Updated 16 Sep 2026: Adds Grafana Agent Observability's now-published pricing and October 1 billing start: Free/Pro include 30k generations and 25M system-initiated Eval/Guard tokens monthly; Pro overages start at $1.50/1k generations and $2/1M LLM Eval/Guard tokens, while telemetry is billed separately.
Grafana Agent Observability links live agent telemetry to evals and CI regression gates
Grafana Cloud’s Agent Observability connects production telemetry, online evaluators, offline experiments and CI/CD gates — and now has a concrete cost model. Generation and LLM-based Eval/Guard billing starts October 1, with included monthly allowances before usage overages apply.
Grafana Agent Observability became generally available in Grafana Cloud on July 30, 2026.
Generation and Evals & Guards token metering/billing begins October 1, 2026; telemetry is billed at standard Grafana Cloud rates separately.
Free and Pro include 30,000 captured generations per month.
Free and Pro include a shared 25-million-token monthly pool for system-initiated AI usage, including LLM-based Agent Observability evals and guards.
Pro generation overage starts at $1.50 per 1,000 generations.
LLM-based Evals & Guards beyond the included token pool are billed at $2 per 1 million tokens on Pro.
Static checks such as schema validation, regex and heuristics consume no Eval/Guard LLM tokens.
Agent Observability tracks latency, token usage, cost, errors and conversation/tool telemetry and supports online evaluations, alerts, offline experiments and versioned test suites.
The Pro Grafana Cloud platform fee is $19 per month; Agent Observability telemetry usage is billed separately.
What builders should take away
Estimate both generation volume and LLM-judge token consumption before October 1; they are separate meters and telemetry is a third cost surface.
Use deterministic schema, regex and heuristic checks for properties that can be verified exactly so you do not spend LLM tokens on mechanical validation.
Remember that the 25M system-initiated token allowance is shared with other automated Grafana AI workloads; do not budget the entire pool to Agent Observability unless that is actually how your organization uses it.
Build eval suites from real production failures and high-risk workflows, not only synthetic happy paths.
Sample LLM-judge passes and failures with humans so a paid evaluator does not become an expensive source of false confidence.
Instrument agent version, model, tool activity and cost together so regressions can be tied back to the actual deployed change.
Control telemetry volume independently from evaluation sampling because traces/logs/metrics follow standard Grafana Cloud billing rather than the generation/Eval allowance.
What changed
Grafana Labs made Agent Observability generally available in Grafana Cloud on July 30, connecting production conversations, token/cost telemetry, online evaluators, failure collections, offline experiments and CI/CD checks. Grafana has now published the pricing mechanics that were previously uncertain. Generation and Evals & Guards token metering/billing begins October 1, 2026; telemetry has been billed at standard Grafana Cloud rates from day one. Free and Pro include 30,000 generations per month and a shared 25-million-token monthly pool for system-initiated AI usage such as LLM-based evals and guards. On Pro, usage beyond those included allowances starts at $1.50 per 1,000 generations and $2 per 1 million Eval/Guard tokens. Static checks such as regex, schema validation and heuristics consume no LLM tokens. Grafana’s current docs also expose the workflow as a broader agent-lifecycle system: production conversations and telemetry feed online rules, guards and alerts, while versioned test suites and experiments can compare candidate agents before release.
Why it matters
Agent teams can now model the cost of putting the full observe–evaluate–release loop into production rather than treating evals as an unpriced preview. The pricing has two separate meters that behave differently: capturing generations is one usage dimension, while LLM-based evaluators and guards draw from a shared system-initiated token pool; traces, logs and metrics remain normal Grafana Cloud telemetry. That creates a practical incentive to reserve LLM judges for semantic checks and use deterministic validators where an exact rule is sufficient. The underlying workflow remains valuable because production failures can become regression tests, but teams now need budgets and sampling policy alongside evaluator quality and instrumentation coverage.
The production layer includes cost and conversation behavior
Agent Observability can track latency, errors, token consumption and model cost alongside instrumented conversation traces. Aggregate metrics expose cost or reliability drift, while individual conversations provide the context needed to understand why an agent went wrong.
Evaluators turn behavior into alertable metrics
Teams can apply deterministic checks and LLM-judge evaluators to live traffic. Evaluator results can become Grafana Cloud Metrics and feed Grafana Alerting. Static schema, regex and heuristic checks do not consume LLM-evaluation tokens, while model-based judges do.
Production failures can become regression cases
Teams can collect low-scoring or otherwise interesting conversations, annotate them and add them to versioned test suites. That provides a direct route from an observed customer failure to a case that later prompt, model, tool or harness changes must survive.
Offline experiments can be part of CI/CD
The Agent Observability SDK can execute a test suite against a candidate agent, score trials and compare versions using stable test-case identifiers. This supports quality-versus-cost comparisons and pull-request or release gates before a change reaches production.
October 1 turns Agent Observability usage into a concrete cost model
Grafana says generations and Evals & Guards tokens are not metered or billed until October 1, 2026. Free and Pro include 30,000 generations each month plus 25 million tokens for system-initiated usage such as LLM-based evals and guards. Pro overages start at $1.50 per 1,000 generations and $2 per 1 million Eval/Guard tokens. The Pro platform fee is $19 per month; telemetry is billed separately at normal Grafana Cloud rates.
The token pool is shared with other system-initiated Grafana AI work
The 25-million-token pool is not dedicated solely to Agent Observability. Grafana says it is shared with other system-initiated AI activity in the organization, including automatically triggered investigations and service-account/API usage. Heavy use elsewhere can therefore change the marginal cost of production evals.
Judge quality remains the main source of false confidence
A metered LLM judge is still not ground truth. Teams need representative test suites, human sampling and deterministic validators where possible. Paying for more evaluation does not make a weak rubric or incomplete instrumentation reliable.
What to watch next
Real customer cost profiles after October 1 once generation and Eval/Guard billing is active rather than preview-only.
Whether Grafana changes included generation counts, token pools or overage prices after observing production usage.
Independent evidence on how Grafana evaluators correlate with human assessments across agent types.
Whether coding-agent session forwarding and additional framework integrations materially expand captured generation volume for existing customers.
Stronger native deployment/rollback integrations tied directly to experiment results and regression thresholds.
Still unclear
Grafana can change pricing, included allowances or product packaging after the October 1 billing transition.
The 25M token pool is shared across system-initiated Grafana AI activity, so Agent Observability's effective included allowance depends on other usage in the same organization.
Telemetry cost depends on trace/log/metric volume and retention, so the headline generation price is not the whole observability bill.
LLM-judge scores remain model- and rubric-dependent and can be unstable or biased.
Independent evidence on large external agent fleets remains more limited than Grafana's own product documentation.
Current Free/Pro/Enterprise Agent Observability pricing, included generation/token allowances, Oct 1 billing start, telemetry boundary and Eval/Guard overage rates.
Investigations has crossed from preview into production and incident.io now reports a large latency improvement in its own measured workflow. The agent continuously reassesses evidence and can hand remediation to coding agents, but the new speed and accuracy figures remain vendor-produced rather than independent.
Vercel Agent now works in Slack as well as the Vercel dashboard, combining logs, metrics, deployments and repository context with team conversation before proposing approved actions such as pull requests, rollbacks, configuration changes and cache purges.
Fin’s new Evals and Releases features let teams test agent changes against simulated conversations before publishing, bundle configuration into a release, ramp traffic or A/B test it, and feed failures from live Monitors back into the next iteration.