diff --git a/.claude/scripts/io-performance-analyzer/Dockerfile b/.claude/scripts/io-performance-analyzer/Dockerfile
deleted file mode 100644
index 83b85bff2c..0000000000
--- a/.claude/scripts/io-performance-analyzer/Dockerfile
+++ /dev/null
@@ -1,10 +0,0 @@
-FROM registry.fedoraproject.org/fedora:43
-
-RUN dnf install -y pcp pcp-system-tools pcp-export-pcp2json python3 python3-pip && \
-    dnf clean all
-
-RUN pip3 install matplotlib gsutil
-
-WORKDIR /data
-
-ENTRYPOINT ["/bin/bash"]
diff --git a/.claude/scripts/io-performance-analyzer/README.md b/.claude/scripts/io-performance-analyzer/README.md
deleted file mode 100644
index d840e2fa8b..0000000000
--- a/.claude/scripts/io-performance-analyzer/README.md
+++ /dev/null
@@ -1,117 +0,0 @@
-# Disk I/O Performance Graphing for MicroShift CI
-
-Tool for visualizing disk I/O activity from MicroShift CI job runs, primarily
-aimed at investigating etcd performance issues.
-
-## Background
-
-MicroShift uses an embedded etcd instance that is highly sensitive to disk I/O
-latency. Symptoms such as slow leader elections, "apply request took too long"
-warnings, or WAL sync delays often correlate with disk I/O spikes on the CI
-node. CI jobs collect [Performance Co-Pilot (PCP)](https://pcp.io/documentation.html)
-archives via the `pcp-zeroconf` package throughout the test run, capturing
-system-wide performance metrics at high resolution.
-
-This tool processes those PCP archives and produces a time-series graph of
-**Disk Read OPS**, **Disk Write OPS**, and **Disk Await** (`disk.dev.await`)
-at 15-second intervals, making it straightforward to correlate etcd issues
-with underlying disk activity.
-
-**Disk Await** is the average time (in milliseconds) that I/O requests spend
-waiting to be serviced by the device, including queue time and actual service
-time. It is the single most useful metric for diagnosing etcd I/O problems
-because etcd requires low-latency `fdatasync` calls on its WAL and snap files.
-When await rises above ~10 ms, etcd heartbeats can be missed and leader
-elections may be triggered. The tool reports the **max await across all block
-devices** at each sample point so that the worst-case device is always visible.
-
-## Obtaining PCP Data from CI
-
-PCP archives are stored with the CI artifacts under:
-
-```text
-artifacts/<test_name>/openshift-microshift-infra-pmlogs/artifacts/<ci_hostname>/
-```
-
-Download them using `gsutil`:
-
-```bash
-mkdir -p ~/pmlogs && cd ~/pmlogs
-python3 -m venv .
-./bin/python3 -m pip install gsutil
-./bin/gsutil -m cp -r gs://<path> ~/pmlogs/
-```
-
-The directory should contain files like `yyyymmdd.hh.mm.{0,index,meta}` and a
-`Latest` folio file.
-
-## Prerequisites
-
-- `podman` (used to build and run the analysis container)
-
-No other local dependencies are required. The container image includes PCP
-tools, Python 3, and matplotlib.
-
-## Usage
-
-```bash
-./run_io_graph.sh [--timezone TZ] [--output-dir DIR] [pcp-data-dir]
-```
-
-| Option | Description | Default |
-|---|---|---|
-| `--timezone TZ` | IANA timezone for timestamps | `UTC` |
-| `--output-dir DIR` | Directory for output files | Script directory |
-| `pcp-data-dir` | Directory with PCP archive files | Auto-detected |
-
-### Examples
-
-```bash
-# Auto-detect PCP data, default timezone (UTC)
-./run_io_graph.sh
-
-# Specify data directory and timezone
-./run_io_graph.sh --timezone US/Eastern ./path/to/pcp-data
-
-# Custom output directory
-./run_io_graph.sh --output-dir /tmp/results --timezone UTC ./path/to/pcp-data
-```
-
-## Output
-
-| File | Description |
-|---|---|
-| `io_data.json` | Extracted data with arrays: `timestamps`, `bi` (reads/s), `bo` (writes/s), `await` (disk await ms) |
-| `disk_io_performance.png` | Time-series chart with Read OPS (blue), Write OPS (red), and Disk Await (green, dashed, right Y-axis) |
-
-### Sample Graph
-
-![Disk I/O Performance](disk_io_performance.png)
-
-## How to Read the Graph
-
-When investigating etcd performance problems, look for:
-
-- **Disk Await spikes** (green, dashed, right Y-axis) are the primary
-  indicator of I/O latency problems. etcd requires `fdatasync` to complete
-  within its heartbeat interval (default 100 ms). Await values above ~10 ms
-  indicate the disk is under pressure; sustained values above ~50 ms almost
-  always correlate with etcd warnings such as "slow fdatasync", "apply request
-  took too long", or missed heartbeats leading to leader elections.
