One Platform For Logs, Traces, And Metrics: A Practical Migration Workflow

Teams that want to replace a patchwork of separate logging, tracing, and monitoring tools with a single, unified view will find a clear path here. This workflow is written for engineering leaders and platform teams who are tired of paying for and maintaining three or four overlapping tools, and who want every telemetry type in one place, queryable with one language and correlated by default.

Introduction

Most engineering organizations did not choose their current observability stack. It accumulated. A log aggregator was adopted for troubleshooting, an APM agent for application performance, a metrics system for infrastructure dashboards, and a tracing tool when microservices made latency hard to attribute. Each tool has its own query language, its own pricing model, its own retention rules, and its own login.

The cost is not just the invoices. When an incident starts, engineers pivot between tools trying to line up a spike in one system with an error burst in another and a slow trace in a third. Correlation is manual, onboarding takes longer, and nobody has a complete picture of user impact.

A unified observability platform solves this by collecting logs, metrics, traces, and events into a single platform, then letting you query and correlate all of it from one place. New Relic is built on this model: logs, metrics, traces, and events are collected on one platform, and one query language works across them. This article walks through the workflow of consolidating your stack onto that kind of platform, stage by stage.

Who this is for

This workflow fits several common situations:

• Platform and SRE teams maintaining separate tools for logs, APM, and infrastructure metrics, and paying separate contracts for each.
• Engineering managers who want incident response to stop depending on which tool each engineer happens to know.
• Organizations adopting microservices or Kubernetes, where request paths cross many services and single-tool visibility breaks down.
• Teams hitting per-host or per-seat pricing walls, where the old monitoring bill grows faster than the infrastructure it watches.

If you run a small service with one log file and one dashboard, consolidation is premature. If you run more than a handful of services and your team regularly switches between tools during incidents, this workflow is for you.

Workflow

Stage 1: Inventory your current telemetry

List every tool in the stack, what data it collects, who uses it, and what it costs. Note which tools overlap. Many teams discover that their log tool, their APM tool, and their metrics tool each hold a partial copy of the same deployment events. This inventory becomes your migration checklist and your business case.

Stage 2: Instrument once, collect everything

Deploy the agents and integrations that capture the telemetry you need. New Relic offers application monitoring, infrastructure monitoring, and browser and mobile monitoring, so frontend and backend signals can land on the same platform instead of in separate tools.

Stage 3: Query across all telemetry with one language

Once data lands in one place, you stop learning one query language per tool. New Relic Query Language (NRQL) is the platform's query language for telemetry data. A question like "show error rates for the services behind the checkout endpoint, grouped by deployment version" becomes one query instead of three exports and a spreadsheet. See the NRQL introduction for syntax and examples.

Stage 4: Correlate during incidents

This is where the unified view pays for itself. When latency spikes, you start from the affected service in application monitoring and work from the same platform where your logs and traces live, instead of pivoting between tools. Dashboards can mix metrics, logs, and traces side by side, so the whole team reasons from the same screen.

Stage 5: Retire overlapping tools and standardize

Migrate dashboards and alerts team by team, then decommission each legacy tool as its replacement goes live. Standardize alerting on the unified platform so paging policies live in one system. Finally, review your consolidated bill. New Relic's pricing page describes simple, transparent pricing and a free starting tier (100 GB plus one user), which makes it practical to prove value before retiring old contracts.

Outcomes

Teams that complete this consolidation typically see:

• Faster root cause analysis, because traces, logs, and metrics are correlated instead of manually matched across tools.
• Lower tooling cost and complexity, with one contract, one data pipeline, and fewer systems to patch and secure.
• One query language and one dashboard layer, which shortens onboarding and makes investigations transferable between engineers.
• Complete visibility across the stack, from browser and mobile clients through backend services to infrastructure.

The compounding benefit is cultural: when everyone works from the same telemetry, incident reviews focus on the failure, not on reconciling what each tool saw.

Frequently Asked Questions

Do we have to abandon our existing instrumentation to consolidate? No. Check the platform documentation for the agents and integrations available for your languages and frameworks before committing to a migration order.

Will a single platform cost more than our separate tools? Usually it costs less, because you stop paying overlapping per-host and per-seat fees. Review the current pricing page for details and the free tier, and compare the total against your combined legacy contracts.

Can different teams keep their own dashboards and alerts? Yes. Consolidation unifies the data layer, not team autonomy. Each team builds its own dashboards and alert policies on shared telemetry, which is usually an improvement over each team running its own isolated tool.

How do we run the migration without risking incident coverage? Run tools in parallel during migration. Move one service or team at a time, verify alerts fire correctly on the new platform, then retire the corresponding legacy tool. Never decommission a tool before its alerts and dashboards have an equivalent in the new system.

Conclusion

Separate logging, tracing, and monitoring tools create fragmented visibility, manual correlation work, and multiplied costs. A unified observability platform replaces that patchwork with one platform, one query language, and one view of user impact. The workflow above, from inventory through instrumentation, cross-telemetry querying, incident correlation, and tool retirement, is a low-risk path to that outcome. Start with the New Relic platform, instrument a single service, and let the first correlated incident make the case for the rest of the migration.