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Observability Costs Rising Faster Than Value

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply.

Top findings of the report include:

  • More than half of leaders allocate over 25% of their observability budget to a single platform, yet only 13% say they are very satisfied with the cost-to-value ratio.
  • Nearly 80% of teams are filtering, archiving, or offloading logs to control costs—reducing critical data visibility when teams need it most.
  • 87% of leaders report that slow queries on observability data were caused by inaccessible data delay workflows such as threat detection and incident response.
  • 87% of respondents are exploring or open to platform alternatives that reduce cost and scale pressure without disrupting current workflows, and 98% say they would adopt a fully compatible option.

Observability Spending Is Increasing While Value Declines

Enterprise teams report rising observability costs year over year, but confidence in platform ROI is slipping. Leaders say platform-centric licensing models and the rapid growth of observability data have created an environment whereby retaining essential logs or adding new workloads often requires difficult trade-offs.

Rising Costs Are Forcing Cuts to Visibility

To manage spend, many organizations are reducing retention or shifting data into lower-cost storage tiers. These common cost-saving measures directly reduce visibility and degrade query performance, and come with significant operational consequences:

  • High-value logs get filtered out before ingestion
  • Investigations slow as teams move data out of cold storage
  • Real-time responsiveness suffers during incidents

"Too many organizations are being priced into flying blind," said Eric Tschetter, Chief Architect at Imply. "They're cutting retention because budgets force their hand, and it shouldn’t be that way. Teams tell us they're pushing data into cold storage to keep costs in check and that can slow investigations, can create dangerous blind spots, and can weaken resilience. In a crisis, those trade-offs are unacceptable."

Teams Want Compatibility, Not Replatforming

Despite these challenges, leaders are not looking to rebuild their entire observability stack. Their frustration centers on the cost and scale limits of current approaches, not the workflows themselves.

  • 98% of leaders would adopt a fully compatible option that eases cost and scale pressure
  • Workflow continuity remains a top priority across respondents

"Teams aren't looking for a rip and replace," said Tschetter. "They want to keep their workflows and scale them. If you can separate cost from data volume and work with the tools they already trust, that's a breakthrough."

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Observability Costs Rising Faster Than Value

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply.

Top findings of the report include:

  • More than half of leaders allocate over 25% of their observability budget to a single platform, yet only 13% say they are very satisfied with the cost-to-value ratio.
  • Nearly 80% of teams are filtering, archiving, or offloading logs to control costs—reducing critical data visibility when teams need it most.
  • 87% of leaders report that slow queries on observability data were caused by inaccessible data delay workflows such as threat detection and incident response.
  • 87% of respondents are exploring or open to platform alternatives that reduce cost and scale pressure without disrupting current workflows, and 98% say they would adopt a fully compatible option.

Observability Spending Is Increasing While Value Declines

Enterprise teams report rising observability costs year over year, but confidence in platform ROI is slipping. Leaders say platform-centric licensing models and the rapid growth of observability data have created an environment whereby retaining essential logs or adding new workloads often requires difficult trade-offs.

Rising Costs Are Forcing Cuts to Visibility

To manage spend, many organizations are reducing retention or shifting data into lower-cost storage tiers. These common cost-saving measures directly reduce visibility and degrade query performance, and come with significant operational consequences:

  • High-value logs get filtered out before ingestion
  • Investigations slow as teams move data out of cold storage
  • Real-time responsiveness suffers during incidents

"Too many organizations are being priced into flying blind," said Eric Tschetter, Chief Architect at Imply. "They're cutting retention because budgets force their hand, and it shouldn’t be that way. Teams tell us they're pushing data into cold storage to keep costs in check and that can slow investigations, can create dangerous blind spots, and can weaken resilience. In a crisis, those trade-offs are unacceptable."

Teams Want Compatibility, Not Replatforming

Despite these challenges, leaders are not looking to rebuild their entire observability stack. Their frustration centers on the cost and scale limits of current approaches, not the workflows themselves.

  • 98% of leaders would adopt a fully compatible option that eases cost and scale pressure
  • Workflow continuity remains a top priority across respondents

"Teams aren't looking for a rip and replace," said Tschetter. "They want to keep their workflows and scale them. If you can separate cost from data volume and work with the tools they already trust, that's a breakthrough."

The Latest

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...