Coralogix integration with TrueFoundry AI Gateway

As teams move from AI experiments to production-grade applications, one theme pops up in every conversation: observability is non-negotiable. It’s no longer enough to know whether a request succeeded or failed—you need to understand why a model behaved a certain way, which prompts or tools were involved, and how that impacts cost, latency, and user experience.

That’s exactly where the integration between TrueFoundry AI Gateway and Coralogix comes in.

TrueFoundry’s AI Gateway gives teams a single control plane for all their LLMs and agents—across clouds, vendors, and even on-prem clusters—complete with routing, rate limiting, guardrails, and cost controls. Coralogix is a full-stack observability platform that unifies logs, metrics, traces, and security data into one place with powerful real-time analytics and AI-assisted insights.

Together, they give you end-to-end AI observability: from a user message hitting the gateway, to prompts sent to models, to traces and metrics flowing into rich dashboards and alerts.

Why Coralogix + TrueFoundry

Modern AI systems aren’t just “one model and one endpoint” anymore. They’re:

• Multi-model: OpenAI, Anthropic, local models, vector DBs, rerankers, tools
• Multi-environment: dev, staging, prod, often spread across regions
• Multi-layered: agents, orchestration, retrieval, business logic, plugins

This complexity makes traditional “log a few lines and hope for the best” monitoring break down quickly.

By exporting OpenTelemetry traces from TrueFoundry AI Gateway directly into Coralogix, you get:

• Unified view of AI traffic
  All LLM and agent requests from the gateway appear as structured traces in Coralogix, alongside the rest of your application telemetry. (truefoundry.com)
• Deep, real-time insight into model behaviour
  Coralogix’s streaming analytics and AI observability features let you slice by model, route, latency, cost, and error patterns—all without indexing delays. (Coralogix)
• Cost and reliability controls at scale
  Coralogix’s architecture is designed for high-volume telemetry with smart data management, while AI Gateway provides rate limiting, retries, and guardrails on the request path. (truefoundry.com)
• Faster incident response
  When something goes wrong—token spikes, latency regressions, prompt bugs—you can go from alert to trace to root cause in a few clicks, instead of grepping logs across systems. (Coralogix)

How the integration works (high-level)

At a high level, the flow looks like this:

1. TrueFoundry AI Gateway instruments LLM and agent requests using OpenTelemetry.
2. The gateway exports traces to Coralogix’s OTEL endpoint over gRPC.
3. Each trace includes rich metadata (model, route, application, subsystem, latency, etc.).
4. Coralogix ingests, enriches, and analyzes this telemetry in real time.
5. Your SRE, platform, and AI teams explore the data via dashboards, queries, and alerts.

Because this is built on OpenTelemetry, you don’t have to maintain a separate, custom integration. You simply configure the exporter once in the AI Gateway, and the rest of your observability strategy stays standards-based. (truefoundry.com)

Step-by-step: Setting up Coralogix with TrueFoundry AI Gateway

The full, detailed configuration is documented in the TrueFoundry Coralogix integration guide, but here’s the integration story in blog-friendly form. (truefoundry.com)

Step 1 – Grab your Coralogix credentials

From the Coralogix dashboard, the team will collect:

• Traces endpoint – the OpenTelemetry gRPC endpoint for the correct region (e.g. ingress.coralogix.com:443 for EU, or regional variants such as the India or US endpoints). (truefoundry.com)
• API key – used to authenticate OTEL traffic.
• Application & subsystem names – human-friendly labels (for example, ai-gateway-prod / llm-traces) that determine how traces are organized in Coralogix.

Choosing meaningful application/subsystem names upfront makes queries and dashboards a lot easier to reason about later.

Step 2 – Enable OTEL export in AI Gateway

Inside the TrueFoundry AI Gateway:

1. Navigate to the Configs section.
2. Open the OTEL Config panel.
3. Enable Traces exporter.
4. Select gRPC as the protocol (recommended for Coralogix).
5. Paste in the Coralogix OTEL traces endpoint gathered in Step 1. (truefoundry.com)

Once saved, the gateway will know where to stream its traces.

