feat: OpenSpec proposal for bcache support (#562)

[rustyrazorblade]

Add OpenSpec change for #562: -- bcache flag on init that configures local NVMe as write-back cache in front of EBS via Linux bcache.

Includes proposal, design, tasks, and specs for the bcache capability and updated instance-storage-validation spec.

Closes #562

Generated with Claude Code

[github-actions]

Code Coverage

File	Coverage [93.77%]	✅
src/main/kotlin/com/rustyrazorblade/easydblab/commands/Init.kt	82.65%	✅
src/main/kotlin/com/rustyrazorblade/easydblab/configuration/ClusterState.kt	100.00%	✅
src/main/kotlin/com/rustyrazorblade/easydblab/services/aws/InstanceSpecFactory.kt	100.00%	✅

Total Project Coverage	67.07%	❌

[claude]

PR Review: bcache Support OpenSpec Proposal

This is a well-structured proposal. The design is thorough, the non-goals are appropriately scoped, and the architectural decisions align with the codebase conventions (TemplateService injection, validation in InstanceSpecFactory, fail-fast). A few things worth addressing before implementation starts:

---

Issues

1. Missing template variable for EBS device name (tasks.md §3.1–3.2)

The design acknowledges that EBSConfig.deviceName is the canonical backing device path, but the tasks only plan to inject __BCACHE_ENABLED__ via TemplateService. The EBS device name should also be injected as __EBS_DEVICE__ (or similar) rather than hardcoding /dev/xvdf in the script. Otherwise the script breaks for any cluster where EBSConfig.deviceName differs from the default.

2. cset_uuid extraction is underspecified (tasks.md §3.3)

The task lists:

echo <cset_uuid> > /sys/block/bcache0/bcache/attach

but doesn't specify how to obtain <cset_uuid>. In practice, after make-bcache -C <device>, the UUID must be read from /sys/fs/bcache/ (e.g., ls /sys/fs/bcache/ gives the set UUID). This is non-obvious and should be spelled out in the task or design, otherwise implementors will likely get stuck here.

3. Idempotency / already-registered devices (tasks.md §3.3)

make-bcache fails with an error if a device already has a bcache superblock. On re-runs or after partial failures, the script could encounter a device that was previously registered. Task 3.3 should explicitly address this — either wipe the superblock (wipefs) before registering, or check for existing bcache state and skip registration if already configured.

4. Validation errors should use the event bus, not IllegalArgumentException (tasks.md §2.1)

The tasks specify throwing IllegalArgumentException, but per the architecture and CLAUDE.md, all user-facing output uses eventBus.emit(Event.Domain.Type(...)). Validation failures in InstanceSpecFactory should emit a domain-specific error event (likely in the Init domain) rather than throwing raw exceptions that get caught and printed without structure. Worth planning the event type alongside the validation code.

---

Suggestions

5. Consider injecting __BCACHE_CACHE_MODE__ as a template variable

The spec locks the cache mode to writeback, and the non-goals section explicitly excludes choosing the mode at runtime. However, if you ever want to add writethrough support in the future (e.g., for safety testing), having the mode in the template from the start costs nothing. This is optional — just noting it given the "open for extension" principle.

6. linux-modules-extra-aws version pinning (tasks.md §4.1)

The Packer install script should install linux-modules-extra-aws matching the running kernel (linux-modules-extra-$(uname -r)) rather than the generic metapackage, to ensure the bcache module is available for the running kernel version. The generic metapackage doesn't always pull in modules for the currently booted kernel in AMI builds. Task 4.1 should clarify this.

7. Spec gap: modprobe bcache failure behavior

The spec says the system SHALL load the bcache module but doesn't specify what happens if modprobe bcache fails (module not found, kernel too old, etc.). A Scenario: bcache module unavailable with a clear error message requirement would round out the spec.

---

What's Good

• Validation placement in DefaultInstanceSpecFactory is exactly right per the architecture.
• Using TemplateService for script injection instead of environment variable injection or a separate script is the correct call.
• The udev symlink approach (/dev/xvdf → /dev/nvme1n1 on Nitro) is correct and avoids fragile device name guessing.
• The risk section is honest — acknowledging bcache data loss on reboot and Nitro device name variability is appreciated.
• BDD scenario format in the specs maps cleanly to the test cases in tasks.md §2.2.
• The bcache-tools unconditional install rationale is sound — small package, simplifies the logic.

Overall this is solid planning work. The issues above are worth addressing in the tasks before implementation begins, especially items 1 (EBS device template variable) and 2 (cset_uuid extraction), which could cause the implementation to diverge from the spec.

