Sign Up

Sign Up to our social questions and Answers Engine to ask questions, answer people’s questions, and connect with other people.

Have an account? Sign In

Have an account? Sign In Now

Sign In

Login to our social questions & Answers Engine to ask questions answer people’s questions & connect with other people.

Sign Up Here

Forgot Password?

Don't have account, Sign Up Here

Forgot Password

Lost your password? Please enter your email address. You will receive a link and will create a new password via email.

Have an account? Sign In Now

You must login to ask a question.

Forgot Password?

Need An Account, Sign Up Here

Please briefly explain why you feel this question should be reported.

Please briefly explain why you feel this answer should be reported.

Please briefly explain why you feel this user should be reported.

Sign InSign Up

The Archive Base

The Archive Base Logo The Archive Base Logo

The Archive Base Navigation

  • Home
  • SEARCH
  • About Us
  • Blog
  • Contact Us
Search
Ask A Question

Mobile menu

Close
Ask a Question
  • Home
  • Add group
  • Groups page
  • Feed
  • User Profile
  • Communities
  • Questions
    • New Questions
    • Trending Questions
    • Must read Questions
    • Hot Questions
  • Polls
  • Tags
  • Badges
  • Buy Points
  • Users
  • Help
  • Buy Theme
  • SEARCH
Home/ Questions/Q 936811
In Process

The Archive Base Latest Questions

Editorial Team
  • 0
Editorial Team
Asked: May 15, 20262026-05-15T21:22:23+00:00 2026-05-15T21:22:23+00:00

Does Google’s App Engine have excessive downtime, specifically with regards to datastore writes? Additionally,

  • 0

Does Google’s App Engine have excessive downtime, specifically with regards to datastore writes?

Additionally, downtime seems to be scheduled during high traffic times, e.g., in the middle of the afternoon vs. 3:00AM in the morning. Is this normal? Will it improve as the technology matures?

  • 1 1 Answer
  • 0 Views
  • 0 Followers
  • 0
Share
  • Facebook
  • Report

Leave an answer
Cancel reply

You must login to add an answer.

Forgot Password?

Need An Account, Sign Up Here

1 Answer

  • Voted
  • Oldest
  • Recent
  • Random
  1. Editorial Team
    Editorial Team
    2026-05-15T21:22:23+00:00Added an answer on May 15, 2026 at 9:22 pm

    Short Answers

    1. Afternoon vs early morning downtime. The datastore has been unavailable for writes about 20-30% more often in the afternoon than in the wee hours of the morning (Pacific time; includes put, update, and delete availability).

      Note: I’m sure Google would like downtime to occur during off-peak hours. Thus I expect they’ll continue to try to minimize downtime, or schedule it for off-peak hours whenever possible.

    2. Downtime trending. The number of 15-minute periods during which the datastore has been unavailable has been decreasing. In the past 366 days, there were an average of 3.8 15-minute periods in which the datastore was unavailable per day. In the past 200 days, this has decreased by 60% to 2.3 per day. Write downtime over the past few months has actually been quite good – since March 1st, there have been less than 0.25 15-minute chunks of write downtime per day. Here’s a graph of datastore write downtime:
      Downtime trending http://imagebin.ca/img/4wkHVQPc.png


    Source of Answers

    To answer your question, I wrote this script which extracts downtime data from GAE’s Datastore Status page.


    Graphs

    Datastore write downtime from 2009-Jul-20 to 2010-Jul-20 (4 hour bins):

    alt text http://imagebin.ca/img/p9ScWTm.png

    Datastore write downtime from 2009-Jul-20 to 2010-Jul-20 (1 hour bins):

    alt text http://imagebin.ca/img/9FbLut2G.png

    Datastore downtime from 2009-Jul-20 to 2010-Jul-20 (4 hour bins):

    alt text http://imagebin.ca/img/t3XKLk.png

    Datastore downtime from 2010-Jan-01 to 2010-Jul-20 (4 hour bins):

    alt text http://imagebin.ca/img/k36T9h.png


    Raw data

    (you can tweak the variables at the top of the script if you’d like to collect your own data with slightly different parameters):

    # RAW Data: Each element counts the number of days in which the datastore
    # was unavailable for at least some portion of a given 15-minute window. The
    # first element corresponds to the time chunk from 00:00 to 00:15, and so on.
    RESULTS_SINCE_2010JAN01_BIN15 = [0, 0, 0, 0, 3, 11, 3, 3, 3, 3, 12, 3, 3, 3, 4, 14, 4, 4, 4, 4, 12, 2, 2, 2, 2, 14, 4, 4, 4, 4, 11, 2, 2, 2, 2, 11, 5, 5, 5, 5, 13, 4, 4, 4, 4, 14, 7, 5, 5, 5, 14, 4, 3, 3, 3, 13, 2, 2, 2, 2, 12, 5, 4, 4, 4, 14, 5, 3, 3, 3, 12, 7, 2, 2, 2, 5, 5, 0, 0, 0, 2, 9, 3, 2, 2, 2, 10, 1, 1, 1, 2, 9, 3, 3, 3, 15]
    RESULTS_SINCE_2009JUL20_BIN15 = [0, 0, 0, 0, 11, 21, 5, 5, 5, 5, 29, 6, 6, 6, 7, 38, 11, 11, 11, 11, 37, 7, 7, 7, 7, 44, 12, 12, 12, 12, 37, 10, 10, 10, 10, 34, 7, 7, 7, 7, 46, 11, 11, 11, 11, 39, 15, 13, 13, 13, 44, 13, 12, 12, 12, 44, 5, 5, 5, 5, 34, 11, 10, 10, 10, 40, 13, 11, 11, 11, 31, 21, 12, 12, 11, 19, 21, 4, 4, 4, 13, 28, 10, 9, 9, 16, 36, 10, 10, 10, 12, 32, 7, 7, 6, 35]
    RESULTS_WRITE_DOWNTIME_SINCE_2009JUL20_BIN15 = [0, 0, 0, 0, 4, 12, 4, 4, 4, 4, 22, 6, 6, 6, 7, 27, 7, 7, 7, 7, 21, 6, 6, 6, 6, 32, 9, 9, 9, 9, 26, 8, 8, 8, 8, 27, 7, 7, 7, 7, 30, 7, 7, 7, 7, 27, 10, 8, 8, 8, 28, 10, 9, 9, 9, 28, 4, 4, 4, 4, 21, 4, 4, 4, 4, 25, 6, 4, 4, 4, 18, 14, 9, 10, 9, 16, 17, 2, 2, 2, 8, 18, 7, 6, 6, 9, 19, 5, 5, 5, 6, 18, 5, 5, 4, 21]
    