Step 3 – Add the required headers

Coralogix expects certain headers to route and authenticate incoming telemetry. In the AI Gateway configuration, you’ll add headers similar to:

• Authorization: Bearer <coralogix-api-key>
• CX-Subsystem-Name: <subsystem-name>
• CX-Application-Name: <application-name>

These identify your data in Coralogix and ensure it’s grouped logically for search, dashboards, and alerts.

Step 4 – Send traffic and verify

With configuration in place:

1. Send some test traffic through TrueFoundry AI Gateway (e.g., a few chat completions or agent runs).
2. Use the Monitor section in TrueFoundry to confirm that traces are being generated correctly.
3. Switch to Coralogix, open the Traces view, and filter by your application/subsystem names.
4. You should see spans representing AI Gateway calls, complete with attributes such as route, model, latency, and status. (truefoundry.com)

From here, your observability journey becomes about modeling the questions you care about, not wiring up plumbing.

What teams can do with this integration

Once TrueFoundry AI Gateway is hooked into Coralogix, a lot of high-value workflows become straightforward.

1. Track latency, errors, and SLOs for every AI surface

You can build dashboards that answer questions like:

• What’s the p95 latency for each model or route?
• How often do timeouts, 4xx, or 5xx happen per provider?
• Are certain regions or tenants seeing systematically worse performance?

Because Coralogix unifies logs, metrics, and traces, you can correlate AI latency with underlying infrastructure issues, database slowdowns, or dependency failures. (Coralogix)

2. Monitor cost behaviour and token usage

AI workloads often hide cost surprises in long-lasting conversations or poorly-bounded prompts. With Coralogix’s AI observability and TrueFoundry’s request-level metadata, you can: (Coralogix)

• Track token usage and call frequency per model, team, or feature.
• Spot spikes in usage tied to new releases.
• Set alerts on anomalous cost patterns before the month-end bill arrives.

Tie this back to AI Gateway’s rate limits, budgets, and routing rules, and you get a feedback loop where observability directly informs control.

3. Debug agent behaviour end-to-end

When an agent responds incorrectly or feels “slow”, there might be multiple root causes: flaky tools, mis-configured retrieval, slow models, or prompt regressions.

With gateway traces flowing into Coralogix, teams can:

• Follow request flows across services and tools via traces.
• Drill down into specific spans representing external calls or model invocations.
• Use Coralogix’s ML-driven analysis to spot anomalies or unusual patterns across large volumes of telemetry. (Coralogix)

4. Build AI-specific dashboards and alerts

Using Coralogix’s dashboards and alerting, you can create AI-centric views such as: (Coralogix)

• “AI Gateway health” – error rate, latency, traffic by route/model.
• “Model performance” – user-facing latency vs. upstream provider latency.
• “Safety & quality signals” – flagged interactions, moderation hits, retry patterns.
• “Cost & usage” – tokens, call volume, cost per feature or team.

Alerts can then notify on deviations—like a sudden surge in error rate for a single provider—so platform teams can automatically fail over via AI Gateway routing or work with the model vendor.

Choosing the right Coralogix region

For performance and compliance, it’s important to send data to the correct regional endpoint. Coralogix provides multiple gRPC endpoints (for example, European, US, and APAC regions), and the TrueFoundry docs include a table of common endpoints along with a link to Coralogix’s own regional documentation for the most up-to-date list. (truefoundry.com)

When configuring AI Gateway, the team simply points the OTEL exporter at the endpoint matching their Coralogix account region.

Bringing it all together

AI applications are rapidly becoming mission-critical, and the bar for reliability, performance, and cost control is rising with them. The integration between TrueFoundry AI Gateway and Coralogix gives teams a practical way to:

• Centralize AI traffic control (routing, guardrails, limits) in the gateway.
• Centralize AI observability (logs, metrics, traces, AI-specific analytics) in Coralogix.
• Ship faster with confidence, backed by rich telemetry and proactive alerting.