How To Build AI Systems That Support Real Time And Batch Processing Without Conflicts Or Performance Tradeoffs In Complex Workflows
· Avery NXR
AI systems often need to handle two very different types of workloads:
Real-time interactions Batch processing
Each has unique requirements.
Balancing both within a single system is challenging.
Understanding The Two Modes
Real-Time Processing
Immediate response required User-facing interactions Low latency critical
Batch Processing
Large volumes of data Offline execution Throughput over latency
Why Combining Them Is Hard
These modes compete for resources.
Real-time needs speed.
Batch needs capacity.
Without proper design, one affects the other.
Common Problems
Batch jobs slow down real-time systems Resource contention Inconsistent performance
Designing Hybrid Systems
- Separate Execution Pipelines
Do not mix real-time and batch workflows.
- Resource Isolation
Allocate resources independently.
- Priority Scheduling
Real-time tasks should take precedence.
- Asynchronous Processing
Decouple tasks where possible.
- Monitoring And Scaling
Track usage and adjust dynamically.
The Role Of System Architecture
Good architecture ensures:
Clear separation Efficient resource usage Predictable performance
How Avery NXR Handles This
Workflows define execution modes.
Systems can handle both real-time and batch tasks without conflict.
Final Thought
Different workloads require different strategies.
And systems must be designed to handle both.