Implement leader election to ensure only one APRS-IS connection across
multiple Kubernetes replicas. This prevents duplicate packet processing
and respects APRS-IS usage policies.
Key changes:
- Add leader election using :global registry
- Create connection manager for dynamic APRS-IS management
- Implement packet distribution from leader to all nodes
- Add Kubernetes headless service for node discovery
- Configure DNS-based clustering with libcluster
- Update deployment to support 3 replicas with clustering
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Add nil check before canceling timer in PacketConsumer to prevent errors
when timer reference doesn't exist (fixes test failures)
- Simplify packet counter reset migration by removing unsupported event
triggers, keeping only manual reset function
- All tests now passing
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Fixed "ParseError does not implement the Access behaviour" error that
occurred during packet batch insert when packets contained ParseError
structs in their data_extended field.
Added special handling for Aprs.Types.ParseError structs in the
struct_to_map function to convert them to simple maps with their
error_code and message fields, preventing the Access behavior error
when the struct is accessed during processing.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
The memory monitoring was incorrectly using total VM memory instead of
per-process memory, causing false positives whenever any process in the
system allocated memory.
Changes:
- Changed memory monitoring to per-process instead of total VM memory
- Reduced thresholds to reasonable per-process values (50MB diff, 100MB total)
- Increased minor GC trigger from 100 to 1000 packets to prevent GC after
every normal batch
This prevents detecting memory changes from other processes and eliminates
the constant GC warnings while still maintaining proper memory management.
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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>
Increased memory thresholds from 10MB/20MB to 500MB/1GB since the server
has 15GB available memory. This prevents constant GC warnings while
maintaining memory safety.
Configured VM garbage collection settings in vm.args.eex:
- Enabled concurrent ports/sockets limit (+Q 65536)
- Set heap sizes and GC parameters optimized for better performance
- Added scheduler and binary heap settings
These changes will reduce unnecessary GC overhead and improve overall
application 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>
This commit introduces several major performance improvements and adds
robust error handling for malformed HTTP requests:
Performance Optimizations:
- Add database migration with BRIN indexes for time-series data and partial
indexes for recent queries, significantly improving query performance
- Create global StreamingPacketsPubSub system for real-time packet distribution
with geographic bounds filtering using ETS for fast lookups
- Refactor PacketConsumer to use Stream module for memory-efficient processing,
preventing memory accumulation during batch operations
- Implement dedicated BroadcastTaskSupervisor pool for async broadcast operations,
preventing GenServer blocking on I/O
- Increase database connection pool from 25 to 45 (production) and 15 to 30 (dev)
for better concurrency support
Error Handling:
- Add SentryFilter to prevent Bandit.HTTPError from missing Host headers from
cluttering Sentry (common with bots/scanners)
- Configure custom 400 Bad Request error handling
- Filter out common bot/scanner paths from error reporting
All changes include comprehensive test coverage following TDD practices.
🤖 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>
- Fixed InsertOptimizer returning map instead of keyword list for Ecto
- Increased batch size ranges to handle high load (100-800 packets)
- Improved consumer responsiveness:
- Reduced batch timeout from 1000ms to 500ms
- Process batches at 80% capacity for better throughput
- Reduced adjustment interval from 10s to 5s
- Added comprehensive logging for debugging buffer status
- Created integration tests for packet pipeline
- Coordinated batch sizing between SystemMonitor and InsertOptimizer
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
