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Apache Kafka is an open-source distributed event-streaming platform for publishing, storing, and processing real-time data as partitioned, replicated logs.
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Ian Cooper says event-driven orgs of up to about five teams can manage async APIs on shared knowledge of each other's services. His model for doing it at scale begins with the address, binding and contract each endpoint has to describe to its consumers.
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Cloudflare opened K2, a serverless event log built on R2 object storage, to public beta at about one second of p99 produce latency. For that wait, teams get producers decoupled from consumers and no Kafka cluster of their own to run.
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Confluent Cloud now holds an OSPAR attestation, adding Singapore's bank-sector audit to the four reports already in its Trust Center. Singapore banks vetting Confluent as an outsourced provider can start from one audit built on the banking association's own control baseline.
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One SaaS team's rebuild of incident detection on Kafka and Flink cut telemetry lag from over 40 seconds to under 10, according to its CNCF post. Over eighteen months its recall ran from about 60% to 86% and back to 64%, so speed alone says little about which outages get caught.
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Monest's CTO kept tag-event fan-out on BullMQ, where each job goes to one worker, for two client integrations and several internal teams. A first attempt, one worker calling every consumer, replayed finished calls on retry and forced one retry count on all of them.
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A developer's write-up of running the outbox pattern in production finds the textbook loop breaks on error to preserve ordering, and never counts attempts. That combination jams forever.
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Moving authz-gateway's key checks from Postgres to a Kafka Streams store cut p99 from 40ms to 4ms, yet a revoked key kept working for four days. Three pods cut off from Kafka for 30 hours rejoined at zero lag and kept honoring it, a dev.to write-up says.
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A dev.to post argues that moving embeddings out of Postgres buys a second source of truth, a four-leg query path and 50 to 150 ms of internet latency. Its 8 ms pgvector counter-figure has no benchmark behind it.
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A dev.to post argues that processing.guarantee=exactly_once_v2 charges coordination overhead to every message and still leaves external side effects for you to deduplicate by hand. The five-line alternative it offers has a gap of its own.
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Kafka cannot take a record back, so trying a Streams predicate on the team's cluster writes output that real consumers may already read. A dev.to post seeds a disposable stack from two folders of your own schemas and records.
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Kafka promises at-least-once delivery, so a consumer that dies after the payment call but before the commit replays the event on restart. A dev.to tutorial puts the guard in a database primary key, keyed on an event ID the producer sets.
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On the platform behind taabi Nexus, the model's only output is a validated rule document, and the code that dials a driver's intercom sits behind a seven-day replay, a role check and one person's approval.
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KIP-932 lets a group run more consumers than a topic has partitions by locking each record for 30 seconds and counting its deliveries. The idempotence, the retries and the lock sizing become the application's job.
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Apache SeaTunnel's Kafka source scans a topic's partitions once, when the job starts. Any partition added afterward goes unread and its records are lost until you set partition-discovery.interval-millis to a positive value.
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Astronomer's State of Apache Airflow 2026 puts 5,818 practitioners behind two migration numbers measured on different denominators. Recomputed on one base, about 62 percent are planning a move they have not started.
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Apache Flink covers most of what Google's managed Dataflow does. A dev.to deployment guide prices the swap in prerequisites: cert-manager goes in before the operator, and the exactly-once path ends in a bucket whose keys you hold.
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An experiment written up on dev.to publishes outbox events from an in-memory queue of committed event IDs and keeps polling only as a recovery scan, so that scan's interval now sets worst-case delivery latency.
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The Inbox pattern makes a consumer idempotent only when the dedup row and the business write commit together, and a Spring Boot walkthrough works through what each of the two wrong orderings costs you.
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KeewanoDB keeps events in the order they arrived, grouped around a customer or device, so an agent can read one entity's history without an ETL job. Keewano expects the warehouse to stay where it is.
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A cluster console shows a stable consumer group while an instance replays 7.5 million changelog records, so Alginte's 0.11.0 view reads the Kafka Streams client inside the process the console itself runs.
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