OpenTelemetry — more commonly OTel among engineers — is a set of APIs, libraries, agents, and collector services to capture distributed traces and metrics from your application. It provides a robust, standards-based approach for telemetry data collection, particularly beneficial for microservices and serverless architectures.
OTel offers several ways for you to deliver better service and outcomes to your customers, whether internal or external:
Observability: A telemetry data standard across services enables a more integrated and holistic end-to-end view of your systems’ performance and security.
Instrumentation: With a single API and format, you don’t need separate libraries for each monitoring service. And you don’t need to convert data to share it among different parts of your infrastructure.
Ubiquity: OTel is developed and supported by the Cloud Native Computing Foundation, a collaboration of nearly 1,000 organizations from AWS to Wikimedia to Lowe’s hardware and DoorDash. All have recognized that a ubiquitous standard helps them succeed.
It’s not the first such standard, but …
OpenTelemetry is neither the first nor only vendor-neutral telemetry standard. But OTel is emerging as the leading choice among today’s Platform Engineers and DevOps professionals. Besides its massive support from businesses, what technically makes OpenTelemetry stand out?
Traces and metrics: Beyond traditional logs, traces and metrics have become critical to monitoring and observability. OTel is focused on making the most of these.
Stronger schemas: OpenTelemetry's versioned schemas get praise as more comprehensive, flexible, interoperable, and future-proof than previous attempts.
Axiom makes OTel even more powerful
Axiom has been architected in parallel with emerging OpenTelemetry standards to ensure it will make the most of OTel data.
Capture 100% of every event: Axiom captures OTel data at full fidelity, with no need for conversion, truncation or sampling. It stores OTel events in their full original form to ensure no nuance is lost.
Query without constraints: Axiom’s APL query language was designed for event data in a way that SQL and others were not, and lets you transform archived data to a new schema at read time. This lets you trace the user experience across modern services using both the crisp schema of OTel and the messier logging of legacy services — without impacting the audit trail through premature transformation.
You can try Axiom with OTel data in our live Axiom Play sandbox. Go to the example OTel dashboard. There you’ll see live monitoring for Slowest Operations, Top 10 Span Errors, and several other charts.
Creating the chart for Average Span Duration in our APL query language was this simple:
['otel-demo-traces'] | summarize avg(duration / 1000000) by bin_auto(_time)
APL was also designed to be easier to figure out than SQL and other legacy syntaxes, while still having power and flexibility. Functions like time-binning make it straightforward to perform time-based analysis. Queries can be piped, rather than requiring nested clauses or subqueries. This also fosters re-use and sharing of query components among team members.
One customer CTO told us, “I can hire an engineer off the street, and they immediately know how to get value out of Axiom. That’s way different from other monitoring.” Others have reported they no longer need a query specialist on duty — product managers and marketing teams are able to create many of their own queries without needing to bring in an engineer.
See more, spend less.
Axiom is likely your most cost-effective OTel option, too. Our pricing starts as low as $25 per month, free for personal projects. No surprise bills, ever. Contact us today to get started: email@example.com