Integrating Datadog with ASI Biont: How an AI Agent Automates Monitoring and DevOps Routine

From “just another panel” to “self-executing monitoring”

Each DevOps team knows this state: Datadog collects metrics, draws dashboards, and sends alerts, but to turn these data into actions, a person is needed. He looks at the graph, sees a spike in latency, opens the log viewer, then goes to Slack to ask: “Who changed the config at 14:32?” If you are a DevOps engineer, you recognized yourself. If you are a product owner, you recognized your nighttime calls.

Datadog is an observability platform that collects metrics, logs, and traces from your infrastructure. But its value is not in graphs, but in reactions to events. This is where the ASI Biont AI agent comes on stage. Its task is not just to read Datadog data, but to automatically perform actions: triage incidents, create tickets, send reports, adjust configuration, and maintain a chronicle of all events.

In this article, I will tell you how to connect Datadog to ASI Biont through a simple chat dialog, which automation scenarios actually work, and why it saves hours of manual work every week.

What is ASI Biont and why does it need Datadog

ASI Biont is an AI agent that connects to external services through their APIs and performs tasks on your behalf. Unlike ordinary chatbots, it does not just “talk”—it takes actions: creates records, analyzes data, writes integration code, sends notifications.

Datadog is one of the most popular monitoring tools. According to the company, thousands of organizations around the world use the platform (Datadog is a public company; the 2025 financial reports are available at investors.datadoghq.com). But the standard workflow in Datadog often looks like this: alert → a person opens the dashboard → the person looks for the cause → the person writes to the ticketing system → the person creates a post-mortem. It is a sequence of five steps, each of which can be automated.

Integrating Datadog with ASI Biont turns monitoring from a “passive metric collector” into an active agent that not only reports a problem but also takes action. And this is not magic—it is an API available to everyone.

How it works: no panels, only dialogue

Most integration platforms (Zapier, Make, custom enterprise solutions) require setup through a web interface: choose a service, authorize, configure triggers, write code. ASI Biont works differently—everything happens in chat.

Here is what the connection looks like in practice:

1. You open a chat with ASI Biont.
2. You give it an API key from Datadog (the key is created in the Datadog dashboard under Organization Settings → API Keys).
3. The AI agent analyzes the structure of the Datadog API, determines the available endpoints, and writes the integration code itself.
4. You can immediately give a command: “Connect Datadog and send me a summary of today’s incidents”—and the agent will execute it.

No “Add Integration” buttons. No long waits while ASI Biont developers add support for a specific service. Because ASI Biont works with any service that has an API. This is the key difference: you are not limited to a list of pre-installed integrations. If Datadog has a programming interface—and it does; detailed documentation is available at docs.datadoghq.com/api/latest—then ASI Biont can work with it.

This makes the platform a universal solution for DevOps. You can connect Datadog for monitoring, PagerDuty for escalations, Jira for tickets, Slack for communication—all through one chat.

Why connect Datadog to an AI agent: 5 tasks that become automated

1. Incident triage

Datadog generates a huge number of alerts. Many of them are false positives. ASI Biont can:

• Receive a webhook from Datadog when a monitor triggers.
• Analyze metrics and logs associated with the alert.
• Determine the likelihood of a false positive based on historical data.
• Create an incident in Jira or ServiceNow with context: time window, affected services, key logs.
• Send a brief summary to Slack: “What happened, where, and how likely it is critical.”

Instead of opening your laptop at 3 a.m. and looking at the dashboard, you wake up to a notification: “The incident has been classified as low priority; the likely cause is a deployment of the auth service; the causes are being analyzed.” This is not a replacement for the on-call engineer, but it is a filter that screens out the noise.

2. Automatic incident reports (post-mortems)

A post-mortem is a document that describes what happened, why it happened, and what to do to prevent it from recurring. ASI Biont can collect such a report automatically:

• Requests metric time series from Datadog (CPU, memory, network, error rate).
• Exports logs and traces for the incident period (via the Logs API and Trace API).
• Correlates deployment and configuration changes.
• Generates a structured Markdown document ready to send to the team.

