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Kafka is a distributed, partitioned and replicated commit log service that provides a messaging functionality as well as a unique design. We can use this functionality for the log aggregation process. The basic messaging terms that Kafka uses are: Topic: These are the categories in which messages are published.

DistributedLog provides knobs for tuning data retention for a wide variety of use cases. DistributedLog also provides control over how Logs are broken up into segments which helps balance data distribution across storage nodes. Tuneable read and write pipelines.

A distributed system is composed of several applications calling each other to complete one operation. Each of these applications emits its own logs and often stores them in different locations.

Centralized Logging Using Log Streams The common way to implement it is to stream microservice logs to a common queue. Distributed logging server listens to the queue and acts as log store. It provides search capabilities to search the trace.

What Is a Log? It keeps the records, and the ordering of records, by when it's appended to the data structure. In a deterministic system, you can reconstruct the state of the systems at any time, by replaying the input in order for every single step of the input.

Log is nothing but a file which contains a sequence of records, each log record refers to a write operation. All the log records are recorded step by step in the log file. We can say, log files store the history of all updates activities.

A "log" would include things such as dates or the time of day in order to show exactly when something occured or how often it occured over a period of time. "Record" is a broader term that means any recording of information, which includes logs.