Pricing

Master your SLA commitments with Tinybird and Swiftask

Connect your Tinybird performance data to Swiftask. Receive intelligent, real-time alerts the moment an SLA threshold is at risk.

Result:

Transition from reactive management to proactive service level oversight.

The challenge of real-time SLA monitoring

Monitoring SLAs on high-volume data is a technical hurdle. Often, alerts arrive too late, after the incident has already impacted users. Without correlating your Tinybird streaming data with business processes, you remain blind to performance drifts.

Main negative impacts:

Delayed incident detection: Standard tools alert after the threshold is breached, with responsiveness limited by data processing delays.
Alert fatigue: Constant data streams generate excessive false positives, making your operations team less responsive to actual emergencies.
Data-to-action silos: Data lives in Tinybird, while remediation happens elsewhere. This lack of fluidity slows down problem resolution.

Swiftask leverages Tinybird's analytical power to turn your streaming metrics into contextual alerts, enabling immediate human or automated intervention.

BEFORE / AFTER

What changes with Swiftask

Traditional SLA monitoring

You manually check Tinybird dashboards. A simple script triggers a generic email to an already overwhelmed team. Context is lost, and resolution depends on manual support analysis.

SLA monitoring with Swiftask

The AI agent continuously analyzes Tinybird streams. It detects a degradation trend before the critical breach. It notifies the relevant team with full context and suggests immediate corrective measures.

Setting up your SLA monitoring

STEP 1 : Integrate your Tinybird data

Connect your Tinybird API endpoints to Swiftask to allow the agent to query your metrics in real time.

STEP 2 : Define performance thresholds

Configure business rules in the Swiftask agent based on Tinybird data (e.g., p99 latency > 200ms).

STEP 3 : Configure alerting channels

Determine where and how the agent should alert: Slack, Teams, email, or by triggering a remediation workflow.

STEP 4 : Automate remediation

The AI agent monitors 24/7 and executes pre-approved actions as soon as a drift is identified.

Swiftask agent analysis capabilities

The agent cross-references Tinybird performance data with your business logs to identify the root cause of an SLA degradation.

Target connector: The agent performs the right actions in tinybird based on event context.
Automated actions: Real-time Tinybird endpoint monitoring. Contextual intelligent alerting. Automated performance report generation. Remediation script execution via webhooks.
Native governance: Alert history is archived for your SLA compliance audits.

Each action is contextualized and executed automatically at the right time.

Each Swiftask agent uses a dedicated identity (e.g. agent-tinybird@swiftask.ai ). You keep full visibility on every action and every sent message.

Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.

Operational advantages of AI monitoring

1. Reduced MTTR

Identify and resolve SLA issues much faster thanks to context provided at the time of the alert.

2. Increased reliability

Constant monitoring eliminates blind spots in your performance measurements.

3. Reduced false positives

AI filters alerts, surfacing only the incidents requiring real attention.

4. Simplified compliance

Generate proof of SLA compliance through full data and alert traceability.

5. Native scalability

Tinybird and Swiftask handle massive data volumes without compromising speed.

Performance data security

Swiftask applies enterprise-grade security standards for your tinybird automations.

Secure Tinybird access: Use restricted API tokens to ensure Swiftask only reads necessary data.
Data encryption: All communication between Tinybird and Swiftask is encrypted in transit.
Audit logs: Every request made by the agent to Tinybird is tracked.
Access isolation: Granular permission management to define who can configure monitoring rules.

To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.

RESULTS

Impact on key metrics

Metric	Before	After
Detection time	Minutes / Hours	Seconds
Alert precision	Low (noisy)	High (contextualized)
Manual effort	High (manual analysis)	Low (AI-assisted)

Take action with tinybird

Transition from reactive management to proactive service level oversight.