Research subagent (Dana Whitfield's session)

{
  "file_path": "/Users/warrenthompson/Source/LoginID/CLAUDE.md"
}

1	# LoginID Take-Home POC — Project Root
2	
3	## Role
4	
5	You are the project manager agent for this repository. This file is the shared context every track refers back to. Each of the five track directories below has its own CLAUDE.md that can be worked independently by a scoped subagent, but that subagent should read this root file first for the assignment, the overall narrative, and how its track fits with the other four.
6	
7	When you spin up agents or subagents to do work in a track, point them at that track's CLAUDE.md as their brief, and tell them this root file exists for cross-track context. Don't let a track's agent silently duplicate scope another track owns — check the "Owns / does not own" boundaries below first.
8	
9	## What this repository is
10	
11	This is a take-home assignment for a LoginID interview, submitted as a full directory. The goal is not just to answer three coding questions — it's to demonstrate capability as an AI architect: how you scope a problem, use AI tooling deliberately, reason about security and data, and produce something that reads as an intentional, well-run engineering effort rather than a quick script.
12	
13	Code does not need to work or be fully complete. LoginID has said explicitly they care more about the design and the reasoning behind it, and about which AI tools/frameworks were used and how. Every track should document its reasoning, not just its output.
14	
15	## The assignment (verbatim from LoginID)
16	
17	Provide code solutions for the following questions in Go (preferably) or other languages — describe any tool, framework, or AI used.
18	
19	1. Code of a database DAO that can store and retrieve `user_profile` (name, address, phone) and `user_credential` (username, method, password), with support for multiple databases (PostgreSQL or CockroachDB, SQLite, etc).
20	2. Design a RESTful API web service to search and retrieve the above user profile data, plus security API authentication.
21	3. Design a service connector to third-party identity providers (referred to generically as ABC or XYZ) to retrieve personal data from vendors, with the following endpoints:
22	   - `/auth` — retrieves an `access_token` based on a POST JSON body `{"username": "<string>", "password": "<string>"}`
23	   - `/identity` — retrieves user PII (name, phone, address: `street_address`, `locality`, `region`, `postal_code`, `country`) based on a POST JSON body `{"phone": "<string>", "name": "<string>"}`
24	
25	Go is the preferred language. Other languages are acceptable if justified.
26	
27	## Track structure
28	
29	Five directories, each independently workable, each owning a distinct slice of the problem:
30	
31	| Directory | Track | Owns |
32	|---|---|---|
33	| `01-product-industry-research-design/` | Product & Industry Research (incl. Design) | Market/industry framing (IAM, passwordless auth, IDP aggregation space), personas and use cases, API and data contract design rationale, UX of the surfaces that would sit on top of this |
34	| `02-ai-security-architecture/` | AI Architecture & Security Architecture | The AI tooling/workflow used to produce this submission, threat modeling, auth/authz design for the API, credential and PII handling, secrets management, third-party connector security |
35	| `03-engineering-delivery/` | Engineering & Delivery | The actual Go code for all three questions, project structure, test strategy, delivery documentation |
36	| `04-infra-devops/` | Infra & DevOps | How this would be built, containerized, deployed, and operated — CI/CD, environments, multi-database configuration, observability |
37	| `05-data-ops/` | Data Ops | Data modeling for `user_profile` / `user_credential`, multi-database abstraction strategy, migrations, PII data governance and retention |
38	
39	Directories are numbered for reading order in the final submission, not for sequencing of work — tracks can be worked in any order or in parallel.
40	
41	## Working principles for every track
42	
43	- State your reasoning, not just your conclusion. LoginID is grading the "why" as much as the "what."
44	- Name the AI tool/workflow you used for that track's output (this project is being built with Claude Code; say so, and say how — e.g., subagents scoped per track, a given skill, a given model).
45	- Keep each track's CLAUDE.md self-contained enough that a fresh agent with no other context can pick it up and do correct work from it alone, plus this root file.
46	- Cross-reference other tracks by relative path (e.g., `../05-data-ops/CLAUDE.md`) rather than restating their content.
47	- Do not start writing code until each track's CLAUDE.md is in place and reviewed.
48	
49	## Status
50	
51	Scaffolding phase — track directories and their CLAUDE.md files are being established. No implementation work has started yet.
52	

{
  "file_path": "/Users/warrenthompson/Source/LoginID/04-infra-devops/CLAUDE.md"
}

1	# Track: Infra & DevOps
2	
3	Refer back to `../CLAUDE.md` for the full assignment text and how this track fits with the other four.
4	
5	## Mission
6	
7	Design how the services from the engineering track would actually be built, packaged, deployed, and operated. This is a design/documentation track for a take-home — it does not stand up real infrastructure, but it should be concrete enough that it clearly could.
8	
9	## Owns
10	
11	- Build and containerization approach for the DAO-backed API service and the IDP connector service (e.g., Dockerfiles, multi-stage Go builds).
12	- Environment/configuration strategy for switching the DAO between PostgreSQL/CockroachDB and SQLite (env vars, config files, or a database driver selection mechanism) — implements the storage-agnostic contract that `../05-data-ops/CLAUDE.md` designs.
13	- CI/CD pipeline design: what would run on a commit/PR (build, lint, test, security scan) for a project like this.
14	- Secrets injection mechanics at deploy time for whatever `../02-ai-security-architecture/CLAUDE.md` specifies needs to be a secret (DB credentials, third-party IDP credentials, signing keys) — this track implements the delivery mechanism, security architecture sets the requirement.
15	- Observability approach: logging, metrics, and tracing considerations for the API and the connector, especially around what must never be logged (raw passwords, tokens, PII) per the security track's guidance.
16	- Local dev-loop story: how a developer would run this stack locally (e.g., docker-compose with a local Postgres and the services).
17	
18	## Does not own
19	
20	- Application code itself — that's `../03-engineering-delivery/CLAUDE.md`.
21	- What counts as a secret and why, or the auth/threat model — that's `../02-ai-security-architecture/CLAUDE.md`; this track only implements the delivery of it.
22	- Database schema/migration content — that's `../05-data-ops/CLAUDE.md`; this track only covers how migrations would run in a pipeline, not their content.
23	
24	## Deliverables
25	
26	- Containerization design (Dockerfile sketch or description) for both services.
27	- A CI/CD pipeline description or config sketch.
28	- A local dev-loop description (e.g., docker-compose sketch).
29	- A short note on observability and what must be excluded from logs.
30	
31	## AI tooling note
32	
33	Record which AI tool/workflow was used to produce this track's design output and how.
34	
35	## Status
36	
37	No infra work has started. Do not begin until the engineering track's service boundaries are defined enough to containerize and deploy against.
38	