-- **Write spikes** (red) coinciding with etcd "slow fdatasync" or WAL warnings
-  in MicroShift journal logs. Sustained write activity above the baseline
-  suggests I/O contention from concurrent workloads or test operations.
-- **Read spikes** (blue) during test setup or image pulls that may starve etcd
-  of I/O bandwidth.
-- **Correlation with timestamps** from etcd log entries. Convert etcd log
-  timestamps to the timezone used in the graph to align events.
-
-## Files
-
-| File | Purpose |
-|---|---|
-| `run_io_graph.sh` | Orchestrator: builds container, runs extraction and plotting |
-| `Dockerfile` | Container image with PCP tools, Python 3, and matplotlib |
-| `extract_io.sh` | Runs `pcp2json` on PCP archives, extracts all metrics in one pass |
-| `parse_pcp.py` | Parses pcp2json output, aggregates per-device instances (sum read/write, max await) |
-| `plot_io.py` | Generates the PNG chart from JSON data using matplotlib |
diff --git a/.claude/scripts/io-performance-analyzer/disk_io_performance.png b/.claude/scripts/io-performance-analyzer/disk_io_performance.png
deleted file mode 100644
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diff --git a/.claude/scripts/io-performance-analyzer/extract_io.sh b/.claude/scripts/io-performance-analyzer/extract_io.sh
deleted file mode 100755
index c4cab8217f..0000000000
--- a/.claude/scripts/io-performance-analyzer/extract_io.sh
+++ /dev/null
@@ -1,28 +0,0 @@
-#!/bin/bash
-# Extract disk IO data from PCP archive using pcp2json with 15-second intervals.
-# Outputs JSON with arrays: timestamps, bi (reads/s), bo (writes/s), await (disk await ms)
-#
-# Usage: ./extract_io.sh <pcp-archive-dir> [output-json] [timezone]
-
-set -euo pipefail
-
-DATA_DIR="${1:?Usage: $0 <pcp-archive-dir> [output-json] [timezone]}"
-OUTPUT="${2:-/data/io_data.json}"
-TIMEZONE="${3:-UTC}"
-SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-
-echo "Using archive directory: ${DATA_DIR}"
-
-# Extract all metrics in a single pcp2json call
-TMPFILE=$(mktemp)
-trap 'rm -f "${TMPFILE}"' EXIT
-
-(cd "${DATA_DIR}" && pcp2json -a . -t 15sec \
-    disk.dev.read disk.dev.write disk.dev.await) \
-    > "${TMPFILE}" 2>/dev/null || true
-
-# Parse pcp2json output into clean plot-ready JSON
-python3 "${SCRIPT_DIR}/parse_pcp.py" --timezone "${TIMEZONE}" \
-    "${TMPFILE}" "${OUTPUT}"
-
-echo "Wrote $(python3 -c "import json; d=json.load(open('${OUTPUT}')); print(len(d['timestamps']))" 2>/dev/null || echo 0) data points to ${OUTPUT}"
diff --git a/.claude/scripts/io-performance-analyzer/io_data.json b/.claude/scripts/io-performance-analyzer/io_data.json
deleted file mode 100644
index 41638bbc4c..0000000000
--- a/.claude/scripts/io-performance-analyzer/io_data.json
+++ /dev/null
@@ -1,3114 +0,0 @@
-{
-  "timestamps": [
-    "2026-02-15 03:12:30",
-    "2026-02-15 03:12:40",
-    "2026-02-15 03:12:50",
-    "2026-02-15 03:13:00",
