Assess Your Data Before Ingestion

Before sending data to LogScale, understand what you have, why you need it, and how it will be used. Good ingest decisions start with a clear assessment of your data.

Identify Data Purpose

Not all data is equally valuable. Before ingesting data, consider the following:

  • What questions do you need this data to answer? Work backwards from your use cases. If you cannot articulate why you need the data, you probably do not need it.

  • Who will be querying it? Different teams have different needs. Security, operations, and engineering teams may interact with the same data differently.

  • How long do you need to retain it? Retention requirements vary significantly by data type and compliance obligations.

Understand Data Structure

LogScale handles many formats, but knowing your data structure upfront saves significant effort later.

  • Is it structured, semi-structured, or unstructured? JSON and key-value formats are easiest to parse. Free-form text requires more parser investment.

  • Is the timestamp reliable and consistent? Timestamp issues are one of the most common ingest problems. Inconsistent formats or missing timestamps cause events to be stored incorrectly in time.

  • Are field names consistent? Inconsistent field naming across sources makes querying harder and can complicate parser design.

Evaluate Volume and Velocity

Understanding the scale of your data shapes almost every other decision.

  • How much data per day? This drives repository sizing, retention planning, and licensing considerations.

  • Is the volume consistent or bursty? Spiky ingest patterns may require buffering or flow control upstream.

  • Is this a one-time load or continuous stream? Historical backfills behave differently than live streaming data and may need special handling.

Assess Sensitivity and Access Control

  • Does the data contain sensitive or regulated information? PII, credentials, or compliance-relevant data may need to be masked or filtered before ingest. Removing sensitive data after ingestion is significantly more difficult.

  • Who should have access? Plan your repository structure and permissions around access boundaries, not just data type.

Plan Tags and Parsers

After you understand your data, you can make informed decisions about how LogScale should organize it.

  • What fields are good tag candidates? Low cardinality, high query value fields — such as environment, region, or log type.

  • Does a parser already exist? Check built-in parsers before building custom ones.

  • What fields matter most for querying? Identifying these early helps you validate that your parser is extracting them correctly.

Plan Before You Ingest

Assessing data before ingest helps you avoid problems that are expensive to fix later. Sensitive data that is ingested, poorly chosen tags, missing timestamps, and unnecessary data all become harder to address after they are stored in your repository. Upfront analysis reduces future remediation effort.