-agent system,
workflow,
task,
service,
robotic operation,
human-AI process,
or another governed intelligence execution object.
6. Resource Allocation Object
The resource being allocated should correspond to an identified Resource Object within the governed resource inventory.
Allocation should not be based upon an undefined resource category where a more precise Resource Object is materially necessary.
7. Allocation Requirement
An Allocation Requirement expresses the resource capacity necessary to support the defined execution under the applicable Operational Requirement.
It should derive from execution need rather than technical availability.
Therefore:
Resource Availability ≠ Allocation Requirement.
8. Allocation Basis
Every material allocation should possess an identifiable Basis.
The Basis may include:
task requirements,
expected workload,
execution configuration,
completion requirements,
quality requirements,
latency requirements,
reliability requirements,
resilience requirements,
applicable constraints,
or another legitimate operational condition.
9. Allocation Purpose
The purpose for which a resource is allocated should be identifiable.
Possible purposes include:
primary execution,
reasoning,
tool use,
validation,
memory,
orchestration,
storage,
communication,
resilience,
or another execution function.
10. Allocation Quantity
RSAM should establish the quantity or capacity allocated where the resource can be meaningfully quantified.
The appropriate unit depends upon the Resource Object.
No universal allocation unit is required.
11. Minimum Sufficient Allocation
Where determinable, the allocation should support the minimum resource level sufficient for the execution to reliably satisfy its Operational Requirement under applicable governed constraints.
Minimum sufficient allocation does not mean minimum possible allocation.
It means:
the least allocation sufficient to support the required governed execution.
12. Allocation Sufficiency
An allocation is sufficient where the assigned resources adequately support the execution requirement under the applicable operating conditions.
Sufficiency should be evaluated against the Operational Requirement rather than against theoretical maximum performance.
13. Allocation Insufficiency
Allocation Insufficiency exists where assigned resources cannot reliably support the required execution.
Possible consequences may include:
failure,
latency,
reduced reliability,
incomplete execution,
or escalation need.
RSAM identifies the allocation state.
DRRM governs subsequent reallocation.
14. Allocation Excess
Allocation Excess exists where assigned resources materially exceed the level justified by the current execution requirement without sufficient operational Basis.
Therefore:
More Allocation ≠ Better Resource Governance.
15. Allocation Proportionality
Allocation should remain proportionate to the governed execution need.
Proportionality may consider:
task complexity,
workload,
required performance,
required reliability,
and applicable constraints.
16. Allocation Precision
Resource allocation may be:
exact,
bounded,
tiered,
estimated,
or dynamically parameterized.
The level of precision should reflect the available evidence and resource characteristics.
17. Allocation Range
Where an exact quantity cannot be justified, RSAM may establish an acceptable allocation range.
A range may include:
minimum sufficient level,
normal operating range,
and maximum governed allocation.
18. Allocation Floor
An Allocation Floor establishes the minimum resource provision required for the governed execution under defined conditions.
The floor should have an operational Basis.
19. Allocation Ceiling
An Allocation Ceiling establishes the maximum resource allocation permitted under the current allocation state.
The ceiling may derive from:
operational requirements,
resource constraints,
budgets,
technical conditions,
or competent governance.
20. Allocation Target
An Allocation Target may define the intended normal resource level between applicable floors and ceilings.
A target is not necessarily a hard constraint.
21. Allocation Margin
Some executions may require a justified resource margin above expected normal demand.
Margins may support:
workload variability,
reliability,
resilience,
or predictable demand fluctuation.
A margin should not become an undefined justification for chronic overprovisioning.
22. Allocation Reserve
A resource reserve may be maintained for conditions requiring additional capacity.
Reserved capacity should remain distinguishable from active allocation and actual consumption.
Therefore:
Reserved Capacity ≠ Active Consumption.
23. Dedicated Allocation
A Dedicated Allocation assigns resource capacity primarily or exclusively to a defined execution object.
Dedicated allocation may be justified by:
performance,
isolation,
reliability,
security,
or another governed requirement.
