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5 Takeaways from the Observability Forecast for Retail and eCommerce

Nic Benders
New Relic

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability.

As economic pressures intensify and customer expectations rise, the retail industry is undergoing a reset. To protect margins and deliver seamless omnichannel experiences, retailers must improve the efficiency and reliability of their IT and digital operations while also managing against complexity created by AI. Drawing on insights from 147 retail and eCommerce leaders, this report reveals how retailers use observability and key benefits.

Here are five key takeaways from the report:

1. AI shapes observability priorities

The data shows that 50% of leaders identified AI as the primary driver of deploying observability platforms in the retail and eCommerce industries. As retailers adopt AI to better connect with shoppers and personalize their experiences, the complexity of their digital estate increases by introducing new models, data pipelines, and dependencies that must be monitored alongside existing applications.

Beyond AI, retailers also cite governance, risk, compliance, cost management, and customer experience management as key drivers of observability adoption, reflecting the need for end-to-end visibility across increasingly interconnected systems.

2. Outages are a costly business risk

Outages are not just IT incidents; they are a business risk that can damage a brand. The report found that 31% of retail organizations report experiencing high-impact outages weekly. Retailers remain quicker than most industries at detecting outages, with a median time to detection of 30 minutes, yet the damage can still be devastating. The financial impact of outages is profound, with respondents citing a median cost of a critical business outage at $1 million per hour.  

Downtime, however, is only one part of the equation. Nearly 60% of respondents recognized that their engineering teams were losing innovation opportunities due to outages and incident response. Reducing incident frequency and downtime allows teams to redirect efforts toward innovation and business growth.

3. Digital experience monitoring is mission-critical

Monitoring offers insights into the digital customer experience and any issues that could impact it. To support seamless, omnichannel journeys, retail organizations are deploying a range of monitoring capabilities that keep customers engaged across every touchpoint. Specifically, they have prioritized database monitoring (67%), network monitoring (66%), alerts (65%), and dashboards (63%). Security also ranks highly, with 61% indicating they have deployed a security monitoring platform.

That focus on deeper visibility now extends to AI-driven systems, with AI monitoring adoption rising from 35% in 2024 to 55% in 2025.

4. Tool consolidation gains momentum

Retail organizations continue to consolidate observability tools to improve visibility across the software stack, prevent incidents, and increase operational efficiency. In 2025, the number of tools retail organizations used dropped from 5.9 just three years ago to 3.9. At the same time, complexity remains a persistent challenge, with 37% of respondents citing complex tool stacks as their primary obstacle to achieving full-stack observability. Having too many tools and the tools being too expensive fall closely behind as the next cited obstacles. This shift reflects a broader push to reduce tool sprawl as retailers manage increasingly distributed, omnichannel environments with fewer resources and tighter margins.

5. Observability makes life better (and provides business value)

For IT decision makers, observability delivers value beyond incident response. 41% of respondents said the technology helps satisfy key performance indicators (KPIs) while 36% said it drives business strategy. In-the-trenches practitioners said it increased productivity, enabling them to find and resolve issues faster (55%). It also reduced the guesswork associated with complex tech stacks (31%).

44% of respondents also noted observability increases operational efficiency, while another 43% reported improvements in system uptime and reliability.

Notably, observability is also delivering clear financial returns. Nearly half (46%) of retailers report an ROI of 2x or higher from their observability spend, reinforcing its role as a core business investment.

Retailers cannot afford business downtime or abandoned shopping carts due to poor customer experiences. As retailers navigate tighter margins, rising customer expectations, and increasingly complex digital environments, observability is proving essential for delivering resilience, efficiency, and business value.

Nic Benders is Chief Technical Strategist at New Relic

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5 Takeaways from the Observability Forecast for Retail and eCommerce

Nic Benders
New Relic

Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability.

As economic pressures intensify and customer expectations rise, the retail industry is undergoing a reset. To protect margins and deliver seamless omnichannel experiences, retailers must improve the efficiency and reliability of their IT and digital operations while also managing against complexity created by AI. Drawing on insights from 147 retail and eCommerce leaders, this report reveals how retailers use observability and key benefits.

Here are five key takeaways from the report:

1. AI shapes observability priorities

The data shows that 50% of leaders identified AI as the primary driver of deploying observability platforms in the retail and eCommerce industries. As retailers adopt AI to better connect with shoppers and personalize their experiences, the complexity of their digital estate increases by introducing new models, data pipelines, and dependencies that must be monitored alongside existing applications.

Beyond AI, retailers also cite governance, risk, compliance, cost management, and customer experience management as key drivers of observability adoption, reflecting the need for end-to-end visibility across increasingly interconnected systems.

2. Outages are a costly business risk

Outages are not just IT incidents; they are a business risk that can damage a brand. The report found that 31% of retail organizations report experiencing high-impact outages weekly. Retailers remain quicker than most industries at detecting outages, with a median time to detection of 30 minutes, yet the damage can still be devastating. The financial impact of outages is profound, with respondents citing a median cost of a critical business outage at $1 million per hour.  

Downtime, however, is only one part of the equation. Nearly 60% of respondents recognized that their engineering teams were losing innovation opportunities due to outages and incident response. Reducing incident frequency and downtime allows teams to redirect efforts toward innovation and business growth.

3. Digital experience monitoring is mission-critical

Monitoring offers insights into the digital customer experience and any issues that could impact it. To support seamless, omnichannel journeys, retail organizations are deploying a range of monitoring capabilities that keep customers engaged across every touchpoint. Specifically, they have prioritized database monitoring (67%), network monitoring (66%), alerts (65%), and dashboards (63%). Security also ranks highly, with 61% indicating they have deployed a security monitoring platform.

That focus on deeper visibility now extends to AI-driven systems, with AI monitoring adoption rising from 35% in 2024 to 55% in 2025.

4. Tool consolidation gains momentum

Retail organizations continue to consolidate observability tools to improve visibility across the software stack, prevent incidents, and increase operational efficiency. In 2025, the number of tools retail organizations used dropped from 5.9 just three years ago to 3.9. At the same time, complexity remains a persistent challenge, with 37% of respondents citing complex tool stacks as their primary obstacle to achieving full-stack observability. Having too many tools and the tools being too expensive fall closely behind as the next cited obstacles. This shift reflects a broader push to reduce tool sprawl as retailers manage increasingly distributed, omnichannel environments with fewer resources and tighter margins.

5. Observability makes life better (and provides business value)

For IT decision makers, observability delivers value beyond incident response. 41% of respondents said the technology helps satisfy key performance indicators (KPIs) while 36% said it drives business strategy. In-the-trenches practitioners said it increased productivity, enabling them to find and resolve issues faster (55%). It also reduced the guesswork associated with complex tech stacks (31%).

44% of respondents also noted observability increases operational efficiency, while another 43% reported improvements in system uptime and reliability.

Notably, observability is also delivering clear financial returns. Nearly half (46%) of retailers report an ROI of 2x or higher from their observability spend, reinforcing its role as a core business investment.

Retailers cannot afford business downtime or abandoned shopping carts due to poor customer experiences. As retailers navigate tighter margins, rising customer expectations, and increasingly complex digital environments, observability is proving essential for delivering resilience, efficiency, and business value.

Nic Benders is Chief Technical Strategist at New Relic

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Seeing is believing, or in this case, seeing is understanding, according to New Relic's 2025 Observability Forecast for Retail and eCommerce report. Retailers who want to provide exceptional customer experiences while improving IT operations efficiency are leaning on observability ... Here are five key takeaways from the report ...

Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...