Skip to main content

Embracing Cost-Effective Observability Through an OpenTelemetry Approach

Mimi Shalash
Splunk

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage.

OpenTelemetry helps organizations understand the performance and health of their cloud-native applications and the infrastructure that supports them. As an open-source, vendor-neutral framework, it delivers the full toolkit to telegraph an organization's telemetry. With APIs, SDKs (software development kits) and a robust set of tools, OpenTelemetry helps teams tune in to the signals their systems are sending. Because when it comes to observability, it actually pays to keep your data well instrumented.

And the data proves it. Recent research shows that 57% of observability leaders have successfully reduced costs with OpenTelemetry by gaining control over what telemetry is collected, how it's routed, and where it goes.

Putting Organizations in Control of Their Valuable Data

Internal data is the engine driving digital transformation. Organizations rely on it to understand system behavior, optimize performance and make informed decisions. But as data volumes grow, so do costs.

OpenTelemetry gives organizations control over their telemetry strategy, enabling them to define where data is sent, what it includes, how it's structured, and how much is collected. This flexibility allows teams to implement intelligent data management policies, prioritizing high value telemetry for real-time analysis while routing lower priority data to cost effective archival storage. For example, critical data such as payment transactions can be sent to object storage for audit compliance, while simultaneously being forwarded to an APM tool for monitoring. It's a strategic shift: decoupling data collection from backend lock in and routing based on performance, compliance or cost requirements.

Boosting Efficiency with People and Process

Beyond cost savings, OpenTelemetry reduces organizational friction. While most developers agree on the need for observability standards, consensus often breaks down when teams push for their preferred tools.

OpenTelemetry solves this problem. It's the pragmatic standard that teams across stacks and languages can align around. It acts as a great equalizer, bringing consistency to data collection, while giving teams the flexibility to route telemetry to multiple backends based on evolving needs. And best of all, it avoids forcing immediate tool consolidation, which is often political, slow, and resource heavy.

Log it if you must … but it's the truth.

Giving Organizations Freedom and Reducing Vendor Lock-in

OpenTelemetry's value doesn't stop at efficiency. It's also about freedom. With OpenTelemetry, organizations can now challenge vendors to differentiate on how they analyze and visualize telemetry, rather than locking value behind proprietary data collection methods. What's the alternative? Getting stuck in tool jail where switching platforms feels like rewriting your entire application … with your wallet.

Proprietary tools might check the box today, but relying on vendor managed agents long term is a liability and creates technical debt. Here's why: out of the box telemetry rarely delivers the context required for intelligent automation. To enable smarter alerting, routing or remediation, teams need to enrich telemetry with custom tags and context. The more tightly you couple that enrichment to a proprietary agent, the more painful it becomes to migrate when pricing changes or architectural needs evolve.

OpenTelemetry has flipped the script by forcing vendors to compete where it matters; the quality of their insights, analytics and user experience.

Empowering Your Business with Observability

While many organizations recognize the business benefits of observability, turning that vision into reality takes more than good intentions. It takes the right skills, clear ownership and cross functional alignment.

Despite being the second largest project under the Cloud Native Computing Foundation (CNCF), OpenTelemetry can still feel overwhelming, especially for those just starting out. But here's the good news; the most successful observability practices don't wait for the perfect hire. They grow their own. They invest in curious, motivated team members and empower them to become OpenTelemetry champions from within. Look for developers and engineers who are excited about improving visibility, then give them the space and support to dive in, whether that's reading the OpenTelemetry docs, exploring CNCF resources, or joining community forums where they can learn from peers and industry experts.

Observability isn't just a tool, it's a mindset. And when teams future proof their instrumentation, they don't just collect data, they unlock answers.

Drive Performance and Save Costs with OpenTelemetry

Remember, with OpenTelemetry, your data stays portable, your tooling stays flexible, and your observability strategy stays future proof. In a world full of noise, only the teams who own their telemetry will trace their way to uptime.