-    "2026-02-15 03:13:10",
-    "2026-02-15 03:13:20",
-    "2026-02-15 03:13:30",
-    "2026-02-15 03:13:40",
-    "2026-02-15 03:13:50",
-    "2026-02-15 03:14:00",
-    "2026-02-15 03:14:10",
-    "2026-02-15 03:14:20",
-    "2026-02-15 03:14:30",
-    "2026-02-15 03:14:40",
-    "2026-02-15 03:14:50",
-    "2026-02-15 03:15:00",
-    "2026-02-15 03:15:10",
-    "2026-02-15 03:15:20",
-    "2026-02-15 03:15:30",
-    "2026-02-15 03:15:40",
-    "2026-02-15 03:15:50",
-    "2026-02-15 03:16:00",
-    "2026-02-15 03:16:10",
-    "2026-02-15 03:16:20",
-    "2026-02-15 03:16:30",
-    "2026-02-15 03:16:40",
-    "2026-02-15 03:16:50",
-    "2026-02-15 03:17:00",
-    "2026-02-15 03:17:10",
-    "2026-02-15 03:17:20",
-    "2026-02-15 03:17:30",
-    "2026-02-15 03:17:40",
-    "2026-02-15 03:17:50",
-    "2026-02-15 03:18:00",
-    "2026-02-15 03:18:10",
-    "2026-02-15 03:18:20",
-    "2026-02-15 03:18:30",
-    "2026-02-15 03:18:40",
-    "2026-02-15 03:18:50",
-    "2026-02-15 03:19:00",
-    "2026-02-15 03:19:10",
-    "2026-02-15 03:19:20",
-    "2026-02-15 03:19:30",
-    "2026-02-15 03:19:40",
-    "2026-02-15 03:19:50",
-    "2026-02-15 03:20:00",
-    "2026-02-15 03:20:10",
-    "2026-02-15 03:20:20",
-    "2026-02-15 03:20:30",
-    "2026-02-15 03:20:40",
-    "2026-02-15 03:20:50",
-    "2026-02-15 03:21:00",
-    "2026-02-15 03:21:10",
-    "2026-02-15 03:21:20",
-    "2026-02-15 03:21:30",
-    "2026-02-15 03:21:40",
-    "2026-02-15 03:21:50",
-    "2026-02-15 03:22:00",
-    "2026-02-15 03:22:10",
-    "2026-02-15 03:22:20",
-    "2026-02-15 03:22:30",
-    "2026-02-15 03:22:40",
-    "2026-02-15 03:22:50",
-    "2026-02-15 03:23:00",
-    "2026-02-15 03:23:10",
-    "2026-02-15 03:23:20",
-    "2026-02-15 03:23:30",
-    "2026-02-15 03:23:40",
-    "2026-02-15 03:23:50",
-    "2026-02-15 03:24:00",
-    "2026-02-15 03:24:10",
-    "2026-02-15 03:24:20",
-    "2026-02-15 03:24:30",
-    "2026-02-15 03:24:40",
-    "2026-02-15 03:24:50",
-    "2026-02-15 03:25:00",
-    "2026-02-15 03:25:10",
-    "2026-02-15 03:25:20",
-    "2026-02-15 03:25:30",
-    "2026-02-15 03:25:40",
-    "2026-02-15 03:25:50",
-    "2026-02-15 03:26:00",
-    "2026-02-15 03:26:10",
-    "2026-02-15 03:26:20",
-    "2026-02-15 03:26:30",
-    "2026-02-15 03:26:40",
-    "2026-02-15 03:26:50",
-    "2026-02-15 03:27:00",
-    "2026-02-15 03:27:10",
-    "2026-02-15 03:27:20",
-    "2026-02-15 03:27:30",
-    "2026-02-15 03:27:40",
-    "2026-02-15 03:27:50",
-    "2026-02-15 03:28:00",
-    "2026-02-15 03:28:10",
-    "2026-02-15 03:28:20",
-    "2026-02-15 03:28:30",
-    "2026-02-15 03:28:40",
-    "2026-02-15 03:28:50",
-    "2026-02-15 03:29:00",
-    "2026-02-15 03:29:10",
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-    "2026-02-15 03:29:30",
-    "2026-02-15 03:29:40",
-    "2026-02-15 03:29:50",
-    "2026-02-15 03:30:00",
