What Event Readiness solves · ZopDev University

Outcome

By the end of this lesson, you will be able to distinguish Event Readiness from reactive autoscaling, identify which events warrant pre-scaling, and recognize when the 5-minute ramp-up gap matters.


Prerequisites	M2.4 (VM autoscaling)
Time	9 minutes

1. Concept

Ordinary autoscaling waits for the traffic, then adds capacity. That is the right design for traffic you did not see coming.

It is the wrong design for Black Friday. You know the date. You know roughly what is coming. Waiting for it to arrive means the first few minutes of your biggest day are served by a system that is still catching up, and the customers in those minutes are the ones who notice.

Event Readiness scales up in advance, so the capacity is already there when the traffic is.

THE PROBLEM:
  Reactive autoscaling has a 5-minute lag
  During lag: capacity saturated; customers feel pain

  For unpredictable events: no choice but reactive
  For PREDICTABLE events: we can do better

THE SOLUTION:
  Define the event in ZopNight
  Pre-scale BEFORE the event start
  Run at event capacity through the event
  Scale back after

  Zero ramp-up gap; smooth customer experience

The trade-off is cost (pre-scaled capacity costs money before traffic arrives).

The reactive autoscaling problem

TIMELINE during Black Friday (reactive only):

T+0       Traffic starts ramping up
T+0       Existing capacity: 12 instances
T+1 min   CPU hits 80% (autoscaler trigger threshold)
T+1 min   Autoscaler triggers scale-out
T+1 min   3 new instances launching
T+3 min   New instances reaching ready state
T+5 min   New instances healthy and serving
T+5 min   Capacity catches up to traffic

DURING T+0 to T+5 min window:
  Existing capacity (12 instances) at 100%+ CPU
  P99 latency spikes 3-5x
  Some users see degraded experience
  Possibly: some traffic dropped or queued

COST OF THE 5-MIN GAP:
  Lost orders (some customers bounce)
  Latency-correlated lower conversions
  Bad customer reviews / support tickets
  Brand impact for high-profile events

The 5-minute gap is the problem. Event Readiness eliminates it.

How Event Readiness works

PHASE 1: PRE-EVENT (days before)
  Define the event in ZopNight: date, scope, expected multiplier
  ZopNight calculates capacity needs
  Customer reviews + approves

PHASE 2: PRE-SCALE (default 30 minutes before event start)
  ZopNight pre-scales the infrastructure:
    Increases ASG / ECS / MIG / VMSS capacity
    Databases are monitor-only (see L4)
  Pre-warm completes BEFORE traffic arrives

PHASE 3: EVENT DURATION (event period)
  Infrastructure is at event capacity
  Traffic arrives; no ramp-up gap
  Performance stays smooth

PHASE 4: EVENT END (default 60 minutes after event end)
  ZopNight scales back down to normal
  Cost returns to baseline
  Audit log captures the full lifecycle

The event window is treated as a special schedule: pre-warm, run at capacity, scale back.

What gets pre-scaled

TARGETS THAT GET PRE-SCALED (automatic):
  ASG (AWS):                 scale_out to event capacity
  ECS service:               desired_count to event capacity
  GCP MIG:                    target_size to event capacity
  Azure VMSS:                 capacity to event capacity
  (No other target types: Lambda and other services are not scaled)

TARGETS THAT ARE MONITORED-ONLY (see L4):
  Databases (RDS, Cosmos, etc.):
    No automated mutation
    Recommendations surface for customer to act manually
    Customer scales DB on their own (because data risk)

The asymmetry is intentional: compute is auto-scaled; data is human-scaled. (Recall M2.3.L5: database denylist.)

Event Readiness vs scheduling

SCHEDULING                       EVENT READINESS
─────────────────────────────────────────────────────────
Recurring (daily, weekly)         One-time event
Cron-driven                       Datetime-driven (event start/end)
Stops at end (off-hours)          Scales back at end (resume normal)
For non-prod                       For prod traffic events
Saves money                        Costs money temporarily
Off → On                           Normal → Higher → Normal

The two layers complement. Most teams have both: schedules for non-prod, Event Readiness for one-off events.

When Event Readiness matters

EVENT TYPE                      USE EVENT READINESS?
─────────────────────────────────────────────────────
Product launch                    YES: large predictable spike
Black Friday                       YES: predictable annual spike
Marketing email blast              YES: known time, known multiplier
Newsletter send                    YES: small but known burst
Load test                          YES: for the test duration
Geo-rollout                        YES: predictable per-region spike
TV ad spot                         YES: known timing
Conference / event broadcast        YES: known traffic window
Random viral moment                 NO (can't predict; reactive autoscale)
Daily peak hours                   NO (use Peak Hours preset)
Steady traffic growth              NO (autoscaler handles)

The principle: Event Readiness wins when the event is predictable.

