AIOps & Managed Services

    Utilizing AIOps platforms to detect anomalies and resolve infrastructure incidents before they impact business operations.

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    AIOps & Managed Services

    Key Capabilities

    1

    Automated Remediation

    Scripts that automatically restart services, clear caches, or reroute traffic when specific failure patterns are detected.

    2

    Anomaly Detection

    Machine learning models that establish baselines for normal performance and alert only on true deviations, reducing alert fatigue.

    3

    Root Cause Analysis (RCA)

    AI that correlates logs across distributed systems to instantly pinpoint the source of an outage.

    Autonomous Reliability

    AI systems are not 'fire and forget'. They are gardens that need tending.

    AI systems are not 'fire and forget'. They are probabilistic gardens that need tending. We implement 'Continuous Observability 2.0' where we monitor not just system metrics (CPU/RAM), but model metrics (Drift, Confidence, Bias).

    We derive the solution by establishing 'Baselines of Normality' over a 2-week period. Once established, our anomaly detection models flag deviations in real-time. If latency spikes or accuracy drops, the system triggers automated remediation - restarting pods, rolling back weights, or clearing caches - without human intervention.

    This creates a self-healing infrastructure that guarantees 99.99% uptime for your mission-critical AI workloads.

    Approach

    Our Methodology

    A structured approach to delivery that ensures consistency and quality.

    1

    Baseline Establishment

    Collecting telemetry data (logs, metrics, traces) for 2-4 weeks to understand normal system behavior and seasonality.

    2

    Correlation Rules

    Configuring the AIOps platform to group related alerts from different systems into single verifiable incidents.

    3

    Automated Remediation

    Building runbooks for common issues (disk full, memory leak, service hang) that trigger automatically upon detection.

    4

    Feedback Loop

    Continuously training the models based on incident resolution data to improve accuracy and reduce false positives.

    Technology Stack

    Built on modern, enterprise-grade frameworks and infrastructure.

    Observability

    DatadogNew RelicPrometheusGrafana

    Log Management

    Elasticsearch (ELK)SplunkFluentd

    Incident Response

    PagerDutyOpsgenieServiceNow ITOM

    Why Choose RSA Tech

    Delivering measurable impact through verified engineering excellence.

    90% Faster MTTR
    Reduced Alert Noise
    Proactive Incident Prevention
    24/7/365 Monitoring
    Capacity Planning Insights
    SLO/SLA Management