I had codex help me, in a long session, convert some grafana dashboard charts i created into betterstack queries. I asked it to save it's context and tips for doing the conversions. this is what it gave me

translating-grafana-to-betterstack.md

Translating Grafana (PromQL) Dashboards to Betterstack SQL

This note captures practical translation patterns from Grafana Prometheus panels to Betterstack SQL charts when data is coming from a Prometheus push metrics source.

1) Know the Betterstack metrics schema first

For Prometheus-style metrics in Betterstack, values are usually stored as aggregate states, not plain numeric columns.

Common columns:

• value_avg (AggregateFunction(avg, Nullable(Float64)))
• rate_avg (AggregateFunction(avg, Nullable(Float64)))
• buckets (AggregateFunction(anyLast, Array(Tuple(String, Float64))))
• buckets_rate (AggregateFunction(anyLast, Array(Tuple(String, Nullable(Float64)))) )
• buckets_sum_rate, buckets_count_rate
• events_count (for logs/events counting)

Implication: plain SELECT value_avg often looks null/binary. Use merge functions.

2) Core mapping: PromQL -> Betterstack SQL

Gauge/counter value over time

Grafana style:

• metric{labels...}

Betterstack:

• filter by name = 'metric'
• filter labels with metricTag('label') = 'value'
• aggregate with avgMerge(value_avg)

Pattern:

WITH per_series AS (
  SELECT
    {{time}} AS time,
    avgMerge(value_avg) AS value
  FROM {{source}}
  WHERE name = 'my_metric'
    AND dt BETWEEN {{start_time}} AND {{end_time}}
    AND metricTag('network') = 'calibration'
  GROUP BY time, series_id
)
SELECT time, avg(value) AS value
FROM per_series
GROUP BY time
ORDER BY time

Unit conversions

If Grafana divides by 1e18, do the same in SQL output:

SELECT time, value / 1e18 AS value ...

3) Ratios (A/B) from two metrics

Grafana style:

• metric_a / metric_b

Betterstack:

• compute each metric independently by time
• join on time
• divide with nullIf(denominator, 0)

4) Status counters (success/failure/pending) from cumulative series

For counter-like status metrics (...Status), compute deltas first.

Pattern:

1. Aggregate cumulative value by time, provider_id, status
2. lagInFrame previous cumulative
3. greatest(value - prev_value, 0) to handle resets
4. Aggregate deltas for totals/success rates

Typical success rate:

100.0 * sumIf(delta, status = 'success') / nullIf(sum(delta), 0)

Common rule used in these dashboards:

• exclude pending from denominator when calculating success rate.

5) Exact tag matching vs regex/substring

If you need exact provider filtering, use:

metricTag('providerId') = {{provider_id}}

Avoid match(...) for exact id matching unless you truly want regex behavior.

6) Histograms: why Betterstack can differ from Grafana

Grafana histogram_quantile expects cumulative bucket behavior with rate over a window.

In Betterstack, quantiles can look wrong when:

• top finite bucket is too low (saturation/flat lines)
• you compute on already degraded bucket data
• binning window differs from Grafana

Practical approach:

• use consistent time bins (toStartOfInterval(..., INTERVAL 30 minute) or similar)
• reconstruct per-bucket rates carefully
• compute weighted quantiles from bucket distribution
• make sure histogram buckets are high enough to avoid clipping

7) Bucket design guidance for throughput metrics

Observed issue: with max finite bucket 5e8 (500 MiB/s), high quantiles collapsed near top bucket.

Fix:

• add denser buckets in expected operating range
• extend top finite bucket above observed peaks

Readable bucket notation in code:

const KiB = 1 << 10;
const MiB = 1 << 20;
const GiB = 1 << 30;

Example throughput bucket shape:

• low-end: 1*KiB ... 100*MiB
• dense range: 256*MiB ... 896*MiB
• upper: 1*GiB, 1.25*GiB, 1.5*GiB, 1.75*GiB, 2*GiB, 2.5*GiB, 3*GiB

8) Betterstack links in table charts

• Prefer URL string columns (HTML <a> generally not rendered).
• Betterstack may append dashboard vars like vs[source] to internal dashboard links.

If vs[source] causes bad routing:

• rename destination dashboard variable source -> e.g. metrics_source
• update destination SQL FROM {{metrics_source}}
• build links with vs[metrics_source]=...

9) Practical checklist when a translated chart is blank

1. Confirm metric name exists in source.
2. Confirm label keys exist (metricTag('providerId'), etc.).
3. Confirm using correct merge function (avgMerge, anyLastMerge, ...).
4. Validate one metric with a minimal query first.
5. Check denominator zero handling (nullIf(..., 0)).
6. For counters, confirm delta logic is applied.
7. For histograms, verify bucket cap and time binning.

10) Minimal translation playbook

For each Grafana panel:

1. Copy PromQL expression.
2. Identify metric names + label filters + math.
3. Build Betterstack SQL in layers (CTEs):
   • raw per-series aggregation
   • per-time aggregation
   • joins/ratios/deltas
4. Add unit conversion in final SELECT.
5. Validate against Grafana for same time window and filters.