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-    "2026-02-15 03:30:30",
-    "2026-02-15 03:30:40",
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-    "2026-02-15 03:31:10",
-    "2026-02-15 03:31:20",
-    "2026-02-15 03:31:30",
-    "2026-02-15 03:31:40",
-    "2026-02-15 03:31:50",
-    "2026-02-15 03:32:00",
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-    "2026-02-15 04:06:10",
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-    1.027,
-    1.142,
-    1.189,
-    1.085,
-    1.014,
-    0.919,
-    1.035,
-    0.876,
-    0.851,
-    0.879,
-    0.846,
-    0.883,
-    0.86,
-    0.879,
-    0.881,
-    0.846,
-    0.905,
-    0.873,
-    0.842,
-    0.84,
-    0.845,
-    0.845,
-    0.837,
-    0.87,
-    0.863,
-    0.872,
-    0.898,
-    0.863,
-    0.879,
-    0.881,
-    0.893,
-    0.892,
-    0.883,
-    0.82,
-    0.869,
-    0.88,
-    0.865,
-    0.916,
-    0.871,
-    0.906,
-    0.975,
-    0.96,
-    0.905,
-    1.045,
-    1.179,
-    1.034,
-    1.24,
-    0.904,
-    0.883,
-    0.877,
-    0.903,
-    0.859,
-    0.956,
-    0.924,
-    0.96,
-    0.886,
-    0.903,
-    0.872,
-    0.895,
-    0.861,
-    0.887,
-    0.885,
-    0.897,
-    0.881,
-    0.897,
-    0.906,
-    0.881,
-    0.888,
-    0.892,
-    0.886,
-    0.895,
-    0.911,
-    0.881,
-    0.901,
-    0.889,
-    0.892,
-    0.856,
-    0.892,
-    0.884,
-    0.891,
-    0.9,
-    0.897,
-    0.899,
-    0.896,
-    0.898,
-    0.904,
-    0.892,
-    0.888,
-    0.898,
-    0.888,
-    0.894,
-    0.897,
-    0.889,
-    0.886,
-    0.895,
-    0.886,
-    0.906,
-    0.895,
-    0.896,
-    0.898,
-    0.878,
-    0.886,
-    0.898,
-    1.04,
-    0.924,
-    0.898,
-    0.895,
-    0.893,
-    0.9,
-    0.886,
-    0.896,
-    0.896,
-    0.893,
-    0.892,
-    0.886,
-    0.85,
-    0.956,
-    0.884,
-    0.859,
-    0.9,
-    1.001,
-    0.874,
-    0.911,
-    0.901,
-    1.06,
-    0.888,
-    0.902,
-    1.051,
-    0.871,
-    0.877,
-    0.904,
-    0.901,
-    0.891,
-    0.905,
-    0.878,
-    0.848,
-    0.873,
-    0.875,
-    0.877,
-    0.892,
-    0.879,
-    0.878,
-    0.901,
-    0.901,
-    0.955,
-    0.897,
-    0.869,
-    0.884,
-    0.894,
-    0.897,
-    0.885,
-    0.895,
-    0.884,
-    0.879,
-    0.89,
-    0.89,
-    0.895,
-    0.905,
-    0.907,
-    0.887,
-    0.89,
-    0.882,
-    0.882,
-    0.906,
-    0.882,
-    0.898,
-    0.935,
-    0.852,
-    0.915,
-    0.875,
-    0.956,
-    0.919,
-    0.939,
-    0.876,
-    0.903,
-    0.899,
-    0.895,
-    0.902,
-    0.893,
-    0.896,
-    0.892,
-    0.894,
-    0.897,
-    0.905,
-    0.892,
-    0.906,
-    0.892,
-    0.896,
-    0.902,
-    0.886,
-    0.9,
-    0.907,
-    0.889,
-    0.889,
-    0.905,
-    0.894,
-    0.844,
-    0.902,
-    0.882,
-    0.895,
-    0.85,
-    0.855,
-    0.901,
-    0.9,
-    0.901,
-    0.878,
