Iris - 将观察转化为可行动的见解，以提升决策能力

Iris (/ˈaɪrɪs/), a name inspired by the Olympian mythological figure who personified the rainbow and served as the messenger of the gods, is a comprehensive observability platform for Extract, Transform, Load (ETL) jobs. Just as the mythological Iris connected the gods to humanity, our Iris platform bridges the gap between raw data and meaningful insights, serving the needs of data-driven organisations. Specialising in meticulous monitoring and tracking of Spark and Presto jobs, Iris stands as a transformative tool for peak observability and effective decision-making.

Iris（/ˈaɪrɪs/）是一个全面的可观察性平台，用于提取、转换和加载（ETL）作业。正如神话中的Iris将众神与人类联系在一起，我们的Iris平台弥合了原始数据和有意义见解之间的鸿沟，满足数据驱动型组织的需求。Iris专注于对Spark和Presto作业进行细致的监控和跟踪，是一个用于实现最佳可观察性和有效决策的变革性工具。

Iris captures critical job metrics right at the Java Virtual Machine (JVM) level, including but not limited to runtime, CPU and memory utilisation rates, garbage collection statistics, stage and task execution details, and much more.
Iris在Java虚拟机（JVM）级别捕获关键作业指标，包括但不限于运行时间、CPU和内存利用率、垃圾回收统计、阶段和任务执行详情等等。
Iris not only regularly records these metrics but also supports real-time monitoring and offline analytics of metrics in the data lake. This gives you multi-faceted control and insights into the operational aspects of your workloads.
Iris不仅定期记录这些指标，还支持数据湖中指标的实时监控和离线分析。这使您能够多方面地控制和洞察工作负载的运营方面。
Iris gives you an overview of your jobs, predicts if your jobs are over or under-provisioned, and provides suggestions on how to optimise resource usage and save costs.
Iris为您提供作业概览，预测作业是否过度或不足配置，并提供优化资源使用和节省成本的建议。

When examining ETL job monitoring across various platforms, a common deficiency became apparent. Existing tools could only provide CPU and memory usage data at the instance level, where an instance could refer to an EC2 unit or a Kubernetes pod with resources bound to the container level.

在检查各种平台上的ETL作业监控时，一个常见的缺陷变得明显。现有工具只能在实例级别提供CPU和内存使用数据，其中实例可以是绑定到容器级别的EC2单元或Kubernetes pod。

However, this CPU and memory usage data included usage from the operating system and other background tasks, maki...