Floci Dashboard

A small Django UI for inspecting, testing, and learning against a local Floci AWS-compatible environment. The dashboard uses an AWS-adjacent console style and shows Floci health, endpoint/profile/identity details, selectable service cards, resource counts, service-specific inventory pages, interactive workbenches, and one-click local AWS workflow labs.

Quickstart

These steps launch Floci and the dashboard together from this repository. They are written for macOS. The dashboard will likely work fine on Windows as well, but Windows has not been tested yet.

Install Docker Desktop if you have not already.

Make sure Docker Desktop is running. You will also need git available in your shell.

Paste the following commands into your terminal one at a time, pressing Enter after each one.

Clone the dashboard repository:

git clone https://github.com/returnvalue/flocidashboard.git

Change into the dashboard directory:

cd flocidashboard

Start Floci and the dashboard:

docker compose up -d

Open http://127.0.0.1:8000 in your browser.

The repo-owned docker-compose.yml starts:

• floci on http://127.0.0.1:4566
• dashboard on http://127.0.0.1:8000
• a shared floci_default Docker network for Floci-spawned containers
• persistent Docker volumes for Floci state and the dashboard SQLite session database

Follow logs while the services start:

docker compose logs -f

Stop everything:

docker compose down

Stop everything and remove local Floci/dashboard state:

docker compose down -v

Copy .env.example to .env before starting if you want to change exposed ports or local defaults.

Local Python Development

Docker Compose is the primary path. You can still run Django directly on your host when you want the fastest edit/test loop against an already running Floci container.

Create the virtual environment:

python3 -m venv .venv

Activate the virtual environment:

source .venv/bin/activate

Upgrade pip inside the virtual environment:

python3 -m pip install --upgrade pip

Install the dashboard requirements:

pip3 install -r requirements.txt

Set the Floci endpoint URL:

export AWS_ENDPOINT_URL=http://localhost:4566

Set the default AWS region:

export AWS_DEFAULT_REGION=us-east-1

Set the local AWS access key:

export AWS_ACCESS_KEY_ID=test

Set the local AWS secret key:

export AWS_SECRET_ACCESS_KEY=test

Or create and use your own AWS profile for Floci before running the dashboard:

Set your Floci AWS profile:

export AWS_PROFILE=floci-admin

Set the default AWS region:

export AWS_DEFAULT_REGION=us-east-1

Set the Floci endpoint URL:

export AWS_ENDPOINT_URL=http://localhost:4566

FLOCI_AWS_ENDPOINT_URL and FLOCI_AWS_REGION are also supported if you prefer Floci-specific names. When no explicit profile or credentials are visible to Django, the dashboard falls back to local test/test credentials so a fresh Floci install can still show service inventory.

Start the Django dev server:

python3 manage.py runserver 127.0.0.1:8000

When Django runs on your host, use http://localhost:4566. When Django runs inside Compose, the dashboard container uses http://floci:4566.

