Tarification

Real-time log analysis for AMQP with AI

Swiftask connects to your AMQP queues to process, filter, and analyze your logs in real time. Spot issues before they impact your users.

Resultat:

Turn raw data streams into actionable insights and drastically reduce your Mean Time To Resolution (MTTR).

Log volume makes manual analysis impossible

As you scale, your systems generate terabytes of logs via AMQP. Traditional static-rule methods miss weak signals, while manual analysis is too slow to react to critical incidents.

Les principaux impacts négatifs :

Delayed incident detection: Critical errors are often buried in the noise, leading to prolonged downtime and degraded customer experience.
DevOps team burnout: Your engineers spend hours digging through logs instead of shipping high-value features.
Exploding storage costs: Storing unfiltered, unanalyzed logs is costly and inefficient. Without intelligent triage, you pay for useless data.

Swiftask acts as an intelligent filter on your AMQP streams. The agent analyzes every message in real time, categorizes errors, and triggers contextual alerts only when necessary.

AVANT / APRÈS

Ce qui change avec Swiftask

Without Swiftask

A system error occurs. Logs pile up in the AMQP queue. No one notices until a customer complains. The IT team must then manually extract logs to find the root cause.

With Swiftask + AMQP

As soon as an error log passes through the AMQP queue, Swiftask analyzes it, identifies the pattern, and alerts the team instantly with a preliminary diagnosis. The issue is resolved before it's even noticed.

How to integrate Swiftask with your AMQP streams in 4 steps

ÉTAPE 1 : Connect your AMQP broker

Configure the secure connection between Swiftask and your AMQP instance (RabbitMQ, etc.) via a simple configuration interface.

ÉTAPE 2 : Define your log patterns

Train the agent to recognize normal logs and isolate anomalies or suspicious patterns in incoming messages.

ÉTAPE 3 : Configure automated actions

Determine the automated responses: Slack notification, Jira ticket creation, or execution of a remediation script.

ÉTAPE 4 : Activate continuous analysis

The agent now processes 100% of the AMQP stream in real time, ensuring constant monitoring and immediate responsiveness.

Advanced analysis capabilities

Swiftask analyzes the context, frequency, and severity of every message passing through AMQP, considering recent history.

Connecteur cible : L'agent exécute les bonnes actions dans amqp selon le contexte de l'événement.
Actions automatisées : Intelligent log filtering. Pattern anomaly detection. Data aggregation for reporting. Multi-channel alert triggering. Selective archiving of critical data.
Gouvernance native : All analyses are logged in Swiftask, making compliance audits and continuous monitoring improvement easy.

Chaque action est contextualisée et exécutée automatiquement au bon moment.

Chaque agent Swiftask utilise une identité dédiée (ex. agent-amqp@swiftask.ai ). Vous gardez une visibilité complète sur chaque action et chaque message envoyé.

À retenir : L'agent automatise les décisions répétitives et laisse à vos équipes les actions à forte valeur.

Why choose Swiftask for your AMQP logs

1. Reduced MTTR

Detect and diagnose outages in seconds, not hours.

2. Contextual intelligence

Unlike classic parsing tools, Swiftask understands log semantics, reducing false positives.

3. Native scalability

Handle massive data streams without modifying your existing AMQP architecture.

4. Data governance

Precisely control which data is analyzed and retained, ensuring GDPR compliance.

5. No-code deployment

Set up enterprise-grade monitoring in minutes, without writing a single line of code.

Security and privacy

Swiftask applique des standards de sécurité enterprise pour vos automatisations amqp.

Stream encryption: The AMQP connection uses TLS to ensure log confidentiality during transfer to Swiftask.
Environment isolation: Each client has an isolated workspace within Swiftask.
GDPR compliance: Data is processed according to the strictest security standards.
Full audit trail: An audit log tracks all agent actions on your log streams.

Pour aller plus loin sur la conformité, consultez la page gouvernance Swiftask et ses détails d'architecture de sécurité.

RÉSULTATS

A direct impact on your IT performance

Métrique	Avant	Après
Incident detection time	Hours (manual)	Seconds (AI)
Log volume processed	Limited by human capacity	Unlimited (asynchronous)
False positives	High (static rules)	Very low (AI analysis)
Operational cost	High (manpower)	Reduced (automation)

Passez à l'action avec amqp

Turn raw data streams into actionable insights and drastically reduce your Mean Time To Resolution (MTTR).

Optimisez vos flux AMQP avec un routage intelligent piloté par l'IA

Cas d'usage suivant.