---
version: "2026"
language: "en"
---
# Advanced timeline configuration

We previously applying advanced techniques in editing a Sequence. Now, let's dive into the advanced techniques for configuring timelines. For the example shown in the video below, we show it by creating a new timeline and naming it something meaningful, such as **Black Friday**. The Timeline will be the main canvas where all sequences and load patterns are orchestrated.

Add your first sequence to the timeline. Go will place it on Track 1 with a default linear ramp.

Adjust the load to reflect the desired load conditions you have. That could be starting at 20 users and ramping to 100 - or starting at 4,000 users ending at 5,000. Go handles it all. The rest of this example will be based on the Black Friday simulation.

## **Simulating multiple actions simultaneously checking out**

As visitors begin browsing, some percentage will proceed to checkout. To simulate this:

1. Add a new track
2. Drag in the **checkout** sequence
3. Offset it slightly so activity begins a little after the storefront load starts

It is common for checkout traffic to come in waves, so you can represent this by placing two checkout segments:

* **Wave 1**: Start at 50 users, peak at 150
* **Wave 2**: Add a second segment later in the timeline with similar behaviour

Use *Zoom to fit* to adjust the view as more tracks and segments are added.

## **Add simulating requests sent to the Order Management System**

Once orders are placed, the Order Management System (OMS) begins processing them. Add a new track and drag in the **order management** sequence.

For the OMS load profile:

* Start at 50 users
* Rise to 400 users in a simple linear pattern
* Keep this part straightforward to focus on the overall flow

This represents back-office processing activity triggered by checkout.

## **Start picking and packing orders**

Fulfillment systems work downstream from OMS. Add a new track and insert the **fulfillment** sequence.

Position it slightly offset to reflect the natural cascade of events. Set a stable load pattern, such as:

* 100 users from start to finish

This simulates continuous workload on warehouse or distribution systems as orders are generated.

## **Simulate real logged-in users for the backend sequences**

For back-office systems such as OMS and fulfillment, Go needs to log in actual users so that the recorded steps behave correctly.

If you have a data item with user accounts, such as **Black Friday users**, apply it to these sequences:

* Select the sequence inside the timeline
* Choose the data item
* Specify how many users to pull (for example, two non-admin roles)

Go will use the browser only for the login step. After that, all actions execute as authenticated users inside the load profile you defined.

## **Simulate customers coming from all corners of the world**

Black Friday traffic rarely comes from one region. To simulate global activity:

1. Add another storefront sequence to the timeline
2. Create the same load pattern as before (4,000 → 5,000 users)
3. Change the region to a different location (for example, Southeast Asia)

Go will calculate and display the combined:

* Virtual user minutes
* Peak virtual users
* Planned runtime

This helps you understand the impact of simultaneous load originating from multiple world regions.

## **Simulate your Black Friday load over \& over with ease**

By the end of this setup, your timeline can simulate:

* Heavy storefront traffic
* Waves of checkout activity
* Order management processing load
* Fulfillment handling
* Real user authentication for ERP-connected systems
* Load originating from multiple global regions

Go allows all these sequences to be coordinated within a single scenario. This mirrors how a full value chain behaves under intense promotional pressure, providing insight into the performance of each component as well as the combined system.