{
  "query": "select:WebSearch,WebFetch",
  "max_results": 2
}

[tool reference: ]
[tool reference: ]

{
  "query": "Go multi-stage Dockerfile distroless scratch best practices 2026"
}

Web search results for query: "Go multi-stage Dockerfile distroless scratch best practices 2026"

Links: [{"title":"How to Containerize Go Apps with Multi-Stage Dockerfiles","url":"https://oneuptime.com/blog/post/2026-01-07-go-docker-multi-stage/view"},{"title":"Docker Multi-Stage Builds for Go: From 1GB to 12MB Images (2026 Guide) - DEV Community","url":"https://dev.to/young_gao/docker-multi-stage-builds-for-go-from-1gb-to-12mb-production-images-2p1h"},{"title":"Docker Multi-Stage Build in Practice: Shrinking Production Images from 1GB to 10MB | Easton","url":"https://eastondev.com/blog/en/posts/dev/20260419-docker-multistage-build/"},{"title":"Docker Multi-Stage Builds: The Complete Guide for 2026 | DevToolbox Blog","url":"https://devtoolbox.dedyn.io/blog/docker-multi-stage-builds-guide"},{"title":"How to Create Minimal Docker Images for Go Applications","url":"https://oneuptime.com/blog/post/2026-02-20-go-docker-minimal-image/view"},{"title":"Build Minimal Go Docker Images from Scratch (2026) | ADHDecode","url":"https://adhdecode.com/articles/docker/docker-scratch-image-golang/"},{"title":"Docker Multi-Stage Builds for Production-Optimized Images · Technical news about AI, coding and all","url":"https://dasroot.net/posts/2026/04/docker-multi-stage-builds-production-optimized-images/"},{"title":"Docker Multi-Stage Builds: From 1.2GB to Production-Ready Images (2026) | Tech Tutorials","url":"https://tutorials.technology/tutorials/docker-multi-stage-builds-2026.html"}]

I've found comprehensive information about Go multi-stage Dockerfile best practices for 2026. Here's what the search results reveal:

## Key Best Practices

**Base Image Choices:**

Start with distroless for most services, drop to scratch if you need the absolute minimum, and use alpine only when you need a shell for debugging. Distroless is the sweet spot for most production services.

**Multi-Stage Build Benefits:**

Multi-stage builds reduce image size by up to 97% compared to traditional monolithic builds. Images can be as small as 5-20 MB instead of 300+ MB, with reduced attack surface and no shell or package manager.

**Scratch vs. Distroless Comparison:**

- **Scratch:** Scratch has no shell, no tools, no users — just your binary. If your application needs to make HTTPS calls, you must copy /etc/ssl/certs/ca-certificates.crt from the builder stage.

- **Distroless:** Distroless adds CA certificates, timezone data, a nonroot user, and /tmp, still with no shell or package manager, and is the sweet spot for most production services.

**Security Considerations:**

A scratch-based Go image typically reports zero OS-level CVEs, and fewer tools in the image means attackers have less to work with if code execution is achieved. Never run containers as root, and distroless provides a nonroot user (UID 65532).

**General Build Strategy:**

Key practices include using the smallest base for runtime, pinning base image versions, ordering for cache efficiency with dependency files before source code, and running as non-root.


REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.

{
  "query": "GitHub Actions CI pipeline Go golangci-lint govulncheck Trivy 2026"
}

Web search results for query: "GitHub Actions CI pipeline Go golangci-lint govulncheck Trivy 2026"

Links: [{"title":"How to Set Up Go CI Pipeline with GitHub Actions","url":"https://oneuptime.com/blog/post/2025-12-20-go-ci-pipeline-github-actions/view"},{"title":"Go Linting Best Practices for CI/CD with GitHub Actions","url":"https://medium.com/@tedious/go-linting-best-practices-for-ci-cd-with-github-actions-aa6d96e0c509"},{"title":"CI/CD Pipeline for Solo Developers: Go + GCP + GitHub Actions - DEV Community","url":"https://dev.to/shusukedev/cicd-pipeline-for-solo-developers-go-gcp-github-actions-1f1b"},{"title":"GitHub - golangci/golangci-lint-action: Official GitHub Action for golangci-lint from its authors · GitHub","url":"https://github.com/golangci/golangci-lint-action"},{"title":"Configure github actions workflow with golangci-lint | by Ashef Tishad | Medium","url":"https://ashef.medium.com/configure-the-golangci-lint-workflow-for-your-golang-applications-6e765f2146c5"},{"title":"How to Use Private Go Modules with golangci-lint in GitHub Actions. - DEV Community","url":"https://dev.to/clanic/using-private-go-modules-with-golangci-lint-in-github-actions-288j"},{"title":"Continuous integration with Go and GitHub Actions","url":"https://aran.dev/posts/continuous-integration-with-go-and-github-actions/"},{"title":"How to Use Go Lint in GitHub Actions - Workflow Hub - CI Cube","url":"https://cicube.io/workflow-hub/golangci-golangci-lint-action/"},{"title":"Go Package CI/CD with GitHub Actions | force push","url":"https://forcepush.tech/go-package-ci-cd-with-git-hub-actions"},{"title":"golang-continuous-integration — AI agent skill | explainx.ai | explainx.ai","url":"https://explainx.ai/skills/samber/cc-skills-golang/golang-continuous-integration"}]

I've found comprehensive information about setting up GitHub Actions CI pipelines for Go projects with the tools you mentioned. Here are the key findings:

## Overview of Go CI Pipeline Tools

golangci-lint is a powerful linter aggregator that supports multiple linters, including govet, staticcheck, and gosec. The official GitHub Action for golangci-lint runs golangci-lint and reports issues from linters.

## Security Scanning with govulncheck

govulncheck should be run in CI as it only reports vulnerabilities in code paths your project actually calls—unlike generic CVE scanners. The typical approach involves installing govulncheck and running it against your project.