[rustyrazorblade]

Needs to support both write back and write through modes. add a --bcache.mode and default to write through, since it's the safer version that I'll almost certainly use. @claude

[claude]

Claude finished @rustyrazorblade's task in 2m 26s —— View job

---

Adding --bcache.mode flag with writethrough/writeback support

• Read existing proposal files
• Update proposal.md to mention mode flag
• Update design.md to add mode parameter details (moved "choosing cache mode" out of Non-Goals, added mode-aware template substitution)
• Update tasks.md to include --bcache.mode flag in CLI (task 1.2), __BCACHE_MODE__ and __EBS_DEVICE__ template injection (task 3.2), mode-specific test scenarios (task 2.2)
• Update specs/bcache/spec.md to add writethrough/writeback mode requirement and scenarios (including invalid mode rejection)
• Commit and push changes

Summary

Updated the OpenSpec proposal to add a --bcache.mode flag:

• Default: writethrough — writes committed to both NVMe cache and EBS before acknowledgement; safe, no data loss risk
• Optional: writeback — writes acknowledged after NVMe cache only, flushed to EBS asynchronously; maximum write performance, small data loss window on termination

Changes also incorporate fixes from the earlier review:

• __EBS_DEVICE__ template variable added to tasks so the EBS device path is injected rather than hardcoded
• cset_uuid extraction procedure spelled out in task 3.3 (ls /sys/fs/bcache/)
• Idempotency via wipefs wipe before bcache registration addressed in task 3.3
  |

[rustyrazorblade]

@claude apply

[claude]

Claude finished @rustyrazorblade's task in 15m 30s —— View job

---

bcache Support Implementation Complete

• Read OpenSpec tasks and design files
• Understand existing codebase structure
• Implement CLI flags --bcache and --bcache.mode
• Add validation in InstanceSpecFactory
• Add bcache shell script template
• Update packer provisioning for bcache-tools
• Add tests
• Commit and push changes

What Was Implemented

13 files changed, 419 insertions, 31 deletions across:

CLI (Init.kt)

• --bcache boolean flag (default: false)
• --bcache.mode flag with writethrough / writeback options (default: writethrough)
• Validation that mode is one of the two valid values

Validation (InstanceSpecFactory.kt)

• bcache=true without EBS config → clear error
• bcache=true without instance storage → clear error

Script template (setup_instance.sh)

• Full bcache setup block injected via TemplateService with __BCACHE_ENABLED__, __BCACHE_MODE__, __EBS_DEVICE__ variables
• Idempotent: wipes superblock with wipefs before registering
• cset_uuid extracted from /sys/fs/bcache/
• Falls back to original disk detection when bcache is disabled

Packer provisioning

• packer/base/install/install_bcache.sh — installs bcache-tools and linux-modules-extra-aws unconditionally
• packer/base/base.pkr.hcl — added bcache install step

State (ClusterState.kt)

• bcache: Boolean = false and bcacheMode: String = "writethrough" added to InitConfig

Tests

• InitTest.kt — invalid mode validation, config stored in state, disabled by default
• InstanceSpecFactoryTest.kt — 5 scenarios covering all bcache validation paths

Docs

• docs/user-guide/cluster-setup.md — bcache usage, prerequisites, cache mode table, caveats
• docs/reference/commands.md — --bcache and --bcache.mode flags documented

OpenSpec

• openspec/specs/bcache/spec.md — formal spec added to permanent specs directory
• openspec/changes/bcache-support/tasks.md — all tasks marked complete
  |

[claude]

PR Review: bcache Support

What This PR Does

Adds Linux bcache caching support so local NVMe instance store can transparently accelerate EBS volumes. Includes two new init flags (--bcache, --bcache.mode), config persistence, init-time validation, shell script generation via TemplateService, Packer AMI changes for bcache-tools, documentation, and full OpenSpec artifacts.

---

Strengths

• Good layering: Validation is split cleanly — validateParameters() in Init checks syntax (valid mode string); DefaultInstanceSpecFactory checks business logic (bcache requires both EBS + NVMe). This is correct per the architecture.
• TemplateService used correctly: Tests use the real TemplateService instance, not a mock. Matches CLAUDE.md requirement.
• Clear error messages: "Instance type ${initConfig.instanceType} has no local instance store." and "--bcache requires an EBS volume..." are specific and actionable.
• Security handled: Shell injection is prevented because bcacheMode is validated against listOf("writethrough", "writeback") before it reaches the shell script.
• Backward compatibility: InitConfig defaults (bcache = false, bcacheMode = "writethrough") ensure existing clusters are unaffected.
• Documentation caveats are explicit: Non-persistence across reboots and writeback data loss risk are both documented.