-    0.924,
-    0.891,
-    0.863,
-    0.855,
-    0.88,
-    0.88,
-    0.891,
-    0.906,
-    0.905,
-    0.922,
-    0.906,
-    0.893,
-    0.91,
-    0.916,
-    0.898,
-    0.89,
-    0.925,
-    0.869,
-    0.899,
-    0.919,
-    0.917,
-    0.936,
-    0.822,
-    0.963,
-    0.878,
-    1.047,
-    0.951,
-    0.977,
-    0.872,
-    0.881,
-    0.96,
-    0.927,
-    0.925,
-    0.86,
-    0.897,
-    0.952,
-    0.852,
-    0.881,
-    0.955,
-    0.876,
-    0.881,
-    0.891,
-    0.884,
-    0.874,
-    0.915,
-    0.907,
-    0.891,
-    0.874,
-    0.969,
-    0.895,
-    0.898,
-    0.888,
-    0.927,
-    0.892,
-    0.9,
-    0.896,
-    0.878,
-    0.877,
-    0.896,
-    0.9,
-    0.891,
-    0.894,
-    0.898,
-    0.906,
-    0.865,
-    0.969,
-    0.913,
-    0.858,
-    0.943,
-    0.964,
-    0.884,
-    0.884,
-    0.905,
-    0.955,
-    0.912,
-    0.882,
-    0.888,
-    0.894,
-    0.883,
-    0.926,
-    0.899,
-    0.909,
-    0.904,
-    0.893,
-    0.881,
-    0.898,
-    0.887,
-    0.885,
-    0.881,
-    0.928,
-    0.895,
-    0.912,
-    0.905,
-    0.899,
-    0.895,
-    0.909,
-    0.892,
-    0.933,
-    0.899,
-    0.938,
-    0.894,
-    0.903,
-    0.875,
-    0.888,
-    0.941,
-    0.896
-  ]
-}
\ No newline at end of file
diff --git a/.claude/scripts/io-performance-analyzer/parse_pcp.py b/.claude/scripts/io-performance-analyzer/parse_pcp.py
deleted file mode 100644
index e2e75b4180..0000000000
--- a/.claude/scripts/io-performance-analyzer/parse_pcp.py
+++ /dev/null
@@ -1,134 +0,0 @@
-#!/usr/bin/env python3
-"""Parse pcp2json output with disk.dev.read, disk.dev.write, and disk.dev.await.
-
-pcp2json produces a nested structure:
-  @pcp.@hosts[].@metrics[] where each metric entry has @timestamp and
-  nested disk.dev.{read,write,await}.@instances[].{name, value}.
-
-Aggregates per-device instances: sum for read/write, max for await.
-Outputs a clean JSON with arrays: timestamps, bi, bo, await.
-"""
-
-import argparse
-import json
-import sys
-from datetime import datetime
-from zoneinfo import ZoneInfo, ZoneInfoNotFoundError
-
-FMT = "%Y-%m-%d %H:%M:%S"
-
-
-def get_instances(sample, *path):
-    """Walk the nested dict to reach @instances list for a metric."""
-    node = sample
-    for key in path:
-        if not isinstance(node, dict) or key not in node:
-            return []
-        node = node[key]
-    return node.get("@instances", [])
-
-
-def aggregate_instances(instances, func):
-    """Aggregate instance values, converting strings to float."""
-    vals = []
-    for inst in instances:
-        try:
-            vals.append(float(inst["value"]))
-        except (KeyError, ValueError, TypeError):
-            continue
-    return func(vals) if vals else 0
-
-
-def convert_timestamp(ts_str, target_tz):
-    """Parse a pcp2json timestamp and convert to the target timezone."""
