AIOps deployment, tuning, and signal hygiene.

Why AIOps tools underdeliver

The recurring failure pattern is not the tool — it is the foundation the tool sits on. Roughly 41% of enterprises report data quality and legacy-integration issues as their primary blocker to AIOps adoption (AIOps Community, 2026). In mid-market environments the specific gap almost always appears in one of four places:

• Tag and metadata inconsistency. Most mid-market AWS or GCP accounts have 30–60% of resources untagged or inconsistently tagged. Watchdog, Davis, and every other correlation engine need a clean service map to fire on signal rather than noise. An AIOps tool pointed at an untagged estate learns the noise pattern and perpetuates it.
• No service-to-team ownership map. Alert routing requires knowing which team owns a service. When ownership mapping is absent or stale (engineers leave, services get renamed, a re-architecture happened), alerts land in the wrong queue or get suppressed because nobody is accountable. The on-call team learns to ignore a class of alert, and the next real incident goes unnoticed.
• Alert volume too high to establish a baseline. Before you can define "anomaly", you need a stable baseline of normal. Environments with runaway alert volume have no stable baseline. Correlation rules tuned against noise-saturated data produce correlation results that are themselves noise-saturated.
• Runbooks that exist in three different Notion pages. The incident workflow is inseparable from the AIOps deployment. A correlation layer that identifies the right incident, routes it to the right team, and offers a runbook link is valuable. One that does the first two but stops there saves a page and costs the same on-call time.

What we actually do

The engagement sequence follows the readiness-then-deploy shape: identify which of the four failure patterns apply, fix the foundation where needed, then deploy and tune the vendor your team has chosen.

The 7-dimension Readiness Scorecard

Before any deployment work, we score your current state across seven dimensions:

1. Telemetry coverage. What percentage of services emit metrics, logs, and traces? Which tiers are dark?
2. Tag hygiene. Tagging policy completeness, enforcement mechanism (tag policies, SCPs, or purely advisory), percentage of untagged resources by spend.
3. Alert volume and signal-to-noise baseline. Alert count per on-call rotation week, percentage of alerts that result in a page, percentage of pages that require a human action.
4. Runbook automation maturity. Which incident classes have documented runbooks? Which runbooks are machine-executable vs. human-read?
5. On-call ownership clarity. Is there a clean map from service to team? How many services have undefined or contested ownership?
6. Incident-response loop closure. What percentage of incidents generate a post-incident review? Are action items tracked and closed?
7. Vendor-fit recommendation. Given your stack, team size, and ownership map, which AIOps vendor fits best — or should you stay cloud-native?

The Scorecard is a 12–15 page PDF delivered in 5 business days. The fee is $500, credited 100% against any Deployment engagement signed within 90 days.

Deployment + Tuning

Deployment covers the work a vendor's professional services team does on a good day — and the foundation work they skip. Deliverables from a 4–6 week engagement:

• Tag policy enforcement in IaC — Terraform or CloudFormation module with mandatory tag enforcement, drift detection via AWS Config or GCP Asset Inventory.
• Service-to-team ownership map in a machine-readable format (a YAML or JSON registry that feeds the correlation engine).
• Correlation rules defined and documented for your top-20 alert classes — what constitutes a real incident, what is correlated noise, what is scheduled maintenance to be suppressed.
• Integration wiring: PagerDuty or Opsgenie routing, Slack channels, ServiceNow incident creation where required.
• Alert threshold calibration against the baseline established in the Scorecard.
• Runbook stubs for the top-10 incident patterns, in the format your on-call tool supports.
• Training session for two named on-call engineers: how to read the correlation output, how to add a new service to the ownership map, how to tune a threshold.
• Signed evidence: alert-volume count pre-deployment, alert-volume count on day 30 post-deployment, named-incident dry-run result.