## Trivy for Container and Dependency Scanning

Trivy checks whether libraries and OS packages contain known vulnerabilities—even if your own code is clean. gosec runs via golangci-lint on every CI run. Trivy runs on a schedule rather than every CI run to keep feedback loops fast.

## Practical Pipeline Example

A typical CI workflow includes: checking out code, setting up Go, running golangci-lint, running tests with coverage, and building the application. For projects that produce Docker images, workflows can build multi-platform images, generate SBOM and provenance attestations, push to registries, and include Trivy container scanning.

The search results contain recent examples (from late 2025 and early 2026) showing how to effectively integrate these tools into modern Go CI/CD pipelines.


REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.

{
  "query": "docker-compose local development Go service Postgres CockroachDB SQLite"
}

Web search results for query: "docker-compose local development Go service Postgres CockroachDB SQLite"

Links: [{"title":"Use containers for Go development | Docker Docs","url":"https://docs.docker.com/guides/golang/develop/"},{"title":"How to Run CockroachDB in Docker with Clustering","url":"https://oneuptime.com/blog/post/2026-02-08-how-to-run-cockroachdb-in-docker-with-clustering/view"},{"title":"Docker Compose: Quick Local Development Setup - Postgresql - DEV Community","url":"https://dev.to/masanedevesh/docker-compose-quick-local-development-setup-postgresql-deo"},{"title":"GitHub - lhsribas/cockroachdb-docker-compose: CockroachDB and Docker-Compose · GitHub","url":"https://github.com/lhsribas/cockroachdb-docker-compose"},{"title":"How to Use Docker Compose for Local Development Environments","url":"https://oneuptime.com/blog/post/2026-02-20-docker-compose-development/view"},{"title":"cockroachdb-docker-compose.md · GitHub","url":"https://gist.github.com/dbist/«REDACTED-HEX»"},{"title":"Use containers for development | Docker ドキュメント","url":"https://matsuand.github.io/docs.docker.jp.onthefly/language/golang/develop/"},{"title":"CockroachDB examples using Docker and Docker Compose","url":"https://github.com/topics/cockroachdb?l=shell"}]

I found relevant information about using Docker Compose for local development with Go services and databases. Here's what the search results reveal:

## Go Services with Docker Compose

Docker Compose can be used to set up development environments for Go services with CockroachDB instances. Docker Compose files can link containers together and provide for easy starting up and tearing down of the development environment.

## Database Compatibility

Go modules that work with Postgres, such as pgx, pq, GORM, and upper/db also work with CockroachDB. Additionally, you can use a wide variety of existing PostgreSQL client drivers to talk to CockroachDB.

## Database Setup Examples

**CockroachDB**: Running CockroachDB in Docker gives you a distributed SQL database for local development and testing.

**PostgreSQL**: Docker-compose can be used to get your local development started with PostgreSQL, with examples showing how to configure containers with environment variables, port bindings, and persistent volumes.

The search results provide practical examples for setting up development environments with either PostgreSQL or CockroachDB using Docker Compose, though specific SQLite integration examples weren't prominently featured in these results.


REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.

{
  "query": "secrets management AWS Secrets Manager Vault vs env vars take-home proportionate 2025"
}

Web search results for query: "secrets management AWS Secrets Manager Vault vs env vars take-home proportionate 2025"

Links: [{"title":"Secrets Management: Vault, AWS Secrets Manager, or SOPS? - DEV Community","url":"https://dev.to/instadevops/secrets-management-vault-aws-secrets-manager-or-sops-2ce1"},{"title":"Best Environment Variable Management Tools for Developers in 2025 - DEV Community","url":"https://dev.to/_d7eb1c1703182e3ce1782/best-environment-variable-management-tools-for-developers-in-2025-2h20"},{"title":"The Secret Life of AWS: The Vault (AWS Secrets Manager) | by Aaron Rose | Medium","url":"https://medium.com/@aaron.rose.tx/the-secret-life-of-aws-the-vault-aws-secrets-manager-9d93fd6fa91d"},{"title":"Secrets Management in DevOps: AWS Secrets Manager vs HashiCorp Vault","url":"https://acquaintsoft.com/blog/secrets-management-aws-vault-devops-implementation"},{"title":"HashiCorp Vault vs AWS Secrets Manager: Enterprise Secret…","url":"https://www.openempower.com/blog/vault-vs-aws-secrets-manager-enterprise-secret-management"},{"title":"HashiCorp Vault vs AWS Secrets Manager | 2025 Guide - Cyber Snowden","url":"https://cybersnowden.com/hashicorp-vault-vs-aws-secrets-manager/"},{"title":"infisical vs vault on aws","url":"https://stackshare.io/stackups/infisical-vs-vault-on-aws"},{"title":"release 2025 03 31 environment secrets","url":"https://docs.aws.amazon.com/es_es/elasticbeanstalk/latest/relnotes/release-2025-03-31-environment-secrets.html"},{"title":"release 2025 03 31 environment secrets","url":"https://docs.aws.amazon.com/fr_fr/elasticbeanstalk/latest/relnotes/release-2025-03-31-environment-secrets.html"},{"title":"vault on aws","url":"https://stackshare.io/doppler/vs/vault-on-aws"}]

Based on the search results, here's what I found about secrets management with AWS Secrets Manager, Vault, and environment variables:

## Key Findings

**Security Risks of Environment Variables:**
Environment variables can be exposed through logs or error messages. Additionally, secrets stored in .env files and environment variables are the leading cause of production credential incidents.

**AWS Secrets Manager vs HashiCorp Vault:**

HashiCorp Vault and AWS Secrets Manager are two of the leading secrets management solutions in 2025, but they suit different needs: Vault excels in multi-cloud flexibility, dynamic secrets, and fine-grained control, while AWS Secrets Manager offers seamless AWS integration, automatic rotation, and managed operations.

**When to Use Each:**

- AWS Secrets Manager is an AWS-native managed service, simpler to set up, with built-in RDS rotation and IAM-based access control. Best for AWS-only teams.

- Choose Vault for complex, hybrid environments and advanced security workflows; pick AWS Secrets Manager if you're primarily within the AWS ecosystem and want ease of use with minimal infrastructure overhead.

