Move packet_retention_days configuration from config.exs (compile-time)
to runtime.exs so it properly reads the PACKET_RETENTION_DAYS environment
variable at runtime instead of baking in the default value during build.
This fixes the issue where the app was using 7 days retention despite
PACKET_RETENTION_DAYS being set to 1 in the deployment, causing disk
to fill up with 54GB of old partition data.
Convert app.js, info_map.js, error_boundary.js, and time_ago_hook.js
to TypeScript with proper typing for Phoenix hooks, Leaflet, DOM
interactions, and timer management. Update esbuild hex package to
~> 0.10 and binary to 0.25.4. Entry point changed to app.ts.
Convert the packets table to a time-partitioned table with daily
partitions (PARTITION BY RANGE on received_at). This replaces the
expensive CTE-based batch DELETE cleanup with instant DROP TABLE
partition drops — no dead tuples, no WAL pressure, no VACUUM needed.
- Add PartitionManager GenServer to create/drop daily partitions
- Simplify PacketCleanupWorker to delegate to PartitionManager
- Replace gridsquare/geocalc deps with local Maidenhead module
- Remove gettext_pseudolocalize dependency
- Fix Decimal comparison in packet consumer test
When the PacketProducer buffer crosses 80% capacity, signal Aprsme.Is
to switch its TCP socket to passive mode, leveraging TCP flow control
to slow APRS-IS intake. Resume active mode when buffer drains below 30%.
A 30-second safety valve timer auto-resumes if backpressure gets stuck.
Disconnect/reconnect/terminate paths all clear backpressure state.
- Remove Exq dependency from mix.exs and application config
- Remove all Exq configuration from config files (config.exs, dev.exs, runtime.exs, test.exs)
- Update CleanupScheduler to run cleanup tasks directly using Task.start instead of queuing jobs
- Update PacketCleanupWorker documentation to remove Exq references
- Cleanup functionality preserved but now runs in supervised Tasks instead of job queue
This resolves the Redis connection error on startup by eliminating the dependency on external job queues.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Combine Chart.js and date adapter into single bundle to ensure proper loading order
- Add validation to skip chart rendering when insufficient weather data (< 2 points)
- Update vendor loader to not load date adapter separately
- Prevents date adapter errors when weather stations have limited data
- Fix zero coordinate handling to distinguish between invalid coordinates and valid 0.0 (equator/prime meridian)
- Add to_float_safe() function that preserves nil for proper coordinate validation
- Add comprehensive coordinate validation with descriptive logging in JavaScript
- Make position change threshold configurable via application config (default: 0.001°)
- Add extensive test coverage for edge cases including nil coordinates and equator crossing
- Improve robustness for real-world APRS coordinate edge cases
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Move Redis connection settings to runtime.exs only
- Remove localhost:6379 hardcoded values that were overriding runtime config
- Keep only non-environment-dependent Exq settings in compile-time config
- Fixes Exq trying to connect to localhost instead of Kubernetes Redis service
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Replace Oban dependency with Exq for Redis-based background jobs
- Update PacketCleanupWorker to use Exq's perform/1 signature
- Add CleanupScheduler GenServer for periodic job scheduling
- Configure Exq with Redis connection and queue settings
- Update tests to work with Exq job format
- Maintain 6-hour packet cleanup schedule functionality
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Download external libraries locally to reduce CDN dependencies
- Create combined vendor bundles for JavaScript and CSS
- Replace CDN script tags with local bundles in layout template
- Add build scripts for vendor bundle creation and optimization
- Configure esbuild to process vendor bundles separately
- Total bundle size: ~512KB JS + 17KB CSS (optimized)
Benefits:
- Reduced external requests and CDN dependencies
- Better caching control and reliability
- Eliminated CORS and SRI integrity issues
- Faster page loads with bundled resources
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Fixed the esbuild errors during Docker build where npm packages couldn't
be resolved. The issue was caused by node_modules being excluded from
the Docker build context in .dockerignore.
