Apa pitfalls lan mistakes umum nalika nggunakake Kafka?

Question

Accepted Answer

Kafka kuat nanging duwe **pitfalls umum** — salah paham lan mistakes babagan partisioning, ordering, consumer behavior, delivery semantics, lan operations. Memahami ini membantu menghindari masalah lan nggunakake Kafka kanthi bener.

## Design lan partisioning pitfalls

```text
✗ Too FEW partitions → limits consumer parallelism (can't scale consumption beyond
  partition count); too MANY → overhead, rebalancing pain → plan partition count carefully
✗ Wrong PARTITION KEY → uneven distribution (hot partitions) or wrong ordering scope →
  choose a key for even distribution AND the ordering you need
✗ Expecting GLOBAL ordering → Kafka only orders WITHIN a partition (a common misunderstanding)
✗ Adding partitions changes key→partition mapping → breaks ordering for keys (be careful)
```

## Consumer lan processing pitfalls

```text
✗ Ignoring CONSUMER LAG → consumers falling behind unnoticed → growing delay
✗ Not handling DUPLICATES → at-least-once means duplicates → need idempotent processing
  (a very common mistake — assuming exactly-once without idempotency)
✗ Slow processing blocking the consumer → causes lag/rebalances; long processing → rebalance issues
✗ Frequent REBALANCES → from slow processing/timeouts → consumption pauses (tune, optimize)
✗ Improper offset committing → reprocessing or message loss
```

## Operational lan usage pitfalls

```text
✗ Using Kafka where a SIMPLE QUEUE suffices → unneeded complexity (over-engineering)
✗ Ignoring DISK/retention → disk fills up (serious failure)
✗ Under-replication / weak durability config (acks=1) → data loss on failures
✗ No monitoring; treating Kafka as simple (it's a complex distributed system)
✗ Not securing Kafka (open access)
→ understand Kafka's model to avoid these common mistakes
```

## Mengapa hal ini penting

Memahami pitfalls Kafka umum yaiku pengetahuan senior-level yang berharga sebab **mengenali lan menghindari mistakes umum membantu nggunakake Kafka kanthi bener**, dadi penting secara praktis kanggo pemakaian Kafka nyata.

Kafka kuat nanging duwe pitfalls halus akeh sing nyebabake masalah nyata, lan manawa ngerti pitfalls iki membantu menghindari mistakes kasebut.

Memahami **design lan partisioning pitfalls** — partitions terlalu sithik (mbatasi parallelism) utawa keterlaluan akeh (overhead), partition keys salah (nyebabake hot partitions utawa ordering salah), ngarepake **global ordering** (salah paham umum, sebab Kafka mung order ing partisi), lan masalah yen nambah partitions mbutuhi key-to-partition mapping (namuhi ordering) — membantu ndhindari partisioning lan ordering mistakes sing asring lan kena dampak.

Memahami **consumer lan processing pitfalls** — ignore consumer lag (consumers ketinggalan ora ketandingan), **ora nangani duplicates** (mistake asring, sebab at-least-once delivery terarti duplicates sing mbutuhake idempotent processing — nganggep exactly-once tanpa idempotency yaiku error asring), processing alon nyebabake lag lan rebalances, rebalances asring, lan offset committing salah — membantu ndhindari mistakes consumer-side sing nyebabake lag, duplicates, lan reprocessing masalah.

Memahami **operational lan usage pitfalls** — nggunakake Kafka nalika simple queue cukup (over-engineering), ignore disk/retention (disk penuh), durability config lemah (aks=1 risiko data loss), monitoring ora ana, lan Kafka ora aman — membantu ndhindari operational lan judgment mistakes.

Manawa ngerti pitfalls iki (khususnya sing umum babagan ordering misunderstanding, duplicate handling, consumer lag, lan over-using Kafka) membantu nggunakake Kafka kanthi bener lan ndhindari masalah nyata sing namuhi akeh users.

Kesadaran iki nuduhake Kafka practical experience.

Sebab Kafka duwe pitfalls halus, umum akeh (partisioning/ordering misunderstandings, duplicate handling, consumer lag, over-use, operational mistakes) sing nyebabake masalah nyata, lan sebab mengenali lan ndhindari pitfalls iki membantu nggunakake Kafka kanthi bener, memahami pitfalls Kafka umum yaiku pengetahuan senior-level berharga — penting secara praktis kanggo ndhindari mistakes asring (khususnya babagan ordering, duplicates/idempotency, lag, lan appropriate use) sing namuhi Kafka users, nuduhake practical experience, lan membantu nggunakake Kafka kanthi bener lan reliable ing real systems.