This dashboard provides comprehensive monitoring of AWS ElastiCache Redis instances using CloudWatch metrics. It offers detailed visibility into both host-level metrics (CPU, memory, network) and Redis engine-specific metrics (cache hits, evictions, replication lag) to help optimize cache performance and troubleshoot issues.
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What This Dashboard Monitors
This dashboard tracks essential AWS ElastiCache Redis metrics to help you:
- Performance Monitoring: Track CPU utilization, memory usage, and cache hit rates
- Capacity Planning: Monitor memory usage percentages and capacity utilization
- Network Analysis: Analyze network traffic patterns and bandwidth utilization
- Cache Efficiency: Track cache hit rates, evictions, and memory fragmentation
- Replication Health: Monitor replication lag and connection metrics
- Resource Optimization: Identify performance bottlenecks and optimize configurations
Metrics Included
CPU and Engine Performance
CPU Utilization
- Description: Host-level CPU utilization percentage for the ElastiCache node
- Use Case: Monitor overall system performance and identify CPU bottlenecks
- Grouping: By cache cluster ID for multi-cluster monitoring
Engine CPU Utilization
- Description: Redis engine-specific CPU utilization percentage
- Use Case: Track Redis process CPU consumption separate from system overhead
- Grouping: By cache cluster ID to compare engine performance across clusters
Memory Management
Database Memory Usage Percentage
- Description: Percentage of allocated memory currently used by Redis
- Use Case: Monitor memory consumption and plan for capacity needs
- Critical Thresholds: High values (>80%) may indicate need for scaling
Database Capacity Usage Percentage
- Description: Percentage of total available memory capacity in use
- Use Case: Track capacity utilization for scaling decisions
- Planning: Essential for understanding growth patterns
Memory Fragmentation Ratio
- Description: Ratio of memory allocated by Redis vs. memory used by the OS
- Use Case: Identify memory fragmentation issues that can impact performance
- Optimization: Values significantly above 1.0 may indicate fragmentation
Freeable Memory
- Description: Amount of memory available for allocation (in bytes)
- Use Case: Monitor available memory before hitting limits
- Unit: Displayed in decimal bytes for precise capacity tracking
Cache Performance
Cache Hit Rate
- Description: Number of successful cache lookups (cache hits)
- Use Case: Measure cache effectiveness and application performance
- Optimization: Higher hit rates indicate better cache utilization
Evictions
- Description: Number of items evicted from cache due to memory pressure
- Use Case: Monitor memory pressure and optimize cache policies
- Troubleshooting: High eviction rates may indicate insufficient memory
Network Activity
Network Bytes In
- Description: Number of bytes received by the ElastiCache node
- Use Case: Monitor inbound network traffic and bandwidth utilization
- Unit: Displayed in decimal bytes for traffic analysis
Network Bytes Out
- Description: Number of bytes sent from the ElastiCache node
- Use Case: Track outbound network traffic and response data volume
- Capacity Planning: Essential for understanding network requirements
Connection and System Metrics
Current Connections
- Description: Number of active client connections to the Redis instance
- Use Case: Monitor connection usage and identify connection leaks
- Capacity Planning: Track connection patterns for scaling decisions
Swap Usage
- Description: Amount of swap space used by the ElastiCache node
- Use Case: Identify memory pressure that forces swapping
- Performance Impact: High swap usage can significantly degrade performance
Replication Lag
- Description: Maximum lag time between master and replica nodes (in seconds)
- Use Case: Monitor replication health in Redis clusters
- Reliability: Essential for ensuring data consistency across replicas
Dashboard Variables
This dashboard includes filtering capabilities:
- cache_cluster_id: Filter metrics by specific ElastiCache cluster ID
- Multi-select: Monitor multiple clusters simultaneously
- All option: View aggregate metrics across all clusters
- Dynamic: Automatically populates from available cluster IDs
Monitoring Best Practices
Performance Optimization
- Monitor Cache Hit Rate to ensure efficient cache utilization
- Track CPU Utilization metrics to identify processing bottlenecks
- Watch Memory Fragmentation Ratio for memory efficiency
Capacity Planning
- Use Database Memory Usage Percentage for scaling decisions
- Monitor Freeable Memory to prevent out-of-memory conditions
- Track Network Bytes for bandwidth planning
Troubleshooting
- High Evictions may indicate insufficient memory allocation
- Elevated Swap Usage suggests memory pressure
- Increased Replication Lag indicates replication issues
Alerting Recommendations
- CPU Utilization > 80% - Consider scaling or optimization
- Memory Usage > 85% - Plan for memory scaling
- Cache Hit Rate < 90% - Review cache strategy
- Replication Lag > 5 seconds - Investigate replication health