**Best Practices:**

Environment variables are fine for configuration settings — like 'Debug Mode' or 'Retry Count'. But for secrets? Always use the Vault.

The search results show that 2025 sources emphasize moving away from environment variables for sensitive credentials and toward dedicated secrets management solutions.


REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.

{
  "query": "Go slog structured logging best practices what not to log PII passwords tokens"
}

Web search results for query: "Go slog structured logging best practices what not to log PII passwords tokens"

Links: [{"title":"Golang Slog Explained: Structured Logging Best Practices","url":"https://uptimerobot.com/knowledge-hub/logging/guide-to-golang-slog/"},{"title":"Structured Logging in Go with slog for Observability and Alerting - Rost Glukhov | Personal site and technical blog","url":"https://www.glukhov.org/observability/logging/structured-logging-go-slog/"},{"title":"How to Implement Structured Logging in Go","url":"https://oneuptime.com/blog/post/2026-01-23-go-structured-logging/view"},{"title":"Golang Logging: A Comprehensive Guide for Developers | Last9","url":"https://last9.io/blog/golang-logging-guide-for-developers/"},{"title":"Logging in Go with Slog: Structured Logging for Production Observability - CubeAPM","url":"https://cubeapm.com/blog/logging-in-go-with-slog/"},{"title":"The Complete Guide to slog (Go 1.21+) Modern Structured Logging in Go (2025) | BuanaCoding","url":"https://buanacoding.com/2025/09/complete-guide-slog-go-structured-logging-2025"},{"title":"Logging Best Practices using slog in Go (Golang)*","url":"https://novrian.substack.com/p/logging-best-practices-in-go-golang"},{"title":"DEV Community","url":"https://dev.to/mizutani/redacting-sensitive-data-in-gos-slog-a-practical-guide-with-masq-158o"}]

Based on the web search results, here are the best practices for Go's slog structured logging, particularly regarding what not to log:

## What Not to Log

Never log sensitive data like passwords and tokens, even at debug level, since debug logs can be left on in more places than intended. Common keys to redact include: password, token, authorization, bearer, secret, api_key, access_token, refresh_token, ssn, credit_card, and cvv.

Additionally, avoid logging full request/response bodies as they contain auth headers and form data.

## Best Practice for Redaction

Sanitize before the log call is made, not after. The recommended approach is to use the `ReplaceAttr` function in `HandlerOptions`: Use ReplaceAttr in HandlerOptions to redact sensitive keys before emission by switching on common sensitive keys and returning a redacted string value.

Custom handlers enable filtering, transformation, and redaction of sensitive fields, which is mandatory for passwords, tokens, and PII to meet security and compliance requirements.

## General Structured Logging Best Practices

Go's log/slog package brings structured logging into the standard library, letting you log consistent key-value data, attach context like request IDs, and output logs in JSON or text formats. Best practices include: always use structured logging in production, include request/trace IDs for correlation, log at appropriate levels, use child loggers for context, configure log level from environment, and output JSON for log aggregation systems.


REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.

{
  "query": "CockroachDB PostgreSQL wire protocol compatibility driver pgx caveats 2025"
}

Web search results for query: "CockroachDB PostgreSQL wire protocol compatibility driver pgx caveats 2025"

Links: [{"title":"PostgreSQL Compatibility - CockroachDB","url":"https://docs.cockroachlabs.com/docs/v26.3/postgresql-compatibility"},{"title":"pgx package - github.com/jackc/pgx/v5 - Go Packages","url":"https://pkg.go.dev/github.com/jackc/pgx/v5"},{"title":"GitHub - jackc/pgx: PostgreSQL driver and toolkit for Go · GitHub","url":"https://github.com/jackc/pgx"},{"title":"Install a Driver or ORM Framework","url":"https://www.cockroachlabs.com/docs/stable/install-client-drivers"},{"title":"Third-Party Tools Supported by Cockroach Labs","url":"https://www.cockroachlabs.com/docs/stable/third-party-database-tools"},{"title":"PostgreSQL Compatibility","url":"https://www.cockroachlabs.com/docs/stable/postgresql-compatibility"},{"title":"Why CockroachDB and PostgreSQL are compatible","url":"https://www.cockroachlabs.com/blog/why-postgres/"},{"title":"CockroachDB","url":"https://en.wikipedia.org/wiki/CockroachDB"},{"title":"jackc/pgx: PostgreSQL driver and toolkit for Go - upd.dev","url":"https://upd.dev/jackc/pgx"}]

Based on the search results, here's what I found regarding CockroachDB's PostgreSQL wire protocol compatibility with the pgx driver:

## Compatibility Overview

CockroachDB supports the PostgreSQL wire protocol and is compatible with version 3.0 of the PostgreSQL wire protocol (pgwire). pgx is tested against the latest version of CockroachDB, indicating strong compatibility between the driver and database.

## General Compatibility

Existing applications built on PostgreSQL can often be migrated to CockroachDB without changing application code, and CockroachDB works with most PostgreSQL drivers and ORMs.

## Caveats and Differences

However, CockroachDB does not support some PostgreSQL features or behaves differently from PostgreSQL because not all features can be easily implemented in a distributed system. Some specific known differences include:

- CockroachDB does not support PostgreSQL range types
- Because CockroachDB has no primary/standby distinction, drivers that read in_hot_standby to detect standby servers always receive off

The search results don't contain detailed pgx-specific caveats or 2025 updates beyond the general compatibility information. For more specific caveats related to pgx usage with CockroachDB, you may want to check the CockroachDB documentation or pgx GitHub repository directly.


REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.