---

Issues

1. Tests don't verify script content (Missing)

The InitTest tests confirm that bcache flags are persisted to InitConfig, but they don't verify that the generated setup_instance.sh actually contains the substituted values. A bug in placeholder replacement would go undetected.

Suggest adding:

@Test
fun `bcache flags are substituted into generated setup script`() {
    val command = Init()
    command.bcache = true
    command.bcacheMode = "writeback"
    command.execute()

    val scriptContent = File("setup_instance.sh").readText()
    assertThat(scriptContent)
        .contains("BCACHE_ENABLED=true")
        .contains("BCACHE_MODE=writeback")
        .doesNotContain("__BCACHE_")  // no unreplaced placeholders
}

2. Hardcoded /dev/xvdf is fragile

Init.kt hardcodes /dev/xvdf as the EBS device name when constructing template variables. EBSConfig already tracks the device name. If EBSConfig.deviceName is ever changed, the init command won't reflect it — silent breakage.

Suggest: Either pull the device name from EBSConfig or define it as a constant in com.rustyrazorblade.easydblab.Constants.

3. Packer test coverage unclear

The design doc states a packer script test should be added for the bcache setup path, but I don't see additions to packer/testing/ in the diff. Please verify that ./gradlew testPacker covers install_bcache.sh and ideally checks:

• bcache-tools installs successfully
• make-bcache is available after installation
• Script is idempotent (no errors on second run)

---

Minor Notes

• No wildcard imports detected. ✓
• Event bus usage looks correct (Event.Setup.WritingSetupScript). ✓
• Shell script properly validates that /dev/bcache0 appears before proceeding. ✓
• Defaults (bcache = false, bcacheMode = "writethrough") are safe for existing clusters. ✓

---

Summary

This is well-implemented and architecturally sound. The main gap is test coverage of actual script content generation — the current tests validate flag persistence but not the end-to-end output. The hardcoded device name is a minor but real brittleness. Neither is a blocker, but the content assertion test would meaningfully increase confidence in the template substitution path.

[rustyrazorblade]

@claude Address the failures and the feedback

[claude]

Claude finished @rustyrazorblade's task in 3m 35s —— View job

---

Addressing PR Review Feedback

• Read existing implementation files
• Fix hardcoded /dev/xvdf device name
• Add script content verification tests
• Add packer test for install_bcache.sh
• Commit and push changes

Changes Made

1. Fixed hardcoded /dev/xvdf (Issue 2)

• Added Constants.EBS.DEFAULT_DEVICE_NAME = "/dev/xvdf" to Constants.kt as a single authoritative definition
• Updated Init.kt extractSetupScript() to use Constants.EBS.DEFAULT_DEVICE_NAME instead of the literal string

2. Added script content verification tests (Issue 1)
Added three new tests to InitTest.kt:

• setup script contains bcache enabled substitution — verifies BCACHE_ENABLED=true, BCACHE_MODE=writeback, and correct EBS device path are present in the rendered script
• setup script contains bcache disabled substitution by default — verifies correct defaults in rendered script
• setup script does not contain unsubstituted placeholders — verifies no __KEY__ placeholders remain after TemplateService substitution

All tests use the real TemplateService instance (not mocked), per CLAUDE.md requirements.

3. Added packer test for install_bcache.sh (Issue 3)
Added a test-bcache service to packer/docker-compose.yml that runs install_bcache.sh in the Docker test environment, consistent with the existing packer test structure.

---

|

[claude]

• This is a general purpose database test tool, not a Cassandra-specific tool. It supports Cassandra, ClickHouse, OpenSearch, and more. In user-facing text (docs, error messages, comments), use "database" or "db" instead of "Cassandra" unless referring to Cassandra-specific functionality. The ServerType.Cassandra / "db" node type is the generic database node — don't assume it's always Cassandra.
• This is a command line tool. The user interacts by reading the output. Do not suggest replacing print statements with logging, because it breaks the UX.
• All user-facing output uses eventBus.emit(Event.Domain.Type(...)) with domain-specific typed events. Events are defined as sealed data classes in events/Event.kt across 28 domain interfaces. See events/CLAUDE.md.
• Do NOT use Event.Message or Event.Error — these generic types exist only for test convenience. All production output must use domain-specific typed events with structured data fields.
• Do not add logging frameworks to command classes unless there is a specific internal debugging need separate from user output.
• When logging is needed, use: import io.github.oshai.kotlinlogging.KotlinLogging and create a logger with private val log = KotlinLogging.logger {}

Project Organization

Architecture Overview

The project follows a layered architecture:

• Commands (PicoCLI) delegate to Services, which interact with External Systems (K8s, AWS, Filesystem)
• Commands and Services emit events via the EventBus
• Listeners consume events: ConsoleEventListener (stdout/stderr), McpEventListener (server MCP status), RedisEventListener (pub/sub, optional)

