post-deployment-monitor

name

post-deployment-monitor

description

Monitor Kubernetes deployments post-release by analyzing code changes and checking metrics. Use when users ask to "monitor deployment", "check deployment health", "verify deployment", "analyze deployment impact", or provide a deployment name with namespace and cluster. Automates deployment image comparison, code diff analysis, repository skill loading, flow impact analysis, and Grafana metrics validation. Generates comprehensive health reports with risk assessment.

Post-Deployment Monitoring

Automated workflow for monitoring Kubernetes deployments after updates by analyzing code changes and checking observability metrics.

Purpose: Validate deployment health by correlating code changes with production metrics to detect regressions, errors, and performance degradation.

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⚠️ CRITICAL: SEQUENTIAL EXECUTION REQUIRED

ALL phases MUST run one at a time, in strict order. NEVER parallelize across phases.

Phase 1: Fetch deployment info (kubectl via remote-friday-mcp-server)
    ↓  [COMPLETE before starting Phase 2]
Phase 2: Get code diff + read changed files
    ↓  [COMPLETE before starting Phase 3]
Phase 3: Load repo skills → identify affected flows + endpoints
    ↓  [COMPLETE before starting Phase 4]
Phase 4: Build Grafana queries (write them out explicitly)
    ↓  [COMPLETE before starting Phase 5]
Phase 5: Execute Grafana queries → generate health report

Combining any two phases in a single step is not allowed.

---

Quick Start

User provides:

• Deployment name (e.g., payments-card-live)
• Namespace (e.g., payments-card)
• Cluster (e.g., cde-green)

---

Phase 1: Fetch Deployment Info from Kubernetes

Tool: remote-friday-mcp-server::kubectl_execute — ALWAYS use this, never gh or Bash for K8s.

1.1: List ReplicaSets to find current and previous images

Use jsonpath output (custom-columns fails on annotation paths):

command: get
options: rs -n <namespace> -l name=<deployment-name> -o jsonpath='{range .items[*]}{.metadata.annotations.deployment\.kubernetes\.io/revision}{"\t"}{.spec.replicas}{"\t"}{.spec.template.spec.containers[0].image}{"\t"}{.metadata.creationTimestamp}{"\n"}{end}'
context: <cluster>-eks

Extract:

• Current: Highest revision number with replicas > 0
• Previous: Second-highest revision (regardless of replica count)
• Deployment time: creationTimestamp of the current ReplicaSet
• Commit SHAs: Parse from image tag — e.g., c.rzp.io/razorpay/offers-engine:api_2da394ff... → 2da394ff...

Example Output:

12   0   c.rzp.io/razorpay/offers-engine:api_7e9891499298...   2026-04-05T10:12:00Z
13   3   c.rzp.io/razorpay/offers-engine:api_2da394ff5437...   2026-04-06T18:26:36Z

Result:

• Current SHA: 2da394ff5437... (deployed at 2026-04-06T18:26:36Z)
• Previous SHA: 7e9891499298...

1.2: Fallback if jsonpath fails

command: get
options: rs -n <namespace> -l name=<deployment-name> -o wide
context: <cluster>-eks

Then narrow down with:

command: describe
options: rs <replicaset-name> -n <namespace>
context: <cluster>-eks

⚠️ Common Mistakes:

• ❌ Using deployment.kubernetes.io/change-cause annotation (often stale)
• ❌ Reading image from the Deployment object (may not reflect live pods)
• ✅ Always use ReplicaSet revision history sorted by revision number

---

Phase 2: Get Code Diff

Tool: Bash with gh api — use GitHub compare endpoint to get commits and changed files.

gh api repos/razorpay/<repo-name>/compare/<previous-sha>...<current-sha> \
  --jq '{
    total_commits: .total_commits,
    commits: [.commits[] | {
      sha: .sha[0:7],
      message: (.commit.message | split("\n")[0]),
      author: .commit.author.name
    }],
    files_changed: (.files | length),
    files: [.files[] | .filename],
    stats: {
      additions: ([.files[].additions] | add),
      deletions: ([.files[].deletions] | add)
    }
  }'

Then read each changed file using Read tool (if repo is in workspace) or gh api to get file content for analysis.

Assess risk:

• 1–10 commits → 🟢 Low
• 11–50 commits → 🟡 Medium
• 51–100 commits → 🔴 High
• 100+ commits → 🔴 Very High

⚠️ Analyze ALL commits, not just the latest.

---

Phase 3: Load Repo Skills → Identify Affected Flows and Endpoints

Complete Phase 2 fully before starting this phase.