24. Shared Allocation
A Shared Allocation permits multiple execution objects to use a common resource pool.
Shared allocation should preserve sufficient governance to understand:
eligible users,
available capacity,
allocation logic,
and material contention.
25. Allocation Pool
Resources may be allocated from a common pool rather than individually reserved.
The pool should have sufficiently defined:
capacity,
scope,
eligible execution objects,
and allocation conditions.
26. Allocation Priority
Where demand exceeds available resource capacity, allocations may require prioritization.
Priority should derive from an authorized Basis.
RSAM may represent the priority state.
It does not independently create institutional authority to establish priority.
27. Priority Class
Where appropriate, allocation may use defined priority classes.
The classification methodology should remain explicit and should not automatically equate technical urgency with organizational importance.
28. Allocation Sequence
Where multiple Resource Objects must be assigned, the order of allocation may matter.
Some resources may be prerequisites for others.
RSAM may preserve allocation sequence where operationally material.
29. Allocation Dependency
An allocation may depend upon another resource being available or allocated.
For example:
tool access may require network capacity,
a model may require compatible hardware,
or a validation service may require additional compute.
Dependent allocations should remain connected.
30. Coupled Allocation
Some Resource Objects should be allocated together because their requirements are operationally coupled.
Independent allocation of coupled resources may create apparent sufficiency while the execution remains unusable.
31. Conditional Allocation
Some resources should be allocated only when defined execution conditions arise.
Conditional allocation may prevent resources needed only for exceptional cases from being permanently provisioned.
32. Triggered Allocation
A resource may become allocated when a defined trigger occurs.
Examples may include:
complex task classification,
tool requirement,
validation requirement,
or escalation state.
The trigger should remain explicit.
33. Persistent Allocation
Some resources remain allocated across multiple executions.
Persistent allocation should retain a continuing operational Basis.
Therefore:
Historical Need ≠ Permanent Allocation Need.
34. Temporary Allocation
Temporary Allocation exists for a bounded task, period, state, or execution condition.
Temporary allocation should possess an identifiable termination or review condition where appropriate.
35. Allocation Duration
The allocation period should be explicit where duration materially affects resource governance.
Duration may be:
execution-specific,
time-bound,
state-bound,
or persistent subject to review.
36. Allocation Start
Where relevant, RSAM should identify when an allocation becomes active.
This may occur:
before execution,
at execution start,
on demand,
or following a defined trigger.
37. Allocation End
Where relevant, an allocation should possess a condition under which it ceases to apply.
This may include:
completion,
termination,
expiry,
release,
configuration change,
or another governed event.
38. Allocation Expiry
Time-bounded allocations should not silently persist beyond their legitimate period.
Where applicable:
Expired Allocation ≠ Current Allocation Authority.
39. Allocation Renewal
Persistent or expiring allocations may require renewal.
Renewal should be based upon current operational need rather than historical allocation alone.
40. Allocation Review
Allocation should be reviewed where:
Operational Requirement changes,
Execution Configuration changes,
workload changes materially,
resource availability changes,
performance changes,
or evidence indicates persistent insufficiency or excess.
41. Allocation State
RSAM may represent allocation states such as:
Not Allocated,
Allocation Proposed,
Allocation Approved,
Allocated,
Conditionally Allocated,
Reserved,
Insufficient,
Sufficient,
Excessive,
Expired,
Suspended,
Released,
or Reassessment Required.
42. Allocation State Transition
Allocation governance should support transitions such as:
Identified → Proposed → Allocated → Active → Released
or:
Allocated → Insufficient → Reallocation Required
or:
Allocated → Excessive → Reduction Required
43. Allocation Evidence
Material allocations should be supported by evidence appropriate to the intended governance purpose.
Evidence may include:
resource requirements,
workload data,
execution configuration,
historical utilization,
performance requirements,
or another relevant Basis.
44. Allocation Assumption
Where allocation depends upon an assumption, that assumption should remain explicit.
