Datadog AI employee

A Superkind AI employee that checks deployments, investigates alerts, explains root causes, and documents incidents inside Datadog. Message it in Teams or Outlook, it does the work in Datadog and reports back with the result. Anything sensitive waits for your approval.

  • Hosted in the EU
  • GDPR data processing agreement
  • Ready to start today
  • Works in Teams, Slack and more

What is a Datadog AI employee?

A Datadog AI employee is an AI that connects to your Datadog account and completes work in it. It does not just answer questions about Datadog, it takes the actions: checking monitors, investigating incidents, analysing logs and traces, creating tickets. Superkind builds this AI employee with your company knowledge and delivers the finished result to wherever your team works.

Unlike workflow builders such as Zapier or Make, there is nothing to configure. No triggers, no zaps, nothing to maintain. You describe the outcome in plain English, the AI employee picks the right Datadog actions, chains them with your other systems, and asks for your approval before anything sensitive runs.

About Datadog

Datadog is an observability platform for infrastructure, applications, logs, traces, digital experiences, and security.

  1. You ask in Teams

    Describe what you need in plain English.

  2. Superkind picks the actions

    Selects the right Datadog actions and chains them together.

  3. Datadog

    Superkind works in Datadog

    Checks monitors, analyses logs, documents incidents. Your real data.

  4. Superkind reports back

    Delivers the finished result to Teams or Outlook.

Try asking

What can you ask Superkind to do in Datadog?

Messages you would actually send. Copy one, swap in your specifics, and Superkind takes it from there.

Check the latest deployment in Datadog and tell me which monitors triggered an alert afterwards.

you, to @Superkind

Explain from the Datadog traces and logs why checkout has been returning errors since this morning.

you, to @Superkind

Create a Jira ticket for this Datadog incident with the cause, priority, and affected service link.

you, to @Superkind

Let me know here as soon as Datadog detects a new incident, with affected services and an initial cause.

you, to @Superkind
How it works

How does Superkind work with Datadog?

  1. Native integrations and connectors for 1,000+ tools

    1Connect your systems

    Datadog connects securely through API and application keys. Add Teams and the systems your team already uses, such as Outlook, Jira, or Slack. Datadog permissions stay limited to the agreed tasks. Superkind handles the setup and gets to work.

  2. Lena Hoffmann9:12 AM

    @Superkind please check in Datadog why the checkout error rate rose after the latest deployment and create an incident.

    @SuperkindApp9:13 AM

    On it. Checking checkout in Datadog and creating the incident.

    2Tell Superkind what you need

    Message your AI employee in Teams like a colleague. Ask it to check an alert in Datadog or explain an error from logs and traces. Plain English is enough. Superkind picks the right actions itself.

  3. @SuperkindApp9:14 AM
    • Monitor checkout latency triggered
    • 5xx rate elevated since deployment
    • Incident INC 184 created
    Datadog
    Incident INC 184SEV 2 · checkout api
    Waiting for your approvalMute the checkout monitor?

    3Superkind operates, you approve

    Superkind opens Datadog, completes the work, and writes the result back in Teams. It evaluates monitors, logs, and incidents in context. Sensitive changes in Datadog wait for your approval. Every step is logged.

Actions

What can Superkind do in Datadog?

Ask in plain English from Teams or Outlook. Superkind picks the right Datadog actions, runs the work, and reports back. No workflows to build.

  • Monitors

    List monitors

    Lists Datadog monitors with status, type, tags, and the latest triggered alert.

  • Monitors

    Inspect monitor

    Reads the query, thresholds, notifications, and current status of a Datadog monitor.

  • MonitorsNeeds approval

    Create monitor

    Creates a Datadog monitor with a query, thresholds, message, and tags.

  • MonitorsNeeds approval

    Update monitor

    Changes the query, thresholds, or notifications of an existing Datadog monitor.

  • MonitorsNeeds approval

    Mute monitor

    Mutes a Datadog monitor or selected groups for a set period.

  • MonitorsNeeds approval

    Delete monitor

    Permanently deletes a Datadog monitor from the account.

  • Incidents

    List incidents

    Lists Datadog incidents by status, severity, service, or time range.

  • Incidents

    Inspect incident

    Reads the status, severity, timeline, commander, and affected services of an incident.