Project Modules

The Gradle project has multiple modules:

• Root module (:) — the main CLI application
• spark/common — shared Spark config (SparkJobConfig), data generation, CQL setup
• spark/bulk-writer-sidecar — Cassandra Analytics bulk writer, direct sidecar transport (requires cassandra-analytics built with JDK 11)
• spark/bulk-writer-s3 — Cassandra Analytics bulk writer, S3 staging transport (requires cassandra-analytics built with JDK 11)
• spark/connector-writer — Standard Spark Cassandra Connector writer
• spark/connector-read-write — Read→transform→write example using Spark Cassandra Connector

Layer Responsibilities

Commands (commands/): Lightweight PicoCLI execution units. Commands are thin wrappers that:

• Parse CLI arguments and options
• Delegate to service layers for actual work
• Handle user-facing output via outputHandler
• Should contain minimal business logic

See commands/CLAUDE.md for detailed command patterns.

Services (services/, providers/): Business logic layer that:

• Interacts with Kubernetes clusters
• Calls cloud provider APIs (AWS EC2, S3, IAM, etc.)
• Manages filesystem operations
• Contains the actual implementation logic

See providers/CLAUDE.md for AWS/SSH/Docker patterns and retry logic.

Server & REPL

Two commands run as long-lived processes instead of the typical run-and-exit pattern:

• Server — starts a hybrid HTTP server with MCP protocol support (Ktor + SSE), REST status endpoints, and background services. See mcp/CLAUDE.md.
• Repl — starts an interactive REPL to reduce typing for repeated commands.

Dependency Injection

Use Koin for dependency injection throughout the codebase:

• Services are registered in Koin modules (AWSModule.kt, ServicesModule.kt, KubernetesModule.kt, etc.)
• Commands receive dependencies via Koin injection
• Tests use BaseKoinTest which provides mocked dependencies

Design Principles

Follow SOLID principles:

• Single Responsibility: Each class has one reason to change
• Open/Closed: Open for extension, closed for modification
• Liskov Substitution: Subtypes must be substitutable for base types
• Interface Segregation: Prefer small, focused interfaces
• Dependency Inversion: Depend on abstractions, not concretions

Testing Approach

Practice reasonable TDD:

• Write tests for non-trivial code with meaningful behavior
• Skip trivial tests on simple configs, small wrappers, and data classes
• Review tests after writing to evaluate test quality
• Focus on testing behavior, not implementation details

No mock-echo tests. Every test must verify real logic. These patterns are banned:

• Tests that only verify a mock was called with the same values that were set up — this proves nothing
• Tests that assert default field values (e.g., assertThat(command.field).isNull()) — the compiler already guarantees defaults
• Tests that verify a method was called but don't assert anything about the outcome or transformation
• Tests where removing the code under test wouldn't cause the test to fail because the mock does all the work

A good test exercises a code path where the system under test makes a decision, transforms data, or could fail in a meaningful way.

See src/test/.../CLAUDE.md for test patterns, BaseKoinTest usage, and custom assertions. See also docs/development/testing.md for comprehensive testing guidelines.

Never mock TemplateService — always use the real instance in tests. It only reads classpath resources and does string substitution with no external side effects.

Quality tools workflow:

# Find test coverage gaps
./gradlew koverHtmlReport
# Report at build/reports/kover/html/index.html

# Format code before committing
./gradlew ktlintFormat

# Find potential code issues
./gradlew detekt

Development Rules

Code Style

• Do not use wildcard imports.
• Always ensure files end with a newline.
• Use AssertJ assertions, not JUnit assertions.
• For serialization, use kotlinx.serialization, not Jackson. Jackson usage in this codebase is deprecated.
• Constants and magic numbers should be stored in com.rustyrazorblade.easydblab.Constants.
• When outputting multiple lines to the console, use a multiline block instead of multiple calls to outputHandler.handleMessage.
• When making changes, use the detekt plugin to determine if there are any code quality regressions.

