IBM Cloud Apache Spark icon
IBM Cloud Apache Spark icon

Is IBM Cloud Apache Spark down?
IBM Cloud Apache Spark is UP

Last checked from IBM Cloud Apache Spark official status page 3 min. 48 sec. ago

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IBM Cloud Apache Spark service health

This chart represents IBM Cloud Apache Spark service health over the last 24 hours, with data points collected every 15 minutes based on issue reports, page visits, and signal strength. Sign up for free to see more IBM Cloud Apache Spark status data.

Service is up
Potential issue
Likely issue

Top reported issues

View and upvote the most commonly reported issues to help us better indicate the service status.

  • Connectivity issue
  • Error message
  • Server not responding
  • Sign in problem
  • Service down
  • Slow performance
  • Unable to download
  • App not loading
  • Other

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IBM Cloud Apache Spark status history

We've been monitoring IBM Cloud Apache Spark outages since November 25, 2018. Here's the history of service outages we've observed from the IBM Cloud Apache Spark Status Page

60 days ago Today
Up
Down
Warn
Maintenance
Unknown

Recent IBM Cloud Apache Spark outages and issues

Follow the recent outages and downtime for IBM Cloud Apache Spark in the table below.

Incident Name Duration Started Severity
Minor incident
2085d 22h 11m
warn icon Warn
Major incident
1m
down icon Down
Major incident
12d 12h 47m
down icon Down

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Get notified about IBM Cloud Apache Spark outages

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Features covering most of your needs in monitoring and communicating outages or downtime.

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About our IBM Cloud Apache Spark status page integration

IBM Cloud Apache Spark is a Cloud Infrastructure solution that StatusGator has been monitoring since November 2018. Over the past about 6 years, we have collected data on on more than 1,865 outages that affected IBM Cloud Apache Spark users. When IBM Cloud Apache Spark publishes downtime on their status page, they do so across 9,634 components and 97 groups using 4 different statuses: up, warn, down, and maintenance which we use to provide granular uptime metrics and notifications.

More than 100 StatusGator users monitor IBM Cloud Apache Spark to get notified when it's down, is under maintenance, or has an outage. We've sent more than 12,200 notifications to our users about IBM Cloud Apache Spark incidents, providing transparency and peace of mind. You can get alerts by signing up for a free StatusGator account.

  • Down Notifications

    If IBM Cloud Apache Spark is having system outages or experiencing other critical issues, red down notifications appear on the status page. In most cases, it means that core functions are not working properly, or there is some other serious customer-impacting event underway.

  • Warning Notifications

    Warn notifications are used when IBM Cloud Apache Spark is undergoing a non-critical issue like minor service issues, performance degradation, non-core bugs, capacity issues, or problems affecting a small number of users.

  • Maintenance Notifications

    IBM Cloud Apache Spark posts separate notifications for planned maintenance work. StatusGator will notify subscribers when IBM Cloud Apache Spark enters a pre-planned maintenance window, keeping you up to date.

  • Status Messages

    When IBM Cloud Apache Spark posts issues on their status page, we collect the main headline message and include that brief information or overview in notifications to StatusGator subscribers.

  • Status Details

    When IBM Cloud Apache Spark has outages or other service-impacting events on their status page, we pull down the detailed informational updates and include them in notifications. These messages often include the current details about how the problem is being mitigated, or when the next update will occur.

  • Component Status Filtering

    Because IBM Cloud Apache Spark has several components, each with their individual statuses, StatusGator can differentiate the status of each component in our notifications to you. This means, you can filter your status page notifications based on the services, regions, or components you utilize. This is an essential feature for complex services with many components or services spread out across many regions.

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