3.1: Discover skills

If repo is in the current workspace:

Glob: .claude/skills/**/*.md

If not in workspace, use gh api:

gh api repos/razorpay/<repo-name>/contents/.claude/skills/<service>/modules/technical/observability/metrics.md \
  --jq '.content' | base64 -d

3.2: Load in priority order

1. Observability docs — modules/technical/observability/metrics.md

   • Extract: metric namespace, metric names, label dimensions, datasource UID

2. Domain flow docs — modules/domain/*/flows.md for each affected entity

   • Cross-reference changed files against flows
   • Identify which flows are modified, which are downstream

3. API routes — modules/integration/apis/*.md

   • Map changed server methods to gRPC/HTTP endpoint names
   • Extract the metric action label values used per endpoint

3.3: Output of this phase

Explicitly state before moving to Phase 4:

Affected endpoints:
  - <endpoint-1> → metric action label: "<action-value-1>"
  - <endpoint-2> → metric action label: "<action-value-2>"

Metric namespace: <oe|cardps|...>
Datasource UID: <uid>
Deployment time (RFC3339): <timestamp>
Deployment time (2h before): <timestamp-minus-2h>

⚠️ Metrics Discovery:

• NEVER assume metric names — always read from observability docs
• Each service has unique naming (e.g., oe_* vs cardps_* vs grpc_server_*)

---

Phase 4: Build Grafana Queries

Complete Phase 3 fully before starting this phase.

Write out ALL queries explicitly before executing any. Do not query Grafana yet.

4.1: Time boundaries

• Before: Use startTime=<deployment-time-minus-2h> in RFC3339 format (e.g., 2026-04-06T16:26:36Z)
• After: Use startTime=now

⚠️ Use startTime parameter in the MCP tool, NOT @ timestamp in PromQL. The @ modifier approach often returns empty results with the Grafana MCP tool.

4.2: Query templates

Replace <namespace>, <action_regex>, <metric_prefix> with values from Phase 3.

Error Rate:

# BEFORE
sum(rate(<metric_prefix>_error_response_total{kubernetes_namespace="<namespace>",action=~"<action_regex>"}[10m]))

# AFTER
sum(rate(<metric_prefix>_error_response_total{kubernetes_namespace="<namespace>",action=~"<action_regex>"}[10m]))

Traffic:

# BEFORE
sum(rate(<metric_prefix>_requests_total{kubernetes_namespace="<namespace>",action=~"<action_regex>"}[10m]))

# AFTER
sum(rate(<metric_prefix>_requests_total{kubernetes_namespace="<namespace>",action=~"<action_regex>"}[10m]))

P95 Latency:

# BEFORE
histogram_quantile(0.95, sum(rate(<metric_prefix>_durations_ms_histogram_bucket{kubernetes_namespace="<namespace>",action=~"<action_regex>"}[10m])) by (le))

# AFTER
histogram_quantile(0.95, sum(rate(<metric_prefix>_durations_ms_histogram_bucket{kubernetes_namespace="<namespace>",action=~"<action_regex>"}[10m])) by (le))

P99 Latency:

# BEFORE
histogram_quantile(0.99, sum(rate(<metric_prefix>_durations_ms_histogram_bucket{kubernetes_namespace="<namespace>",action=~"<action_regex>"}[10m])) by (le))

# AFTER
histogram_quantile(0.99, sum(rate(<metric_prefix>_durations_ms_histogram_bucket{kubernetes_namespace="<namespace>",action=~"<action_regex>"}[10m])) by (le))

Per-action error breakdown (always include):

sum by (action, error) (rate(<metric_prefix>_error_response_total{kubernetes_namespace="<namespace>",action=~"<action_regex>"}[10m]))

For gRPC services (Razorpay Foundation framework):

# Error rate
sum(rate(grpc_server_handled_total{kubernetes_namespace="<namespace>", grpc_code!="OK"}[10m]))

# P95 latency
histogram_quantile(0.95, sum(rate(grpc_server_handled_duration_seconds_bucket{kubernetes_namespace="<namespace>"}[10m])) by (le))

4.3: Discover datasource UID (if not in skills docs)

Tool: grafana::list_datasources
params: type=prometheus

Default Victoria Metrics UID: ALvd9Tgnz

---

Phase 5: Execute Grafana Queries + Generate Report

Complete Phase 4 fully (queries written out) before running any Grafana calls.

