White Paper

High-Performance Data Storage for Observability and Telemetry

About This Resource
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Who This is For:

Engineering and infrastructure leaders — including VP Engineering, CIO, and CISO — responsible for enterprise observability, telemetry cost management, and platform modernization.

Key Takeaways
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44% of enterprises spend over $1 million per year on observability, with more than half driven by log storage — the root cause is coupled compute-storage architectures and per-operation cloud pricing, not data volume.

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AIStor's erasure coding delivers the same 11-nines durability as 3x replication at just 33% storage overhead instead of 200%, allowing organizations to store 2–3x more telemetry on the same hardware.

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AIStor maintains near line-speed reads across the full retention window with no cold-tier penalties — customers report retrieving historical data up to 12x faster than traditional archive-tier storage solutions.

Enterprise observability costs have crossed a threshold. Gartner data cited in this white paper shows 44% of enterprises spending over $1 million annually on observability, with log storage accounting for more than half of that. At 1 TB/day with 30-day retention, costs on platforms like Datadog can exceed $1.2 million per year. The typical response is to shorten retention windows, sample data, and accept detection gaps that surface during incidents. This white paper presents a structural alternative: MinIO AIStor as a high-performance primary storage layer for Splunk, Elastic, and Grafana observability stacks. AIStor integrates natively via S3, decouples storage from compute, and sustains consistent throughput across both recent and historical data, eliminating cold-tier penalties. Technical topics include erasure coding overhead, ingest throughput at scale, single-namespace architecture, and Kubernetes-native deployment for air-gapped and sovereign environments. Production customer results are included.

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