Architecture

• Use resilience4j for retry logic instead of custom retry loops. See providers/CLAUDE.md for RetryUtil factory methods.
• NEVER build YAML with strings in Kotlin. If you are building a config in memory to execute with K8s, use fabric8. If it's something that needs to be written to disk, use kotlinx.serialization with data classes. ALWAYS prefer typed objects over big strings.
• Write new K8s configuration using fabric8. If there are configuration files, store them as a resource and load them with the TemplateService.
• If you need to modify a K8s configuration, ask if you should migrate it to the new fabric8 based configs in src/main/kotlin/com/rustyrazorblade/easydblab/configuration/.
• Check if the codebase already has a way of accomplishing something before writing new code.
• When migrating code, it is not necessary to maintain backwards compatibility.
• Fail fast is usually preferred.
• Never disable functionality as a solution. If something isn't working, fix the root cause. Adding flags to skip features, making things optional, or suggesting users disable components is not an acceptable solution. When there's a port conflict, assign a different port — don't disable the service. When a feature crashes, fix the crash — don't remove the feature. "Disable it" is never the answer.
• Never add memory limiters to OTel collectors or other observability components. The memory_limiter processor causes data to be refused and dropped under load. The nodes have enough memory — let them use it.
• Configuration problems require configuration fixes. If a service can't connect to a dependency, the fix is to provide the correct endpoint/credentials, not to make the dependency optional.

Testing

• All tests should pass before committing.
• Always add tests to new non-trivial code.
• Tests should extend BaseKoinTest to use Koin DI.
• Always use @tempdir for temporary directories in tests - JUnit handles lifecycle automatically.
• Include testing when planning. Integration tests use TestContainers.
• CRITICAL: Tests must pass, in CI, on my local, and in the devcontainer. It is UNACCEPTABLE to say that tests are only failing in devcontainers and to ignore them.
• When running Gradle tests, run them in a subagent. Never attribute a test containers failure as a pre-existing problem. Raise it to my attention, I may need to restart docker.
• Minimal mocking. Only mock what you must:
  • Mock external services with real side effects (AWS API calls that spin up instances, send emails, etc.)
  • Mock dependencies to simulate specific failure modes you need to test
  • Prefer TestContainers over mocks for anything that interacts with external state (databases, Redis, K8s). TestContainers give more predictable results and increase real code coverage.
  • Do NOT mock classes that have no side effects (e.g., TemplateService, data transformations, pure functions) — use the real implementation.

Workflow & Planning

• ABSOLUTE RULE: Never try to commit without explicit instruction to do so.
• ABSOLUTE RULE: NEVER attribute commit messages to Claude.
• ABSOLUTE RULE: When posting a plan to github, do not include 'Test plan' section.
• When planning, iterate with me. Ask questions. Don't automatically add features I didn't ask for. Ask if I want them first.
• Include updates to the documentation as part of planning.
• When making changes, keep CLAUDE.md and subdirectory CLAUDE.md files up to date if the change affects architecture, file locations, or patterns described in them.
• If this document needs to be updated in order to provide more context for future work, do it.
• When describing directory structure, use normal lists. Don't draw them, I don't find them useful.
• Do not use remote docker-compose commands, use docker compose, the subcommand version.
• Activate kotlin and java for context7.
• Activate the serena MCP server.

Development Setup

Java Version Management (SDKMAN)

The devcontainer uses SDKMAN to manage Java versions:

• Java 21 (Temurin) - Default for the main project
• Java 11 (Temurin) - Required for building cassandra-analytics

SDKMAN is pre-configured in the devcontainer with both versions installed and Java 21 as the default.

Why two versions? The bulk-writer module depends on cassandra-analytics which requires JDK 11 to build. The bin/build-cassandra-analytics script automatically switches to JDK 11 for that build.

Common commands:

# Check current Java version
java -version

# List installed versions
sdk list java

# Temporarily use a different version (current shell only)
sdk use java 11.0.25-tem

# Switch default version permanently
sdk default java 21.0.5-tem

Building Cassandra Analytics Dependencies

The bulk-writer module depends on cassandra-analytics SNAPSHOT artifacts that aren't published to Maven Central. Run bin/dev test and they will be built automatically if missing. To manually build or rebuild:

# Build cassandra-analytics (auto-skips if already built)
bin/dev build-analytics

# Force rebuild
bin/dev build-analytics --force

This clones the cassandra-analytics repo, builds with JDK 11, and publishes artifacts to the local Maven repository (~/.m2/repository).

Pre-commit Hook Installation

Install the ktlint pre-commit hook to automatically check code style before commits:

./gradlew addKtlintCheckGitPreCommitHook

Important: Pre-commit hooks are stored in .git/hooks/ which is local-only and not tracked by Git. Each developer must run this command individually to install the hook on their machine.

The hook automatically runs ktlintCheck on staged Kotlin files before each commit, preventing style violations from being committed.

Configuration Cache

The project uses Gradle configuration cache for faster builds, enabled via gradle.properties:

• org.gradle.configuration-cache=true - Enables configuration caching
• org.gradle.caching=true - Enables build caching

When to clear the cache:

• After modifying .editorconfig or ktlint rules
• After changing Gradle plugins or build scripts
• When encountering unexpected build behavior

# Clear configuration cache
rm -rf .gradle/configuration-cache

# Or clean everything
./gradlew clean

Why this matters: If you modify .editorconfig (which configures ktlint rules), the configuration cache may prevent ktlint from seeing the new rules. This can cause local builds to pass while CI fails with style violations.

