Event Store Fundamentals

Understand how Event Store clusters work and the best ways to leverage it’s features is critical to a stable application. Understanding the best practices for reading, writing, projections, and subscriptions along with clustering, node replacement, backups and replication is critical for achieving this.


This course focuses on ensuring any member of the team either developing applications or focused more on operations can gain a strong understanding of how Event Store works in order that systems may be operated smoothly in various configurations and both hosted or on-prem environments and how to best use Event Store in order simplify the application and provide repeatable stable application results.


Learn how to:

  • Reading and Writing Data
  • Catchup and Persistent Subscriptions
  • Patterns using Optimistic Concurrency
  • Read Model and Other Consumer Patterns
  • Projections
    1. Using the standard projections
    2. How to create custom projections and when not to
  • Basic maintenance operations
  • Avoid Common Errors and Troubleshoot issues
  • Event Store as part of a Larger Architecture





Internals of an Event Store node


  • Client API Operations and their semantics
    • Append to stream
    • Read from stream
    • Subscribe to stream
    • Read from all
    • Subscribe to all
  • Storage on disk
    • Index
    • Transaction log
  • The read path of events
    • Index
    • Transaction log
  • The write path of events
    • Transaction log
    • Index
    • Safety options and tuning
  • Projections
    • Projections model
    • Implementation
    • Pitfalls - write amplification


General design principals for Event Sourced systems


  • Event Sourcing vs Event Streaming
  • Event Store as part of a Larger Architecture
    • Common Patterns
    • Managing Data Schemas
    • "Closing the books" as part of a domain model
    • Separation of ephemeral messaging vs permanent storage
  • Optimistic Concurrency
    • Guaranteed Ordering
    • Implementing simple and effective HA
  • Read Model and Other Consumer Patterns
    • Leveraging Reads and Subscriptions
    • Competing Consumers
    • Snapshots Checkpoints
  • Basic Operations
    • Cluster Fundamentals
    • Garbage Collection (Scavenging)
    • Backup


Replication & General Operations


  • Clustering semantics
    • CAP Theorem
    • Leader election
    • Replication semantics
    • Failure modes
    • Tuning elections for an environment
  • Garbage Collection (Scavenging)
    • Semantics and implementation
    • Pitfalls
  • Backup
    • Backup procedures and semantics
    • Cluster backup
  • Interpreting monitoring information
    • SEDA architecture
    • Interpreting the monitoring dashboard
    • Tuning based on operational metrics
  • Optimising start-up time
    • Disk guarantees and safety
    • Trade-offs for safety vs startup speed
    • Tuning options based on operational requirements

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