This saves 2–3 hours of manual work after each incident. And the report is more complete because AI does not skip data—it systematizes it.

3. Metric analysis and generating management reports

Managers rarely want to see dashboards. They need answers: “Is everything stable?”, “Which services are the slowest?”, “What was the effect of the recent release?”. ASI Biont can send a report to a messenger or email on schedule:

• Service uptime for the week.
• Top 5 slowest endpoints.
• Number of incidents by severity.
• Comparison of indicators with the previous period.

This is not just a data export, but analytics with conclusions: “API latencies increased by 8% after the Thursday deployment; the likely cause is the increased response size.” Such a report is generated in minutes, not half a day.

4. Monitoring the monitoring

Even Datadog has outages, silent alerts, and incorrect threshold values. ASI Biont can check:

• Validity of API keys.
• Presence of “dead” monitors that have not triggered for 30+ days.
• Missed webhook deliveries.
• Correctness of tags on metrics.

This is a task that a person usually does not do because it has no immediate effect. But a missed alert can cost more than any routine.

5. On-call rotation and escalation

If you use Datadog together with PagerDuty or Opsgenie, ASI Biont can automatically:

• Create escalations on schedule.
• Check that an on-call engineer is assigned for every day.
• Remind about duty shifts in Slack.

All of this is done through the Datadog API (Schedule Maintenance API, Downtime API).

Practical scenarios: from words to code

Scenario 1: Auto-response to low-priority alerts

Imagine that in your infrastructure every night there is an alert “High CPU on worker-node-3”. An engineer wakes up, checks, sees that a process is processing data, and falls asleep again. ASI Biont can do this instead.

User: Connect Datadog, here is the API key: <key>. Make it so that when an alert with the tag environment:staging comes in, you check the average load over the last 5 minutes yourself, and if it is below 70%, automatically close the alert with the comment "Known noise".
ASI Biont: The integration with Datadog is configured. I have created filtering logic: for environment:staging alerts, I will request the system.cpu.user metric through the Query API and, if the value is below the threshold, send a comment and close the event.

This does not remove real incidents, but it removes nighttime noise.

Scenario 2: Generating a post-mortem after a release

After each release, the team spends time checking whether they broke production. ASI Biont can:

1. Get the list of deployments from CI/CD (for example, GitHub Actions).
2. Correlate them with Datadog metrics before and after the deployment.
3. If a significant degradation is detected, create an alert in Slack and suggest rolling back.

The team gets a result: “Release v2.4.1 caused the error rate to grow from 0.1% to 2.3% in the payments service. A rollback or a fix is recommended within 30 minutes.” This is a decision based on data, not intuition.

Scenario 3: Weekly report for the CTO

Every Monday morning, ASI Biont sends a report to Telegram or Slack:

It looks like manual work by an analyst, but it is an automatic query to Datadog via API and formatting into a clear view.

Time savings: what you get in numbers

Exact numbers depend on the scale, but the logic is simple. According to DORA research (State of DevOps Report, 2023), highly effective DevOps teams spend significantly less time on routine operations—they simply have more time for feature development. If an engineer on average spends 2–3 hours a day checking alerts and writing reports, automating even half of this time returns 5–7 working hours per week per person to the team. With a DevOps engineer’s salary of 300–500 thousand rubles per month, this is hundreds of thousands of rubles in savings monthly—simply because the AI takes over the watchfulness.

But even more important is the speed of reaction. An incident discovered 5 minutes after the failure is fixed faster and costs less than an incident discovered an hour later. Automatic notification with context from Datadog reduces MTTR (Mean Time To Recovery)—the service recovery time—because the person receives not “it fell” but “it fell, here are the logs, here is the likely cause.”

Technical details: how ASI Biont works with Datadog

Datadog provides a REST API with a large set of endpoints. The main ones used by ASI Biont:

• Metrics API (/api/v1/query) — retrieving metric time series.
• Events API (/api/v1/events) — reading events and alerts.
• Logs API (/api/v2/logs) — searching and exporting logs.
• Monitors API (/api/v1/monitor) — creating and modifying monitors.
• Downtime API (/api/v1/downtime) — managing maintenance periods.

