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DevOps & observability · #newrelic
Learn how to add New Relic custom attributes in Java, query them with NRQL, and isolate latency spikes in your checkout API.
Learn how to enrich New Relic APM traces with custom key‑value pairs (e.g., user‑role, tenant‑id) using the Java agent API, verify the data, and roll back safely if needed.
Guide to decide between New Relic Java agent auto‑instrumentation and manual custom instrumentation for Java microservices, with constraints, a comparison table, trade‑offs, implementation steps, validation, limitations, and rollback.
Learn how to enable New Relic Distributed Tracing in a Java microservice stack, configure sampling, verify header propagation, and balance observability with cost. Practical steps, code snippets, and troubleshooting tips included.
Learn how to diagnose and resolve data ingestion gaps in New Relic by analyzing NRQL buckets, testing network egress, and auditing agent logs for handshake failures.
Stop guessing where latency lives in your Kubernetes cluster. Learn how to use New Relic Distributed Tracing to map request flows and pinpoint the exact service or external API causing delays.
NRQL Query Builder Modal Focus Trap Configuration Goal: Ensure that when the NRQL query builder modal is opened, keyboard focus remains trapped inside the modal until it is closed, preventing navigation to the background page for screen‑reader and keyboard‑only users. Constraint: The New Relic One UI does not expose a documented setting or API to enforce foc
Step‑by‑step guide to diagnose and fix high error rates seen in New Relic APM for Java apps, with checks, fixes, and verification tips.
The “Data ingestion rate limit exceeded” error appears when an agent sends more trace or event data than the plan allows. In a low‑traffic application, enabling full transaction tracing or distributed tracing can trigger this limit and inflate the bill. New Relic offers a global or per‑agent trace_sampling setting and a transaction_tracer.enabled toggle that
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