Technology & telecom
Digital traffic forecasting
Forecast traffic, transactions, and concurrency before campaigns, launches, and seasonal peaks.
Sound familiar?
- Launch-day traffic that finds the ceiling before autoscaling does
- Capacity provisioned year-round for peaks that rarely arrive
- Marketing campaigns that reach infrastructure as a surprise
Requests and sessions
requests / second · Live forecast
Driver
Active users
Driver
Campaigns
Driver
Release calendar
Forecast horizon
Minutes–12 weeks
Refresh cadence
Minute or hourly
Built for
Site reliability · Platform engineering
What you can predict
One forecast can answer several operational questions.
Use product telemetry, marketing schedules, release calendars, user growth, and recurring traffic patterns to forecast demand across services and regions.
Requests per second
Sessions and transactions
Peak concurrency
Regional traffic
Questions teams need answered
- How large will launch-day traffic be?
- When will concurrency peak?
- Which service will reach capacity first?
- How much uncertainty should autoscaling absorb?
Data that can improve the forecast
Start with the history you already have. Add internal or external drivers only when backtesting shows that they improve the forecast on held-out periods.
What-if planning
Test a change before committing to it.
Compare a proposed change with the current baseline. See the expected direction, timing, range, and the assumptions behind the result.
Campaign reach doubles
Estimate peak requests and capacity
Launch moves to another hour
Compare regional traffic overlap
Requests and sessions
requests / second · Scenario comparison
What if
Campaign reach doubles?
Driver
Active users
Driver
Campaigns
Driver
Release calendar
From forecast to action
Keep the people making the decision in the loop.
01 · MONITOR
Forecast continuously
Refresh requests and sessions on a minute or hourly cadence as new data arrives.
02 · NOTIFY
Alert on meaningful changes
- Forecast traffic exceeds safe capacity
- A launch produces demand outside the expected range
03 · DECIDE
Put the result to work
From the handbook
How the forecast is actually built.
Guide
Time series forecasting, explained
Time series forecasting predicts the next values of something that was recorded in order — sales by day, load by hour, tickets by week — by learning from its own past, and from anything that regularly moves with it.
Guide
How much history do you need to forecast?
Enough to see the pattern you are betting on. A weekly seasonal business wants more than one year; an hourly series can learn a week of shape faster. Quality of the target beats another dusty decade of the wrong grain.
Guide
What is good forecast accuracy?
Good is beating a naive baseline on the same grain, horizon, and folds — by enough to change a decision. Industry round numbers are gossip until they match your SKU mix and your clock.
Build a digital traffic forecast with your data.
Start with sample data, connect your own history, or talk with us about your target, horizon, and production requirements.