Data retention policies must be adjusted based on the type of data being stored. High granularity data is critical for short-term analysis and troubleshooting, typically retained for 7-30 days. In contrast, older data, like archival records, should be stored long-term in systems such as S3 or Glacier for compliance. Observability tools can help optimize resources by identifying idle assets, enabling automatic scaling and cost savings. Organizations may also explore decentralized observability strategies and self-hosting options for open-source tools to reduce reliance on expensive solutions.
Short-term storage requires high granularity for timely troubleshooting (7-30 days), while long-term storage utilizes S3 or Glacier for compliance and historical analysis.
Retention periods vary by data type; immediate application logs may require only days, while audit logs may need several years.
Automating archiving and deletion based on retention policies can enhance data management efficiency.
Observability tools identify inefficiencies in cloud infrastructure that lead to cost savings through resource optimization.
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