-    utc = ZoneInfo("UTC")
-    for fmt in (FMT, "%Y-%m-%d %H:%M:%S%z", "%Y-%m-%dT%H:%M:%S",
-                "%Y-%m-%dT%H:%M:%S%z"):
-        try:
-            ts = datetime.strptime(ts_str, fmt)
-            break
-        except ValueError:
-            continue
-    else:
-        return None
-    if ts.tzinfo is None:
-        ts = ts.replace(tzinfo=utc)
-    return ts.astimezone(target_tz).strftime(FMT)
-
-
-def main():
-    parser = argparse.ArgumentParser(
-        description="Parse pcp2json output into plot-ready JSON")
-    parser.add_argument("input_json", help="Raw pcp2json output file")
-    parser.add_argument("output_json", help="Output JSON file")
-    parser.add_argument("--timezone", default="UTC",
-                        help="Target timezone for timestamps (default: UTC)")
-    args = parser.parse_args()
-
-    try:
-        target_tz = ZoneInfo(args.timezone)
-    except (KeyError, ZoneInfoNotFoundError):
-        print(f"ERROR: Unknown timezone '{args.timezone}'", file=sys.stderr)
-        sys.exit(1)
-
-    with open(args.input_json) as f:
-        raw = f.read()
-
-    # Strip pcp2json comment lines (lines starting with { "//" ... })
-    lines = []
-    for line in raw.splitlines():
-        stripped = line.strip()
-        if stripped.startswith('{ "//":') and stripped.endswith("}"):
-            continue
-        lines.append(line)
-    raw = "\n".join(lines)
-
-    try:
-        data = json.loads(raw)
-    except json.JSONDecodeError as e:
-        print(f"ERROR: Failed to parse pcp2json output: {e}", file=sys.stderr)
-        sys.exit(1)
-
-    # Navigate to the metrics array
-    hosts = data.get("@pcp", {}).get("@hosts", [])
-    if not hosts:
-        print("ERROR: No hosts found in pcp2json output", file=sys.stderr)
-        sys.exit(1)
-
-    samples = hosts[0].get("@metrics", [])
-    if not samples:
-        print("ERROR: No metric samples found in pcp2json output",
-              file=sys.stderr)
-        sys.exit(1)
-
-    result = {"timestamps": [], "bi": [], "bo": [], "await": []}
-
-    for sample in samples:
-        ts_str = sample.get("@timestamp", "")
-        ts = convert_timestamp(ts_str, target_tz)
-        if ts is None:
-            continue
-
-        read_insts = get_instances(sample, "disk", "dev", "read")
-        write_insts = get_instances(sample, "disk", "dev", "write")
-        await_insts = get_instances(sample, "disk", "dev", "await")
-
-        # Skip samples with no metric data (e.g. first interval)
-        if not read_insts and not write_insts and not await_insts:
-            continue
-
-        result["timestamps"].append(ts)
-        result["bi"].append(aggregate_instances(read_insts, sum))
-        result["bo"].append(aggregate_instances(write_insts, sum))
-        result["await"].append(aggregate_instances(await_insts, max))
-
-    if not result["timestamps"]:
-        print("ERROR: No valid data points found", file=sys.stderr)
-        sys.exit(1)
-
-    with open(args.output_json, "w") as f:
-        json.dump(result, f, indent=2)
-
-
-if __name__ == "__main__":
-    main()
diff --git a/.claude/scripts/io-performance-analyzer/plot_io.py b/.claude/scripts/io-performance-analyzer/plot_io.py
deleted file mode 100755
index a6a6277d20..0000000000
--- a/.claude/scripts/io-performance-analyzer/plot_io.py
+++ /dev/null
@@ -1,126 +0,0 @@
-#!/usr/bin/env python3
-"""Generate Disk IO Performance graph from pcp2json-derived data.
-
-Reads a JSON file with arrays: timestamps, bi, bo, await.
-Produces a line chart of Disk Read OPS, Disk Write OPS, and Disk Await.