  • IncidentsNeeds approval

    Declare incident

    Creates a Datadog incident with a title, severity, and affected services.

  • Incidents

    Summarise incident

    Summarises the timeline, signals, changes, and open tasks of a Datadog incident.

  • Logs and traces

    Search logs

    Searches Datadog logs by service, status, host, tag, and time range.

  • Logs and traces

    Analyse traces

    Analyses Datadog traces by service, resource, latency, error, and dependency.

  • Logs and traces

    Explain root cause

    Connects logs, traces, deployments, and monitor alerts into a likely root cause.

  • Logs and traces

    Get events

    Reads Datadog events for deployments, configuration changes, and monitor states.

  • Logs and traces

    Compare services

    Compares error rate, latency, and throughput across multiple Datadog APM services.

  • Dashboards

    List dashboards

    Lists Datadog dashboards with title, author, tags, and modification date.

  • Dashboards

    Inspect dashboard

    Reads the widgets, queries, variables, and layout of a Datadog dashboard.

  • Dashboards

    Create graph snapshot

    Creates a Datadog snapshot for a metric and selected time range.

  • Dashboards

    Query metrics

    Queries Datadog metrics with aggregation, tags, and a time range.

  • SLOs and Synthetics

    List SLOs

    Lists Datadog SLOs with target, time window, status, and remaining error budget.

  • SLOs and Synthetics

    Check SLO status

    Checks target achievement, error budget, and history for a Datadog SLO.

  • SLOs and Synthetics

    Inspect Synthetic tests

    Reads status, locations, assertions, and recent results from Datadog Synthetic tests.

  • SLOs and Synthetics

    Explain failed tests

    Analyses failed Datadog Synthetic tests using assertions and run details.

  • Other

    List hosts

    Lists Datadog hosts with status, sources, tags, and last reported data.

  • Other

    Check usage

    Reads Datadog Usage Metering data for hosts, logs, metrics, and other products.

  • OtherNeeds approval

    Create webhook

    Creates a Datadog webhook integration with a URL, payload, and optional headers.

Works with your stack

Superkind uses Datadog together with your other systems

Ask for outcomes that span tools. The AI employee pulls data from Datadog, cross-references your stack, and delivers one finished result.

Matching AI employees

Superkind AI employees that work with Datadog

Every role brings its expertise and uses Datadog as one of its tools.

Companies working with Superkind

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FAQ

Frequently asked questions

Everything you need to know about your AI employee for Datadog.

Yes. Datadog is one of the integrations Superkind connects through a managed connector. Once connected, your team can put the AI employee to work in Datadog from Microsoft Teams or Outlook. It can inspect monitors, analyse logs and traces, summarise incidents, and report results. You need neither a workflow builder nor custom code.

An admin creates the required API and application keys in Datadog and grants only the agreed permissions. Superkind securely connects those credentials to the AI employee and checks the connection. We set this up with you during onboarding. Your team can then start tasks directly from Teams or Outlook.

It can inspect monitors and alerts, search logs and traces, explain root causes, create and summarise incidents, read dashboards, check SLOs and error budgets, and evaluate Synthetic tests. The list above shows typical Datadog actions. We define which actions your team actually uses together for each use case.

No. With Zapier or Make, you build triggers and steps and maintain them whenever something changes. With the AI employee, you describe the desired result in plain English. Superkind picks the right Datadog actions itself, connects them with Jira, GitHub, or Slack when needed, and asks if information is missing.

Only with your approval. Superkind can independently read and summarise monitors, alerts, logs, traces, and SLOs. Deleting, changing, or muting a monitor waits for a yes from a responsible person, directly in Teams. Your team decides which Datadog actions are sensitive and who is allowed to approve them.

The AI employee works with minimal Datadog permissions limited to the agreed tasks. Superkind is hosted in the EU and signs a GDPR data processing agreement with you. Your data is not used to train models. Every action is logged so your team can trace access and changes.

Datadog Infrastructure Pro publicly starts at about 15 US dollars and Enterprise at about 23 US dollars per host per month with annual billing. Zapier starts at about 20 euros and Make at about 10 euros per month, both plus setup time. Superkind is priced per use case, a fraction of a full-time hire. Your Datadog licence is additional.

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