Examples may include:
expected task volume,
expected complexity,
expected concurrency,
or expected latency requirement.
45. Allocation Uncertainty
Resource requirements may not always be known precisely.
Where uncertainty exists, RSAM should represent it rather than create artificial precision.
Allocation may therefore include justified uncertainty margins.
46. Allocation Confidence
Where useful, an allocation may include an evidence-based confidence state reflecting the strength of the allocation Basis.
Confidence should not replace the underlying evidence.
47. Allocation Validation
Where required, allocation assumptions or quantities may be validated against observed execution.
Validation may reveal:
insufficiency,
excess,
or incorrect assumptions.
The resulting evidence may trigger reassessment or reallocation.
48. Allocation vs Consumption
Allocation establishes resource availability for execution.
Consumption establishes actual resource use.
Therefore:
Allocated Resource ≠ Consumed Resource.
RCTM governs Consumption Traceability.
49. Allocation Utilization
Utilization may indicate how much of allocated capacity is actually used.
Low utilization may indicate:
legitimate reserve,
variable demand,
or overprovisioning.
RSAM should not assume the cause without evidence.
50. Chronic Underutilization
Persistent underutilization may justify reassessment of allocation.
However, low utilization alone does not prove allocation excess where reserve capacity serves a legitimate requirement.
51. Allocation Overprovisioning
Overprovisioning occurs where allocated capacity materially exceeds justified need.
It may be legitimate where the additional capacity supports:
resilience,
peak demand,
or another governed purpose.
The justification should remain explicit.
52. Allocation Underprovisioning
Underprovisioning occurs where assigned resources are insufficient to support required execution.
Persistent underprovisioning may create:
failure,
rework,
latency,
or reduced reliability.
53. Allocation and Workload
Resource allocation should reflect relevant workload characteristics.
These may include:
volume,
complexity,
concurrency,
variability,
and timing.
Workload estimates should remain distinguishable from actual workload.
54. Allocation and Task Complexity
More complex tasks may require additional resources.
Complexity should not automatically be translated into greater allocation without evidence of resource need.
Therefore:
Higher Task Complexity ≠ Automatic Maximum Allocation.
55. Allocation and Concurrency
Concurrent execution may increase resource requirements.
RSAM should consider relevant concurrency where it materially affects resource sufficiency.
56. Allocation and Latency
Some operational requirements impose latency conditions that legitimately affect allocation.
Additional resource capacity may be justified where necessary to satisfy the required latency state.
57. Allocation and Reliability
Reliability requirements may justify:
redundancy,
reserve capacity,
or other additional resource allocation.
The relationship should remain explicit.
58. Allocation and Resilience
Resilience requirements may justify resource capacity that is not continuously consumed.
Therefore:
Unused Resilience Capacity ≠ Waste by default.
The resilience Basis should remain governable.
59. Allocation and Model Selection
Different models may require materially different resource allocations.
RSAM does not determine which model should be selected.
COS governs relevant optimization.
RSAM governs the resources assigned to the selected execution configuration.
60. Allocation and Agents
Multi-agent systems may require separate allocations for:
individual agents,
coordination,
shared context,
tools,
validation,
and orchestration.
Agent count alone does not determine allocation requirement.
61. Allocation and Human Support
Where human support forms part of the Execution Configuration, relevant human capacity may be allocated.
This may include:
review capacity,
exception handling,
validation,
or operational supervision.
RSAM does not govern employment or staffing policy.
62. Allocation and Hardware
Hardware capacity may be allocated where required for execution.
The existence of higher-performance hardware does not create a requirement to use it.
Therefore:
Available Hardware Capability ≠ Required Hardware Allocation.
63. Allocation and Compute
Compute allocation should correspond to the requirements of the governed Execution Configuration.
RSAM determines allocation state.
COS determines computational optimization.
64. Allocation and Energy
Execution-related energy capacity may form part of resource allocation where material.