What It Shows

• Local Floci health and version diagnostics
• Environment diagnostics for AWS endpoint, region, profile, credential source, caller identity, S3 authorization mode, and local-endpoint warnings
• Clickable service cards for 65 supported local services, with a top-24 default home view, persisted home-page service filtering, and a Tracked Resources view that shows only services with discovered resources
• Service Matrix coverage page showing registry maturity (58 interactive workbenches), API paths, shared console status, action counts, tags, and linked service pages
• Labs directory at /labs/ showing 17 services with 63 active workflow labs, 349 runnable step counts, and direct links
• Multi-SDK code generation for every lab step: toggle instantly between AWS CLI, Python boto3, and Terraform HCL, with user preference persistence via localStorage
• Automated "Run All Steps" (Play Through) runner with live step-by-step progress tracking, auto-scrolling, speed regulation, and contextual explanations
• Activity page at /activity/ with browser-local recent API Gateway requests, EventBridge events, Lambda invokes, and SQS sends/receives, plus links back to activity-enabled workbenches for safe replay or prefill
• AWS CLI Console at /console/ for running AWS-only CLI commands against the active local Floci endpoint, with endpoint injection, JSON parsing, a draggable curated command palette, command history, and destructive-command confirmation
• AWS Cloudscape Design System alignment with semantic status indicators (🟢 Positive, 🟡 Warning, 🔴 Negative, 🔵 Info, ⚪ Inactive), 2–4 column key-value attribute grids, and crisp container cards
• 100% Pedagogical Coverage: Structured, educational About Floci <Service> accordions across all 65 services
• Local AWS workflow labs for IAM, S3, KMS, SSM Parameter Store, Secrets Manager, Cognito, SQS, SNS, EventBridge Scheduler, DynamoDB, Lambda, API Gateway, EventBridge, Step Functions, CloudWatch, EC2 compute/networking, and CloudFormation, with exact AWS CLI commands, approved one-click execution, live-state verification, reset actions, next-batch recommendations, and breadcrumb navigation
• Interactive workbenches for 58 services: S3, IAM, EC2, SQS, SNS, Lambda, DynamoDB, CloudWatch, Step Functions, EventBridge, EventBridge Pipes, EventBridge Scheduler, API Gateway, AppSync, Kinesis, KMS, Secrets Manager, SSM Parameter Store, CloudFormation, Cognito, AWS Config, RDS, Auto Scaling, ELB v2, CloudFront, AWS Cloud Map, Route 53, ACM, ECS, ECR, EKS, ElastiCache, OpenSearch, Athena, Backup, Firehose, Glue, Kafka, Neptune, SES, Transfer Family, Textract, Transcribe, CodeDeploy, CodeBuild, Bedrock Runtime, AppConfig, Resource Groups Tagging, Amazon DocumentDB, MemoryDB, Amazon MQ, WAF v2, IoT Core, S3 Vectors, Cost Explorer, and AWS Price List & Calculator
• IAM-focused identity tooling with user, group, role, managed policy, inline policy, access key, role trust, instance profile, cleanup, policy simulation, session identity switching, assumed-role credential, and tutorial/lab workflows
• Interactive Cost & Pricing Sandbox: Local Cost Explorer with stacked daily usage bar charts, cost forecast metrics, and anomaly alerts, alongside a multi-service AWS Pricing Calculator Simulator (EC2, S3, Lambda, RDS)
• Deepened EC2 guided local compute workflows: guest IMDS socket querying (169.254.169.254), UserData script verification, IAM instance role assume-role validation, security-group-published web servers, broken-route diagnosis & repair, private S3 gateway endpoints, and SSM RunCommand agent dispatch
• First-class Lambda, ECS, EKS, and ECR workbenches covering function lifecycle, local k3s cluster resources, OCI repositories, image manifests, stored policies, and Docker push/pull workflows
• Release-aware service notes refreshed through Floci 1.5.32, including optional S3 authorization enforcement, default SSE-S3 behavior, Lambda failure destinations, Cognito session revocation, SES contact CRUD, and Step Functions JSONata variables
• Loading state with the Floci cloud image while service data is fetched

Local AWS Workflow Labs

The Labs directory at /labs/ lists every service with curated labs. Individual service pages also link to their own lab batches when labs are available.

Labs show the command shape across AWS CLI, Python boto3, and Terraform. Each Run button invokes a registered boto3-backed action, displays the response, and independently verifies the result against live Floci state. Users can also click Run All Steps to play through multi-step workflows automatically with paced scrolling and live descriptions. Reset removes only the resources owned by that lab. When the final lab in a service batch is complete, the lab page recommends the next batch in the recommended cloud engineering learning order: IAM $\rightarrow$ S3 $\rightarrow$ KMS $\rightarrow$ SSM $\rightarrow$ Secrets Manager $\rightarrow$ Cognito $\rightarrow$ SQS $\rightarrow$ SNS $\rightarrow$ Scheduler $\rightarrow$ DynamoDB $\rightarrow$ Lambda $\rightarrow$ API Gateway $\rightarrow$ EventBridge $\rightarrow$ Step Functions $\rightarrow$ CloudWatch $\rightarrow$ EC2 $\rightarrow$ CloudFormation.

