Datadog Bits AI vs Dynatrace Davis AI vs New Relic AI: Real AIOps Cost per 1,000 Incidents in 2026
The short answer: only Datadog prices its AI investigations in a way you can convert into a per-incident number. At the listed AI Credit prices, an average Bits investigation costs about $6.50–$8.45, or $6,500–$8,450 per 1,000 incidents, depending on whether credits are bought on an annual commit, a monthly commit or on demand. Dynatrace and New Relic fold their AI into consumption and compute meters that do not publish a per-incident rate, so their AI cost per 1,000 incidents is unknown from public data. The larger number in every case is the observability platform underneath, and the AI layer is cheap by comparison if, and only if, it saves engineers a few minutes per incident.
What each vendor bills
Datadog Bits AI (OFFICIAL). Datadog's US pricing lists three ways to buy AI Credits: Annual Commit at $500 per 500 credits per month ($1.00 per credit when fully consumed), Monthly Commit at $600 per 500 credits per month ($1.20 per credit when fully consumed), and on demand at $1.30 per credit. An autonomous Bits investigation is listed at an average of 6.5 credits, with the note that actual consumption varies with task complexity and the amount of context processed. The same credit pool feeds Bits Chat (about 0.5 credits per message), Bits Code (about 5 credits per fix) and Agent Builder runs (about 3 credits). Before the credit model, investigations were reported at $25 committed or $36 on demand, a 74–82% price cut (REPORTED).
Datadog base platform (REPORTED). Infrastructure Pro at $15 per host per month billed annually ($18 on demand); APM at $31 per host; log ingestion at $0.10 per GB; log indexing at $1.70 per million events with 15-day retention. Datadog bills hosts on a high-water-mark basis: it drops the top 1% of hourly counts and bills the whole month at the next-highest hour.
Dynatrace Davis AI (REPORTED). Consumption-based (DPS) with multiple meters: full-stack monitoring at $0.01 per GiB-hour with a 4 GiB minimum per host, log ingest at $0.20 per GiB, log retention at $0.02 per GiB-day, RUM at $0.00225 per session, and Kubernetes pods at $0.002 per pod-hour. A typical mid-market deployment was reported at $9,000–$12,000 per month. Davis AI is part of the platform; no separate per-incident meter was public (QUOTE-ONLY / UNKNOWN).
New Relic (OFFICIAL). 100 GB of data ingest free per month, then $0.40 per GB ($0.60 for Data Plus). Full platform users cost $349 per user per month on Pro with an annual commitment ($418.80 pay-as-you-go), and AIOps is among the capabilities of a full platform user. Advanced Compute, which unlocks New Relic AI and other newer capabilities, is metered in compute capacity units, reported at $0.60 per CCU (REPORTED). How many CCUs one incident analysis consumes was not public (QUOTE-ONLY / UNKNOWN).
The reference environment
The environment is ILLUSTRATIVE and is used only to size the base layer: 100 hosts averaging 16 GiB, 2,048 GB of logs a month, 300 million indexed log events, and 10 engineers with full platform access.
| Vendor | Calculation | Monthly base |
|---|---|---|
| Datadog | 100 × $15 + 100 × $31 + 2,048 GB × $0.10 + 300 M × $1.70 per M | $5,314.80 |
| New Relic | (2,048 − 100) GB × $0.40 + 10 users × $349 | $4,269.20 |
| Dynatrace | 100 × 16 GiB × $0.01 × 730 h + 2,048 GiB × $0.20 + 2,048 GiB × $0.02 × 30 days | $13,318.40 |
Dynatrace note: hosts $11,680 + log ingest $409.60 + steady-state retention $1,228.80 (30 days of retained logs). Because Dynatrace bills on memory, the same estate on 8 GiB hosts halves the host line to $5,840. These list-rate totals exclude custom metrics, synthetics, RUM, security modules, containers beyond the included allowance, and any discounts.