RSAM does not govern energy generation, markets, or broader energy allocation systems.
65. Allocation and Cost
Allocation may create economic consequences.
RSAM does not determine whether the resulting cost is justified by Value.
IES governs economic treatment.
Therefore:
Resource Allocation ≠ Economic Justification.
66. Allocation and Productivity
Additional resource allocation may improve productivity, have no material effect, or reduce overall efficiency.
IPS governs productivity.
Therefore:
More Resources ≠ More Productivity by default.
67. Allocation and Value
A resource allocation may support high-Value or low-Value execution.
VGS governs Value.
Therefore:
Resource Allocation ≠ Value Creation.
68. Allocation and Authority
The technical ability to allocate a resource does not establish authority to allocate it.
Applicable authorization and governance constraints remain external to RSAM where appropriate.
Therefore:
Allocation Capability ≠ Allocation Authority.
69. Allocation and Permission
Resource allocation should remain compatible with applicable permissions.
Optimization pressure does not override permission boundaries.
Therefore:
Optimization ≠ Permission.
70. Allocation and Governed Constraints
RSAM must respect constraints established by competent governance sources.
It may determine an appropriate allocation within those constraints.
It does not weaken constraints to improve execution performance.
71. Allocation Conflict
An Allocation Conflict exists where execution requirements cannot be satisfied within the available resources and applicable constraints.
The conflict should become explicit.
It should not be hidden by uncontrolled allocation.
72. Allocation Exception
An Allocation Exception may temporarily permit a different resource state under a legitimate governed Basis.
Exceptions should be:
identified,
bounded,
evidenced,
and reassessed.
73. Allocation Exception Expiry
Temporary allocation exceptions should have a defined:
expiry,
review condition,
or termination trigger
where appropriate.
74. Allocation Drift
Allocation Drift occurs where actual allocation progressively departs from the intended governed allocation state without explicit reassessment.
Possible causes include:
configuration changes,
workload changes,
manual intervention,
or historical provisioning.
75. Allocation Lock-In
A resource allocation may become difficult to reduce because of:
technical dependencies,
architecture,
contractual arrangements,
or operational design.
RSAM may identify the allocation condition.
ISS and DGS may govern broader dependency and lifecycle consequences.
76. Allocation Reassessment
Reassessment should occur where material evidence indicates that the existing allocation no longer reflects the current Operational Requirement.
The objective is not constant reallocation.
It is continued allocation legitimacy.
77. Allocation Versioning
Material changes to:
allocation quantity,
duration,
Basis,
resource type,
Execution Configuration,
or applicable assumptions
should remain versioned where required for traceability.
78. Allocation Provenance
A Governed Resource Allocation State should remain traceable to:
Resource Object,
Allocation Object,
Operational Requirement,
allocation Basis,
quantity,
duration,
conditions,
assumptions,
evidence,
version,
and relevant decision state.
79. Allocation Integrity
RSAM should resist:
allocating maximum capacity by default,
treating historical provisioning as current necessity,
treating availability as requirement,
hiding allocation assumptions,
ignoring persistent underutilization,
ignoring underprovisioning,
preserving expired allocations,
using resource abundance as justification for excess,
and weakening governed constraints to increase performance.
The governing principle is:
Allocate resources according to demonstrated execution need, not available technical appetite.
80. Governed Resource Allocation State
The principal output of RSAM is:
Governed Resource Allocation State
It should identify, where applicable:
Allocation Object,
Resource Object,
Allocation Requirement,
Allocation Basis,
Allocation Purpose,
allocation quantity,
minimum sufficient allocation,
sufficiency,
insufficiency,
excess,
allocation range,
floor,
ceiling,
target,
margin,
reserve,
dedicated or shared status,
priority,
dependencies,
conditional allocation,
duration,
start,
end,
expiry,
review state,
assumptions,
uncertainty,
utilization,
overprovisioning,
underprovisioning,
exceptions,
drift,
evidence,
version,
and provenance.
