Automate your progressive releases with ConfigCat and Swiftask
Swiftask orchestrates your ConfigCat releases. Deploy features in automatic, data-driven tiers based on real-time performance metrics.
Result:
Secure your deployments, reduce error rates, and accelerate your development cycle.
AI Agents
configcat
Connector configcat · Secure OAuth 2.0
Manual deployments slow down your velocity
Managing progressive rollouts manually is error-prone. Adjusting feature flag percentages on ConfigCat at odd hours, monitoring crash logs, and manually deciding to move to the next stage is time-consuming and risky.
Main negative impacts:
Higher incident risk
A minor mistake in flag configuration can instantly expose an unstable feature to 100% of your users.
Operational overhead
Your engineers spend valuable time monitoring deployments instead of building new features.
Lack of real-time feedback
Decisions to move to the next rollout stage are often based on guesswork rather than concrete monitoring data.
Swiftask connects your monitoring tools to ConfigCat. Your AI agent analyzes performance in real-time and automatically adjusts your feature flag percentages based on your safety criteria.
BEFORE / AFTER
What changes with Swiftask
Manual deployment
A developer deploys a feature to 5%. They wait an hour, check logs, then manually increase to 25%. If a bug appears, they must rush to disable the flag. It's slow, stressful, and prone to human error.
Swiftask orchestration
Swiftask automatically monitors your metrics. If error rates stay low, it incrementally increases the flag on ConfigCat. If an anomaly is detected, the agent immediately kills the feature to protect your users.
Implementing automated releases
1
STEP 1 : ConfigCat integration
Connect your ConfigCat account to Swiftask via API Key. Your flags become manageable by our agents.
2
STEP 2 : Define your rules
Set performance thresholds (error rates, latency) that authorize or block the progression of the rollout.
3
STEP 3 : Link to data sources
Connect your monitoring tools (Datadog, New Relic) so the AI can make decisions based on telemetry.
4
STEP 4 : Enable autonomous rollout
Start the deployment. The agent manages the tiers and notifies you of every success or failure.
AI orchestration capabilities
The agent continuously analyzes system logs, error reports, and user feedback to adjust flag exposure.
- Target connector: The agent performs the right actions in configcat based on event context.
- Automated actions: Dynamic flag percentage adjustment. Automatic rollback upon anomaly detection. Progress notifications on Slack/Teams. Detailed release phase reporting.
- Native governance: Swiftask acts as an intelligent layer above ConfigCat to guarantee safe delivery.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-configcat@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.
Benefits of automation
Enhanced security
Automatic rollback protects your users in case of unforeseen issues.
Increased velocity
Free your team from repetitive monitoring tasks related to releases.
Data-driven decisions
No more guesswork: your deployments follow strict system health rules.
Standardization
Apply the same security protocols to every new feature deployed.
Full visibility
Track the state of every feature flag directly from your Swiftask dashboard.
Governance and compliance
Swiftask applies enterprise-grade security standards for your configcat automations.
- Secure authentication: Access management via API tokens restricted to your ConfigCat environments.
- Full audit log: Every flag percentage change is tracked and timestamped.
- Environment isolation: Manage your development, staging, and production flags separately.
- Manual override: Stay in control: you can take full control of your flags at any time.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Impact on your operations
| Metric | Before | After |
|---|---|---|
| Release management time | Several hours per week | One-time setup (minutes) |
| Mean Time To Detect (MTTD) | Depends on human vigilance | Instantaneous via automation |
| Human error risk | High | Near zero |
| Deployment frequency | Limited by cognitive load | Optimized by automation |
Take action with configcat
Secure your deployments, reduce error rates, and accelerate your development cycle.