-"""
-
-import argparse
-import json
-import sys
-from datetime import datetime
-
-import matplotlib
-matplotlib.use("Agg")
-import matplotlib.pyplot as plt  # noqa: E402
-import matplotlib.dates as mdates  # noqa: E402
-
-FMT = "%Y-%m-%d %H:%M:%S"
-
-
-def main():
-    parser = argparse.ArgumentParser(description="Plot disk IO from JSON data")
-    parser.add_argument("json_file", help="Path to JSON file with timestamps/bi/bo/await")
-    parser.add_argument("-o", "--output", default="/data/disk_io_performance.png",
-                        help="Output PNG file path")
-    parser.add_argument("--timezone", default="UTC",
-                        help="Timezone label for the chart (default: UTC)")
-    args = parser.parse_args()
-
-    with open(args.json_file) as f:
-        data = json.load(f)
-
-    timestamps = []
-    bi_values = []
-    bo_values = []
-    await_values = []
-
-    for i, ts_str in enumerate(data["timestamps"]):
-        try:
-            ts = datetime.strptime(ts_str, FMT)
-        except ValueError:
-            continue
-        timestamps.append(ts)
-        bi_values.append(float(data["bi"][i]))
-        bo_values.append(float(data["bo"][i]))
-        await_values.append(float(data["await"][i]))
-
-    if not timestamps:
-        print("ERROR: No data points found in JSON", file=sys.stderr)
-        sys.exit(1)
-
-    print(f"Loaded {len(timestamps)} data points")
-
-    # Find peak values
-    bi_peak_idx = max(range(len(bi_values)), key=lambda i: bi_values[i])
-    bo_peak_idx = max(range(len(bo_values)), key=lambda i: bo_values[i])
-    q_peak_idx = max(range(len(await_values)), key=lambda i: await_values[i])
-    bi_peak_ts = timestamps[bi_peak_idx].strftime("%H:%M:%S")
-    bo_peak_ts = timestamps[bo_peak_idx].strftime("%H:%M:%S")
-    q_peak_ts = timestamps[q_peak_idx].strftime("%H:%M:%S")
-    bi_peak_val = bi_values[bi_peak_idx]
-    bo_peak_val = bo_values[bo_peak_idx]
-    q_peak_val = await_values[q_peak_idx]
-
-    print(f"Peak bi (read):  {bi_peak_val:,.0f} blk/s at {bi_peak_ts}")
-    print(f"Peak bo (write): {bo_peak_val:,.0f} blk/s at {bo_peak_ts}")
-    print(f"Peak await:      {q_peak_val:,.1f} ms at {q_peak_ts}")
-
-    fig, (ax, ax_tbl) = plt.subplots(
-        2, 1, figsize=(16, 7),
-        gridspec_kw={"height_ratios": [8, 1]},
-    )
-
-    ax.plot(timestamps, bi_values, label="Disk Read OPS (bi)", color="tab:blue",
-            linewidth=0.8, alpha=0.9)
-    ax.plot(timestamps, bo_values, label="Disk Write OPS (bo)", color="tab:red",
-            linewidth=0.8, alpha=0.9)
-
-    ax.set_xlabel(f"Time ({args.timezone})")
-    ax.set_ylabel("Block I/O (blocks/s)")
-    ax.set_title("Disk I/O Performance (15-second intervals)")
-    ax.grid(True, alpha=0.3)
-
-    # Disk await on secondary Y axis
-    ax2 = ax.twinx()
-    ax2.plot(timestamps, await_values, label="Disk Await (ms)", color="tab:green",
-             linewidth=0.8, alpha=0.7, linestyle="--")
-    ax2.set_ylabel("Disk Await (ms)")
-
-    # Combined legend
-    lines1, labels1 = ax.get_legend_handles_labels()
-    lines2, labels2 = ax2.get_legend_handles_labels()
-    ax.legend(lines1 + lines2, labels1 + labels2, loc="upper right")
-
-    ax.xaxis.set_major_formatter(mdates.DateFormatter("%H:%M"))
-    ax.xaxis.set_major_locator(mdates.AutoDateLocator())
-    plt.setp(ax.xaxis.get_majorticklabels(), rotation=30, ha="right")
-
-    # Small table showing peak values
-    ax_tbl.axis("off")
-    table = ax_tbl.table(
-        cellText=[
-            ["Disk Read (bi)", bi_peak_ts, f"{bi_peak_val:,.0f}"],
-            ["Disk Write (bo)", bo_peak_ts, f"{bo_peak_val:,.0f}"],
-            ["Disk Await (ms)", q_peak_ts, f"{q_peak_val:,.1f}"],
-        ],
-        colLabels=["Type", "Time", "Peak"],
-        cellColours=[["#dbe9f6"] * 3, ["#f6dbdb"] * 3, ["#dbf6db"] * 3],
-        colColours=["#cccccc"] * 3,
-        loc="center",
-        cellLoc="center",
-    )
-    table.auto_set_font_size(False)
-    table.set_fontsize(9)
-    table.scale(0.4, 1.2)
-
-    fig.text(0.99, 0.01, f"Generated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}",
-             ha="right", va="bottom", fontsize=7, color="gray")
-
-    plt.tight_layout()
-    plt.savefig(args.output, dpi=150)
-    print(f"Saved chart to {args.output}")
-
-
-if __name__ == "__main__":
-    main()
diff --git a/.claude/scripts/io-performance-analyzer/run_io_graph.sh b/.claude/scripts/io-performance-analyzer/run_io_graph.sh
deleted file mode 100755
index e2adace3bb..0000000000
--- a/.claude/scripts/io-performance-analyzer/run_io_graph.sh
+++ /dev/null
@@ -1,65 +0,0 @@
-#!/bin/bash
-# Build the PCP container and generate a Disk I/O performance graph.
