[obulpathi]

Two things keep coming up while comparing GCP and AWS:

* This accomplishment would not have been possible for our three-person team of engineers with out Google Cloud (AWS is too low level, hard to work with and does not scale well).

* We’ve also managed to cut our infrastructure costs in half during this time period (Per minute billing, seamless autoscaling, performance, sustained usage discounts, ... )

[vira28]

This thread here came at the right time. Today whole day I attended the DynamoDB training. Honestly, one thing that I understood is its cost based on reads and writes per second. Irrespective of the amount of read data per operation (whether its 1 bytes or 100 bytes), its always charged for 1KB. So, as a work around what they suggested is using a Kinesis, a Lambda and an another service to make the write operation as a batch, in such a way the reads are near 1KB always. He pitched it like thats the perfect way to do. The problem I see is too many moving pieces for a simple thing to achieve. If the Dynamo team makes the reads cost based on the actual data we are all set.

[obulpathi]

Yep, same problems with many other services:

* Kinesis Streams: Writes limited to 1K/sec and 1 MB / shard, reads limited to 2K/shard. Want a different read/write ratio? Nop, not possible. Proposed solution: use more shards. Does not scale automatically. There is another service called Kinesis Streams that does not offer read access to streaming data.

* EFS: Cold start problems. If you have small amount of data in EFS, reads and writes are throttled. Ran into into some serious issues due to write throttling.

* ECS: Two containers can not use same port on same node. Anti pattern to containers.

AWS services have lots of strings attached and minimums for usage and billing. Building such services (based on fixed quotas) is much easier than building services which are billed purely pay per use. This complexity + cost optimization pressures lead to complexity and require more human resources and time as well. AWS got good lead in Cloud space, but they need to improve their services without letting them rot.

[vira28]

Agree totally. The solution to overcome those shortcomings in AWS, is to sort of put bandaid's with more services (at least their suggestion). I do understand, its not feasible to provide service which fits for everyone, however it will be good if they solve the fundamental problem.

One more to add in the list.

In DynamoDB during peak (or rush hour) you can scale which increases the underlying replica's(or partitions) to keep the reads smooth. However, after the rush hour there is no way to drop those additional resources. May be someone can correct me, if I am wrong.

[BoorishBears]

You can scale down, but it is limited.

You start each 24hr period with 4 chances to scale down, and after those are depleted you can scale down once every 4 hrs regardless

[bonesss]

You can scale DynamoDB down the same way you scale it up.

Perhaps you're thinking of some kind of autoscaling that only works in one direction?

[vira28]

Thanks. Not the auto scaling part. I thought even manually if you scale up with new replica's, we can't scale down. I should read the manual and get a clear picture.

[oblio]

> * ECS: Two containers can not use same port on same node. Anti pattern to containers.

Could you elaborate for this? I'm not sure I understand, are you saying that 2 containers cannot be mapped to the same host port? Because that would seem normal, you can't bind to a port where there's already something listening. But I guess I must be missing something.

[steven_h]

The OP is talking about how when using a classic load balancer in AWS, your containers will be deployed all exposing the same port, kind of like running "docker run -p 5000:5000" on each ec2 in your cluster. Once the port is in use, you can't deploy another of that container on the same ec2 node.

The solution is to use AWS's Application Load Balancers instead, which will allow you dynamically allocate ports for your containers and route traffic into them as ECS Services.

[alexeldeib]

I'm not familiar with the details of AWS here, but maybe the OP means mapping two different host ports to the same port on two different containers? That's all I can imagine that would be a container antipattern in the way described.

[hobofan]

That is perfectly possible with ECS, so I don't know what OP was referring to. The thing I remember though is that you have to jump through a lot of hoops like making 4 APIs calls (or worse with pagination) for what should have been a single call to make such a system work on ECS.

[eicnix]

Nowaday you would often run containers with a container network(flannel, calico, etc.) that assigns an unique IP per container thus avoids conflicting port mappings regardless how many containers with the same port run on a single host.

[kuschku]

Or you have them on a physical private network, each bound to a separate IP, but yes.

[teoruiz]

> * ECS: Two containers can not use same port on same node. Anti pattern to containers.

