Coralogix TCO Optimizer cuts observability costs by up to 70 percent
Coralogix provides a guide on observability cost optimization, detailing strategies such as value-based routing, log-to-metric conversion, and object storage archiving. The article highlights how its TCO Optimizer platform enables teams to manage telemetry volume and reduce costs by 40 to 70 percent.
Key Takeaways
- Delhivery reduced annual observability spend by 50 percent while maintaining only two percent of logs in hot storage
- WSC Sports maintained visibility across 700 microservices while cutting its total observability bill by more than half
- Value-based routing enables alerting and dashboards on data stored in Amazon S3 without requiring expensive indexing
- Tail-based sampling and log deduplication processors reduce telemetry volume at the source to prevent ingest cost spikes
Why It Matters
Rising telemetry volume from Kubernetes and microservices often outpaces infrastructure budgets, forcing teams to choose between high costs or blind spots. By shifting from index-everything models to value-based routing, platforms like Coralogix allow streaming engineers to retain full-fidelity data in cold storage while keeping only critical incident signals in expensive hot tiers. This technical shift reflects a broader industry move toward decoupling data ingestion from search costs to maintain operational visibility during scaling. Watch for whether competitors adopt similar in-stream processing engines to eliminate the rehydration delays typically associated with querying archived telemetry.
Additional Context
Coralogix operates in a rapidly consolidating observability market where cost optimization has become a primary differentiator. In early 2025, Coralogix raised $70 million in a Series D round led by Goldman Sachs Growth to accelerate its TCO Optimizer platform and expand enterprise adoption, valuing the company at approximately $1 billion. The funding reflects investor confidence that telemetry cost management represents a distinct category from traditional APM, particularly as streaming platforms and CDN operators generate exponentially growing log and trace volumes from distributed microservices architectures.
The competitive landscape for observability cost control has intensified across multiple vendors. Datadog announced in May 2025 that its Flex Logs feature had reached general availability, allowing customers to index only a subset of ingested logs while retaining the remainder in a searchable archive at reduced cost, a model that directly parallels Coralogix's value-based routing approach. Meanwhile, Grafana Labs observability growth hit $600 million ARR in 2026, as the company continues to launch features like Adaptive Metrics to identify unused data and reduce waste. OpenTelemetry adoption continues to accelerate as the vendor-neutral instrumentation standard, with the CNCF reporting that OpenTelemetry is the second most active project by contributor count as of mid-2025, which increases the addressable market for any platform that can reduce the cost of processing OTel-native telemetry at scale.
Technical benchmarks for observability cost reduction remain difficult to standardize, but independent analyses provide useful reference points. Gartner estimated in its 2025 Market Guide for Observability Platforms that enterprises spend an average of $1.2 million annually on observability tooling, with data ingestion and indexing accounting for 60 to 80 percent of total platform costs. For streaming infrastructure operators running thousands of microservices across CDN edge nodes, the cost per gigabyte of ingested telemetry can exceed $15 per month on legacy platforms, making the 40 to 70 percent reduction claims from Coralogix's TCO Optimizer commercially significant at scale. Amazon Web Services published guidance in 2025 recommending that customers use Amazon CloudWatch metric streams and S3 Intelligent-Tiering to achieve similar tiered-cost outcomes natively within the AWS ecosystem, signaling that hyperscalers are building competing cost-optimization layers directly into their managed observability services.
Read full article at coralogix.com
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