# Datadog Log Management optimization | Cloud Efficiency Hub

Canonical: https://www.pointfive.co/efficiency-hub/cloud-services/log-management

2 documented Datadog Log Management cost inefficiencies, each with how to detect it and how to fix it.

[Cloud Efficiency Hub](https://www.pointfive.co/efficiency-hub) 

2 documented Datadog Log Management cost inefficiencies, each with how to detect it and how to fix it.

## 2 inefficiencies

[All services](https://www.pointfive.co/efficiency-hub#browse-by-service)

- Datadog Log Management  CER-0235

### [Unnecessary Default Log Retention in Datadog](https://www.pointfive.co/efficiency-hub/inefficiencies/unnecessary-default-log-retention-in-datadog)

Many organizations keep Datadog's default log retention settings without evaluating business requirements. Defaults may extend retention far beyond what is useful for troubleshooting, performance monitoring, or compliance. This leads to...

Other

- Datadog Log Management  CER-0539

### [Indexing All Ingested Datadog Logs Without Exclusion Filters](https://www.pointfive.co/efficiency-hub/inefficiencies/indexing-all-ingested-datadog-logs-without-exclusion-filters)

Datadog Log Management charges separately for ingesting logs and for indexing them. At list prices, indexing a million 1 KB events for 15 days ($1.70) costs many times more than ingesting that gigabyte ($0.10). By default a log index has...

Other

## More Datadog services

- [Datadog Infrastructure Monitoring  2](https://www.pointfive.co/efficiency-hub/cloud-services/datadog-infrastructure-monitoring)

- [Datadog Custom Metrics  1](https://www.pointfive.co/efficiency-hub/cloud-services/datadog-custom-metrics)

- [Datadog Commitments  1](https://www.pointfive.co/efficiency-hub/cloud-services/datadog-commitments)

- [Datadog APM  1](https://www.pointfive.co/efficiency-hub/cloud-services/datadog-apm)

- [Datadog RUM  1](https://www.pointfive.co/efficiency-hub/cloud-services/datadog-rum)

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Source: the public page above. Product screenshots and illustrative interfaces are examples, not live customer data.