That's solved if you use Application Load Balancer instead of ELB classic for your ECS service.

[tim333]

>too many moving pieces for a simple thing to achieve

Maybe put all the users data in a blob with a JSON.stringify type thing and then JSON.parse it when you get it back?

[fha]

> AWS . . . does not scale well

GCP may have some advantages over AWS, but the reverse is also true and it's hard to take what you say seriously when you say something like that.

[obulpathi]

Adding more context. Sorry for missing it out in first place. I mostly work in Big Data Space. Google Clouds Big Data stuff is built for Streaming / Storing / Processing / Querying / Machine Learning at Internet Scale data (PubSub / Bigtable / Dataflow / BigQuery / Cloud ML). AWS scales to terabyte level loads. But, beyond that, its hard and super costly. Google's services autoscale to Petabyte levels / millions of users smoothly (for example BigQuery / Load Balancers). On AWS, it requires pre warming / allocating capacity beforehand and that costs tons of money. In companies working at that scale, that usual saying is "to keep scaling, keep throwing cash at AWS". This is not a problem with Google.

[look_lookatme]

You need petabyte scale for the NYT Crossword?

[obulpathi]

Quoting from the article: "This accomplishment would not have been possible for our three-person team of engineers to achieve without the tools and abstractions provided by Google and App Engine."

Talking about the use case from the article, they release the puzzle at 10 and need to have infra ready to serve up all the requests. On AWS, you need to pre warm load balancers, increase the quota of your Dynamo DB, scale up instances so that they can withstand the wall of traffic, ... and then scale down after the traffic. All this takes time, people and money. Adding few other things author mentioned: Monitoring/Alerting, Local Development, Combined Access and App Logging ... will take focus from developing great apps to building out the infrastructure for apps.

[sigmaml]

I concur.

Currently, I am working on projects that use both Amazon and Google clouds.

In my experience, AWS requires more planning and administration to handle the full workflow: uploading data; organisation in S3; partitioning data sets; compute loads (EMR-bound vs. Redshift-bound vs. Spark (SQL) bound); establishing and monitoring quotas; cost attribution to different internal profit centres; etc.

GCP is - in a few small ways - less fussy to deal with.

Also, GCP console - itself not very great - is much easier to use and operate than AWS console.

Of course, YMMV!

[jacquesm]

Could you please post the URL for the resource and the number of hits it receives? I'm interested in high load websites and I have a hard time picturing how this could lead to petabytes.

[joatmon-snoo]

The impression I'm getting is not that GCP scales better, but it scales with less fuss - the anecdotes here all suggest that with AWS, once you hit any meaningful load (i.e. gigabytes), you need to start fiddling with stuff.

I don't know if this is actually true, I've never done any serious work in AWS.

[zjaffee]

Hold on, please do not say google cloud scales well, yes they do have services that make a ton of claims, but unlike AWS, things don't work as promised which is magnified by the fact that their support is way worse.

Additionally, Big Query is far more expensive than Athena, where you have to pay a huge premium on storage.

The biggest difference is that what amazon provides you in infrastructure, where as google provides you a platform. While app engine is certainly easier to use than elastic bean stalk, you have very little control over what is done in the background once you let google do its thing.

[manigandham]

GCP support can sometimes be bad but these other claims don't add up. What isn't working as promised? BigQuery can do a lot more than Athena and it's storage pricing is the same or cheaper than S3.

We've used 5 different providers for a global system and GCP has won by both performance and price. We still use Azure and AWS for some missing functionality but the core services are much more solid and easy to deal with on GCP, which is also far more than just app engine.

[CharlesW]

Totally. Also…

> AWS is too low level

It seems very strange to paint AWS with such a broad brush, considering that AWS has tons of services at various levels of abstraction (including high-level abstractions like Elastic Beanstalk and AWS Lambda).

[obulpathi]

Sorry to not add context. I was referring to the use case the author of article was talking about: running a website: You need to stitch: ELB / EC2 / Database / Caching / Service Splitting / Auth / Scaling / ... Where as on Google Cloud, App Engine covers most of the points.

[tomcam]

Jeez, you're taking a lot of hits. Thanks for the patient answers

[obulpathi]

Thanks for your kind comment!