81. Meaning of the Output
A Governed Resource Allocation State establishes what resources are assigned to an intelligence execution and the operational Basis for that assignment.
It may establish that:
allocation is sufficient,
allocation is insufficient,
allocation is excessive,
additional reserve is justified,
an allocation is conditional,
an allocation has expired,
or reassessment is required.
It does not determine dynamic reallocation itself.
That mechanism belongs to DRRM.
82. Minimum Implementation Framework
A conforming implementation of RSAM must provide exactly the following six capabilities:
1. Allocation Object & Requirement Governance
Capability to connect identified Resource Objects with the execution objects and Operational Requirements they support.
2. Allocation Quantity & Sufficiency Governance
Capability to establish quantities, ranges, floors, ceilings, targets, margins, and resource sufficiency states where appropriate.
3. Allocation Condition & Duration Governance
Capability to govern dedicated, shared, conditional, persistent, temporary, triggered, reserved, and time- or state-bounded allocations.
4. Allocation Dependency & Priority Governance
Capability to represent coupled resources, dependencies, priority states, workload conditions, concurrency, reliability, and resilience requirements where relevant.
5. Allocation Evidence & Integrity Governance
Capability to preserve assumptions, uncertainty, utilization evidence, exceptions, drift, versioning, provenance, and reassessment.
6. RGS Dynamic Reallocation Handoff Governance
Capability to produce a Governed Resource Allocation State sufficiently explicit for subsequent Dynamic Resource Reallocation governance.
83. Governance Logic
The canonical RSAM governance logic is:
Governed Execution Resource Inventory
↓
Identify Allocation Object
↓
Identify Relevant Resource Objects
↓
Establish Allocation Requirement
↓
Establish Allocation Basis / Purpose
↓
Assess Workload / Complexity / Concurrency
↓
Apply Applicable Governed Constraints
↓
Determine Minimum Sufficient Allocation
↓
Establish Quantity / Range / Floor / Ceiling
↓
Establish Duration / Conditions / Reserve
↓
Assess Dependencies / Priority / Resilience Requirements
↓
Assess Sufficiency / Insufficiency / Excess
↓
Assess Evidence / Assumptions / Uncertainty
↓
Establish Governed Resource Allocation State
↓
Handoff to Dynamic Resource Reallocation Governance
84. Governance Outputs
RSAM may produce:
Allocation Object
Allocation Requirement
Allocation Basis
Allocation Purpose
Resource Allocation Quantity
Minimum Sufficient Allocation
Allocation Sufficiency State
Allocation Insufficiency State
Allocation Excess State
Allocation Range
Allocation Floor
Allocation Ceiling
Allocation Target
Allocation Margin
Resource Reserve State
Dedicated Allocation State
Shared Allocation State
Allocation Priority State
Allocation Dependency Record
Conditional Allocation State
Allocation Duration
Allocation Start State
Allocation End State
Allocation Expiry State
Allocation Review State
Allocation Assumption Record
Allocation Uncertainty
Allocation Utilization State
Overprovisioning State
Underprovisioning State
Allocation Exception State
Allocation Drift State
Allocation Evidence
Allocation Version
Allocation Provenance
The principal output is:
Governed Resource Allocation State
85. Critical Distinctions
RSAM preserves the following distinctions:
Available Capacity ≠ Required Allocation
Resource Availability ≠ Allocation Requirement
More Allocation ≠ Better Resource Governance
Minimum Sufficient Allocation ≠ Minimum Possible Allocation
Reserved Capacity ≠ Active Consumption
Historical Need ≠ Permanent Allocation Need
Expired Allocation ≠ Current Allocation Authority
Allocated Resource ≠ Consumed Resource
Higher Task Complexity ≠ Automatic Maximum Allocation
Unused Resilience Capacity ≠ Waste by default
Available Hardware Capability ≠ Required Hardware Allocation
Resource Allocation ≠ Economic Justification
More Resources ≠ More Productivity by default
Resource Allocation ≠ Value Creation
Allocation Capability ≠ Allocation Authority
Optimization ≠ Permission
Resource Allocation ≠ Dynamic Resource Reallocation
86. Cross-Architecture Boundary
RSAM governs Resource Allocation within RGS.