Mimi Shalash is Observability Advisor at Splunk, a Cisco company

The Latest

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 ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

Embracing Cost-Effective Observability Through an OpenTelemetry Approach

Mimi Shalash
Splunk

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage.

OpenTelemetry helps organizations understand the performance and health of their cloud-native applications and the infrastructure that supports them. As an open-source, vendor-neutral framework, it delivers the full toolkit to telegraph an organization's telemetry. With APIs, SDKs (software development kits) and a robust set of tools, OpenTelemetry helps teams tune in to the signals their systems are sending. Because when it comes to observability, it actually pays to keep your data well instrumented.

And the data proves it. Recent research shows that 57% of observability leaders have successfully reduced costs with OpenTelemetry by gaining control over what telemetry is collected, how it's routed, and where it goes.

Putting Organizations in Control of Their Valuable Data

Internal data is the engine driving digital transformation. Organizations rely on it to understand system behavior, optimize performance and make informed decisions. But as data volumes grow, so do costs.

OpenTelemetry gives organizations control over their telemetry strategy, enabling them to define where data is sent, what it includes, how it's structured, and how much is collected. This flexibility allows teams to implement intelligent data management policies, prioritizing high value telemetry for real-time analysis while routing lower priority data to cost effective archival storage. For example, critical data such as payment transactions can be sent to object storage for audit compliance, while simultaneously being forwarded to an APM tool for monitoring. It's a strategic shift: decoupling data collection from backend lock in and routing based on performance, compliance or cost requirements.

Boosting Efficiency with People and Process

Beyond cost savings, OpenTelemetry reduces organizational friction. While most developers agree on the need for observability standards, consensus often breaks down when teams push for their preferred tools.

OpenTelemetry solves this problem. It's the pragmatic standard that teams across stacks and languages can align around. It acts as a great equalizer, bringing consistency to data collection, while giving teams the flexibility to route telemetry to multiple backends based on evolving needs. And best of all, it avoids forcing immediate tool consolidation, which is often political, slow, and resource heavy.

Log it if you must … but it's the truth.

Giving Organizations Freedom and Reducing Vendor Lock-in

OpenTelemetry's value doesn't stop at efficiency. It's also about freedom. With OpenTelemetry, organizations can now challenge vendors to differentiate on how they analyze and visualize telemetry, rather than locking value behind proprietary data collection methods. What's the alternative? Getting stuck in tool jail where switching platforms feels like rewriting your entire application … with your wallet.

Proprietary tools might check the box today, but relying on vendor managed agents long term is a liability and creates technical debt. Here's why: out of the box telemetry rarely delivers the context required for intelligent automation. To enable smarter alerting, routing or remediation, teams need to enrich telemetry with custom tags and context. The more tightly you couple that enrichment to a proprietary agent, the more painful it becomes to migrate when pricing changes or architectural needs evolve.

OpenTelemetry has flipped the script by forcing vendors to compete where it matters; the quality of their insights, analytics and user experience.

Empowering Your Business with Observability

While many organizations recognize the business benefits of observability, turning that vision into reality takes more than good intentions. It takes the right skills, clear ownership and cross functional alignment.

Despite being the second largest project under the Cloud Native Computing Foundation (CNCF), OpenTelemetry can still feel overwhelming, especially for those just starting out. But here's the good news; the most successful observability practices don't wait for the perfect hire. They grow their own. They invest in curious, motivated team members and empower them to become OpenTelemetry champions from within. Look for developers and engineers who are excited about improving visibility, then give them the space and support to dive in, whether that's reading the OpenTelemetry docs, exploring CNCF resources, or joining community forums where they can learn from peers and industry experts.

Observability isn't just a tool, it's a mindset. And when teams future proof their instrumentation, they don't just collect data, they unlock answers.

Drive Performance and Save Costs with OpenTelemetry

Remember, with OpenTelemetry, your data stays portable, your tooling stays flexible, and your observability strategy stays future proof. In a world full of noise, only the teams who own their telemetry will trace their way to uptime.

Mimi Shalash is Observability Advisor at Splunk, a Cisco company

The Latest

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 ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...