DataStream use cases

DataStream proves an unparalleled tool on many occasions. Let’s have a look at the most typical ones.

Monitoring

You can configure your data streams to send raw logs every 30 seconds or aggregated logs as often as every minute. This low latency streaming can help you proactively monitor performance, detect, and quickly resolve performance degradations.

You can use a preferred log analytics platform to continuously ingest logs and set up real-time dashboards or alerts. This helps you proactively mitigate connectivity problems, service disruptions, and configuration-tuning complications as well as minimize your mean time to recovery (MTTR).

You can use DataStream for:
Performance and QoS monitoring
  • Proactively monitor performance, detect, and quickly resolve performance degradations.
  • Determine traffic split based on real time performance and availability metrics.
  • Validate the success of your new code or CDN configuration enhancements in real time. You can do this type of monitoring in production and at scale, without risking downtime or jeopardizing end-user experience. At the same time, you can measure the impact of a recent code change or new deployments on CDN health, efficiency, and usage.
Event monitoring
  • Monitor live and streaming events
  • Monitor software and game releases
Usage tracking
Monitor for usage spikes to avoid exceeding commits.
Alerting
Receive alerts with potential issues based on violation of thresholds.

Troubleshooting

After you’ve detected an issue, you need the necessary data to investigate and isolate the root cause. The log data you receive can help enable long term trend analysis. You can use your data to perform:

  • Forensic analysis
  • Session analysis
  • Content analysis
DevOps and diagnostics
Understand the impact of changes caused by the configuration, player, or workflow updates

You can receive pre-aggregated metrics over a specific window of time. Use this option to easily switch between aggregated and raw data views for diagnostics or root cause analysis.

For example, you can have your aggregated stream always on for a continuous, high-level view of your CDN health. If the aggregated logs identify high error counts or high average origin response times, you can turn on a raw logs stream for root cause analysis and diagnostics.

Benchmarking
Access recent data for up to 12 hours on CDN health, efficiency, and usage for analysis and benchmarking, without the overhead of managing an endpoint infrastructure.