If you haven’t yet been shaken by this expensive reality even in your worst dreams - consider yourself lucky. But not for long. Or maybe your organization has a team of OG engineers who have cracked the code. Or maybe you just haven’t faced the bill yet. But just ask the crypto company that got slapped with a staggering $65 million quarterly bill - all because of an outdated monitoring setup. And they’re not alone. The internet is full of similar horror stories - organizations blindsided by multimillion-dollar observability costs. Sometimes, engineers can trace the cause. Other times, no one has a clue.
As cloud-native adoption grows, allocating a significant share of budgets to what many call "robust visibility" has become the norm. However, observability has turned into a financial and operational burden for many organizations. The core issue? Traditional observability tools were never designed to handle the influx of high-cardinality data at the scale and complexity of modern environments.
Logging, monitoring, and application performance monitoring (APM) tools each come with inherent flaws that make them costly and inefficient in modern infrastructure. Logging tools, for example, were built for human readability. Engineers were accustomed to inserting any data they wanted into logs, but the sheer volume of cloud-based applications today has surpassed "human scale." Reading logs manually or maintaining indices for improved search speed is now impractical and expensive.
Monitoring tools, on the other hand, were optimized for speed rather than flexibility. In an era of microservices, where an application may span hundreds of containers and Kubernetes pods, traditional monitoring struggles to keep up. What once worked for a monolithic application on a few servers is now ill-equipped to handle the constant flux of cloud environments.
APM tools, too, have their flaws. Many were built on the assumption that software followed consistent patterns - such as the days when Rails applications dominated. In those cases, observability vendors could offer "magical" solutions that automatically detected and diagnosed common issues. But today’s engineering landscape is vastly different. Teams use multiple languages, frameworks, and architectures, making it nearly impossible for one-size-fits-all APM solutions to provide meaningful insights.
The Influence of SREs on Observability Costs
Beyond technological limitations, the rise of SRE has placed new demands on observability. SRE emphasizes service-level objectives (SLOs) and focuses on user experience rather than just system health. As a result, observability tools must now measure business impact, customer experience, and operational efficiency - all of which require more data, more processing power, and, inevitably, higher costs.
Many organizations adopting SRE principles struggle with observability because the very tools meant to help them track key performance indicators end up being prohibitively expensive. Some teams have even started reducing the data they collect - defeating the purpose of observability in the first place.
The Path Forward: Balancing Cost and Effectiveness
“ You can't manage what you can't measure - but measuring everything isn't managing.” So, what’s the solution? Organizations need observability strategies that scale with modern infrastructure while remaining cost-effective. This means:
Rethinking Logging – Instead of capturing every possible data point, teams should focus on structured logging with a clear purpose.
Smarter Monitoring – Instead of relying on dashboards filled with endless metrics, organizations should prioritize real-time insights that adapt to dynamic environments.
Targeted APM Usage – Rather than depending on "magical" APM tools that may not fit their diverse systems, teams should adopt flexible, vendor-agnostic approaches that align with their specific architectures.
The challenge of observability is not just a technical one - it’s an economic and operational problem. As infrastructure evolves, so do our approach to monitoring and understanding it. Organizations that strike the right balance between visibility and cost will be best positioned to deliver reliable, high-quality services to their users. Hence, Observability needs to be strategic, not excessive.