Scalability

EverTask is designed to scale from modest workloads to extreme high-load scenarios. This section covers features that help you achieve horizontal and vertical scalability for your background task processing.

Overview

When your application needs to handle increasing workload volumes, EverTask provides specialized features to maintain performance and reliability:

• Multi-Queue Support - Isolate workloads and optimize resource allocation with multiple independent execution queues
• Sharded Scheduler - Scale scheduling infrastructure to handle extreme loads (>10,000 tasks/second)

When to Consider Scalability Features

Most applications work well with EverTask’s default configuration. Consider these scalability features when you’re experiencing:

Multi-Queue Support

• Need to separate critical operations from background tasks
• Different workload types with varying resource requirements
• Priority-based task execution
• Workload isolation requirements

Sharded Scheduler

• Sustained scheduling load above 10,000 Schedule() calls per second
• Lock contention in profiling showing scheduler bottlenecks
• 100,000+ tasks scheduled concurrently
• Need for extreme throughput capacity

Scaling Strategy

Vertical Scaling (Single Instance)

Start here for most applications:

1. Optimize Queue Configuration - Tune parallelism and capacity
2. Add Multi-Queue Support - Separate workloads by characteristics
3. Enable Sharded Scheduler - Scale scheduling throughput

Horizontal Scaling (Multiple Instances)

For distributed deployments:

1. Shared Storage - Use SQL Server or SQLite with shared database
2. Queue-Based Distribution - Multiple instances process from shared queues
3. Load Balancing - Natural distribution through persistent storage

Note: Full distributed clustering with leader election and automatic failover is planned for future releases.

Best Practices

Start Simple

Begin with the default configuration and measure performance under realistic load before optimizing.

Measure Before Optimizing

Use the monitoring dashboard to identify actual bottlenecks rather than optimizing prematurely.

Scale Gradually

Enable multi-queue support first, then consider sharded scheduler only if needed for extreme loads.

Monitor Continuously

Track queue depths, processing rates, and scheduler throughput to validate scaling decisions.

Performance Targets

Scenario	Default Config	With Multi-Queue	With Sharded Scheduler
Task execution	~1k-5k tasks/sec	~5k-15k tasks/sec	~5k-15k tasks/sec
Scheduling calls	~5k-10k/sec	~5k-10k/sec	~20k-40k/sec
Queue isolation	Single queue	Multiple queues	Multiple queues
Lock contention	Low	Low	Very Low

Next Steps

• Multi-Queue Support - Isolate workloads with independent queues
• Sharded Scheduler - Scale to extreme scheduling loads
• Configuration Reference - Performance tuning options
• Monitoring - Track performance metrics
• Architecture - Understand internal performance characteristics

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Table of contents

• Multi-Queue Support
• Sharded Scheduler