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T2 / M2.11 / L5 OF 5 / Engineer TIER / 9 min

Provisioned throughput optimization

Outcome

By the end of this lesson, you will be able to decide between on-demand and provisioned throughput, right-size provisioned capacity, and schedule provisioned throughput for time-aware optimization.


TierEngineer
JTBD”Pick the right Bedrock pricing mode (on-demand vs provisioned) and right-size provisioned capacity for actual usage.”
PersonasML Engineer · Platform Engineer · FinOps Lead
PrerequisitesM2.11.L1 - L4
Time9 minutes
Bloom verbDecide (Evaluate), Right-size (Apply), Schedule (Apply)

1. Concept

Bedrock will sell you model capacity two ways, and the right one depends entirely on how steady your usage is.

Pay per request and you pay only for what you send, at a higher unit price. Reserve capacity and you pay a fixed hourly amount whether you use it or not, at a much lower unit price.

Terminal window
ON-DEMAND:
Pay per token (no commitment)
Variable cost
No upfront commitment
PROVISIONED THROUGHPUT:
Pay per hour for guaranteed throughput
Commit 1 or 6 months
Up to 50% off effective per-token rate
THE CHOICE: depends on workload's pattern + maturity

The two modes trade flexibility for cost. Provisioned wins when usage is predictable.

When provisioned wins

Terminal window
SCENARIO PROVISIONED OR ON-DEMAND?
─────────────────────────────────────────────────────────────
Predictable high-volume PROVISIONED (1-month or 6-month)
Variable low-volume On-demand
Burst-mode On-demand
Always-on, steady throughput PROVISIONED
New workload, unknown load On-demand (until known)
Mature workload, stable pattern PROVISIONED
Long-term commitment OK PROVISIONED 6-month (best discount)
Variable traffic On-demand

The break-even point: roughly 70% utilization of provisioned throughput.

Right-sizing provisioned throughput

Terminal window
MEASUREMENT (the workload's actual usage):
Average tokens/sec: 2,400
Peak tokens/sec: 9,800
Sustained periods at peak: 5% of time
PROVISIONED OPTIONS:
Option A: Provision for peak (10K tokens/sec)
Capacity: 24/7
Cost: $X (highest baseline)
Utilization: 24% (mostly idle)
Performance: never throttled
Option B: Provision for average (2,400 tokens/sec)
Falls back to on-demand for bursts
Cost: ~30% of Option A
Utilization: ~80%
Bursts: occasional on-demand cost
Total cost: typically 35% of Option A
Option C: Provision at peak × 0.7 (7K tokens/sec)
On-demand for the burst above
Cost: ~50% of Option A
Utilization: ~65%
Better burst handling than Option B
Option D: Schedule-aware provisioned
Provisioned during business hours
On-demand off-hours
Cost: ~40% of Option A
Maintains peak handling

Option B usually wins for variable-load workloads. Option D handles diurnal patterns.

Detecting over-provisioning

Terminal window
SIGNAL INTERPRETATION
─────────────────────────────────────────────────────────────────
Utilization < 30% sustained Over-provisioned (RC-1602)
Reduce throughput OR switch to on-demand
Utilization > 95% sustained Under-provisioned
Consider increase to avoid throttling
Periodic peak hits ceiling Provisioned for average; OK
On-demand handles peaks (if configured)
Periodic drop to near-zero Idle periods
Consider scheduling
Spiky utilization On-demand might be more cost-effective
Variable patterns don't suit provisioned

The 30% threshold catches most over-provisioning. The 95% catches under-provisioning.

Idle period scheduling

Terminal window
PROVISIONED THROUGHPUT is per-hour
If a workload is genuinely idle overnight or weekends:
PROVISIONED 24/7: paying for 168 hours/week
PROVISIONED schedule-aware:
ZopNight schedules the provisioned capacity off overnight + weekends
Cost saving:
Non-prod: 60-80% (long idle windows)
Prod: 30-40% (shorter idle windows)
ZOPNIGHT'S AUTOSCALER-STYLE SCHEDULING on Bedrock provisioned throughput:
Acts like other scheduling
Cron-driven start/stop
Audit log; lifecycle management
Same patterns as M5.2 schedules

The schedule pattern extends to Bedrock provisioned throughput.

Commitment math

Terminal window
1-MONTH PROVISIONED:
Discount: ~20-30%
Break-even: ~70% utilization
Commitment: 30 days
Risk: medium-low
6-MONTH PROVISIONED:
Discount: ~40-50%
Break-even: ~50% utilization (lower because longer commit)
Commitment: 180 days
Risk: medium (workload pattern must hold)
ANNUAL PROVISIONED (if available):
Discount: ~50-60%
Break-even: ~40% utilization
Commitment: 365 days
Risk: higher (workload assumptions over long horizon)

For mature workloads with stable patterns, 6-month wins on discount.

Hybrid pattern: provisioned + on-demand

Terminal window
THE BEST PATTERN for most workloads:
Provisioned: base load (e.g., 70% of peak)
On-demand: bursts above provisioned capacity
EXAMPLE:
Workload peaks 10K tokens/sec; sustains 4K
Provision 7K tokens/sec
Cost: provisioned hourly rate
Burst above 7K: on-demand
Pay for the burst tokens
Most days: minimal on-demand cost
TOTAL COST: significantly lower than provisioning for peak
PERFORMANCE: handles peaks without throttling

The hybrid pattern is the standard for variable-but-predictable workloads.