Tool: grafana::query_prometheus

Execute in this order:

1. Error rate BEFORE (startTime=<2h-before-RFC3339>)
2. Error rate AFTER (startTime=now)
3. Traffic BEFORE
4. Traffic AFTER
5. P95 latency BEFORE
6. P95 latency AFTER
7. P99 latency BEFORE
8. P99 latency AFTER
9. Per-action error breakdown AFTER

Report Template

# Post-Deployment Monitoring Report

**Deployment:** <name>
**Namespace:** <namespace>
**Cluster:** <cluster>
**Deployment Time:** <RFC3339 timestamp>

---

## Deployment Scope

- **Previous SHA:** <sha>
- **Current SHA:** <sha>
- **Total Commits:** <count>
- **Files Changed:** <count>
- **Lines Added / Deleted:** <+X / -Y>

---

## Commit Breakdown

### Commit 1: `<sha>` — <title>
**Author:** <name>
**Risk:** 🟢 Low / 🟡 Medium / 🔴 High
**Affects:** <endpoint(s)> → metric action: `<action-label>`
**Summary:** <what changed  >

---



| Endpoint | Action Label | Changed By |
|----------|-------------|------------|
|  |  | Commit  |

---







| Action | Before | After | Change | Status |
|--------|--------|-------|--------|--------|
|  | X.XX/s | X.XX/s | X% | ✅/⚠️/❌ |
| Combined | X.XX/s | X.XX/s | X% | ✅/⚠️/❌ |



| Action | Error | Before | After | Status |
|--------|-------|--------|-------|--------|
|  |  | X.XX/s | X.XX/s | ✅/⚠️/❌ |



| Metric | Before | After | Change | Status |
|--------|--------|-------|--------|--------|
| P95 | Xms | Xms | +X% | ✅/⚠️/❌ |
| P99 | Xms | Xms | +X% | ✅/⚠️/❌ |

---



 ✅ HEALTHY / ⚠️ WARNINGS / ❌ ISSUES



  — ✅/⚠️/❌ 
 
 

---



 ✅ No regressions / ⚠️ Minor issues / ❌ Rollback recommended

 
 Victoria Metrics (Grafana), Kubernetes (remote-friday-mcp-server), GitHub

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Alert Thresholds

Error Rate

• 🟢 Green: <10% increase
• 🟡 Warning: 10–20% increase
• 🔴 Critical: >20% increase

4XX Errors

• 🟢 Green: <15% increase
• 🟡 Warning: 15–30% increase
• 🔴 Critical: >30% increase OR new 4xx codes appearing

Latency P95

• 🟢 Green: <20% increase
• 🟡 Warning: 20–30% increase
• 🔴 Critical: >30% increase

Latency P99

• 🟢 Green: <30% increase
• 🟡 Warning: 30–50% increase
• 🔴 Critical: >50% increase

Traffic Volume

• 🟢 Green: <10% change (or explainable by time-of-day)
• 🟡 Warning: 10–50% drop (unexplained)
• 🔴 Critical: >50% drop OR zero traffic on active endpoints

Deployment Size Risk

• 🟢 Low: 1–10 commits
• 🟡 Medium: 11–50 commits
• 🔴 High: 51–100 commits
• 🔴 Very High: 100+ commits

---

Troubleshooting

jsonpath query returns empty

Use -o wide first to see available fields, then describe for the specific ReplicaSet.

@ timestamp PromQL returns empty in Grafana MCP

Use startTime=<RFC3339> parameter in the tool call instead. Pass the evaluation time as the tool's startTime, not as an in-query modifier.

Metric names return no data

Use grafana::list_prometheus_metric_names with a regex prefix (e.g., ^oe_server) to discover actual metric names before querying.

Label values differ from docs

Use grafana::list_prometheus_label_values with the metric name filter to find actual label values in use.

No previous ReplicaSet

First deployment — report as "Initial deployment, no baseline available."

Multiple ReplicaSets with replicas > 0

Rolling update still in progress. Use highest revision as current; wait for rollout to stabilize.

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Tool Reference

Task	Tool
Get ReplicaSet images	remote-friday-mcp-server::kubectl_execute
Get commit diff	Bash gh api repos/razorpay/<repo>/compare/<prev>...<curr>
Read repo skill files	Read tool (if in workspace) or gh api for file content
Discover metric names	grafana::list_prometheus_metric_names
Discover label values	grafana::list_prometheus_label_values
Query metrics	grafana::query_prometheus

Default Victoria Metrics datasource UID: ALvd9Tgnz

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Skill Version: 3.0.0 Last Updated: 2026-04-07