Local Validation

Before pushing code, verify it passes all checks:

# Run all checks (matches CI)
./gradlew check

# Run only ktlint check (verify style compliance)
./gradlew ktlintCheck

# Auto-fix ktlint violations (when possible)
./gradlew ktlintFormat

Note: ktlintFormat auto-fixes many violations but can't fix all issues (e.g., line length). Always run ktlintCheck after formatting to catch remaining issues.

Packer Script Testing

Test packer provisioning scripts locally using Docker (no AWS required):

# Test base provisioning scripts
./gradlew testPackerBase

# Test Cassandra provisioning scripts
./gradlew testPackerCassandra

# Run all packer tests
./gradlew testPacker

# Test a specific script
./gradlew testPackerScript -Pscript=cassandra/install/install_cassandra_easy_stress.sh

For more details, see packer/README.md and packer/TESTING.md.

Documentation & Specifications

User documentation is in docs/ (mdbook format). When making user-facing changes, make sure the docs for that feature are up to date.

This project relies on OpenSpec to maintain product specifications. Specs live in openspec/specs/ and are managed via the OpenSpec workflow (skills: openspec-propose, openspec-explore, openspec-apply-change, openspec-archive-change). Specs are the source of truth for product decisions. Before making any change, check relevant specs to ensure the change does not conflict. If a conflict is found, notify the user before proceeding — do not silently override the spec. If a change requires updating a spec, plan the spec update before moving on to implementation.

After running openspec-apply-change, use the simplify skill to review and improve the code quality of the changes.

If I refer to Kubernetes configs or k8 configs, I am referring to these: src/main/resources/com/rustyrazorblade/easydblab/commands/k8s/ by default.

Observability

The cluster runs a full observability stack on the control node. When modifying any part of this stack, keep the related K8s manifests, Kotlin services, and user docs in sync.

All observability K8s resources are built programmatically using Fabric8 manifest builders in configuration/ subpackages. No raw YAML files remain in the core observability stack. See configuration/CLAUDE.md for detailed builder documentation.

Collectors (run on cluster nodes): OTel Collector, Fluent Bit (journald), Grafana Alloy (eBPF profiling), Beyla (L7 RED metrics), ebpf_exporter (TCP/block I/O/VFS), YACE (CloudWatch), MAAC agent (Cassandra metrics)

Storage backends (control node): VictoriaMetrics (metrics, port 8428), VictoriaLogs (logs, port 9428), Tempo (traces, port 3200), Pyroscope (profiles, port 4040)

Grafana (port 3000): Dashboards built via GrafanaManifestBuilder. Dashboard JSON in configuration/grafana/dashboards/ with __KEY__ template substitution. GrafanaDashboard enum is the single source of truth for dashboard metadata.

OTel Instrumentation in Kotlin: The observability/ package provides TelemetryProvider with withSpan(), recordDuration(), incrementCounter(). See docs/reference/opentelemetry.md.

CLI commands: grafana update-config, logs query/backup/import/ls, metrics backup/import/ls

All builder paths are relative to src/main/kotlin/com/rustyrazorblade/easydblab/. Config resources are at corresponding paths under src/main/resources/com/rustyrazorblade/easydblab/.

Subdirectory Documentation

Detailed patterns live in package-level CLAUDE.md files:

• events/CLAUDE.md — Event bus, event hierarchy, adding new events, serialization
• commands/CLAUDE.md — command patterns, available services
• services/CLAUDE.md — SystemD service management
• services/aws/CLAUDE.md — AWS service classes (AMI, EC2, EMR, OpenSearch, S3)
• providers/CLAUDE.md — AWS SDK wrappers, SSH/Docker patterns, retry logic
• configuration/CLAUDE.md — cluster state, templates, K8s manifest builders, observability stack details
• mcp/CLAUDE.md — Server architecture (MCP, REST, background services)
• kubernetes/CLAUDE.md — K8s client patterns
• src/test/.../CLAUDE.md — test infrastructure

[claude]

User Documentation (docs/)

This directory contains the user-facing documentation for easy-db-lab, built with mdbook.

Purpose

These docs are for end users of the tool — people setting up clusters, running stress tests, and using the observability stack. This is NOT developer/architecture documentation (that lives in CLAUDE.md files throughout the source tree).

