Coralogix

What makes Coralogix different

Coralogix positions itself as an AI-native observability platform that fundamentally differs from traditional SaaS tools by storing telemetry in your cloud using open formats—eliminating vendor lock-in. Rather than forcing data reduction or aggressive retention policies like hyperscalers, Coralogix enables indefinite retention of all dimensions at high cardinality, with costs controlled through intelligent tiering rather than sampling.

The platform emphasizes agent-ready architecture from day one, with conversational investigation (Olly), Model Context Protocol integration for Slack/PagerDuty/IDE workflows, and a programmable CLI. This reflects a shift from dashboard-first workflows to AI-first investigation patterns. The unified query language across logs, metrics, traces, and custom data types reduces context-switching and enables cross-signal correlation that hyperscalers typically require custom engineering to achieve.

Cost optimization is structural: Coralogix’s Cost Optimizer automatically routes critical logs to hot storage while offloading low-value data to your cloud storage, claiming 50% more data at lower cost. This architecture benefit—storing in your own cloud rather than a centralized platform—is antithetical to how AWS, GCP, and Azure monetize observability.

Pricing model

Coralogix uses usage-based pricing tied to data ingestion volume and storage duration. The exact per-GB rates are not published on the website; interested customers are directed to request a quote or contact sales. The platform emphasizes cost predictability through:

• Tiered ingestion: Critical logs analyzed in real-time; lower-priority data archived to your cloud storage at lower cost.
• Retention flexibility: Indefinite retention in your cloud storage (S3, GCS, Azure Blob) costs only what your cloud provider charges; query acceleration in Coralogix’s hot layer is priced separately.
• No forced sampling: Unlike traditional observability platforms, you retain all dimensions and cardinality without paying exponentially higher rates.

This model undercuts hyperscaler pricing by removing their storage markup—you pay only the cloud provider’s base storage cost plus Coralogix’s query and indexing fee, typically a fraction of what AWS X-Ray, GCP Cloud Trace, or Azure Monitor charge for equivalent data volume.

When it fits

• High-cardinality environments: Kubernetes clusters, microservices platforms, and multi-tenant SaaS with thousands of unique tag combinations benefit from not dropping dimensions.
• Compliance and long-term forensics: Organizations requiring 1+ year retention at reasonable cost, using your own cloud for audit trails.
• AI-driven operations: Teams adopting autonomous agents or LLM-based incident investigation; Olly and MCP are designed for agent workflows.
• Multi-signal correlation: Engineering teams investigating incidents across logs, metrics, and traces simultaneously without separate UIs.
• Cost-sensitive scale: Organizations ingesting 100GB+/day where traditional SaaS pricing becomes prohibitive.

When it doesn’t

• Simple, lightweight observability: Teams with low data volume (< 10GB/day) may find the multi-cloud setup and AI-first UX unnecessary overhead compared to simpler tools.
• Fully managed SaaS preference: Organizations avoiding cloud storage management or preferring single-vendor solutions may prefer Datadog or New Relic’s simpler all-in-one model.

Inclusion criteria

✅ Transparent pricing: Usage-based model described publicly; quote-based for specific rates but methodology is clear.
✅ Self-service signup: Available at https://coralogix.com/ with immediate trial onboarding.
✅ Public SLA/status page: Status monitored; SLA terms available to customers.