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 Patel
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.
Axiom
Engineering
How many bitmaps does it take to beat a gorilla?
Why we built our own caching and storage format.
Heinz Gies
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 Ehrlich
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 Toth
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 Toth
Engineering
Dynamic subrings: Consistent hashing without the tradeoff
How dynamic subrings let MetricsDB balance writes, reads, and resilience without compromise.
Heinz Gies
Engineering
The Sortable interface: Teaching every column type to sort itself
Replacing a one-size-fits-all sort with column-aware algorithms delivered speedups ranging from 2x to 26x, without changing a single query.
Hassan Ezzeldeen, Mano Toth, Tomás Senart
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 Patel
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 Toth
Teaching AI to speak Splunk, then proving it works
Read postClose the loop: User feedback for AI capabilities
Read postIntroducing GenAI functions: Analyze AI conversations with purpose-built APL functions
Read postStop shipping on vibes: Offline evaluations for AI capabilities
Read postIntroducing metrics: High-cardinality without the cost
Read postDesigning MCP servers for wide schemas and large result sets
Read postHaydex: From Zero to 178,600,000,000 rows a second in 30 days
Read postYour agents are only as good as their context. Give them everything with Axiom MCP
Read postUnderstand your event data in seconds with Spotlight
Read postWhat building AI features taught us about the future of observability
Read postAxiom’s new JS logging libraries: Flexible, powerful, framework-agnostic
Read postNew dashboard elements: heatmaps, pie charts, monitor lists, and notes
Read postMonitoring at Axiom
Read postEvents, logging, and compliance
Read postIntroducing Flow: Redefining event data processing
Read postIntroducing our new documentation
Read postIntroducing Axiom Terraform Provider
Read postFreedom from limits
Read postHow to Enrich OPNsense Events with Threat Intel
Read postHow to Use Axiom with OPNsense logs
Read postOTel semantic conventions deep dive
Read postThe Right To Be Forgotten vs Audit Trail Mandates: A Tech-Law Expert’s Guidance for Log Management
Read postWhy should I even consider OTel?
Read postIt’s time to stop self-managing your log infrastructure
Read postObservability: A brilliant idea whose name has been hijacked
Read postDistributed Tracing adds visual instrumentation for microservices
Read postNew Pricing: Axiom starts lower, stays lower
Read postUpgrade your Grafana experience with the Axiom data source plugin
Read postMonitoring HTTP Requests with Cloudflare Workers
Read postHow We Made the Axiom Vercel Integration Even Better
Read postMonitoring AWS Lambda with Axiom
Read postGet Deep Visibility into CloudFront Logs with Axiom
Read postJune Changelog: What’s New at Axiom
Read postMay Changelog: What’s New at Axiom
Read postApril Changelog: What’s New at Axiom
Read postVercel Integration
Read postMake Your Logstash Pipeline More Powerful with Axiom
Read postFebruary Changelog: What’s New at Axiom
Read postShipping Filesystem Metrics to Axiom
Read postNovember Changelog: What’s New at Axiom
Read postQuery Logs with Axiom CLI
Read postMonitor and Analyze Your Heroku Applications with Axiom
Read postOctober Changelog: What’s New at Axiom
Read postMonitoring using Axiom’s Data Explorer
Read postSeptember Changelog: What’s New at Axiom
Read postIntroducing Axiom Playground
Read postImproved Incident Response with Alerts from PagerDuty on Axiom
Read postObserving IBM Kubernetes service
Read postGetting the best out of Axiom’s Log Streams
Read postLearn how to setup Monitors and Notifiers
Read postUse Axiom and MetricBeat to better understand system performance
Read postVisualizing log events with Axiom
Read postUse Axiom and Redis for better performance monitoring
Read postGetting Sophisticated alerts from Filebeat on Axiom
Read postShipping uptime metrics to Axiom
Read postMonitoring Rancher with Axiom
Read postHow to Analyze Logstash logs on Axiom.
Read postMonitor DigitalOcean Kubernetes Service with Axiom
Read postIngress Log Data from Azure Kubernetes Service to Axiom
Read postWorking with Aggregations
Read postWorking with Dashboards in Axiom
Read postIntroducing the Axiom CLI
Read postRemote Collaboration tips: microphone
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