Datorios is a powerful observability platform tailored for Apache Flink, providing unparalleled visibility into your data streams. Whether you’re running large-scale streaming applications or managing complex event processing, Datorios equips your team with the insights needed to maintain peak performance and reliability.
Get a detailed overview of your Flink jobs, including session data, statistics, and processed record tracking. This helps identify inefficiencies and optimize job execution.
Monitor state evolution throughout operators event processing. Easily identify state changes occurring during processing.
Gain deep visibility into Flink states and checkpointing. Understand how state size and checkpoint execution impact job and cluster performance. Uncover the complex interactions between data, code, and infrastructure to enhance problem-solving and optimization.
Access real-time insights into resource utilization, throughput, and latency across your Flink job. Identify bottlenecks and optimize execution using custom metrics.
Capture and store detailed logs for every event processed by Apache Flink. Access historical logs to troubleshoot errors and optimize performance by tracing system behavior across jobs.
Learn more about how BYOC can elevate your Apache Flink observability while keeping your cloud environment secure.
Follow data records as they flow through your Flink jobs. Trace the path from source to sink, uncover transformation points, and quickly identify bottlenecks or errors with precise real-time tracking.
Analyze the evolution of the state within Apache Flink. State Investigation allows you to see how the state changes over time, providing critical insights into operator behavior to refine your data flows with precision.
Visualize various time windows (tumbling, sliding, session) to identify events within each window and detect missing data, offering a comprehensive view of your data.
Utilize interactive job graphs to trace your data back from sink to source for process validation and bad quality data source causes.
Datorios extracts certain client statistical information. All customer data remains visible only to the customer.
The Datorios client collects record metadata, state data, window details, along with Logs and Metrics produced by Flink.
The data collected by the Datorios client is either hashed or encrypted based on your preference, and then it is uploaded to Datorios using SSL to our internal backend.
Yes, you can permanently delete any job and its associated data by navigating to the job screen and clicking the trashcan icon. To remove your organization, go to the organization screen and click the wheel cog at the top right corner.
Datorios supports Java, Python, and Scala.
Datorios supports Flink version 1.6.x and above. For specific requirements, please contact us.
Yes, Datorios allows you to run in either session mode or application mode.
Datorios supports installation via Docker and Kubernetes. For other installation types, please contact us.
Datorios continuously collects metrics and logs, similar to other observability products like Datadog and Prometheus. Tracing data is collected only when triggered by specified metrics exceeding thresholds.
Yes.
Yes.
No, Datorios uses a cache that continuously overwrites itself until a critical event is recognized. Only three minutes of data before a critical event are stored.
Yes, click here to get started.
Yes, please refer to our GitHub and the preloaded jobs available in the application.
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