Fix all unresolved CodeRabbit comments on this PR:

• Push a commit to this branch (recommended)
• Create a new PR with the fixes

acm-deploy-load/utils/output.py (1)

228-285: 🩺 Stability & Availability | 🟠 Major | ⚡ Quick win

Add the missing no_deploy=True + no_policy=True branch before using phase2_label.

phase2_label is uninitialized in the both-true mode and then used at Line 285, causing UnboundLocalError during report generation.

Suggested fix

     elif cliargs.no_deploy == True and cliargs.no_policy == False:
       phase2_label = "Policy Updates"
       log_write(report, " * Mode: Policy configmap updates only")
       log_write(report, " * Phase 1 / Idle Baseline (Start delay): {}s :: {}".format(
           cliargs.start_delay, str(timedelta(seconds=cliargs.start_delay))))
       log_write(report, " * Phase 2 ({}):".format(phase2_label))
       log_write(report, "  * Update policy configmap ({} keys) in namespace {} per {}s interval".format(
           cliargs.hub_policy_cm_keys, cliargs.hub_policy_namespace, cliargs.interval_policy))
       log_write(report, "   * Maximum number of policy intervals to run: {}".format(cliargs.max_policy_intervals))
       log_write(report, " * Phase 3 / Soak Baseline (End delay): {}s :: {}".format(
           cliargs.end_delay, str(timedelta(seconds=cliargs.end_delay))))
+    else:
+      phase2_label = "No active workload"
+      log_write(report, " * Mode: Idle baseline + soak baseline only")
+      log_write(report, " * Phase 1 / Idle Baseline (Start delay): {}s :: {}".format(
+          cliargs.start_delay, str(timedelta(seconds=cliargs.start_delay))))
+      log_write(report, " * Phase 2 ({}): no deploy/policy actions".format(phase2_label))
+      log_write(report, " * Phase 3 / Soak Baseline (End delay): {}s :: {}".format(
+          cliargs.end_delay, str(timedelta(seconds=cliargs.end_delay))))

🤖 Prompt for AI Agents

Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In `@acm-deploy-load/utils/output.py` around lines 228 - 285, The variable
phase2_label is initialized in three conditional branches checking combinations
of cliargs.no_deploy and cliargs.no_policy, but the fourth case where both are
True is missing, causing an UnboundLocalError when phase2_label is used later at
line 285. Add an elif branch for the case where cliargs.no_deploy == True and
cliargs.no_policy == True, and initialize phase2_label with an appropriate
descriptive label (such as "No Operations" or similar) for this scenario to
ensure the variable is always defined before being used in the subsequent
log_write calls.

acm-deploy-load/utils/analysis.py (1)

38-50: 🩺 Stability & Availability | 🟠 Major | ⚡ Quick win

Move command logging/build into guarded path and validate kubeconfig before join.

At Line 48, " ".join(cmd) can throw if kubeconfig is not a string, and that happens before the try, so the function can crash instead of hitting the controlled warning path.

Suggested fix

-  cmd = [
-    sys.executable,
-    analyzer_script,
-    "-k", kubeconfig,
-    "-s", start_str,
-    "-e", end_str,
-    "-b", "0",
-    "-p", phase_name,
-    report_dir,
-  ]
-  logger.info("Prometheus analysis command: {}".format(" ".join(cmd)))
   log_file = os.path.join(report_dir, "pa-{}.log".format(phase_name))
   try:
+    if not isinstance(kubeconfig, str) or not kubeconfig:
+      logger.warning("Skipping prometheus analysis phase {}: kubeconfig is not set".format(phase_name))
+      return
+    cmd = [
+      sys.executable,
+      analyzer_script,
+      "-k", kubeconfig,
+      "-s", start_str,
+      "-e", end_str,
+      "-b", "0",
+      "-p", phase_name,
+      report_dir,
+    ]
+    logger.info("Prometheus analysis command: {}".format(" ".join(cmd)))
     with open(log_file, "w") as f:
       proc = subprocess.Popen(
         cmd,

🤖 Prompt for AI Agents

Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In `@acm-deploy-load/utils/analysis.py` around lines 38 - 50, The command logging
at line 48 using the join operation happens before the try block, which means if
kubeconfig is not a string, the join will fail and crash the function instead of
being handled by the exception handler. Move the logger.info call that logs the
command and the log_file assignment inside the try block so they are guarded by
exception handling. Additionally, validate that kubeconfig is a string before
constructing the cmd list to prevent the join operation from failing due to
invalid kubeconfig type.

acm-deploy-load/acm-deploy-load.py (1)

338-345: 🩺 Stability & Availability | 🔵 Trivial | ⚡ Quick win

Validate kubeconfig before running AAP detection.

Running detect_aap_install(...) before validate_kubeconfig(...) can log a misleading “AAP install not detected” when kubeconfig is invalid, then fail immediately after. Validate first, then run detection.

Suggested reorder

-  # Detect AAP install
-  if detect_aap_install(cliargs.kubeconfig, cliargs.dry_run):
-    logger.info("AAP install detected, waiting for playbook completion")
-    cliargs.wait_playbook = True
-  else:
-    logger.info("AAP install not detected")
-
-  # Validate parameters
-  validate_kubeconfig(cliargs.kubeconfig)
+  # Validate parameters
+  validate_kubeconfig(cliargs.kubeconfig)
+
+  # Detect AAP install
+  if detect_aap_install(cliargs.kubeconfig, cliargs.dry_run):
+    logger.info("AAP install detected, waiting for playbook completion")
+    cliargs.wait_playbook = True
+  else:
+    logger.info("AAP install not detected")

🤖 Prompt for AI Agents

Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In `@acm-deploy-load/acm-deploy-load.py` around lines 338 - 345, Reorder the
validation logic so that validate_kubeconfig is called before the
detect_aap_install check. Move the validate_kubeconfig(cliargs.kubeconfig) call
to execute first, before the if block that calls detect_aap_install. This
ensures the kubeconfig is validated as valid before attempting AAP detection,
preventing misleading "AAP install not detected" log messages when the
kubeconfig is actually invalid.