Automatically adjust your Google Cloud resources with AI
Swiftask connects your AI agents to Google Cloud to anticipate your resource needs. Adjust your infrastructure in real-time before traffic spikes hit.
Result:
Cut your cloud bills by avoiding over-provisioning, while ensuring maximum availability for your users.
AI Agents
google cloud
Connector google cloud · Secure OAuth 2.0
Over-provisioning is costing your organization dearly
Manual management of Google Cloud infrastructure often leads to two extremes: paying for unused resources or facing downtime during traffic spikes. Traditional reactive auto-scaling triggers too late, impacting both user experience and your budget.
Main negative impacts:
High cloud overcosts
Maintaining over-provisioned resources to handle unpredictable spikes wastes a major part of your IT budget every month.
Performance degradation
Classic reactive auto-scaling takes time to spin up. During this delay, your applications slow down, damaging the customer experience.
Complex IT management
Manually adjusting scaling thresholds for every service becomes unmanageable as your infrastructure grows in complexity.
Swiftask deploys AI agents that analyze load trends and adjust your Google Cloud resources predictively. The AI anticipates needs before they occur.
BEFORE / AFTER
What changes with Swiftask
Traditional reactive approach
Traffic suddenly increases. The system waits for CPU usage to hit 80% for 5 minutes. It then triggers the start of new instances. Meanwhile, users experience significant slowdowns.
Predictive auto-scaling with Swiftask
The AI agent analyzes history and trends. It detects an imminent load increase. It provisions the necessary resources 10 minutes before the spike. No slowdown is noticed, and resources are released as soon as demand drops.
Setting up your intelligent scaling in 4 steps
1
STEP 1 : Connect Swiftask to Google Cloud
Link your Google Cloud project via secure API. No complex access required, Swiftask follows the principle of least privilege.
2
STEP 2 : Configure the load analysis agent
Define the services and instances to monitor. The agent starts collecting metrics to train its prediction model.
3
STEP 3 : Establish your scaling rules
Set resource limits (min/max) and performance targets. The AI learns to respect these business constraints.
4
STEP 4 : Activate predictive mode
The agent takes control of scaling. Monitor its decisions and the savings achieved directly from Swiftask.
AI-driven piloting capabilities for Google Cloud
The AI analyzes time patterns, traffic seasonality, and system logs to refine its capacity predictions.
- Target connector: The agent performs the right actions in google cloud based on event context.
- Automated actions: Automatic adjustment of Compute Engine or GKE instances. Scaling based on load forecasts. Real-time cost optimization. Intelligent alerting in case of consumption anomalies.
- Native governance: All scaling actions are logged in an audit trail for total transparency on your infrastructure management.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-google-cloud@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 and financial benefits
Drastic cost reduction
Eliminate waste linked to over-provisioning thanks to surgical resource allocation.
Guaranteed performance
Anticipate needs to offer a smooth user experience, even during intense traffic spikes.
Governance and compliance
Keep a complete record of every infrastructure change for your internal audits.
Effortless agility
The AI adapts to changes in user behavior without you having to manually reconfigure thresholds.
Freeing up DevOps teams
Automate repetitive scaling tasks and let your engineers focus on product innovation.
Secure and compliant infrastructure
Swiftask applies enterprise-grade security standards for your google cloud automations.
- Secure authentication: Swiftask uses Google Cloud's IAM protocols for secure and limited integration.
- Granular control: You maintain final control over the resource limits allowed in your environment.
- Full audit trail: Every agent decision is tracked, allowing immediate verification of performed actions.
- Assured compliance: Automation respects your security policies and industry standards.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Measurable impact on your cloud
| Metric | Before | After |
|---|---|---|
| Resource costs | Paying for constant peak capacity | Paying for optimized real demand |
| System response time | Slowdowns during load spikes | Consistent and smooth performance |
| Human intervention | Daily threshold management | Zero intervention — autonomous steering |
| Error rate | Spikes in errors due to timeouts | Error rate reduced to its minimum |
Take action with google cloud
Cut your cloud bills by avoiding over-provisioning, while ensuring maximum availability for your users.