AI layer per 1,000 incidents
Assuming one AI investigation per incident (ILLUSTRATIVE), the Datadog AI layer is:
| Incidents per month | Credits (6.5 each) | Annual Commit ($500 per 500-credit block) | Monthly Commit ($600 per 500-credit block) | On demand ($1.30 per credit) |
|---|---|---|---|---|
| 100 | 650 | $695 | $795 | $845 |
| 1,000 | 6,500 | $6,500 | $7,800 | $8,450 |
| 10,000 | 65,000 | $65,000 | $78,000 | $84,500 |
| Incidents per month | Annual Commit per 1,000 incidents | Monthly Commit per 1,000 incidents | On demand per 1,000 incidents |
|---|---|---|---|
| 100 | $6,950 | $7,950 | $8,450 |
| 1,000 | $6,500 | $7,800 | $8,450 |
| 10,000 | $6,500 | $7,800 | $8,450 |
A committed block is not divisible at low volume. At 100 incidents a month, 650 credits are consumed: the first 500 fall inside one committed block ($500 on Annual Commit or $600 on Monthly Commit) and the remaining 150 credits are billed on demand at $1.30, or $195. That gives $695 on Annual Commit, $795 on Monthly Commit, and $845 if everything is bought on demand (650 × $1.30).
For Dynatrace and New Relic, the AI cost per 1,000 incidents is QUOTE-ONLY / UNKNOWN. The honest budget is the base layer plus a written quote for the AI-related meters.
Base layer allocated per 1,000 incidents
This is an allocation of a fixed cost, not a marginal cost, but it shows why incident volume matters.
| Incidents per month | Datadog base | New Relic base | Dynatrace base |
|---|---|---|---|
| 100 | $53,148 | $42,692 | $133,184 |
| 1,000 | $5,315 | $4,269 | $13,318 |
| 10,000 | $531 | $427 | $1,332 |
Formula: monthly base ÷ incidents per month × 1,000.
Break-even: minutes saved per incident
Formula: minutes saved needed = AI cost per investigation ÷ loaded engineer cost per hour × 60.
| Engineer cost per hour | At $6.50 | At $8.45 |
|---|---|---|
| $60 | 6.5 min | 8.5 min |
| $90 | 4.3 min | 5.6 min |
| $150 | 2.6 min | 3.4 min |
At $90 an hour, a $6,500-per-1,000-incidents AI layer breaks even at about 72 engineer-hours saved per 1,000 incidents, or about 94 hours at the on-demand rate. Under the earlier $25–$36 per-investigation pricing, the same break-even was 17–24 minutes per incident, so the credit change moved the threshold from "must save a meaningful chunk of an hour" to "must save a few minutes."
Sensitivity
- Noisy alerts. If 30% of investigations are triggered by non-actionable alerts and save nothing, the cost per useful investigation rises by about 43% (6.5 ÷ 0.7 = $9.29), and break-even moves to about 6.2 minutes at $90 an hour.
- Credit variance. The 6.5-credit figure is an average; a complex investigation consumes more.
- Purchase mode. $1.00, $1.20 and $1.30 per credit apply on Annual Commit, Monthly Commit and on demand respectively when blocks are fully consumed, and unused credits inside a block raise the effective rate.
- Estate size. Dynatrace's memory-based meter and Datadog's host-based meter scale differently: doubling host memory doubles the Dynatrace host line but leaves Datadog's host line unchanged.
Budgeting traps
1. The AI only sees what the platform sees. Investigations are limited to telemetry already stored in that vendor's platform, so a mixed stack reduces the value of the AI. 2. Shared credit pools. One pool feeds four Datadog agents, so chat and code usage can consume credits intended for incident work. 3. High-water-mark billing. A short traffic spike can set the host bill for the whole month. 4. Log double-charging. Datadog bills for ingestion and again for indexing. 5. Seats are a hidden meter. On New Relic, ten full platform users cost $3,490 a month before a single gigabyte of data.
What to ask before you buy
Ask each vendor for the AI meter in dollars per investigation, the pool structure, the overage price, and whether AI usage requires a higher platform tier. Then apply the break-even table above to your own loaded engineering cost.