Datadog, Inc. has recently unveiled a groundbreaking tool, Storage Management, designed to tackle the plaguing issue of unchecked cloud object storage costs. Already available for Amazon S3, with previews set for Google Cloud Storage and Azure Blob Storage, this innovation empowers teams to optimize their cloud expenditure strategically.
The proliferation of data-heavy and AI-driven workloads, encompassing extensive training datasets and inference logs, has significantly elevated cloud storage spending. With these growing expenses, operations and cloud efficiency teams are hard-pressed to pinpoint the major cost drivers among massive shared storage resources. A further complication lies in the lack of detailed context on metadata and access patterns, which are crucial for enforcing effective storage policies.
Consequently, streamlining costs—whether by transitioning dormant data to more cost-effective tiers, eradication of duplicate entries, or curtailing the buildup of obsolete versions—often devolves into a labor-intensive manual chore.
The Storage Management solution by Datadog directly confronts these hurdles. It delivers expansive insights into the entirety of cloud object storage, allowing teams to detect storage growth anomalies, analyze data usage in context, and implement automated cost-reduction strategies promptly. This tool seamlessly integrates with Datadog's overarching Cloud Cost Management suite, zeroing in on object storage and offering profound insights into usage patterns, cost trends, and optimization opportunities.
As highlighted by Yrieix Garnier, VP of Product at Datadog, “For companies building AI products, data storage and processing is consistently the third-highest contributor to cost—greater than expenses for AI model training and inferencing.” Storage Management empowers organizations to mitigate unforeseen expenditures, redirecting focus toward product development and market readiness.
Core offerings of Datadog's Storage Management include:
- Granular Visibility: Identify cost drivers such as sporadically accessed, transitional, or duplicate data across workloads, teams, and environments.
- Unified Context: Connect cost, usage, and metadata across storage segments for assured implementation of lifecycle, tiering, and retention protocols.
- Proactive Anomaly Detection and Alerts: Swiftly pinpoint and address irregularities in storage growth, sudden cost increases, and unexpected access patterns.
- Targeted Optimization Recommendations: Foster savings through tangible, directive guidance on re-tiering, archiving, or data deletion decisions.
With its refined approach, Datadog Storage Management offers a powerful ally for organizations striving not only to manage but to optimize cloud storage costs efficiently.
