THE ICONIC scales Datadog to handle peak sales surges

THE ICONIC has expanded its use of Datadog for observability across its engineering teams, as the online retailer prepares for periods of sharply higher traffic during major sales events.

The fashion and lifestyle retailer said demand can rise to as much as 10 times normal levels during national shopping moments such as end of financial year sales, Black Friday and Christmas. It said that platform reliability during those windows has a direct impact on customers and order completion.

The company operates in Australia and New Zealand and sits within Global Fashion Group. It said it has more than 2 million active customers and lists more than 200,000 products from 1,500 brands.

Peak trading

THE ICONIC pointed to its most recent Black Friday performance as an example of the stakes involved in peak trading. During the 2025 Black Friday weekend, it processed more than 63,000 orders, averaging about two items per second. The retailer said that any slowdown, outage or checkout failure during such periods has immediate consumer impacts.

Andrew Burton, Head of Platforms at THE ICONIC, said the group had previously split visibility across multiple systems.

"Before Datadog, visibility was split across multiple platforms, which made troubleshooting slower and more complex," said Andrew Burton, Head of Platforms at THE ICONIC.

Burton linked platform performance to the pressure on engineering teams during retail peaks.

"For any online retailer, performance during peak periods like upcoming Black Friday and Christmas seasons can make or break the customer experience. By consolidating observability, our engineers can detect issues faster, understand their impact, and keep the platform running smoothly when demand surges," said Burton.

Monitoring stack

THE ICONIC said it runs on AWS and continues to expand a microservices architecture. It now uses Datadog to monitor logs, traces, and metrics across its technology stack.

The company said it uses automated anomaly detection after deployments. It also uses Service Level Objectives to track reliability trends over time. It said it has set service ownership, which routes alerts to specific teams when performance drops.

"Datadog's AI capabilities help us surface regressions without developers babysitting dashboards, SLOs give us a longer-term view we can take back to the organisation, and clear team ownership means the right people get notified at the right time," Burton said.

Engineering operations

THE ICONIC said it has also integrated Datadog with tools including GitHub. It said these integrations centralise data that previously sat across separate systems. It said this approach provides a single source of truth for technical and business stakeholders.

The company linked the consolidation work to incident response. It said the changes produce faster incident resolution and more confidence ahead of sales events such as Black Friday and Cyber Monday, when traffic can spike significantly.

Burton described observability as a governance and accountability issue for engineering teams.

"Observability is how our teams meet their ownership responsibilities," Burton said.

He also described the impact on instrumentation and diagnostics across services.

"Datadog makes it easier for developers to instrument services correctly, see issues early, and find root causes quickly. That supports what the organisation cares about, reliable performance and a smooth customer experience," Burton said.

Datadog view

Datadog's regional leadership framed the engagement in commercial terms tied to checkout performance.

"Fashion eCommerce lives or dies on speed and reliability, especially during major sales events. If a customer can't check out, that's lost money," said Roz Gregory, Regional Vice President for ANZ at Datadog.

Next steps

THE ICONIC said it plans to deepen its use of SLOs and improve the developer experience for on-call and alerting. It also said it will experiment with Datadog's security capabilities and explore external service monitoring as its platform and partner ecosystem changes.