{
  "query": "OpenTelemetry Go lightweight instrumentation metrics tracing API service 2025"
}

Web search results for query: "OpenTelemetry Go lightweight instrumentation metrics tracing API service 2025"

Links: [{"title":"Announcing the Beta Release of OpenTelemetry Go Auto-Instrumentation using eBPF | OpenTelemetry","url":"https://opentelemetry.io/blog/2025/go-auto-instrumentation-beta/"},{"title":"OpenTelemetry for Go: Traces, Metrics & Logs with OpenObserve | OpenObserve","url":"https://openobserve.ai/opentelemetry/go/"},{"title":"Distributed Tracing with OpenTelemetry in Go: A Practical Guide (2026) - DEV Community","url":"https://dev.to/young_gao/distributed-tracing-with-opentelemetry-a-practical-guide-for-go-services-pep"},{"title":"OpenTelemetry Go Tracing | Uptrace","url":"https://uptrace.dev/get/opentelemetry-go/tracing"},{"title":"The Ultimate Go Observability Cheat Sheet (OpenTelemetry Edition) | by Ancilar | Blockchain Services | Medium","url":"https://medium.com/@ancilartech/the-ultimate-go-observability-cheat-sheet-opentelemetry-edition-9e020eecc747"},{"title":"Go instrumentation sample | Cloud Trace | Google Cloud Documentation","url":"https://docs.cloud.google.com/trace/docs/setup/go-ot"},{"title":"GitHub - open-telemetry/opentelemetry-go: OpenTelemetry Go API and SDK · GitHub","url":"https://github.com/open-telemetry/opentelemetry-go"},{"title":"Instrumentation | OpenTelemetry","url":"https://opentelemetry.io/docs/languages/go/instrumentation/"}]

Here are the search results for OpenTelemetry Go lightweight instrumentation metrics tracing API service 2025:

## Key Findings:

**Recent Developments (2025-2026):**

OpenTelemetry Go offers seamless extension of auto-instrumentation with custom spans using the OpenTelemetry Go Trace API. The proposed donation of Beyla to OpenTelemetry presents an opportunity to enhance OpenTelemetry's eBPF-based auto-instrumentation capabilities, which will help expand support for additional signals, protocols, and languages.

**Core Features:**

OpenTelemetry's goal is to provide a single set of APIs to capture distributed traces and metrics from your application and send them to an observability platform, which it does for applications written in Go. As of mid-2026, traces and metrics are covered by the project's stability guarantees, and the logs signal is usable in production.

**Instrumentation Options:**

OpenTelemetry Go supports gRPC instrumentation for collecting telemetry data from gRPC clients and servers, and kafka-go instrumentation for monitoring and tracing Kafka messaging. The instrumentation libraries in the opentelemetry-go-contrib repository wrap common dependencies with a line or two of code.

**Lightweight Design:**

For Go developers, OpenTelemetry's lightweight design aligns with Go's performance focus.


REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.

{
  "query": "CockroachDB transaction retry errors 40001 SERIALIZABLE client-side retry pgx"
}

Web search results for query: "CockroachDB transaction retry errors 40001 SERIALIZABLE client-side retry pgx"

Links: [{"title":"Transaction Retry Error Reference - CockroachDB","url":"https://www.cockroachlabs.com/docs/v26.2/transaction-retry-error-reference"},{"title":"Transaction Retry Error Reference","url":"https://www.cockroachlabs.com/docs/stable/transaction-retry-error-reference"},{"title":"Advanced Client-side Transaction Retries","url":"https://www.cockroachlabs.com/docs/stable/advanced-client-side-transaction-retries"},{"title":"Troubleshoot SQL Statements","url":"https://www.cockroachlabs.com/docs/stable/error-handling-and-troubleshooting.html"},{"title":"Transactions","url":"https://www.cockroachlabs.com/docs/stable/transactions"},{"title":"Ecto and CockroachDB TransactionRetryWithProtoRefreshError issue - Questions - Elixir Programming Language Forum","url":"https://elixirforum.com/t/ecto-and-cockroachdb-transactionretrywithprotorefresherror-issue/62171"},{"title":"Middleware to handle retries for SQLSTATE value of '40001' (PostgreSQL, CockroachDB) · Issue #11183 · prisma/prisma","url":"https://github.com/prisma/prisma/issues/11183"},{"title":"What to do when a transaction fails in CockroachDB","url":"https://www.cockroachlabs.com/blog/what-to-do-when-a-transaction-fails-in-cockroachdb/"},{"title":"CockroachDB - Transactions & Serializable Isolation","url":"https://www.lexuankha.com/blog/cockroachdb-transactions-serializable-isolation"}]

Based on the search results, here's information about CockroachDB transaction retry errors with SQLSTATE 40001, SERIALIZABLE isolation, and client-side retry handling with pgx:

## Understanding Error 40001

CockroachDB signals a serialization error with the SQLSTATE error code 40001 and an error message that begins with the string "restart transaction". These errors indicate that a transaction failed due to contention with another concurrent or recent transaction attempting to write to the same data, and the transaction needs to be retried by the client.

## SERIALIZABLE Isolation and Automatic Retries

At the default SERIALIZABLE isolation level, CockroachDB always attempts to find a serializable ordering among all currently-executing transactions. Whenever possible, CockroachDB will auto-retry a transaction internally without notifying the client, and will only send a serialization error to the client when it cannot resolve the error automatically without client-side intervention.

## pgx and Client-side Retry Handling

Go developers using pgx can use the github.com/cockroachdb/cockroach-go/crdb package for automatic retry handling. This is the recommended approach for applications using the pgx driver with CockroachDB.

## Recommended Actions

Under SERIALIZABLE isolation, you should update your application to support client-side retry handling when transaction retry errors are encountered. Additionally, if a statement returns a retry error, you can issue the ROLLBACK TO SAVEPOINT statement to restart the transaction.


REMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks.

