Knowledge Base

Some people, when confronted with a problem, think "I know, I'll use floating point!" Now they have 1.9999997 problems.

Some people, when confronted with a problem, think "I know, I'll use idea!" Then they solve their problem.

If you have a problem and decide to use Java ... Now you have a Problem and a ProblemImpl

{ "some people": { "when confronted with": "a problem", "think": "I know, I'll use javascript!" }, "now they have": "two problems." }

Some people, when confronted with a problem, think "I know, I'll use jwz!" Now they're confronted with a problem about using jwz, and think "I know, I'll use jwz!". Now they're confronted with a problem about using jwz a

Some people, when confronted with a problem, think "I know, I'll use operator overloading!" Now they != 2 [problems]

Some people, when confronted with a performance problem, think "I know, I'll optimize!" Now they have two problems: slow code and a highly optimized block of code that's inconsequential when it comes to performance.

Some people, when confronted with a problem, think "I know, I'll use OSGi!" Now they have eight million, seven hundred forty three thousand, three hundred and one problems. Until they add more by trying to fix some of th

Some people, when confronted with a problem, think "I know, I'll use prolog!" No.

Some people, when confronted with a problem, think "I'll use reflection!" Now they have information about, and access to, their problem but still no solution in sight.

Some people, when confronted with a problem, think "I know, I'll use scala!" Now they have 847,172.3716 problems and can only somewhat define one of them. Boy howdy, have they screwed themselves over.

Some people, when confronted with a problem, think "I know! I'll use SGML!" Now <?xml version="1.0?"><person><possessions><problem id="p01"><description lang="en">Whatever your first problem was</description></problem><p

Grafana k6 — a developer-friendly CLI load tester written in Go, scripted in JS/TypeScript, with native cloud and Prometheus integration.

the Spring Kafka setting that controls when consumer offsets are committed. Key modes: BATCH (default, commits after listener returns), MANUAL (developer calls Acknowledgment.acknowledge() explicitly), and RECORD (commit

a set of consumers that cooperate to consume a topic, each assigned exclusive ownership of one or more partitions. Kafka tracks read progress per group, not per consumer instance.

the act of persisting a consumer group's read position to the broker. In Spring Kafka's default BATCH mode, the commit happens after the listener thread returns - not when downstream or async processing finishes.

the unit of parallelism and ordering in Kafka. Each partition is an independent ordered log; ordering is guaranteed within a partition but not across partitions in a topic.

the named channel to which Kafka producers write and from which consumers read. Topics are subdivided into partitions for parallelism and ordering guarantees.

Jetbrains' AI agent coordination framework.