Organization

docs/
├── CLAUDE.md              # This file
├── SUMMARY.md             # Table of contents — mdbook requires this
├── book.toml              # mdbook configuration
├── index.md               # Landing page
├── getting-started/       # Installation, prerequisites, initial setup
├── user-guide/            # Feature documentation (the bulk of the docs)
├── reference/             # Ports, commands, infrastructure details
├── development/           # Developer guides (building, testing, publishing)
├── integrations/          # External tool integrations (server)
└── plans/                 # Implementation plans (not published)

Key Rules

• SUMMARY.md is the table of contents. Every new page MUST be added here or it won't appear in the built site. mdbook uses this file to generate navigation.
• Keep docs in sync with code changes. When a user-facing feature changes (new command, new dashboard, new config option, port change), update the relevant doc page.
• Write for users, not developers. Explain what things do and how to use them. Don't explain internal implementation details — that belongs in source-level CLAUDE.md files.
• Use mdbook-admonish for callouts. The project uses the admonish preprocessor for warning/info/tip blocks.

When to Update

Update docs when:

• Adding or removing a CLI command → update reference/commands.md
• Changing a port number → update reference/ports.md
• Adding a new observability component → update user-guide/monitoring.md or create a new page
• Changing profiling behavior → update user-guide/profiling.md
• Adding a new datasource or dashboard → update user-guide/monitoring.md
• Changing cluster setup flow → update user-guide/cluster-setup.md and user-guide/tutorial.md

Adding a New Page

1. Create the .md file in the appropriate subdirectory
2. Add an entry to SUMMARY.md in the correct section
3. Use other pages as a style reference

Building Locally

# Install mdbook if needed
cargo install mdbook mdbook-admonish

# Build and serve
cd docs
mdbook serve

The site builds to ../site/ (per book.toml).

[rustyrazorblade]

@claude i don't think the disks are known ahead of time right now. Is there a way we can know this deterministically? Either by providing the devices or by inspection?

[claude]

Claude finished @rustyrazorblade's task in 1m 19s —— View job

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• Analyze disk device discovery in the bcache implementation

Disk Device Discovery Analysis

You're right that device paths aren't known ahead of time in a reliable way. Here's the breakdown of both devices involved:

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EBS backing device (__EBS_DEVICE__)

Currently hardcoded as Constants.EBS.DEFAULT_DEVICE_NAME = "/dev/xvdf" in Init.kt:315. This is deterministic on Nitro-based instances because AWS creates a stable udev symlink /dev/xvdf → /dev/nvme* when you attach the volume as /dev/xvdf. However, Init.kt ignores EBSConfig.deviceName (which also defaults to /dev/xvdf) and uses the constant directly — so if the EBS device name were ever changed via EBSConfig, the script wouldn't reflect it.

This part is fine in practice but should pull from EBSConfig.deviceName instead of the constant.

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NVMe instance store (cache device)

This is the fragile part. The script in setup_instance.sh:59-66 iterates nvme0n1, nvme1n1 and picks the first one with no children (lsblk has no children = unpartitioned). On Nitro instances, both EBS volumes and instance store volumes appear as NVMe devices — they're indistinguishable by device name alone. The "no children" check is a heuristic proxy, not deterministic identity.

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Deterministic Options

Option A — nvme id-ctrl inspection (recommended)

The nvme CLI tool reports a model field that definitively identifies the device type:

nvme id-ctrl -v /dev/nvme0n1 | grep -i model

• Instance store: Amazon EC2 NVMe Instance Storage
• EBS volume: Amazon Elastic Block Store

This works fully offline (no metadata service needed) and is the approach AWS documentation recommends for distinguishing NVMe device types. The shell script could iterate all /dev/nvme*n1 devices and pick the one matching the instance store model.

Option B — EC2 instance metadata API

Query http://169.254.169.254/latest/meta-data/block-device-mapping/ to get the device mapping (e.g., ephemeral0 → /dev/sdb). This requires the metadata service to be reachable, but is authoritative.

Option C — Explicit user-provided device paths

Add --bcache.cache-device (instance store) and optionally --bcache.backing-device (EBS) flags. Users who need exact control specify them; the script falls back to discovery otherwise. This is the most flexible but adds CLI surface area.

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Recommendation

Option A is the right fix for the shell script. Replace the "first unpartitioned NVMe" heuristic with an nvme id-ctrl loop that identifies instance store vs EBS by model string. The EBS device path should come from EBSConfig.deviceName in Init.kt rather than the constant.

Do you want me to implement Option A (or a combination with Option C as an escape hatch)?

[rustyrazorblade]

What about multiple disks?

[rustyrazorblade]

@claude what about multiple disks?

[rustyrazorblade]

@claude Option a, but still need to address the case where there are 2 ebs volumes or 2 local disks.