Decision framework

Terminal window
QUESTIONS TO ANSWER for any Bedrock workload:
1. Is the workload mature? (running stable >3 months)
Yes → consider provisioned
No → stay on-demand
2. Is utilization predictable?
Yes → provisioned at average + on-demand for bursts
No → on-demand
3. Does it have idle periods (overnight/weekend)?
Yes → schedule the provisioned capacity
No → provisioned 24/7
4. Can you commit 6 months?
Yes → 6-month for best discount
No → 1-month or on-demand
5. Is current cost a concern?
Yes → optimize aggressively (right-size + schedule)
No → accept current pattern

The framework guides the decision per workload.


2. Demo

A team’s provisioned throughput optimization:

Terminal window
WORKLOAD: customer support chatbot
Mature pattern over 6 months
Average: 4,000 tokens/sec
Peak: 7,500 tokens/sec
Distribution: 95% of time within 2.5x of average
Off-hours: significant drop in volume (but not zero)
OPTION A (CURRENT): on-demand
Cost: ~$28,000/month
Predictable; variable; no commitment
OPTION B: provisioned at 4,500 tokens/sec; on-demand for bursts
Cost: ~$15,000/month provisioned + ~$2,000/month on-demand bursts
Total: $17,000/month
Savings: ~$11,000/month (39%)
OPTION C: SCHEDULE PROVISIONED off overnight
Provisioned 80 hours/week (during peak hours)
On-demand for off-hours
Total: ~$11,000/month
Savings: ~$17,000/month (60%)
OPTION D: 6-month commitment for Option C
Additional discount on provisioned hours
Total: ~$8,500/month
Savings: ~$19,500/month (70%)
DECISION: Option D for the year-long mature workload pattern
IMPLEMENTATION (4 weeks):
Week 1: validate utilization measurements
Week 2: configure provisioned throughput at 4,500 tokens/sec
Week 3: configure schedule for peak hours
Week 4: monitor + validate cost projections
OUTCOMES (1 month in):
Actual cost: $8,700/mo (within 2% of projection)
Quality: unchanged
Performance: peaks handled by on-demand burst
Engineer satisfaction: high

Scheduled provisioned + on-demand for bursts is often the optimal pattern for mature workloads.


3. Hands-on (5 min)

Optimize your provisioned throughput:

Terminal window
□ STEP 1: Inventory provisioned throughput
Workload: __________
Current capacity: _____ tokens/sec
Current cost: $_____/mo
□ STEP 2: Measure actual usage
Average: _____ tokens/sec
Peak: _____ tokens/sec
Utilization: ____%
□ STEP 3: Right-sizing options
Reduce to average + on-demand bursts: $_____/mo
Schedule off-hours: $_____/mo
Commit 6-month: $_____/mo
□ STEP 4: Pick best option
Recommended: __________
Projected savings: $_____/mo
□ STEP 5: Plan
Implementation effort: ___ weeks
Risk: __________
Monitoring plan: __________

A 15-minute optimization exercise per workload.


4. Knowledge check

Q1

A workload has 25% sustained utilization on its provisioned throughput. The decision:

A. Increase throughput
B. Investigate over-provisioning: reduce throughput or switch to on-demand
C. Commit for a longer term to lower the effective hourly rate further
D. Keep as is

Show answer

Correct: B. RC-1602 (PT Underutilized) likely surfaced this; RC-1601 fires only on zero invocations. 25% utilization is well below the 70% break-even; over-provisioned. Over-provisioning at 25% utilization.

Q2

Provisioned throughput discount vs on-demand:

A. Same price
B. 90% discount
C. A flat 75% off, on any commitment length
D. ~20-50% discount depending on commit length

Show answer

Correct: D. 1-month: 20-30%; 6-month: 40-50%. Break-even at 50-70% utilization. Trade flexibility for cost. 20-50% discount, utilization-dependent break-even.

Q3

A mature workload with predictable peak hours and idle off-hours:

A. Provisioned 24/7
B. Provisioned during peak hours, scheduled off overnight
C. On-demand always
D. On-demand at the peaks, and provisioned overnight

Show answer

Correct: B. Hybrid pattern reduces cost significantly. Combines: lower base capacity + schedule discipline + on-demand fallback for bursts. Schedule-aware provisioned.


5. Apply

RC-1601 (idle) and RC-1602 (underutilized) surface provisioned-throughput optimization; RC-1610 catches a PT still pinned to a deprecated model generation. Customer adjusts in the Bedrock console.

For your team: right-size provisioned throughput; schedule for idle periods; commit 6-month for mature workloads.


Module quiz

Complete M2.11 → 10-question module quiz.


Track 2 complete

You have now completed all 54 lessons of T2: ZopNight Engineer track. Take the Engineer cert exam at the Engineer certification page.

You should now be able to:

  • Read + apply the 450+ rule library (M2.1)
  • Read evidence + reconcile against billing (M2.2)
  • Configure auto-remediation safely (M2.3)
  • Manage VM autoscaling (M2.4)
  • Adopt-or-replace cloud scaling (M2.5)
  • Schedule K8s workloads (M2.6)
  • Schedule Databricks (M2.7)
  • Use Smart Tags derived values (M2.8)
  • Pre-scale for events (M2.9)
  • Investigate cost anomalies (M2.10)
  • Optimize Bedrock + ML costs (M2.11)

Glossary terms touched

Provisioned throughput · On-demand vs provisioned · Right-sizing throughput · Schedule-aware provisioned


Start with the bill.

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