Bigtecsys Data Streams Monitoring (DSM).
Bigtecsys Data Streams Monitoring (DSM) is a comprehensive solution designed to monitor and manage data streams effectively across diverse IT environments.
- Monitor data streams in real-time to ensure continuous availability and reliability of data transmission.
- Identify and address performance bottlenecks in data streams to maintain optimal throughput and responsiveness.
DSM provides real-time visibility and control over data streams,ensuring reliability, performance across your IT infrastructure.
Detect slowdowns anywhere in your event-driven applications
To detect slowdowns in event-driven applications and effectively manage latency across your pipeline.
Comprehensive Latency Measurement: Measure latency between any two points in your pipeline, including queues, producers, and consumers. This capability ensures you have visibility into the entire data flow.
Actionable Lag Metrics: Easily identify delayed messages by viewing actionable lag metrics. These metrics should provide insights into latency both in seconds and offset, allowing for quick identification and resolution of issues.
Threshold Monitoring: Set up threshold monitors to detect abnormal latency or throughput across your streaming data pipelines. Define thresholds based on historical data or expected performance metrics to trigger alerts when deviations occur.
Localize and resolve pipeline bottlenecks and failures
To localize and resolve pipeline bottlenecks and failures effectively, follow these steps using advanced monitoring and troubleshooting techniques.
End-to-End Mapping: Automatically map the topology of your pipeline, including dependencies between queues, producers, and consumers. This visualization provides a clear understanding of data flow and dependencies.
Failing Dependency Detection: Easily detect failing dependencies between queues, producers, and consumers. This capability helps in pinpointing where bottlenecks or failures are occurring within the pipeline.
Remediate floods of backed-up messages
To remediate floods of backed-up messages and ensure smooth message flow across your services and queues, implement the following strategies
Downstream Bottleneck Detection: Utilize monitoring tools to quickly detect downstream bottlenecks. This proactive approach helps prevent long lags, message downtime, and delays in message processing.
Resolution: Take immediate action to resolve identified bottlenecks to maintain optimal message flow and prevent accumulation of backed-up messages.
Improved Reliability: Ensure consistent message flow and adherence to SLAs by visualizing and monitoring message flow across dependencies.
Correlate streaming data pipeline metrics with all telemetry in context
To correlate streaming data pipeline metrics with all telemetry and streamline incident response effectively.
Contextual Correlation: Integrate DSM metrics, distributed traces, infrastructure metrics, and logs into a unified monitoring platform. This integration allows for seamless pivoting between different telemetry sources to diagnose and resolve application issues efficiently.
Incident Resolution: Resolve application issues faster by correlating metrics and logs, gaining deeper insights into performance bottlenecks or anomalies across your streaming data pipeline.
Latency and Throughput Metrics: Enhance Kafka or RabbitMQ integration dashboards by adding latency and throughput metrics.
Data Streams Monitoring
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- Goes beyond problem analysis by providing expert advice with table tuning and query advisors
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Bigtecsys was founded by IT professionals solving complex problems in the simplest way. Our digital agility solutions are built to help companies of any size accelerate business transformation today and into the future.