AIOps Managed

The ongoing retainer scope is signal hygiene, not incident handling. Each month: review correlation-rule performance, flag rules producing sustained false positives, update the ownership map as your team's service portfolio changes, verify anomaly model baselines haven't drifted with a new deployment, and coordinate with the vendor on any platform updates that affect tuning. Quarterly written report with alert-volume trend and MTTR from baseline. Same named engineer across the retainer. See the broader Platform Management retainer if you need full operational coverage beyond AIOps signal hygiene.

Which vendors we work with

We are not a reseller or referral partner for any AIOps vendor. We deploy what your team has chosen or recommends. The vendors we have worked with and can configure competently:

• Datadog Watchdog. Watchdog anomaly detection, alert correlation, service-map configuration, tag policy enforcement for Datadog agents. Pricing anchor: Datadog Enterprise + Watchdog bolt-on (typically $15–23/host/month for Watchdog at standard tiers, source: Datadog pricing page, checked June 2026).
• Dynatrace Davis. Davis causation engine, Smartscape dependency map, tag and metadata standardisation in the Dynatrace platform. Pricing anchor: Dynatrace Full-Stack Monitoring ~$58–69/host/month full-stack (source: MonitoringCost.com, checked June 2026).
• PagerDuty AIOps. Noise reduction, event correlation, intelligent alert grouping on top of existing PagerDuty Incident Management. Pricing anchor: PagerDuty AIOps from ~$699/month per-event tier (source: PagerDuty pricing page, checked June 2026).
• Cloud-native. AWS CloudWatch Anomaly Detectors, CloudWatch Composite Alarms, GCP Cloud Monitoring alerting policies, Azure Monitor AIOps. For teams where adding a third-party platform is not justified by the alert volume or compliance posture.

We do not claim a vendor partnership with any of the above. We deploy what you choose and do not receive referral fees or co-marketing credits from vendors.

What we do not do

• Incident response. We do not join your on-call rotation, handle live SEV-1s, or staff an operations centre. That is the scope of the broader Platform Management retainer.
• SOC operations. Security incident detection, threat hunting, and SIEM operations are cloud-security scope — not this offering.
• Custom ML model development. We tune the models that come with your chosen AIOps vendor. We do not train or build proprietary anomaly-detection models from scratch.
• Platforms with no existing monitoring. The Deployment + Tuning engagement requires that your services are already emitting some form of telemetry. If your platform has no monitoring at all, start with a Platform Assessment.

Methodology developed running platform engineering

The observability-foundation approach — tag-first, ownership-map second, correlation-rules third — was developed running platform engineering at an India consumer commerce platform serving tens of millions of users, where alert noise in a high-velocity deployment environment was the primary on-call quality problem. The Scorecard dimensions reflect what actually matters at that scale, not a vendor checklist.

FAQ

Can you run the Scorecard without access to our monitoring console?

No — the Scorecard requires read-only access to your existing monitoring platform (Datadog, Dynatrace, CloudWatch, or PagerDuty). The tag-hygiene dimension requires read-only cloud account access (AWS, GCP, or Azure). We operate under read-only credentials throughout; we do not push changes to your configuration during the Scorecard phase.

What if the Scorecard finds we're not ready for an AIOps deployment at all?

That is the most valuable outcome a Scorecard can return. If the fundamental issue is missing telemetry rather than an AIOps tuning problem, we say so — and the Deployment engagement is the wrong next step. The honest answer is worth the $500 either way.

Do you recommend a vendor or are you genuinely vendor-agnostic?

The Scorecard includes a vendor-fit recommendation. For some teams, the right answer is "you already have CloudWatch and your alert volume doesn't justify a third-party AIOps licence." We surface that. We do not receive reseller margin or referral fees from any vendor.

How does this fit with the Platform Management retainer?

AIOps Managed is a narrower scope than the full Platform Management retainer — signal hygiene and correlation-rule maintenance only. If you need broader operational coverage (IAM governance, DR, compliance, incident participation), the Platform Management retainer absorbs AIOps Managed as part of its scope. Talk to us about the right shape.

Can you work alongside an existing MSP?

Yes. Most AIOps engagements run alongside an existing monitoring or operations vendor. We scope the boundary explicitly in the SOW so that there is no overlap confusion.