The complete list is in the official Datadog documentation (docs.datadoghq.com/api/latest). ASI Biont uses these endpoints to read data and perform actions.

Important: the AI agent does not “break” the API and does not use undocumented capabilities. It works within the official limits provided by Datadog. For most operations, a standard API key is enough; changing monitors may require a key with administrator rights.

Security and limitations

The key question of any integration is: “Will the AI agent get too much access?” Let me answer:

• The API key is stored encrypted and is used only for requests to Datadog.
• You can use an API key with limited permissions (Datadog allows creating keys with different scopes, see the RBAC documentation).
• ASI Biont does not transfer data to third parties and does not use it for model training without your explicit consent.
• Any action of the agent can be canceled in the dialog at any time.

Limitation: ASI Biont is not a real-time system. If you need to react in milliseconds, that is a task for classic alerting pipelines. But if you need fast, intelligent response with a delay of a few seconds, this is an ideal case.

Comparison table: before and after implementing ASI Biont

This is not a replacement of an engineer, but an enhancement: the agent does routine work, the engineer solves complex problems.

How to connect: step-by-step instruction

Step 1: Get a Datadog API key

1. Go to the Datadog Web UI.
2. Navigate to Organization Settings → API Keys.
3. Click “New Key”, name it, for example, asibiont, and copy the key.

Please note: the API key is confidential information. Do not publish it in open channels.

Step 2: Open a chat with ASI Biont

Go to asibiont.com and start a new dialog.

Step 3: Provide the key and describe the task

Just write:

“Connect Datadog. My API key: . I want you to automatically analyze alerts, send me an incident summary every morning, and generate post-mortems for critical incidents.”

Step 4: In a minute, get the result

ASI Biont will write the integration code itself, test the API connection, and confirm: “The integration is active. I will monitor Datadog monitors and send reports.” If you want to clarify the behavior, just write about it in chat. No admin panels, no “integrations with two dozen setting fields”—only natural dialogue.

What distinguishes ASI Biont from other automation tools

The main difference is the absence of predefined templates. Zapier or Tray.io require choosing actions from a list and configuring them manually. ASI Biont understands the task from language and selects the necessary API calls itself. If Datadog adds a new endpoint, you don’t need to wait for a platform update—the AI agent already understands the new API the next day because it can read documentation.

In addition, it is safe. The code that ASI Biont writes for integration can be viewed in the dialog. You always know what requests the agent makes to your Datadog.

Typical connection mistakes and how to avoid them

1. Too broad access rights. Do not give the agent an administrator key if you are not sure. Start with a key with read rights, and later, when you see how the agent works, expand the rights.
2. Passing the key in plain text. Use secure channels and do not leave the key in the chat history if your security policy does not allow it.
3. Undefined scenarios. If you simply say “connect Datadog and work,” the agent will wait for specific commands. It is better to immediately formulate what exactly you want to automate.

Recommendations for successful use

• Start small. Choose one task, for example, “a daily incident summary,” and polish it. Then add the next one.
• Use iteration. ASI Biont can change the integration logic at your request. “Add latency metrics,” “exclude the staging tag”—it works.
• Check critical actions. Before allowing the agent to change monitor configuration, try a “read-only” mode for a couple of days.

Conclusion

The integration of Datadog with ASI Biont is not just “another connector,” but a change of approach to observability. Monitoring stops being a passive system that screams about problems and becomes an active participant in the process: it diagnoses, classifies, creates reports, and saves hours of engineering work.

If you use Datadog and want to return time to the team for development rather than “watching graphs,” try connecting ASI Biont. It will take 5 minutes: just open the chat at asibiont.com, provide the Datadog API key, and formulate what you want to automate. The AI agent will write the integration itself and show the result.

Connect Datadog to ASI Biont today—and tomorrow you will get the first automated report that you used to assemble manually. asibiont.com is waiting for you.