{
  "file_path": "/Users/warrenthompson/Source/LoginID/04-infra-devops/research-infra-devops-best-practices.md",
  "content": "# Infra & DevOps — Research: Current Best Practices (2025–2026)\n\nThis is a research/recommendation document only. No infrastructure is stood up here; this informs the containerization, CI/CD, local-dev, secrets, and observability design for the DAO service, its REST API, and the third-party IDP connector service described in `../CLAUDE.md` and `./CLAUDE.md`.\n\nAI tooling note: produced with Claude Code (Sonnet 5), using `WebSearch`/`WebFetch` against current (2025–2026) sources, read and synthesized directly rather than copy-pasted — citations are included per section so the reasoning can be checked against the primary source.\n\n---\n\n## 1. Containerization for small Go services\n\nGo's static binaries make it a natural fit for minimal multi-stage Docker builds — the build toolchain never needs to ship in the runtime image.\n\n**Pattern (build stage + minimal runtime):**\n\n- **Build stage**: `golang:1.2x` (pinned minor version, not `latest`) — `go mod download` before copying source so dependency layers cache independently of code changes; `CGO_ENABLED=0 GOOS=linux go build -ldflags=\"-s -w\" -o /app ./cmd/service` to produce a static, stripped binary.\n- **Runtime stage**: copy only the binary (and, if HTTPS calls are made, `/etc/ssl/certs/ca-certificates.crt` from the build stage or a `ca-certificates` layer) into a minimal base.\n\n**Base image choice** — current guidance converges on three tiers:\n- **`scratch`**: literally nothing but the binary. Smallest possible image (single-digit MB), zero OS-level CVEs to patch, but no shell, no CA certs, no non-root user by default — you must supply certs and a numeric `USER` yourself if the binary makes outbound TLS calls.\n- **`gcr.io/distroless/static` (distroless)**: adds CA certificates, timezone data, and a built-in non-root user (UID 65532), still with no shell or package manager. This is described repeatedly as \"the sweet spot for most production services\" — nearly as small as scratch, but without having to hand-roll certs/user setup.\n- **`alpine`**: only worth it when you need a shell in the runtime image for debugging/exec-ing in; it carries a package manager and more attack surface than the two above.\n\n**Recommendation for this project**: distroless (`gcr.io/distroless/static-debian12` or similar) as the default runtime base for both the DAO/API service and the IDP connector, non-root by default, with scratch offered as a \"how you'd shrink further\" footnote. Other practices worth naming: pin exact base image digests/tags, order Dockerfile layers for cache efficiency (`go.mod`/`go.sum` copy + download before source copy), and never run as root even though distroless already defaults to a non-root UID.\n\nSources:\n- [How to Containerize Go Apps with Multi-Stage Dockerfiles](https://oneuptime.com/blog/post/2026-01-07-go-docker-multi-stage/view)\n- [Docker Multi-Stage Builds for Go: From 1GB to 12MB Images (2026 Guide)](https://dev.to/young_gao/docker-multi-stage-builds-for-go-from-1gb-to-12mb-production-images-2p1h)\n- [How to Create Minimal Docker Images for Go Applications](https://oneuptime.com/blog/post/2026-02-20-go-docker-minimal-image/view)\n- [Build Minimal Go Docker Images from Scratch (2026)](https://adhdecode.com/articles/docker/docker-scratch-image-golang/)\n- [Docker Multi-Stage Builds: The Complete Guide for 2026](https://devtoolbox.dedyn.io/blog/docker-multi-stage-builds-guide)\n\n---\n\n## 2. CI/CD pipeline design for a Go project\n\nA modern Go pipeline separates fast local-signal checks from slower/scheduled security scans, so PR feedback stays quick.\n\n**Typical stage sequence** (on every push/PR):\n1. **Checkout + setup Go** (pinned version, module cache restored).\n2. **`go vet`** and **`golangci-lint run`** — `golangci-lint` is a linter aggregator that already includes `go vet`, `staticcheck`, and `gosec` (a security-focused linter) as constituent linters, so gosec-class findings (weak crypto, SQL injection patterns, unhandled errors) surface here rather than needing a separate step. The official `golangci-lint-action` is the standard way to wire this into GitHub Actions.\n3. **`go build ./...`** — fail fast on compile errors before spending time on tests.\n4. **`go test ./... -race -cover`** — race detector and coverage on every run.\n5. **`govulncheck ./...`** — scans for known vulnerabilities *reachable from your actual call graph*, which is why it's kept distinct from a generic CVE scanner: it reports far fewer false positives than \"does any dependency have a CVE\" tools, so it's cheap to run on every PR.\n6. **Container build + Trivy scan** — once a Dockerfile/image exists, Trivy scans the built image for OS package and dependency CVEs. Some pipelines run this on every PR; a common cost/speed tradeoff seen in current sources is to run it on `main`/nightly/schedule rather than every PR, since it's slower and image-layer CVEs change on OS vendor timelines rather than on your commit cadence.\n7. (If publishing images) build multi-arch image, generate SBOM/provenance attestation, push to registry.\n\n**Sequencing logic**: cheap/fast checks (vet, lint, build) run first and gate everything else; `go test` next since it's the main correctness signal; `govulncheck` is cheap enough to run on every PR because of its call-graph-aware filtering; Trivy (container scan) is heavier and more often scheduled/gated to `main` merges rather than every PR push.\n\nSources:\n- [How to Set Up Go CI Pipeline with GitHub Actions](https://oneuptime.com/blog/post/2025-12-20-go-ci-pipeline-github-actions/view)\n- [golangci-lint-action (official)](https://github.com/golangci/golangci-lint-action)\n- [Go Linting Best Practices for CI/CD with GitHub Actions](https://medium.com/@tedious/go-linting-best-practices-for-ci-cd-with-github-actions-aa6d96e0c509)\n- [Continuous integration with Go and GitHub Actions](https://aran.dev/posts/continuous-integration-with-go-and-github-actions/)\n- [Go Package CI/CD with GitHub Actions](https://forcepush.tech/go-package-ci-cd-with-git-hub-actions)\n\n---\n\n## 3. Local development loop\n\n**docker-compose pattern**: a `docker-compose.yml` that runs the Go service(s) alongside a local database container, with the service configured (via env vars) to point at the compose-network hostname rather than localhost.\n\n- **PostgreSQL**: standard `postgres:<pinned-version>` image, environment-configured user/db/password, a named volume for data persistence across restarts, and a healthcheck (`pg_isready`) so the app container's `depends_on` can wait for readiness rather than racing startup.\n- **CockroachDB**: runs equally well in Docker; single-node `cockroach start-single-node --insecure` is the common local/dev pattern (insecure mode is explicitly a local-dev-only convenience, never a deployment recommendation). Because CockroachDB speaks the Postgres wire protocol, the same Go Postgres drivers/ORMs (pgx, pq, GORM, upper/db, etc.) work against it — see section 6.