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TLA+ for Designing and Verifying Distributed Systems

• 0:00:00 Introduction: Marcus Cooper, a Principal Research Software Developer at Microsoft, introduces a methodology using TLA+ for designing and verifying distributed, reactive, and microservice-based systems.

• 0:01:04 Contrasting Methodologies: The talk contrasts the TLA+ approach with the traditional "write code, write tests, debug into production" method.

• 0:01:19 Example Distributed System: A simplified webshop architecture is presented, featuring a front-end, back-end, database, and message queue, designed to sell pierogis.

• 0:03:35 Architecture Diagram: The system's architecture is visualized, highlighting the interaction between components (front-end, database, message queue, back-end).

• 0:04:06 Prototype Development Challenges: Building a simple first prototype involves setting up a cloud subscription, deploying infrastructure, implementing the workflow, and, very importantly, testing it.

• 0:05:28 Initial Code (Java): Initial Java code demonstrates a very basic interaction: writing to a database in one region (West US) and reading from another (Poland Central) to check consistency.

• 0:08:50 Initial Test Failure: The initial Java test, running in a loop, eventually fails (after 1800 iterations), revealing an inconsistency.

• 0:09:50 Introducing the TLA+ Model: The same system is modeled in TLA+, using five variables to represent the database (log), front-end (requests, future), back-end, and message queue.

• 0:11:01 Modeling System Actions: The TLA+ model defines actions (transactions) that describe state transitions, like frontEndWrite (writing to the database) and frontEndEnqueue (acknowledging the write and adding to the queue).

• 0:15:34 Back-end Operations: Other operations are modeled, such as backEndDequeue operation (reading from the queue and database).

• 0:16:11 Adding the Correctness Property: A crucial "test" (correctness property) is added to the TLA+ model: eventually, all acknowledged requests should be present in the back-end's data. This highlights the advantage of TLA+'s temporal logic (the "eventually" operator) over traditional timeouts in tests.

• 0:19:25 TLA+ Model Checking: The TLA+ model checker quickly finds the same inconsistency as the Java test, but much faster (less than a second) and reproducibly.

• 0:20:53 TLA+ Error Trace: The model checker provides a shortest error trace, showing the complete system state at each step, leading to the failure. This is a significant advantage over debugging with logs, which only provide a partial, node-specific view.

• 0:22:31 Root Cause Analysis: The error trace reveals the problem: eventual consistency in the database allows the back-end to read before the data is fully replicated.

• 0:24:10 Fixing the Issue (Strong Consistency): The Java code is changed to use "strong consistency." The TLA+ model is also updated, and the model checker confirms the fix.

• 0:26:25 Scaling Considerations: The talk discusses scaling challenges and the need to relax consistency for performance. Strong consistency, while correct, might not scale.

• 0:27:36 Exploring Session Consistency: Session consistency is introduced as a middle ground. The Java code is updated, but again, testing is difficult.

• 0:28:29 TLA+ Model Reveals Another Bug: The TLA+ model, using session consistency, initially fails again, showing the same error trace as with eventual consistency.

• 0:29:07 The Missing Session Token: The problem is identified: the back-end read in the TLA+ model was not using the correct session token. Fixing this in the TLA+ model (passing the future as the token) resolves the issue.

• 0:30:36 Modeling the Database: The talk emphasizes that the database itself was modeled in TLA+ (in about 200 lines of code), capturing the essential behavior and consistency levels.

• 0:32:09 Paper Reference: A paper ("Understanding Eventual Consistency in Azure Cosmos DB with TLA+") provides details on the database modeling.

• 0:32:45 Non-Determinism in TLA+: TLA+'s first-class support for non-determinism is key to modeling real-world system behavior (network delays, node failures, etc.).

• 0:33:32 State Graph: TLA+ generates a state graph representing all possible system executions, which tools can analyze to find errors.

• 0:34:40 TLA+ Users and Applications: Various companies (AWS, Microsoft, etc.) and applications (consensus algorithms, distributed databases, hardware verification) are mentioned.

• 0:36:31 TLA+ Origins: The presentation introduces the language's creator, Turing Award winner Leslie Lamport.

• 0:36:54 TLA+ as a Specification Language: TLA+ is a specification language, not a programming language. It's used for design, documentation, and verification before implementation.

• 0:37:54 Learning Resources: Links to learn more about TLA+ (tlapl.us, examples.tlapl.us) and an upcoming webinar are provided.

• 0:38:51 Q&A - Code/Spec Synchronization: How to ensure the production code and TLA+ spec match? Answer: CI/CD integration can help, but the primary value is in the high-level design and analysis. Perfect synchronization isn't the main goal.

• 0:40:58 Q&A - When to Introduce TLA+: Introduce TLA+ as early as possible in the design phase, when the team is small and focused on the core architecture.

• 0:41:52 Q&A - Graphical Tools to TLA+ Spec: Is there a tool to generate TLA+ specs from graphical designs? Answer: Graphical tools often lack the necessary semantic depth. Translating a whiteboard design to TLA+ is relatively straightforward due to TLA+'s expressiveness.