vgt

41 ms·

391.
by vgt 11y ago
Good point on IaaS front. One major use case for GPUs is ML. Google Cloud externalizes its ML through serverless APIs. At that point what matters is your ability to derive value from ML, rather than having exposure to building blocks.
392.
by vgt 11y ago
I'm going to plug Google Cloud's Preemptible VMs as a simpler alternative to Spot Instances: - Preemptible VMs are sold at a fixed 70% off discount, removing pricing volatility entirely - Google Cloud's Compute Engine has far
393.
by vgt 11y ago
Your points resonate with me very strongly, but I do have a counter argument. I work on Google Cloud, where we have both closed-source - BigQuery, open source - Dataproc, and closed source that makes open source rock - Dataflow/Beam. T
394.
by vgt 11y ago
You can listen and read Spotify engineers talking about their experiences with Google, including running 2,000,000 qps load tests without ever telling anyone at Google. If you read some of their blogs, you can see how brutally honest they a
395.
by vgt 11y ago
This narrative gets repeated time and time again, and it really doesn't hold up to even surface debate: - Google TI and Cloud merged. Same teams. Per Urs Holzle in Jan2014 - Just last week Sundar (CEO), Eric Schmidt (chairman), Jeff De
396.
by vgt 11y ago
You can use Colossus today! It's a very low level service, leveraged by other GCP services. For example, Google Cloud Storage and BigQuery Storage both sit on Colossus. Read more on BQ here: https://cloud.google.com/blo
397.
Creating a Serverless ETL Nirvana(blog.shinetech.com)
4 points by vgt 11y ago|0 comments
398.
by vgt 11y ago
Kudos to Looker, great partners here! We're just getting started :)
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by vgt 11y ago
You can always create a dataset and make it public by setting open ACLs to it. The only downside is paying $0.02 per GB per month. To participate in the Public Datasets program, you must contact us - there's a lot of legal mumbo jumbo
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by vgt 11y ago
Ah yes, point well taken. I think we've seen this historically at Google, but things have changed in the past few years.
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by vgt 11y ago
I'm happy to respond to every single person that makes this argument in perpetuity :) There's a difference between experimental free services and Enterprise-grade SLA'd SLO'd fully-supported paid services with a very cle
402.
by vgt 11y ago
Looker has been a great launch partner for this program. Really helped us develop and deliver great interactive dashboards.
403.
by vgt 11y ago
BigQuery is a truly fully-managed service. This means that SREs are on call 24/7. It's not software that one downloads. Hence it really doesn't make a lot of sense to have it available to just a few folks, incremental overhea
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by vgt 11y ago
Sounds like a good one. We'll be sure to reach out to them. Or, if you know them, have them shoot us a note at: bq-public-data@google.com
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by vgt 11y ago
Apologies, but where do you find the implication that these datasets are "big"? There is "big" in BigQuery, so apologize if you misunderstood. We try to keep datasets reasonable, so that folks can get the most out of the
406.
by vgt 11y ago
Google BigQuery is a paid service, Dremel under the hood, used internally at Google by ~80% of Googlers every week. It's simply not going away because Google relies on it heavily. Externally, companies like Spotify and Kabam Games rely
407.
by vgt 11y ago
Of course! BigQuery export operations are free. Although compared with other cloud technologies, BigQuery is incredibly cost-effective :)
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by vgt 11y ago
One large difference between this program and alternative programs is that data already resides in Google BigQuery: - You do not need to spin up a database to work with BigQuery - You can simply start writing SQL on top of BigQuery - You ma
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Google launches Public Datasets program(cloud.google.com)
423 points by vgt 11y ago|93 comments
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BigQuery now charges you just $10,000/mo for a PB of long term storage(cloud.google.com)
2 points by vgt 11y ago|0 comments
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by vgt 11y ago
I'm one of the folks working on BigQuery. Among other improvements, on Wednesday BigQuery dropped price of long term storage by 50%, to just $0.01 per GB per month.
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Google BigQuery – now only $10,000 per month for a Petabyte Data Warehouse(cloud.google.com)
3 points by vgt 11y ago|1 comments
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Snapchat shares security best practices of running in the cloud(cloudplatform.googleblog.com)
2 points by vgt 11y ago|0 comments
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BigQuery drops historical storage cost by 50%, performance 2x-1000x, AVRO format(cloud.google.com)
3 points by vgt 11y ago|0 comments
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by vgt 11y ago
Your story is exactly the story of Atomic Fiction: https://cloudplatform.googleblog.com/2015/10/Atomic-Fiction-...
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by vgt 11y ago
Have you looked at Google's Preemptible VMs? The big difference is that it's a flat 70% off fee, rather than a volatile market, and Google has relatively few but versatile VM types, which makes it easier to architect infrastructur
417.
by vgt 11y ago
When it comes to Big Data, per-minute billing + rapid startup is significant. When you can have a 10,000-core Hadoop cluster in 45 seconds, you stop thinking about it in terms of clusters and start thinking about it in terms of jobs. Before
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Spotify’s experiments with stream processing on Google Cloud Dataflow(cloud.google.com)
1 points by vgt 11y ago|0 comments
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by vgt 11y ago
I think there's tremendous value still in GAE. To this day the fact that a company the size of Snapchat is able to operate on a PaaS, with virtually no ops people, is STILL a game-changer. The fact that it's still true 3+ years in
420.
by vgt 11y ago
While there's arguments on both side for TCO of Cloud, I'll offer one idea - a solution like BigQuery is zero-Ops, lets you scale to thousands of cores in a second, and you pay per-second. This is both cheaper, faster, and easier

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