The curriculum includes 63 labs across 17 services (349 total steps):

• IAM (11 labs): admin bootstrap, users, policies, access keys, groups, roles, STS session policies, instance profiles, switched dashboard identities, and permission-enforcement checks.
• S3 (12 labs): buckets, objects, prefixes, metadata, tags, versioning, presigned URLs, security, encryption, lifecycle retention, CORS, S3-to-SQS notifications, and multipart uploads.
• KMS (1 lab): key lifecycle, alias creation, envelope encryption, and decryption round trips.
• SSM (1 lab): hierarchical Parameter Store application configuration and secure string storage.
• Secrets Manager (1 lab): secret creation, runtime retrieval, and secret rotation updates.
• Cognito (2 labs): User Pools, App Clients, authentication flows, user groups, and custom attributes.
• SQS (9 labs): queue inspection, message lifecycle, visibility timeouts, delayed delivery, batch operations, dead-letter queues, managed redrive, FIFO ordering, duplicate suppression, and purge.
• SNS (2 labs): SNS-to-SQS fan-out, resource policies, raw delivery, and subscription filter policies.
• Scheduler (1 lab): scheduled SQS delivery through scoped IAM execution roles.
• DynamoDB (2 labs): table schema definitions, item CRUD, Partition/Sort keys, query/scan filters, and Lambda write integration.
• Lambda (3 labs): function creation, synchronous/asynchronous invocation, SSM/Secrets reads, SQS event source mappings, and CloudWatch log tailing.
• API Gateway (1 lab): HTTP API route creation, integrations, and live request proxying to Lambda.
• EventBridge (1 lab): application-spine capstone joining API Gateway, Lambda, a custom event bus, transformed SQS targets, notification handlers, and failure simulations.
• Step Functions (2 labs): State Machine Choice branching workflows and Parallel execution branches.
• CloudWatch (2 labs): custom metric filters, CloudWatch Alarms, and Log Group streams.
• EC2 (11 labs): public/private VPC routing, stateful security groups, network ACLs, VPC endpoints, guest IMDS inspection, UserData validation, IAM instance roles, web server SG routing, broken route repair, private S3 gateway endpoints, and SSM RunCommand dispatch.
• CloudFormation (1 lab): template validation, change set creation, stack provisioning, and resource lifecycle management.

The EventBridge capstone also includes a live, dependency-free SVG resource graph. It lays serverless resources out in deterministic semantic columns, deep-links nodes to their workbenches, exposes configuration evidence for every relationship, and distinguishes healthy, disabled, broken, unverified, and locally unsupported states.

Lab definitions and implementation notes live in buildinglabs.md.

Configuration

Host-development defaults live in flocidashboard/settings.py:

• FLOCI_AWS_ENDPOINT_URL: http://localhost:4566
• FLOCI_AWS_REGION: us-east-1
• FLOCI_AWS_PROFILE: floci-admin

Environment variables override those defaults. If floci-admin is not configured locally, the dashboard uses local test/test credentials instead of failing the homepage with missing-credential cards.

Set FLOCI_SERVICES_S3_ENFORCE_AUTH=true to make Floci enforce S3 ACL and bucket-policy public/private reads and reject unknown signed access keys. The Compose default remains false for compatibility; Environment Details reports whether enforcement is active.

The Docker Compose quickstart overrides the endpoint to http://floci:4566 inside the dashboard container and uses local test/test credentials by default. Compose defaults can be overridden in .env; see .env.example for the supported ports, credentials, and Floci runtime toggles.

Quick Check

docker compose exec dashboard python manage.py check

Then refresh the browser. Service cards should appear once Floci responds.

For host Python development, run the same check from your activated virtual environment:

python3 manage.py check

Testing & Verification

Run the full Django test suite inside Docker:

docker compose exec -T dashboard python manage.py test

Or on your local host virtual environment:

python3 manage.py test

Contributing

For guidelines on adding new service workbenches, labs, or custom UI components, please see CONTRIBUTING.md.