Audit logging platform is a deceptively strategic choice: you can spend $360k and six months building a bespoke system, or hand $2k–$100k/month to a vendor and get faster compliance coverage. The right decision is not “always build” or “always buy”; it’s a quantifiable trade-off between event volume, retention horizon, regulatory needs, and operational risk.

Direct answer: Build an audit logging platform if you expect more than 2 TB/day of raw logs, need 24–60 months of immutable retention with attested provenance, or require sub-100ms query latency against hot audit indexes; buy a vendor if you ingest under 500 GB/day, have standard 12–36 month retention, and prefer integrated alerting and SIEM connectors. TCO break-even usually appears between $250k and $750k total over three years.

The stakes are concrete. A single senior engineer in the U.S. costs $170k–$210k loaded per year; running four engineers for six months to spec, implement, and harden an audit pipeline costs roughly $360k–$420k. By contrast, an off‑the‑shelf logging or SIEM vendor will bill $2k–$100k/month depending on ingest volume and retention choices.

Storage and egress are material. Storing 90 TB/month in S3 Standard at $0.023/GB-month costs about $2,070/month or $24,840/year. Egress of 10 TB out of cloud can add ~$900 in one‑time transfer costs at $0.09/GB. These numbers drive the economics when retention exceeds 12 months and when exportability becomes part of your switching cost.

audit logging platform build vs buy

Start by segmenting three realistic volume classes. Low volume: <100 GB/day (small SaaS, early stage). Mid volume: 100 GB–2 TB/day (growing B2B, multi‑tenant apps). High volume: >2 TB/day (telemetry‑heavy platforms, infrastructure providers). Each class maps to different vendor price points and different engineering effort to build and operate.

Vendor economics scale non-linearly with ingest. Elastic Cloud or Datadog will advertise per-GB pricing or indexed‑unit pricing; expect $0.25–$5.00 per GB of effective billed ingestion when you include parsing, retention tiers, and indexed fields. Historically, Splunk’s high-end ingestion pricing ran $100+/GB for premium indexing, which is why many companies moved to tiered vendors or self-hosted pipelines.

Building your own pipeline has distinct cost buckets: engineers for initial build and ongoing ops, storage (hot vs cold tiers), indexing and query infrastructure (Elasticsearch/ClickHouse/ClickHouse Cloud/Snowflake), secure key management (AWS KMS/HSM), and attestations for immutability (hash chains, WORM policies). Typical 3‑year TCO for a custom solution that reaches mid-volume is $400k–$1.2M when you factor staff, infra, incident fatigue, and occasional migrations.

Operational risk is underpriced in most build conversations. A custom system requires SLOs, backup drills, and on‑call capacity. If a single engineer is 0.2 FTE of on‑call for audit systems, that’s roughly $34k/year of recurring cost at $170k loaded, plus the operational overhead of playbooks and legal runbooks.

Compliance needs change the math. If you need WORM storage, signed attestations, or a chain of custody that a regulator will audit, vendors like Sumo Logic, Splunk, and IBM QRadar offer compliance-focused features with certifications and audits already baked in. Implementing equivalent controls in-house requires extra engineering (HSM integration, signed manifests), which is commonly $50k–$200k of initial and annual audit support cost.

If your logs are small and your retention is standard, buy; if your logs reshape your infrastructure or you must prove immutability on unique timelines, build. The crossover is a dollars‑and‑days calculation, not folklore.

What this means for a CTO deciding on an audit logging platform

You should start by running three simple calculations: projected ingest (GB/day), projected retained data after your required retention window (GB), and the expected query/forensic latency budget. If projected retention exceeds 100 TB after 12 months, the financial and operational drag of vendor pricing often justifies building a tailored pipeline.

Second, audit your regulatory constraints. If auditors require attested WORM storage or a signed chain of custody, request vendor proof of certifications and ask for export and eDiscovery SLA clauses. If the vendor cannot deliver a certified attestation without a bespoke contract addendum, that’s a red flag and may push you toward building.

Third, measure integration and time-to-compliance. If you need coverage in 30–90 days to pass SOC 2 or a contractual audit, buying a vendor with prebuilt SIEM connectors and managed parsers typically beats building, because vendors amortize parser work across customers and deliver rule packs for common compliance frameworks.

Quick checklist: audit logging platform decision items

1) Calculate your 36‑month TCO: include engineer cost ($170k loaded), storage, egress, and contract minimums. 2) Define retention and immutability needs: 12, 24, or 60 months; WORM or attestations. 3) Measure ingest profile: bursts vs steady state and peak qps for queries. 4) Evaluate vendor exportability: test an actual 10 TB export and measure time and egress. 5) Require SLA clauses: search latency, data durability, and proof-of-deletion policies.

When you choose to build, pick the right primitives. Ingest with Kafka (or managed MSK), store raw compressed events in S3 with lifecycle rules (move to Glacier Deep Archive for >24 months), index hot fields in ClickHouse for sub-100ms queries, and place immutability controls in front of buckets with object lock and KMS‑backed keys. These choices map to predictable costs and make future migrations easier.

If you choose to buy, negotiate the right metrics. Insist on per-GB pricing transparency (ingest vs indexed), egress caps, and a migration playbook with a real export time guarantee. Ask for access to raw compressed events within a contractual SLA—without raw export you get lock-in, not service.

Decide where the audit logging product lives in your org. If the legal team drives requirements you’ll likely vendor; if platform engineering owns telemetry and your product commits to nonstandard retention and low-latency for investigators, you’ll likely build. The organizational owner determines acceptable latency, security posture, and tolerance for technical debt.

Finally, treat switching costs as a first-class metric. Migrating 100 TB out of a vendor can easily cost $9k in egress plus weeks of engineering time and parsing normalization work. Build a migration plan and budget the one-time cost—this number often decides whether the vendor saves money long-term.

The right answer is seldom ideological. Buy when you value time-to-compliance, integration, and predictable monthly cost; build when you control scale, retention, or unique immutability requirements and the 3‑year TCO favors owning primitives. Quantify ingest, retention, and auditability first—and let those numbers decide.