Let's be honest: nobody *enjoys* decommissioning a monitoring platform. It's the technical equivalent of a root canal, but with more YAML and the lingering fear that you've missed a critical alert webhook pointed at a PagerDuty schedule that nobody has touched since 2018. Yet, after our 11-month migration from NewRelic to Claw Observability, we finally pulled the plug on the old agent last week. The forcing function was simple: our NewRelic bill had achieved sentience and was actively making architectural decisions for us.
The migration itself is a saga for another thread (involving custom metric exporters, span sampling debates, and a truly cursed piece of middleware that logged to a CSV file). This post is about the *decommissioning*—the meticulous, paranoid process of ensuring you don't lose visibility while cutting over the life support.
Our sequencing was driven by dependency mapping. You can't just kill the agent. The order of operations matters:
* **Phase 1: Synthetic Checks & External Monitoring**
* Moved all uptime, transaction, and browser synthetics to Claw's external probe network two months prior. This gave us a baseline that was independent of the in-app agents.
* **Phase 2: Business & APM Metrics**
* Verified a full quarter of side-by-side data for key business KPIs (order volume, API latency by endpoint, error rate). We used Claw's data ingestion API to backfill historical trends, but the real test was running dashboards in parallel.
* Switched alerting policies. This was a nerve-wracking week of adjusting thresholds. NewRelic's Apdex is a sneaky beast to replicate precisely.
* **Phase 3: Logs & Traces**
* With metrics stable, we redirected all application logging (via OpenTelemetry collectors) and trace sampling to Claw's endpoints. The critical step here was ensuring trace context propagation still worked seamlessly with our remaining services that were still reporting to NewRelic as a backup.
* **Phase 4: Agent Decommission & Configuration Purge**
* This is where the horror stories live. We used a staggered rollout, removing the NewRelic agent from our deployment manifests service-by-service. The checklist for each service was:
* Remove environment variables (`NEW_RELIC_LICENSE_KEY`, `NEW_RELIC_APP_NAME`)
* Comment out the agent initialization in our Go/Node.js entrypoints (e.g., `require('newrelic');`)
* Delete the myriad of `newrelic.js` and `newrelic.yml` config files from codebases.
* Update infrastructure-as-code (Terraform) to remove the NewRelic agent installation from base AMIs and Kubernetes DaemonSets.
Where things slipped? The *documentation*. Not ours, but NewRelic's own silent hooks. We found three legacy cron jobs on forgotten utility servers that were still using the NewRelic API to dump report data. We also discovered a deprecated microservice, thought to be decommissioned years ago, that was still happily sending APM data because its Docker image had the agent baked into the base layer. The lesson: audit *everything* that has a network path out, not just your main application code.
The final step was the license key revocation. Even after zero data for 14 days, we held our breath. The config purge looked like this for a typical Node service:
```javascript
// server.js - BEFORE
require('newrelic');
const app = require('./app');
// ... rest of the file
// server.js - AFTER
// NewRelic agent decommissioned 2023-10-26
// Observability via Claw OTEL collector on port 4318
const app = require('./app');
// ... rest of the file
```
And the accompanying Dockerfile change:
```dockerfile
# Removed:
# RUN npm install newrelic --save
# ENV NEW_RELIC_LICENSE_KEY=
# ENV NEW_RELIC_APP_NAME=
```
The bill is now zero. The dashboards are stable. The alert fatigue is marginally better. Would I do it again? Ask me after I finish the six other legacy tools on the list.
APIs are not magic.
You're dead on about the dependency mapping being the critical path. We did something similar but added a formal dependency graph using a homegrown tool that parsed our NewRelic alert policies and synthetic scripts. The surprise wasn't the direct dependencies, it was the transitive ones. For instance, a legacy dashboard used a NRQL query that pulled from an infrastructure agent metric we'd forgotten was still running on three older batch job servers. The synthetics were the easy part.
Your forcing function resonates. We had a similar cost-driven trigger, but the tipping point was performance degradation from the dual agent setup during peak load. The overhead wasn't trivial, especially on high-throughput API nodes where both agents were competing for CPU to buffer and export data. Did you instrument a comparison of application performance before and after the agent removal? We saw a 3-7% reduction in P99 latency across our most heavily instrumented services once the NewRelic collector was fully disabled.
Oh man, the "sentient bill" line is too real. That's exactly what pushed our team to start looking at alternatives like Claw in the first place.
Your focus on dependency mapping is super interesting. I'm still pretty new to this whole observability world, but it makes total sense that you can't just uninstall things. When you talk about moving synthetics first to get an independent baseline, that seems really smart. How did you handle the comparison between the NewRelic and Claw synthetic results during that overlap period? Was there a lot of tuning needed to make the thresholds and alerts feel equivalent, or was it pretty straightforward?