\n- **SQLite**: doesn't need a compose service at all — it's the \"zero-dependency\" option, a single file on disk (or `:memory:`) the binary talks to directly via `database/sql` + a SQLite driver (e.g. `mattn/go-sqlite3` or the pure-Go `modernc.org/sqlite`). This is the natural default for fast local iteration and for unit/integration tests in CI (no container startup latency, trivially parallelizable, disposable).\n\n**Recommendation for this project**: a docker-compose file offering Postgres and CockroachDB as selectable/swappable profiles (matching the DAO's storage-agnostic driver-selection design from `../05-data-ops/CLAUDE.md`), with SQLite as the documented no-compose-needed path for quick local runs and for the test suite — the DAO's storage abstraction is exactly what makes swapping among all three a config change rather than a code change.\n\nSources:\n- [Use containers for Go development — Docker Docs](https://docs.docker.com/guides/golang/develop/)\n- [How to Run CockroachDB in Docker with Clustering](https://oneuptime.com/blog/post/2026-02-08-how-to-run-cockroachdb-in-docker-with-clustering/view)\n- [cockroachdb-docker-compose](https://github.com/lhsribas/cockroachdb-docker-compose)\n- [How to Use Docker Compose for Local Development Environments](https://oneuptime.com/blog/post/2026-02-20-docker-compose-development/view)\n\n---\n\n## 4. Secrets management: proportionate vs. over-engineered\n\nCurrent guidance is consistent: plain environment variables are acceptable for *non-secret configuration* (log level, retry counts, feature flags) but are explicitly discouraged for actual secrets in a real deployment, because env vars are exposed through process listings, crash dumps, and accidental logging, and `.env`-file/env-var leakage is cited as a leading cause of real production credential incidents.\n\n**Real-deployment options** (in increasing operational weight):\n- **Cloud-native managed secret store** — AWS Secrets Manager or GCP Secret Manager: managed, IAM/role-scoped access, automatic rotation support (e.g., built-in RDS credential rotation), lowest operational overhead if you're already on that cloud. Best fit when the deployment target is a single cloud.\n- **HashiCorp Vault**: more powerful (dynamic/short-lived secrets, multi-cloud, fine-grained policy), but meaningfully more infrastructure to run and operate (Vault itself needs to be deployed, unsealed, and maintained) — the right call for multi-cloud/hybrid or when dynamic secret issuance is a real requirement, overkill otherwise.\n- **Env-var injection at deploy time from a secret store** (not secrets committed to env files) — i.e., the platform (Kubernetes Secrets backed by a external-secrets operator, ECS task definition secrets pulled from Secrets Manager, etc.) injects the value into the process environment at container start, so the *application code* still just reads `os.Getenv(...)`, but the secret's at-rest storage, access control, and rotation are handled by the managed store rather than a plaintext file in the repo.\n\n**What's proportionate for this take-home**: naming a managed secrets manager (AWS Secrets Manager or GCP Secret Manager, whichever the rest of the take-home's narrative leans toward) as the target-state design, with env-var injection at container start as the actual mechanism the containers see — i.e., \"secrets never live in the image or the repo; they're injected as env vars at deploy time, sourced from a managed secret store with rotation and IAM-scoped read access.\" Standing up Vault, writing rotation Lambdas, or designing a full PKI would be over-engineering for a take-home whose code doesn't need to run in a live environment — the design should *name* the mechanism and *why* the DB credentials/IDP credentials/signing keys never touch source control, not build the secret store.\n\nSources:\n- [Secrets Management: Vault, AWS Secrets Manager, or SOPS?](https://dev.to/instadevops/secrets-management-vault-aws-secrets-manager-or-sops-2ce1)\n- [HashiCorp Vault vs AWS Secrets Manager: Enterprise Secret Management](https://www.openempower.com/blog/vault-vs-aws-secrets-manager-enterprise-secret-management)\n- [Secrets Management in DevOps: AWS Secrets Manager vs HashiCorp Vault](https://acquaintsoft.com/blog/secrets-management-aws-vault-devops-implementation)\n- [HashiCorp Vault vs AWS Secrets Manager | 2025 Guide](https://cybersnowden.com/hashicorp-vault-vs-aws-secrets-manager/)\n\n---\n\n## 5. Observability basics for a Go API service\n\n**Structured logging**: Go's standard-library `log/slog` (stable since Go 1.21) is the current default choice — structured key/value logging, JSON output for aggregation, `context`-aware child loggers for request/trace-ID correlation, and level control from environment/config. This avoids adding a third-party logging dependency for a service of this size.\n\n**What must never be logged** (directly relevant to this project, which handles `user_credential.password`, third-party IDP `access_token`s, and PII in `user_profile`/`/identity` responses):\n- Raw passwords or password hashes, at any log level — sources are explicit that this holds even for debug-level logs, since debug logging tends to get left on in more environments than intended.\n- Access tokens, refresh tokens, `Authorization`/bearer headers, API keys, and other credential-shaped secrets.\n- Full request/response bodies logged wholesale, since they often carry the above (auth headers, form data) even when the intent was just to log \"the request.\"\n- PII fields returned by `/identity` (name, phone, street address, etc.) beyond what's needed for a correlation ID — log a request ID / hashed identifier, not the person's actual data, in ordinary operational logs.\n- Standard practice for redaction: don't rely on \"remembering not to log it\" per call site — use `slog.HandlerOptions.ReplaceAttr` (or an equivalent middleware/wrapper) to redact known-sensitive keys (`password`, `token`, `authorization`, `secret`, `api_key`, `access_token`, `refresh_token`, and PII field names) centrally, so a redaction rule applies uniformly rather than depending on every call site getting it right.\n\n**Metrics/tracing**: OpenTelemetry (OTel) is the standard, vendor-neutral choice for Go — the Go SDK/API cover traces and metrics under OTel's stability guarantees (logs support has also reached usable-in-production maturity as of 2026), and `opentelemetry-go-contrib` provides near-zero-effort instrumentation wrappers for common dependencies (HTTP handlers, gRPC, SQL drivers, Kafka clients). For a take-home, the honest framing is: name OTel as the mechanism you'd wire in (a tracer for request spans across the API → DAO → IDP-connector call chain, and basic RED metrics — rate, errors, duration — per endpoint) without actually standing up a collector/backend, since doing so wouldn't be exercised by anyone reviewing the take-home.