[claude]

Claude finished @rustyrazorblade's task in 6m 37s —— View job

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Implementing multi-disk bcache support with nvme id-ctrl detection

• Read existing implementation files
• Design multi-disk handling approach
• Update install_bcache.sh with nvme-cli
• Update setup_instance.sh with nvme id-ctrl detection and multi-disk support
• Update Init.kt — remove EBS_DEVICE injection
• Update Constants.kt — remove EBS object
• Update InitTest.kt
• Commit and push changes

What changed

Device discovery (setup_instance.sh)

Replaced the fragile "first unpartitioned NVMe" heuristic with nvme id-ctrl model string inspection. On Nitro EC2 instances both instance store and EBS appear as NVMe devices — the model field is the only reliable way to tell them apart:

• "Amazon EC2 NVMe Instance Storage" → instance store (bcache cache device)
• "Amazon Elastic Block Store" → EBS (bcache backing device)

Multiple instance store disks

All discovered instance store NVMe devices are passed to make-bcache -C together, creating a single bcache cache set across all of them. This is native bcache multi-device support — no RAID required.

Multiple EBS volumes

The first EBS NVMe device is used as the bcache backing device. If more are found, a log message identifies which one was selected and lists the others.

Non-bcache disk selection

Uses the same discovery: prefers instance store NVMe, falls back to EBS NVMe, then xvdb/xvdc for non-Nitro instances with legacy device names.

__EBS_DEVICE__ removed

The EBS device is now discovered at runtime via nvme id-ctrl, so the template injection is gone. Constants.EBS.DEFAULT_DEVICE_NAME and its references in Init.kt and InitTest.kt are removed.

nvme-cli added to install_bcache.sh

nvme id-ctrl requires the nvme-cli package, which is now installed alongside bcache-tools and linux-modules-extra-aws.
| Branch

[claude]

PR Review: bcache Support

Overall this is a solid, well-structured feature addition. The design is thoughtful (TemplateService injection, fail-fast validation, NVMe device discovery via nvme id-ctrl), the spec coverage is thorough, and the test cases are meaningful. A few issues to address before merging:

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Blocking: CI quality check is failing

The quality job (ktlint/detekt) is failing. Per project guidelines, all checks must pass before merging. Run:

./gradlew ktlintFormat && ./gradlew ktlintCheck
./gradlew detekt

Then clear the config cache if needed (rm -rf .gradle/configuration-cache) since .editorconfig changes can cause cache stale issues.

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Stale task in tasks.md

Task 3.2 specifies substituting __EBS_DEVICE__ with EBSConfig.deviceName, but this placeholder doesn't exist in setup_instance.sh — the implementation correctly uses nvme id-ctrl model-string discovery instead. The tasks entry is superseded by the design decision documented in design.md. Mark it as done (with a note) or remove it to keep the spec consistent.

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Test hygiene: missing @TempDir in InitTest

The InitTest writes setup_instance.sh to the working directory (not a @TempDir). The @AfterEach cleanup is fragile — if a test fails before cleanup, the file lingers and could affect other tests. Per project conventions, use @TempDir for all temp file operations:

@TempDir
lateinit var tempDir: Path

// then pass tempDir to extractSetupScript()

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Low-signal success tests in InstanceSpecFactoryTest

should succeed when bcache enabled with EBS and instance store in writethrough mode and the writeback variant both just assert specs.hasSize(3). Since InstanceSpecFactory doesn't differentiate by mode (by design), these two tests are functionally identical and neither verifies mode-specific behavior. Consider collapsing them into a single parameterized test or replacing one with a test that actually verifies something distinct about the two modes at a higher level (e.g., in ClusterState or Init).

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Minor: unchecked task 4.2

Task 4.2 ("Verify testPackerBase still passes with the added packages") is explicitly unchecked. The test-bcache docker-compose service was added and the Test Changed Scripts CI job passes, but confirm the full base provisioning sequence test passes before merging.

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Pre-existing issue (not blocking)

setup_instance.sh still sets cassandra soft/hard limits in limits.conf (lines ~26–31). Not introduced by this PR, but inconsistent with the project guideline against Cassandra-specific naming in generic contexts. Worth a follow-up ticket.

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What's done well

• Fail-fast validation in InstanceSpecFactory with clear error messages is exactly right.
• NVMe device classification via nvme id-ctrl is more robust than the old hardcoded device list.
• Template substitution approach via TemplateService is clean and consistent with project patterns.
• The BcacheOptions tests in InitTest meaningfully verify substitution correctness and absence of unresolved placeholders — good test quality.
• Idempotency handling in install_bcache.sh (skip if already installed) and setup_instance.sh (wipe superblocks before re-registration) is solid.
• Documentation is comprehensive with appropriate caveats about non-persistence across reboots.