Implemented a proper vendor bundle strategy following Phoenix 1.7+ patterns:
- Created vendor.js that bundles all npm dependencies (Leaflet, Chart.js,
topbar) and their CSS files into a single pre-built bundle
- Added vendor esbuild profile in config.exs with proper CSS/image loaders
- Updated mix.exs to build vendor bundle before app bundle in assets.deploy
- Modified JavaScript imports to use globally loaded libraries from vendor
bundle instead of importing from node_modules
- Added vendor.js script tag to root.html.heex before app.js
This approach avoids Docker build failures by pre-bundling all vendor
dependencies, eliminating the need for node_modules during production builds.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Moved CSS imports from Tailwind config to JavaScript to let ESBuild handle them.
This fixes the Docker build error where Tailwind couldn't resolve node_modules paths.
- Removed CSS @import statements from app.css
- Added CSS imports to map.ts where Leaflet is used
- Configured ESBuild to handle CSS and image files
- Added missing topbar package to package.json
- Updated both dev and prod ESBuild configs
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
The Docker build was failing because the Chart.js date adapter was trying
to require("chart.js") but esbuild couldn't resolve it since Chart.js is
loaded as a UMD file, not a CommonJS module.
Added --external:chart.js to the vendor esbuild configuration to tell
esbuild not to try bundling chart.js when it encounters require("chart.js")
in the date adapter. This is correct because Chart.js is already loaded
globally from the UMD file.
This fixes the "Could not resolve 'chart.js'" error during production builds.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
This change eliminates all external CDN dependencies by bundling JavaScript
libraries locally using esbuild. All vendor files are now served from the
application's own assets, improving reliability and privacy.
Changes:
- Created assets/js/vendor.js to bundle all external libraries
- Added vendor bundle configuration to esbuild in config files
- Updated all templates to use local vendor.js instead of CDN scripts
- Created download-vendor-files.sh script to fetch vendor libraries
- Added vendor files to .gitignore (they're downloaded during setup)
- Updated CSS imports to include vendor stylesheets
- Added vendor build step to assets.deploy mix task
Bundled libraries:
- Leaflet 1.9.4 (mapping library)
- Leaflet.heat 0.2.0 (heatmap plugin)
- Leaflet.markercluster 1.5.3 (marker clustering)
- OverlappingMarkerSpiderfier 0.2.6 (overlapping marker handling)
- Chart.js 4.5.0 (charting library)
- chartjs-adapter-date-fns 3.0.0 (date adapter for Chart.js)
All functionality tested and working correctly with local bundles.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Reduced batch processing parameters to prevent excessive GC:
- Reduced batch_size from 500 to 100 packets
- Adjusted batch_timeout from 2000ms to 1000ms for faster processing
- Reduced max_demand from 750 to 300 to match smaller batches
- Updated hardcoded fallback from 500 to 100 in packet_consumer.ex
- Changed minor GC trigger from 500 to 100 packets to match batch size
These smaller batch sizes were proven to work well in production and
should significantly reduce the frequency of garbage collection while
maintaining good performance.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Create PacketConsumerPool to run 3 parallel consumers (configurable)
- Increase max_demand from 250 to 750 total (250 per consumer)
- Fix timer management to properly cancel/restart on batch processing
- Configure proper GenStage subscriptions with backpressure control
- Allow unnamed consumers for pool usage
This 3x increase in processing capacity prevents the "Packet buffer full"
warnings by ensuring consumers can keep up with incoming packet rate.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Restored original PacketConsumer implementation from before optimizations
- Reverted to fixed batch size of 50 packets (original value)
- Removed SystemMonitor and InsertOptimizer from application startup
- Restored original config with buffer size 1000 and batch timeout 1000ms
- Removed all dynamic batch sizing and optimization logic
The recent performance optimizations were causing packet buffer overflows
because the dynamic batch sizing was actually slowing down processing.
Reverting to the simpler, working implementation that processes packets
consistently without buffer overflows.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Increased packet buffer size from 1,000 to 10,000 to handle traffic spikes
- Removed InsertOptimizer dynamic batch sizing that was slowing processing
- Reverted to fixed batch size of 200 for consistent performance
- Simplified insert options to use static configuration
- Added telemetry metrics for buffer overflow and utilization monitoring
- Fixed unused variable warning in packet_consumer.ex
The root cause was the recent performance optimizations that introduced
dynamic batch sizing, which actually degraded performance and caused
the producer buffer to overflow when the consumer couldn't keep up.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
