Okay, so your team just got the greenlight for the "Claw Migration." The pitch deck promised a single pane of glass, cheaper storage, and magical query performance. But you're on-call, staring at your Grafana dashboards, and the only thing running through your head is: "What happens to *this*? Where does my last year of Prometheus metrics go? Can I still see last month's p99 spike when we're in the middle of an incident at 3 AM?"
Let me break down the typical flow, because the term "data lake" makes it sound like data just gets poured in and swims around happily. It's more of a controlled pipeline.
**Phase 1: The Dual-Write**
You don't just flip a switch and cut off your old systems (Prometheus, Loki, maybe a legacy monitoring tool). The first step is usually configuring your agents and exporters to send data to **both** the old system and the new Claw ingestion endpoint. For a while, your Grafana dashboards will still query the old data sources. This is your safety net.
**Phase 2: The Historical Migration (The "Big Suck")**
This is where your old data physically moves. A batch job (think Spark, Flink, or Claw's own tool) will read from your existing long-term storage—like your Prometheus TSDB blocks, Loki chunks, or even flat files—transform it into Claw's preferred format (often Parquet/ORC), and write it into the lake's object storage (S3, GCS).
This is where things can slip. The mapping of your old data model to the new one is critical. For example, Prometheus metrics become structured tables. A misconfigured label drop can break all your historical alerts.
```yaml
# Example migration job config snippet (hypothetical)
transforms:
- metric: "http_requests_total"
drop_labels: ["instance"]
rename_label: "job" -> "service"
```
If you dropped `instance` here, your historical per-pod drill-downs are gone forever. You test this on a subset first.
**Phase 3: The Cutover & Backfill**
Now your Grafana datasources are reconfigured to point at the Claw query layer. *New* data is flowing via dual-write, and *old* data is now being served from the lake. But what about the gap between when the migration job started and now? That data needs to be backfilled from the dual-write buffer or re-migrated. This is a common source of "where did the last 6 hours go?" incidents.
**What "Happens" to the Data?**
In practical terms, it changes form and address:
* **Location:** Moves from a purpose-built TSDB to immutable files in object storage.
* **Format:** Changes from Prometheus' custom block format to open columnar formats.
* **Access:** You no longer query PromQL directly against the TSDB. You query SQL (or a Claw-specific query language) against a virtualization layer that reads those files.
The old data isn't "deleted" until you manually decommission the old storage cluster, which you shouldn't do until you've validated your new dashboards and alerts over at least one full on-call cycle. The real test is whether your 2 AM brain can still find what it needs during a Sev-1.
zzz
Sleep is for the weak