Product - Axiom Blog

Product, Engineering
At petabyte scale, telemetry ingestion becomes a data-centre architecture problem
Why the shaping work hiding inside "ingest" should move to where telemetry is produced.
Neil Jagdish PatelJuly 30, 2026
Product, Engineering
Introducing Bifrost: A new loading path for petabyte-scale OpenTelemetry
Bifrost is a new high-volume OpenTelemetry data-loading path for Axiom's machine data platform, now in private preview.
AxiomJuly 29, 2026
Product, Engineering
Introducing Correlations: from symptom to system state
Connect logs, traces, and metrics so investigations can move from the first clue to the surrounding system state without manual query stitching.
Christopher EhrlichJune 22, 2026
Product, Engineering
Measure less, learn more: Open-source documentation observability from Axiom
Most analytics tools tell you how docs pages are consumed. They rarely tell you whether they're effective. Do11y is our open-source attempt to close that gap by treating documentation as instrumented software.
Mano TothApril 20, 2026
Product, Engineering
The humble placeholder: A small documentation problem worth fixing
Axiom is simple to get started with. But there is one small, reliable stumbling point for new users: placeholder replacement in code examples. We built a small tool to fix it.
Mano TothApril 14, 2026
Company, Product
From cost center to strategic asset: How Monks transformed observability with Axiom
Global digital services company Monks cut observability costs by 40%, eliminated security blind spots, and unlocked AI readiness, guided by strategic technology advisor Three Tree Tech.
Johanan Dixon, Stefan BogdanisMarch 30, 2026
Product, Engineering
Metrics are generally available
Metrics are now generally available. Hyper-cardinality, unified with logs and traces, and fully queryable by AI agents through MCP and a dedicated metrics skill.
Neil Jagdish PatelMarch 25, 2026
Product, Engineering
Catch what tests miss: Online evaluations for AI capabilities
Score your AI capability's outputs on live production traffic. Run reference-free scorers as fire-and-forget, control cost with per-scorer sampling, and trace every score back to the request that produced it.
Mano TothFebruary 27, 2026
Product, Engineering
Teaching AI to speak Splunk, then proving it works
We built open-source agent skills for Splunk-to-Axiom migration. Then we built evals to measure them, so every change is tested before it ships.
Tomás Senart, Igor BedesquiJanuary 29, 2026
Product, Engineering
Close the loop: User feedback for AI capabilities
Capture user ratings and comments on AI outputs, link them to traces, and see exactly what your capability did when users were unhappy. The missing signal for continuous improvement.
Dominic Chapman, Christopher EhrlichJanuary 23, 2026

At petabyte scale, telemetry ingestion becomes a data-centre architecture problem

Introducing Bifrost: A new loading path for petabyte-scale OpenTelemetry

Introducing Correlations: from symptom to system state

Measure less, learn more: Open-source documentation observability from Axiom

The humble placeholder: A small documentation problem worth fixing

From cost center to strategic asset: How Monks transformed observability with Axiom

Metrics are generally available

Catch what tests miss: Online evaluations for AI capabilities

Teaching AI to speak Splunk, then proving it works

Close the loop: User feedback for AI capabilities

Introducing GenAI functions: Analyze AI conversations with purpose-built APL functions

Stop shipping on vibes: Offline evaluations for AI capabilities

Introducing metrics: High-cardinality without the cost

Stop guessing. Ship AI products with confidence

Your agents are only as good as their context. Give them everything with Axiom MCP

Understand your event data in seconds with Spotlight

What building AI features taught us about the future of observability

Axiom’s new JS logging libraries: Flexible, powerful, framework-agnostic

Reimagining pricing: Axiom's new approach

From burden to asset: reimagining logs at scale

New dashboard elements: heatmaps, pie charts, monitor lists, and notes

Monitoring at Axiom

When you’ve outgrown CloudWatch, turn to Axiom

Sampling could be a costly mistake

Events, logging, and compliance

Introducing Flow: Redefining event data processing

Axiom + Tailscale: Elevate your network visibility and security

Introducing our new documentation

Monitorama 2024: Booth A, new tees, and a party!

A tech writer’s adventure

Introducing Axiom Terraform Provider

Feature Recap

KubeCon Paris 2024: Drinks, chats, logs and traces with Axiom

Freedom from limits

How to Enrich OPNsense Events with Threat Intel

How to Use Axiom with OPNsense logs

OTel semantic conventions deep dive

Join us at re:Invent!

The Right To Be Forgotten vs Audit Trail Mandates: A Tech-Law Expert’s Guidance for Log Management

Join us at KubeCon!

Why should I even consider OTel?

It’s time to stop self-managing your log infrastructure

Traces are just logs — unify your approach for deeper insights

Introducing the Axiom Cloudflare Logpush app

Introducing New Chart Types for Advanced Logging and Observability in Axiom

Observability: A brilliant idea whose name has been hijacked

Distributed Tracing adds visual instrumentation for microservices

New Pricing: Axiom starts lower, stays lower

Upgrade your Grafana experience with the Axiom data source plugin

Monitoring HTTP Requests with Cloudflare Workers

How We Made the Axiom Vercel Integration Even Better

Monitoring AWS Lambda with Axiom

Working with Aggregations

Working with Dashboards in Axiom