RIM governs Resource Identification.
DRRM governs Dynamic Resource Reallocation.
RCM governs Resource Constraint.
RCTM governs Consumption Traceability.
XGS governs intelligence execution.
IPS governs productivity.
COS governs computational optimization.
IES governs execution economics.
ISS governs long-term intelligence sustainability.
VGS governs Value.
DGS governs lifecycle decisions.
VALIDOS™ may govern relevant validation methodology.
ADIT® may govern evidence and auditability.
ORA™ may establish relevant Operational Reality.
RSAM may consume evidence from these governed spaces without replacing their authority or methodology.
87. Canonical Boundary
RSAM begins where RIM has established a sufficiently governed inventory of execution Resource Objects.
RSAM governs:
Allocation Objects,
Allocation Requirements,
Allocation Bases,
Allocation Purposes,
allocation quantities,
minimum sufficient allocation,
allocation sufficiency,
allocation insufficiency,
allocation excess,
allocation precision,
allocation ranges,
floors,
ceilings,
targets,
margins,
reserves,
dedicated allocation,
shared allocation,
resource pools,
priority,
allocation sequence,
dependencies,
coupled allocation,
conditional allocation,
triggered allocation,
persistent allocation,
temporary allocation,
duration,
start,
end,
expiry,
renewal,
review,
allocation states,
state transitions,
assumptions,
uncertainty,
allocation validation,
utilization,
overprovisioning,
underprovisioning,
workload relationships,
task complexity,
concurrency,
latency,
reliability,
resilience,
human-support allocation,
hardware allocation,
compute allocation,
execution-related energy allocation,
allocation conflicts,
exceptions,
drift,
lock-in indicators,
reassessment,
versioning,
evidence,
and provenance.
RSAM does not independently govern:
Resource Identification,
Dynamic Resource Reallocation,
Resource Constraint methodology,
Consumption Traceability,
computational optimization,
productivity,
economic justification,
Value,
Harm,
Liability,
or lifecycle decisions.
RSAM ends when the resource assignment has been represented as a:
Governed Resource Allocation State
for subsequent RGS governance.
88. Use Case 1 — Large Model Receives Maximum Compute by Default
An organization deploys an advanced AI model and automatically provisions the maximum available compute capacity for every execution.
RIM has already established the relevant resource inventory.
RSAM evaluates the actual execution requirement, expected workload, latency requirements, reliability conditions, and applicable constraints.
The resulting allocation may establish a lower normal allocation with justified reserve capacity for exceptional workloads.
The system therefore receives resources according to operational need rather than technical maximum.
Available Capacity ≠ Required Allocation.
89. Use Case 2 — Variable Agent Workload Requires Conditional Resources
A multi-agent workflow handles both routine and exceptional cases.
Routine executions require limited compute and tool access, while exceptional cases require additional agents, specialized tools, validation capacity, and human review.
RSAM establishes a normal resource allocation for routine execution and identifies additional resources as conditional allocations rather than permanently assigning maximum capacity.
The resulting Governed Resource Allocation State preserves both sufficient routine operation and the legitimate ability to support exceptional workloads.
Resources can be available without being permanently allocated.
90. Canonical Closing Statement
A resource should not be allocated because a system can use it.
It should be allocated because the execution requires it.
The difference matters.
Maximum capacity can hide weak allocation discipline.
Historical provisioning can survive long after the requirement that created it disappears.
And abundant resources can make overprovisioning look harmless even when it becomes the default architecture of the system.
Resource allocation therefore requires a current relationship between operational need and assigned capacity.
Available Capacity ≠ Required Allocation.
Allocate enough to satisfy the requirement — not enough to satisfy every possible appetite.
Good allocation is not the largest resource state a system can obtain. It is the resource state the execution can justify.