    # RESULTS DISTILLED FROM COLLECTED_RESULTS
    RESULTS_SINCE_2010JAN01_BIN60 = [RESULTS_SINCE_2010JAN01_BIN15[i*4]+RESULTS_SINCE_2010JAN01_BIN15[i*4+1]+RESULTS_SINCE_2010JAN01_BIN15[i*4+2]+RESULTS_SINCE_2010JAN01_BIN15[i*4+3] for i in xrange(24)]
    RESULTS_SINCE_2010JAN01_BIN240 = [RESULTS_SINCE_2010JAN01_BIN60[i*4]+RESULTS_SINCE_2010JAN01_BIN60[i*4+1]+RESULTS_SINCE_2010JAN01_BIN60[i*4+2]+RESULTS_SINCE_2010JAN01_BIN60[i*4+3] for i in xrange(6)]
    RESULTS_SINCE_2010JAN01_BIN480 = [RESULTS_SINCE_2010JAN01_BIN60[i*2]+RESULTS_SINCE_2010JAN01_BIN60[i*2+1] for i in xrange(3)]
    RESULTS_SINCE_2009JUL20_BIN60 = [RESULTS_SINCE_2009JUL20_BIN15[i*4]+RESULTS_SINCE_2009JUL20_BIN15[i*4+1]+RESULTS_SINCE_2009JUL20_BIN15[i*4+2]+RESULTS_SINCE_2009JUL20_BIN15[i*4+3] for i in xrange(24)]
    RESULTS_SINCE_2009JUL20_BIN240 = [RESULTS_SINCE_2009JUL20_BIN60[i*4]+RESULTS_SINCE_2009JUL20_BIN60[i*4+1]+RESULTS_SINCE_2009JUL20_BIN60[i*4+2]+RESULTS_SINCE_2009JUL20_BIN60[i*4+3] for i in xrange(6)]
    RESULTS_SINCE_2009JUL20_BIN480 = [RESULTS_SINCE_2009JUL20_BIN240[i*2]+RESULTS_SINCE_2009JUL20_BIN240[i*2+1] for i in xrange(3)]
    RESULTS_WRITE_DOWNTIME_SINCE_2009JUL20_BIN60 = [RESULTS_WRITE_DOWNTIME_SINCE_2009JUL20_BIN15[i*4]+RESULTS_WRITE_DOWNTIME_SINCE_2009JUL20_BIN15[i*4+1]+RESULTS_WRITE_DOWNTIME_SINCE_2009JUL20_BIN15[i*4+2]+RESULTS_WRITE_DOWNTIME_SINCE_2009JUL20_BIN15[i*4+3] for i in xrange(24)]
    RESULTS_WRITE_DOWNTIME_SINCE_2009JUL20_BIN240 = [RESULTS_WRITE_DOWNTIME_SINCE_2009JUL20_BIN60[i*4]+RESULTS_WRITE_DOWNTIME_SINCE_2009JUL20_BIN60[i*4+1]+RESULTS_WRITE_DOWNTIME_SINCE_2009JUL20_BIN60[i*4+2]+RESULTS_WRITE_DOWNTIME_SINCE_2009JUL20_BIN60[i*4+3] for i in xrange(6)]
    RESULTS_WRITE_DOWNTIME_SINCE_2009JUL20_BIN480 = [RESULTS_WRITE_DOWNTIME_SINCE_2009JUL20_BIN240[i*2]+RESULTS_WRITE_DOWNTIME_SINCE_2009JUL20_BIN240[i*2+1] for i in xrange(3)]
    
    • 0
    • Reply
    • Share
      Share
      • Share on Facebook
      • Share on Twitter
      • Share on LinkedIn
      • Share on WhatsApp
      • Report

Sidebar

Explore

  • Home
  • Add group
  • Groups page
  • Communities
  • Questions
    • New Questions
    • Trending Questions
    • Must read Questions
    • Hot Questions
  • Polls
  • Tags
  • Badges
  • Users
  • Help
  • SEARCH

Footer

© 2021 The Archive Base. All Rights Reserved
With Love by The Archive Base

Insert/edit link

Enter the destination URL

Or link to existing content

    No search term specified. Showing recent items. Search or use up and down arrow keys to select an item.