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Skills service-mesh-observability
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service-mesh-observability
Content revision r2 High Risk ⚙️ External commands🌐 Network access📁 Filesystem access
Build Service Mesh Observability
Service mesh telemetry can be difficult to configure, correlate, and operate. This skill provides practical patterns for metrics, tracing, dashboards, and alerts.
Supports: Claude Codex Code(CC)
Stop for confirmation before installing.
Review the plan and obtain explicit user consent before changing files.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Agent request
Review the Skillstore skill "service-mesh-observability" from https://skillstore.io/skills/sickn33-service-mesh-observability.md and its manifest at https://skillstore.io/api/skills/sickn33-service-mesh-observability/manifest. Verify the artifact. Stop and obtain explicit user consent before installing or changing files.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "service-mesh-observability". Define a baseline dashboard for an Istio checkout service.
Expected outcome:
- Overview: request volume, success rate, P50 latency, P99 latency, and active connections.
- Breakdowns: source workload, destination service, response code, route, and cluster.
- Alerts: sustained error rate, latency threshold, traffic anomaly, and certificate expiration.
Using "service-mesh-observability". Help investigate high latency between frontend and payments.
Expected outcome:
- Confirm the latency increase by destination and compare P50 with P99.
- Inspect service topology for unexpected routes, retries, or dependency changes.
- Use correlated traces to identify the slow span and validate the affected workload.
Using "service-mesh-observability". Recommend trace sampling for development and production.
Expected outcome:
Use complete sampling in small development environments when affordable. Start production sampling near one to ten percent, then adjust using volume and cost.
Security Audit
High Riskv5 • 8/26/2026 Open versioned report
All static findings are false positives caused by Markdown formatting, documentation links, standard in-cluster addresses, listener bindings, and a PromQL regex. Semantic review found insecure Kiali access defaults and disabled TLS for the Jaeger exporter in example configurations.
1
Files scanned
404
Lines analyzed
0
Review items
0
False positives ignored
Confirmed security concerns (2)
High
Kiali Example Enables Broad Anonymous Access
The Kiali template selects anonymous authentication and the wildcard namespace scope. A reachable deployment could expose mesh topology and telemetry across all namespaces.
The example explicitly sets the authentication strategy to anonymous and accessible_namespaces to a wildcard. Both settings are visible in the cited YAML.
Medium
Jaeger Exporter Disables TLS
The OpenTelemetry example sets insecure transport for the Jaeger exporter. Telemetry may cross the cluster without encryption or collector identity verification.
The exporter configuration explicitly sets tls.insecure to true for the Jaeger endpoint. This disables secure transport in the provided deployment template.
Risk Factors
⚙️ External commands (18)
🌐 Network access (11)
📁 Filesystem access (1)
Audited by: codex View Audit History →
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<iframe src="https://skillstore.io/embed/skills/sickn33-service-mesh-observability.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
sickn33. (2026). service-mesh-observability security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-service-mesh-observability/audits/5BibTeX citation
@techreport{sickn33-sickn33-service-mesh-observability-2026,
author = {sickn33},
title = {service-mesh-observability security audit report (audit version 5)},
institution = {Skillstore},
year = {2026},
number = {5},
url = {https://skillstore.io/skills/sickn33-service-mesh-observability/audits/5},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "service-mesh-observability security audit report (audit version 5)"
version: "unspecified"
type: report
authors:
- name: "sickn33"
date-released: "2026-08-26"
url: "https://skillstore.io/skills/sickn33-service-mesh-observability/audits/5"
identifiers:
- type: other
value: "skillstore:sickn33-service-mesh-observability:audit:5"
description: "Skillstore immutable audit report identifier"
Compare variants
2 installable variantsEach author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
Higher Skillstore usage
Author / source Skillstore Score Evidence Confidence Skillstore usage Updated
wshobson Recommended
wshobson-service-mesh-observability
Skillstore Score 38
Evidence Confidence Medium
Skillstore usage 14
Updated
2026-09-09
sickn33 Current
sickn33-service-mesh-observability
Skillstore Score 38
Evidence Confidence Medium
Skillstore usage 10
Updated
2026-09-09
Skillstore Score
Why this score Evidence Confidence: Medium 55
Architecture
85
Maintainability
87
Content
69
Community
83
Spec Compliance
What You Can Build
Plan a Mesh Monitoring Baseline
Define golden signals, dashboards, alerts, and trace sampling before a new mesh enters production.
Investigate Service Latency
Combine service metrics, dependency views, and distributed traces to isolate slow upstream or downstream calls.
Standardize Telemetry Across Teams
Create shared Prometheus queries, Grafana panels, and OpenTelemetry conventions for multiple application teams.
Try These Prompts
Explain the Observability Basics
Explain the essential metrics, traces, and logs for my [Istio or Linkerd] mesh. Include the golden signals and simple validation steps.
Design a Service Dashboard
Design a dashboard for [service name] using [mesh] metrics. Include request rate, error rate, P99 latency, saturation, and useful filters.
Troubleshoot a Mesh Incident
Create an investigation plan for [symptom] in [mesh]. Correlate Prometheus metrics, traces, topology, and proxy logs. Include verification checkpoints.
Architect Production Telemetry
Design production observability for [cluster details]. Cover OpenTelemetry pipelines, sampling, cardinality, retention, authentication, TLS, RBAC, alerts, and rollout validation.
Best Practices
- Validate metric names, labels, ports, and APIs against the deployed mesh version.
- Use representative traffic and failure tests to verify dashboards, traces, and alerts before production rollout.
- Protect observability endpoints with authentication, TLS, RBAC, namespace restrictions, and network policies.
Avoid
- Do not apply example manifests without reviewing security, capacity, and compatibility requirements.
- Do not use high-cardinality labels or complete production trace sampling without cost controls.
- Do not expose dashboards, collectors, or telemetry backends through anonymous or unrestricted access.
Frequently Asked Questions
Which service meshes does this skill cover?
It focuses on Istio and Linkerd, with related patterns for Kiali, Jaeger, Prometheus, Grafana, and OpenTelemetry.
Can it generate Prometheus queries?
Yes. It provides patterns for traffic, errors, latency, TCP connections, and request size.
Does it deploy monitoring components?
No. It supplies guidance and examples, but an operator must review, apply, and validate every change.
Are the configurations production ready?
No. They require version checks and stronger controls for authentication, TLS, RBAC, storage, networking, and capacity.
Can it help troubleshoot incidents?
Yes. It can structure investigations using metrics, traces, topology, and logs when you provide the environment and symptoms.
How should trace sampling be selected?
Choose sampling from traffic volume, diagnostic needs, retention, and cost. Validate the rate under representative workloads.
Developer Details
Author
sickn33License
MIT
Skillstore revision
r2
Version notice
The author did not declare a version.
Repository
https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/service-mesh-observabilityRef
4804b3d672af16b8afca785bbb6c5d7c7400a78f
Maintenance freshness
8/27/2026
Usage
10 downloads · 105 views
File structure
📄 SKILL.md
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