How deeply does Kafka for Architects cover two-phase commit?

Defines prepare, commit, and abort steps, then stops at Kafka’s lack of current 2PC support and the outbox workaround.

Two-phase commit

Two-phase commit is a distributed transaction protocol in which a coordinator first prepares all participants and then directs them to commit or abort as a group.

Two-phase commit (2PC) coordinates a distributed transaction across independent systems so every participant commits, or all participants abort. section 7.4.3

The protocol divides coordination into two stages:

Prepare: the transaction manager asks each participant to complete its work and report either readiness or failure. section 7.4.3
Commit or abort: if every participant is ready, the manager commits the transaction; otherwise, it instructs all participants to roll back. section 7.4.3

Profile update and the dual-write problem

A ProfileService updates its transactional database and publishes a profile-change event to Kafka. If either action occurs first and the second fails, the systems diverge. Kafka does not currently support 2PC, so the transactional outbox pattern stores the event with the database update; a separate process later publishes it to Kafka. section 7.4.3

How Kafka for Architects covers it

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Also explained in

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Think Distributed SystemsA distributed transaction commit protocol that coordinates commitment in two phases among participating processes.
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PostgreSQL Mistakes and How to Avoid ThemTwo-phase commit is a distributed transaction protocol in which participants first prepare to commit and then commit or abort based on a coordinator decision.
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Amazon Web Services in Action, Third Edition: An in-depth guide to AWSTwo-phase commit is a distributed transaction protocol that first obtains participant decisions and then instructs all participants to commit if every participant agrees.

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Related concepts

protocolkind of · A protocol is a defined set of rules and conventions governing communication or interaction among systems, components, or participants.
livenessaddresses · Liveness is a correctness property requiring that a system eventually makes specified progress or produces a desired event or condition.
Apache Kafkaused by · Apache Kafka is a distributed event-streaming platform for publishing, storing, processing, and consuming streams of records.
distributed transactionuses · A distributed transaction is a unit of work whose operations span multiple resources or systems and whose outcome is coordinated across them.

This explainer was generated by Manning's knowledge graph from the text of Kafka for Architects. The section links point to the parts of the book it draws on.