Spring Cloud Data Flow Status Details
Spring Cloud Data Flow is a platform capable of stream and batch data pipelines having the tools to create delicate topologies.
There are no reported issues during the last 24h.
Use the 'Report an Issue' button to report any issues you may have with the service.
Check out our list of Spring Cloud Data Flow alternatives.
Community feedback on Spring Cloud Data Flow's status
Do you have any problems with the service or want to share a tip?
Spring Cloud Data Flow Alternatives
When Spring Cloud Data Flow is down, try these alternatives
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Try for freeTurn SQL Data into Decisions. Build professional dashboards and data visualizations without technical expertise. Easily embed analytics anywhere, receive automated alerts, and discover AI-powered insights all through a straightforward interface.
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/spark-streaming-alternativesSpark Streaming makes it easy to build scalable and fault-tolerant streaming applications.
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/google-cloud-dataflow-alternativesGoogle Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
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/amazon-kinesis-alternativesAmazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
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/confluent-alternativesConfluent offers a real-time data platform built around Apache Kafka.
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/apache-flink-alternativesFlink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
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/lenses-alternativesDiscover our high quality range of over 40 interchangeable camera lenses including A-mount and E-mount lenses crafted for a range of shooting situations.
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/striim-alternativesStriim provides an end-to-end, real-time data integration and streaming analytics platform.
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Try for free
Turn SQL Data into Decisions. Build professional dashboards and data visualizations without technical expertise. Easily embed analytics anywhere, receive automated alerts, and discover AI-powered insights all through a straightforward interface.
Related status pages
Draxlr status · Spark Streaming status · Google Cloud Dataflow status · Amazon Kinesis status · Confluent status · Apache Flink status · Lenses status · Striim status · Draxlr status ·Status Check FAQ
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Why our public status pages are better than others?
We rely on the combination of both automated checks and user reported issues. Quite often, purely automated uptime monitoring cannot provide the full picture.
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How often do you check if a service is down?
If there are reported issues or interest in a specific service, we might check as frequently as every minute. However, we may check less frequently for services with less interest or fewer reported issues. For example, once every hour.
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What is the best way to report an issue?
The easiest way to report an issue is to use the single-click light-yellow buttons at the top of this page. They represent the most common issues and are the fastest way to report an issue. Nevertheless, you can also use the 'Report an Issue' button or link at the top to report any issue you may have with the service. Also, you are more than welcome to use the comments box and discuss any tips, solutions or resolutions with the community.
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What is "Uptime Monitoring" and do you track it?
Service Uptime Monitoring is a service that checks the availability of a website or service. It can be used to monitor the uptime and downtime of a website or service. Yes, we do track it, but we also rely on user reported issues to provide the most accurate status. Some of the benefits are: Early detection of service disruptions; Better communication with users; Increased reliability.
SaaSHub's Down Detector checks the status of services automatically and regularly. However, we cannot promise 100% accuracy. That is why we depend on user reported issues as well. The Spring Cloud Data Flow status here can help you determine if there is a global outage and Spring Cloud Data Flow is down for everyone or if it is just you who is experiencing problems. Please report any issues to help others know the current status.