-#
-# Usage: ./run_io_graph.sh [--timezone TZ] [--output-dir DIR] [pcp-data-dir]
-#   --timezone TZ    : IANA timezone for timestamps (default: UTC)
-#   --output-dir DIR : directory for output CSV and PNG (default: script directory)
-#   pcp-data-dir     : directory containing PCP archive files (default: auto-detect)
-
-set -euo pipefail
-
-SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-TIMEZONE="UTC"
-OUTPUT_DIR=""
-
-# Parse options
-while [[ $# -gt 0 ]]; do
-    case "$1" in
-        --timezone)
-            TIMEZONE="${2:?--timezone requires a value (e.g. UTC, US/Eastern)}"
-            shift 2
-            ;;
-        --output-dir)
-            OUTPUT_DIR="${2:?--output-dir requires a directory path}"
-            shift 2
-            ;;
-        *)
-            DATA_DIR="$1"
-            shift
-            ;;
-    esac
-done
-
-OUTPUT_DIR="${OUTPUT_DIR:-${SCRIPT_DIR}}"
-mkdir -p "${OUTPUT_DIR}"
-OUTPUT_DIR="$(cd "${OUTPUT_DIR}" && pwd)"
-
-DATA_DIR="${DATA_DIR:-$(find "${SCRIPT_DIR}" -name 'Latest' -exec dirname {} \; | head -1)}"
-
-if [[ -z "${DATA_DIR}" || ! -d "${DATA_DIR}" ]]; then
-    echo "ERROR: PCP data directory not found. Usage: $0 [--timezone TZ] [--output-dir DIR] <pcp-data-dir>" >&2
-    exit 1
-fi
-
-DATA_DIR="$(cd "${DATA_DIR}" && pwd)"
-IMAGE_NAME="pcp-io-graph"
-
-echo "==> Building container image..."
-podman build -t "${IMAGE_NAME}" -f "${SCRIPT_DIR}/Dockerfile" "${SCRIPT_DIR}"
-
-echo "==> Extracting IO data and generating graph from ${DATA_DIR} (timezone: ${TIMEZONE})..."
-podman run --rm \
-    -v "${DATA_DIR}:/data/pcp:ro,Z" \
-    -v "${SCRIPT_DIR}/extract_io.sh:/data/extract_io.sh:ro,Z" \
-    -v "${SCRIPT_DIR}/parse_pcp.py:/data/parse_pcp.py:ro,Z" \
-    -v "${SCRIPT_DIR}/plot_io.py:/data/plot_io.py:ro,Z" \
-    -v "${OUTPUT_DIR}:/data/output:Z" \
-    -e MPLCONFIGDIR=/tmp/matplotlib \
-    "${IMAGE_NAME}" -c "
-        /data/extract_io.sh /data/pcp /data/output/io_data.json ${TIMEZONE} && \
-        python3 /data/plot_io.py /data/output/io_data.json -o /data/output/disk_io_performance.png --timezone ${TIMEZONE}
-    "
-
-echo "==> Done!"
-echo "    JSON:  ${OUTPUT_DIR}/io_data.json"
-echo "    Graph: ${OUTPUT_DIR}/disk_io_performance.png"
diff --git a/.claude/settings.json b/.claude/settings.json
index 30cc311f65..c924cd5be4 100644
--- a/.claude/settings.json
+++ b/.claude/settings.json
@@ -3,8 +3,6 @@
     "allow": [
       "Read(//tmp/**)",
       "Write(//tmp/**)",
-      "Bash(bash .claude/scripts/*)",
-      "Bash(python3 .claude/scripts/*)",
       "WebFetch(domain:prow.ci.openshift.org)"
     ],
     "deny": [],