\n\nSources:\n- [Golang Slog Explained: Structured Logging Best Practices](https://uptimerobot.com/knowledge-hub/logging/guide-to-golang-slog/)\n- [Redacting Sensitive Data in Go's slog: A Practical Guide with masq](https://dev.to/mizutani/redacting-sensitive-data-in-gos-slog-a-practical-guide-with-masq-158o)\n- [Logging Best Practices using slog in Go (Golang)](https://novrian.substack.com/p/logging-best-practices-in-go-golang)\n- [Instrumentation — OpenTelemetry Go docs](https://opentelemetry.io/docs/languages/go/instrumentation/)\n- [OpenTelemetry Go (GitHub)](https://github.com/open-telemetry/opentelemetry-go)\n- [The Ultimate Go Observability Cheat Sheet (OpenTelemetry Edition)](https://medium.com/@ancilartech/the-ultimate-go-observability-cheat-sheet-opentelemetry-edition-9e020eecc747)\n\n---\n\n## 6. CockroachDB's Postgres-wire-protocol compatibility — deployment/config impact\n\nCockroachDB implements the PostgreSQL wire protocol (pgwire v3), which is why the same Go Postgres drivers (`pgx`, `lib/pq`) and ORMs (GORM, upper/db, etc.) work against both Postgres and CockroachDB largely unchanged — for many applications, the connection-string-and-driver layer really can be shared, which is directly relevant to this DAO's requirement to support both databases through one abstraction.\n\n**Caveats that matter for a DAO design**, not just \"it's compatible\":\n- **Not full feature parity**: CockroachDB does not support everything Postgres does (e.g., no PostgreSQL range types; no primary/standby distinction, so drivers checking `in_hot_standby` always read `off`). The DAO's SQL should stay in the common subset — standard DDL/DML, no Postgres-only extensions — if it's meant to run unmodified against both.\n- **Transaction retries are the real semantic difference.** CockroachDB defaults to `SERIALIZABLE` isolation and, being a distributed database, can surface a client-visible serialization error (SQLSTATE `40001`, \"restart transaction\") when it cannot resolve a write conflict automatically — something that essentially never happens the same way against a single-node Postgres instance under normal load. The documented fix is **client-side retry handling**: catch `40001`, and either issue `ROLLBACK TO SAVEPOINT` and replay the transaction, or use a retry-wrapping library (Cockroach Labs ships `cockroachdb/cockroach-go/crdb` specifically for this, compatible with `pgx`-based code). A DAO written only against Postgres semantics and pointed at CockroachDB without this retry loop will intermittently fail under concurrent writes in a way it never would locally.\n- **Practical implication for this project's abstraction layer**: the DAO's CockroachDB code path should wrap write transactions in a retry helper (or use `crdb.ExecuteTx`-style helper), while the Postgres/SQLite paths don't need one — this is exactly the kind of driver-specific behavior the storage-agnostic interface (`../05-data-ops/CLAUDE.md`) needs to isolate behind the abstraction rather than leaking into API/service-layer code.\n- **Local dev implication**: `cockroach start-single-node --insecure` for local/dev is fine (no TLS, no retry contention at that scale) but should be called out as dev-only, matching how Postgres's dev docker-compose setup uses trust-auth/simple passwords that also wouldn't be appropriate in production.\n\nSources:\n- [PostgreSQL Compatibility — CockroachDB docs](https://www.cockroachlabs.com/docs/stable/postgresql-compatibility)\n- [Why CockroachDB and PostgreSQL are compatible](https://www.cockroachlabs.com/blog/why-postgres/)\n- [Install a Driver or ORM Framework — CockroachDB docs](https://www.cockroachlabs.com/docs/stable/install-client-drivers)\n- [Transaction Retry Error Reference — CockroachDB docs](https://www.cockroachlabs.com/docs/stable/transaction-retry-error-reference)\n- [Advanced Client-side Transaction Retries — CockroachDB docs](https://www.cockroachlabs.com/docs/stable/advanced-client-side-transaction-retries)\n- [What to do when a transaction fails in CockroachDB](https://www.cockroachlabs.com/blog/what-to-do-when-a-transaction-fails-in-cockroachdb/)\n- [pgx (jackc/pgx) — Go Packages](https://pkg.go.dev/github.com/jackc/pgx/v5)\n\n---\n\n## Recommendations for this assignment\n\nA concrete, proportionate design — enough to show intentionality, not enough to be a real ops project:\n\n**Containerization**: One multi-stage Dockerfile per service (DAO/API service, IDP connector service). Build stage: `golang:1.2x`, `CGO_ENABLED=0`, static stripped binary. Runtime stage: `gcr.io/distroless/static-debian12`, non-root (distroless's built-in UID 65532), CA certs copied in for outbound TLS to the IDP vendor endpoints. Pin base image versions. Mention scratch as a further-shrink option, not the default.\n\n**CI pipeline (GitHub Actions, sketch only — no actual workflow file)**: On every PR — checkout, setup-go, `golangci-lint run` (covers vet + gosec-class checks), `go build ./...`, `go test ./... -race -cover`, `govulncheck ./...`. On merge to main (or nightly) — build the container image and run Trivy against it, since image-layer CVE scans are heavier and track OS vendor timelines rather than every commit. Keep PR feedback fast; push the slow/scheduled scan to main.\n\n**Local dev loop**: `docker-compose.yml` with two profiles — Postgres and CockroachDB (`cockroach start-single-node --insecure` for the latter), each with a healthcheck the app container's `depends_on` waits on. SQLite documented as the no-compose-needed default for quick iteration and for the test suite (fast, disposable, parallelizable). The DAO's driver-selection config (env var choosing the backend) is what makes all three swappable without touching the app.\n\n**Secrets**: Name AWS Secrets Manager (or GCP Secret Manager) as the target-state store for DB credentials, IDP vendor credentials, and signing keys, with env-var injection at container start as the actual delivery mechanism the app sees (`os.Getenv`, never a literal in the image or repo). Explicitly scope out Vault as over-engineered for this take-home's actual deployment footprint — name it as \"the multi-cloud/dynamic-secret answer if this grew,\" not something to build now.\n\n**Observability**: `log/slog` with a central `ReplaceAttr`-based redaction rule for password/token/PII-shaped keys, so no call site can accidentally leak a credential or a citizen's PII into logs; JSON output; request-ID correlation. Name OpenTelemetry (traces across API → DAO → IDP-connector, RED metrics per endpoint) as the intended instrumentation approach without standing up a collector — this is a \"here's what I'd wire in\" note, not a working pipeline.\n"
}

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