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.
Accommodate your future needs for performance and capacity.
Fine tune your data retention policies to optimise costs and minimize liability.
Provide verifiable measures to govern the usage, transport, and storage of your data.
Forecast and prepare for new requirements due to upcoming data transformation pipeline changes.
Align your log analytics infrastructure planning with the broader corporate strategy.
Identify the future volumes of different query types, such as ad hoc or point queries.
Plan for impacts on log data formatting and delivery caused by changes in the environment.
Ensure that your data transformation tools and applications are sufficient for your future needs.
Designate your log data’s criticality and sensitivity in your security and backup/Restore policies.
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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