Cost of Event Readiness

EXAMPLE: Black Friday event for 24 hours
  Normal capacity: 12 instances ($24/hr)
  Event capacity: 36 instances ($72/hr)
  Cost during event: $1,728 (3x normal)
  Cost above baseline: $1,152

  Total cost of pre-scaling: $1,152
  Plus 1 hour pre-warm: $48
  Plus 1 hour buffer scale-down: $48
  Total event cost: $1,248

VALUE:
  Lost orders prevented: typically $50K-$500K
  Customer experience preserved: priceless
  Brand impact avoided: significant

ROI: usually >100x for major events

The cost is real but small relative to the value.

Cost during the event

BEFORE YOU SCHEDULE:
  The cost estimate: current $/hr, event $/hr,
  and the difference times the event duration

DURING THE EVENT:
  No live tracker or remaining-cost figure in Event Readiness
  Watch spend in Cost Reports instead
  Targets are frozen once the event leaves draft;
  there is no mid-event scale up or scale back

TO END EARLY:
  Cancel the event; ZopNight puts the original capacity back

The estimate is your pre-event number. During the event, Cost Reports is where you watch spend.

2. Demo

A team’s Black Friday preparation:

EVENT: Black Friday 2026
SCOPE: production checkout service + product API + database tier

PLANNING (October: 5 weeks ahead):
  Define event in ZopNight:
    Date: November 28, 00:00 - 23:59 UTC
    Scope: production-prod-checkout group + production-prod-api group
    Expected multiplier: 3x normal capacity
    Pre-warm: 1 hour
    Scale-down buffer: 1 hour

CAPACITY CALCULATION:
  Current capacity: 12 instances
  Expected: 36 instances (3x)
  Adjustment: round up to 40 for buffer

COST ESTIMATE:
  ZopNight quotes $4,200 additional for the 24-hour event window
  Customer approves

NOVEMBER 27 23:00 UTC (1 hour before event):
  ZopNight pre-scales:
    ASG-checkout: scale to 40 instances
    ASG-api: scale to 60 instances
  Pre-warm 40 + 60 = 100 instances over ~10 minutes
  Database tier: monitored-only; team adjusted manually beforehand

NOVEMBER 28 00:00 - 23:59 UTC (event):
  Traffic arrives
  P99 latency: 110ms (normal)
  Capacity utilization: 75% (healthy)
  No degradation during traffic ramp
  Conversion rate: stayed at expected level

NOVEMBER 28 23:59 UTC (event ends):
  Autoscaler scales back to baseline
  Cost returns to normal
  Audit log captures full lifecycle

RESULT:
  $4,200 spent on pre-scaling
  ~$300K of customer orders processed without issues
  Customer experience: smooth
  Engineering team: confident
  ROI: 70:1

Pre-scaling cost is real but worth it for the customer experience.

3. Hands-on (5 min)

Plan a hypothetical event:

□ STEP 1: Identify upcoming event
  Event: __________
  Date: __________
  Duration: __________

□ STEP 2: Estimate traffic multiplier
  Normal traffic: __________
  Expected event traffic: __________
  Multiplier: ___x

□ STEP 3: Identify scope
  Affected workloads: __________
  Database tier: __________

□ STEP 4: Calculate capacity needs
  Current capacity: __________
  Event capacity needed: __________
  Buffer: __________

□ STEP 5: Estimate cost
  Normal cost: $_____
  Event cost: $_____
  Additional cost: $_____
  Estimated value of preventing latency spike: $_____

A 20-minute exercise reveals the math. Most events: ROI strongly favors pre-scaling.

4. Knowledge check

Q1

Reactive autoscaling vs Event Readiness:

A. Same thing
B. Different cloud providers
C. Event Readiness is reactive as well, only rather slower to act on it
D. Reactive triggers after traffic hits the saturation threshold (5-min lag)

Show answer

Correct: D. Event Readiness pre-scales before. Use both: reactive for unexpected traffic, Event Readiness for known events.

Q2

A team has a marketing launch in 3 weeks. The right approach:

A. Trust reactive autoscaling
B. Manual escalation
C. Use Event Readiness; define the event, pre-scale before the start, scale back after
D. Pre-scale absolutely everything by hand on the morning of the launch day itself

Show answer

Correct: C. Predictable events warrant Event Readiness: it removes the 5-minute ramp-up gap. The pre-scale window defaults to 30 minutes and the scale-back to 60 minutes after the end; both are configurable.

Q3

A viral moment causes unexpected traffic. Best approach:

A. Event Readiness (define event)
B. Reactive autoscaling: viral events are by definition unpredictable
C. Define an event retroactively so as to cover it afterwards
D. Manual

Show answer

Correct: B. Event Readiness can’t pre-schedule an event nobody saw coming. The 5-minute lag is unavoidable but rare; reactive autoscaling handles it.

5. Apply

Event Readiness at Automate → Event Readiness. Define events, calculate capacity, approve, schedule.

For your team: identify upcoming predictable events; use Event Readiness for them.

Glossary terms touched

Event readiness

Outcome

1. Concept

The reactive autoscaling problem

How Event Readiness works

What gets pre-scaled

Event Readiness vs scheduling

When Event Readiness matters

Cost of Event Readiness

Cost during the event

2. Demo

3. Hands-on (5 min)

4. Knowledge check

Q1

Q2

Q3

5. Apply

Related lessons

Glossary terms touched

Start with the bill.