Nine Guideposts for Effective Log Analytics Planning

PURE STORAGE

Analyse Log Data Quicker

Organisations are improving application and infrastructure performance—and maximising business outcomes with effective log analytics planning.

Here are the best practices and considerations to show you the way.

Identify Trends for Ingest Rates

Accommodate your future needs for performance and capacity.

Determine How Long You Need to Retain Log Data

Fine tune your data retention policies to optimise costs and minimize liability.

Consider Regulatory Issues Affecting Log Analytics

Provide verifiable measures to govern the usage, transport, and storage of your data.

Evaluate New Data Sources and Formats

Forecast and prepare for new requirements due to upcoming data transformation pipeline changes.

Prepare for Changing Business Realities

Align your log analytics infrastructure planning with the broader corporate strategy.

Decide Ongoing Query Requirements

Identify the future volumes of different query types, such as ad hoc or point queries.

Address Data Management Challenges

Plan for impacts on log data formatting and delivery caused by changes in the environment.

Plan Your Data Transformations

Ensure that your data transformation tools and applications are sufficient for your future needs.

Don’t Forget Your Data Protection and Availability Needs

Designate your log data’s criticality and sensitivity in your security and backup/Restore policies.

Don’t Miss the Ebook

Log analytics is becoming more demanding. It’s also becoming more valuable to the enterprise. Putting these key considerations into play is vital if you want to realize the true potential of your log analytics.

To learn about the nine guideposts in greater detail, download the ebook O’Reilly: Understanding Log Analytics at Scale

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