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Coralogix Releases Tracing TCO Optimizer

Coralogix launched the Tracing TCO Optimizer, enabling Coralogix users to assign use cases to their tracing data, and realize up to 90% savings on their ingestion costs.

"Traces are typically employed to provide a detailed operational view, but this is just one part of their value. Coralogix is now the only platform that allows users to define the use case for their data: whether the data be queried frequently, drive dashboards or be retained for historical analysis," said Yoni Farin, Coralogix CTO and co-founder. "This, combined with the power of Coralogix Remote Query and the Streama architecture, enables customers to infinitely retain and analyze their traces over years, while still delivering the remarkable cost optimizations that make Coralogix stand out in the industry."

New features and benefits of Tracing TCO Optimizer include:

- Significant Tracing Cost Savings - Users can now assign use cases to their Tracing data. High priority data is indexed and queried frequently and enjoys access to every feature, Medium priority data (75% cost savings) drives dashboards, machine learning models, in-stream alerting and more, while Low priority data (90% cost savings) is retained for historical analysis and regulatory reasons within the Coralogix Archive.

- Fine-grained Control - Data can be matched on whatever fields are attached to the trace, everything from language, to library version and error details.

- Infinite Retention. Instant Access - Combined with Coralogix Remote Query, traces can be retained indefinitely and still accessed in seconds at no extra costs, without the need to reindex.

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Coralogix Releases Tracing TCO Optimizer

Coralogix launched the Tracing TCO Optimizer, enabling Coralogix users to assign use cases to their tracing data, and realize up to 90% savings on their ingestion costs.

"Traces are typically employed to provide a detailed operational view, but this is just one part of their value. Coralogix is now the only platform that allows users to define the use case for their data: whether the data be queried frequently, drive dashboards or be retained for historical analysis," said Yoni Farin, Coralogix CTO and co-founder. "This, combined with the power of Coralogix Remote Query and the Streama architecture, enables customers to infinitely retain and analyze their traces over years, while still delivering the remarkable cost optimizations that make Coralogix stand out in the industry."

New features and benefits of Tracing TCO Optimizer include:

- Significant Tracing Cost Savings - Users can now assign use cases to their Tracing data. High priority data is indexed and queried frequently and enjoys access to every feature, Medium priority data (75% cost savings) drives dashboards, machine learning models, in-stream alerting and more, while Low priority data (90% cost savings) is retained for historical analysis and regulatory reasons within the Coralogix Archive.

- Fine-grained Control - Data can be matched on whatever fields are attached to the trace, everything from language, to library version and error details.

- Infinite Retention. Instant Access - Combined with Coralogix Remote Query, traces can be retained indefinitely and still accessed in seconds at no extra costs, without the need to reindex.

The Latest

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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 ...