How a sandwich shop explains the value of observability in IT operations

By Tiago Dias Generoso

Editor’s note: This article, originally published in November 2023, was updated in December 2025.

My favorite sandwich shop hums with activity seven days a week.

The food is delicious, but what impresses me most is how the business operates so seamlessly. Happy customers benefit from the orchestration of everything from inventory and ordering to assembly and checkout.  

Ironically, this symphony of sandwich operations makes me think about IT observability for large companies.

No matter the industry, organizations need to understand how customer behaviors, high-demand periods, system bottlenecks and other factors impact the bottom line. Information fuels these insights, but many companies still struggle to glean real, actionable insights from their data.

Observability can help address these issues. By providing a clear view of a company’s technology ecosystem, observability empowers tech teams to spot issues and optimize performance while cutting costs and driving innovation. These capabilities, in turn, help organizations provide seamless customer experiences.

In an environment where CTOs must deliver business results through technology, observability becomes an IT differentiator.

Misconceptions and myths about observability

Observability faces an identity crisis caused by misconceptions and myths. For starters, many people believe observability and monitoring are one and the same. They aren’t.

Monitoring tracks specific metrics and alerts teams when something is wrong. Observability collects data from across your ecosystem and uses machine learning (ML) to determine what’s happening and why. In other words, observability provides context to monitoring.

This misconception and others have led to several widely held myths about observability. 

Myth 1: Observability is always expensive
This simply isn’t true. Several cost-effective observability solutions, including many open-source options, are available. Costs vary depending on automation requirements, the intelligence behind it, ease of implementation and other factors. Think of observability as an investment that pays off by helping you avoid costly outages and performance problems.

Myth 2: Observability can be achieved by installing a tool
There are an array of observability products in the market. However, observability is more than a collection of solutions — it’s a holistic approach to managing IT estates that requires new ways of thinking and working. Tools won’t generate significant business value until teams work together to align operating models and processes with company goals.

Myth 3: Observability is only for large enterprises
Companies of every size and type struggle with outages, performance issues and operating costs. Observability principles apply across industries, so it makes sense for most organizations that rely on IT systems to do business. Understanding how your organization’s systems work and perform can help everyone from the frontline to the C-suite make better decisions.

Myth 4: Observability and data observability are the same
While the core idea of making things “observable” is the same, data observability focuses specifically on maintaining the health and performance of data ecosystems, including data pipelines, data warehouses, data lakes and the data itself. IT observability encompasses the entire IT stack, from infrastructure and applications to microservices and networks.

Observability in action

Observability delivers far more value than sightlines into your IT estate.

Consider the experience of a Fortune 500 automotive manufacturer with limited visibility across more than 10 production facilities and 500-plus suppliers. Manual patching and inconsistent inventory management led to inaccurate data. Platform and workload monitoring were non-existent, and observability was nearly impossible due to missing KPIs and dashboards.

Working with two technology providers, we helped the company integrate a cloud-based observability platform and a SaaS solution for internal monitoring and observability. The process began with understanding the customer’s objectives and overall strategy, which guided the design of a solution aligned with their operational goals. Now, custom dashboards and proactive alerting give IT teams real-time insights into infrastructure, applications and data.

Since implementing the framework, the vehicle maker has seen significant improvements in systems availability, monitoring and observability. Proactive alerting achieves a 99.95% response and resolution rate, significantly enhancing service-level agreements (SLAs). Meanwhile, a defect prevention plan that addresses root causes for alerts and customer KPIs (for example, host checks, memory, CPU and disk space) has helped reduce ticket submissions by roughly 79%.

3 steps to start your observability journey

Depending on the size, needs and complexity of your IT estate, it can take anywhere from a few days or weeks to several months or quarters to implement observability. These steps will help get you started:

Step 1
Assess your observability readiness by understanding the tools and technologies used by the company. Pay special attention to how teams use IT data, the quality of the data and whether the company is satisfied with the performance and reliability of your systems. This information will help you prioritize the focus areas for starting an observability program.

Step 2
Define what success looks like for your organization’s observability efforts. Are you aiming to make more informed decisions with IT data, reduce operational costs, improve system reliability, enhance customer satisfaction or align technology outcomes with business strategy? Setting clear, measurable goals will guide investment, execution and ongoing optimization.

Step 3
Choose the right observability tools and technologies. Evaluate solutions not only on cost or features but on how effectively they can scale, integrate with existing systems and produce measurable business outcomes. Conduct due diligence through vendor assessments, customer stories and pilot programs to ensure each investment supports long-term resilience and innovation.

When evaluating options, remember to include AI-driven capabilities and open integration platforms as part of your assessment. Automated anomaly detection, predictive insights and intelligent alerting help shape modern observability workloads.

Observability is a long game. Embrace it to help your organization stay resilient and customer focused, and just like a well-run sandwich shop, you keep customers returning for more.

Tiago Dias Generoso is a Distinguished IT Architect | Senior SRE | Master Inventor based in Pocos de Caldas, Brazil.