Google Cloud Pub/Sub vs. Google Compute Engine

If you want to stream high volumes of data, be it for ETL streaming or event sourcing, Google Cloud Pub/Sub is your go-to tool. It's easy to learn, easy to observe its metrics and scales with ease without additional configuration so if you have more producers of consumers, all you need to do is to deploy on k8s your solutions so that you can perform autoscaling on your pods to adjust to the data volume. The DLQ is also very transparent and easy to configure. Your code will have no logic whatsoever regarding orchestrating pubsub, you just plug and play. However, if you are not in the Google Cloud Pub/Sub environment, you might have trouble or be most likely unable to use it since I think it's a product of Google Cloud.

You can use Google Cloud Compute Engine as an option to configure your Gitlab, GitHub, and Azure DevOps self-hosted runners. This allows full control and management of your runners rather than using the default runners, which you cannot manage. Additionally, they can be used as a workspace, which you can provide to the employees, where they can test their workloads or use them as a local host and then deploy to the actual production-grade instance.

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• With a pub/sub architecture the consumer is decoupled in time from the publisher i.e. if the consumer goes down, it can replay any events that occurred during its downtime.
• It also allows consumer to throttle and batch incoming data providing much needed flexibility while working with multiple types of data sources
• A simple and easy to use UI on cloud console for setup and debugging
• It enables event-driven architectures and asynchronous parallel processing, while improving performance, reliability and scalability

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• Scaling - whether it's traffic spikes or just steady growth, Google Compute Engine's auto-scaling makes sure we've got the compute power we need without any manual juggling acts
• Load balancing - Keeping things smooth with that load balancing across multiple VMs, so our users don't have to deal with slow load times or downtime even when things get crazy busy
• Customizability - Mix and match configs for CPU, RAM, storage and whatnot to suit our specific app needs

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• Would be nice if the queue could be extended beyond 7 days.
• We found it a bit tricky replay unacknowledged messages when needed.

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• Built-in monitoring via Stackdriver is quite expensive for what it provides.
• Initially provided quotas (ie. max compute units one can use) are very low and it took several requests to get an appropriate amount.
• Support on GCE is limited to their knowledge base and forums. For more hands-on support provided by Google, you must pay for their Premium services.

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It serves all of our purposes in the most transparent way I can imagine, after seeing other message queueing providers, I can only attest to its quality.

Its pretty good, easy and good performance. Also, interface is very good for starters compared to competitors. Infra as Code (IaC) using Terraform even added easiness for creation, management and deletion of compute Virtual Machines (VM). Overall, very good and very easy cloud based compute platform which simplified infrastructure, very much recommend.

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It is easy to create Google Cloud Pub/Sub topics from both Web Console and CLI commands.

Google Cloud Pub/Sub supports creation of one or more subscriptions.

By supporting a BigQuery Pub/Sub subscription to automatically write to a BigQuery table it simplifies development by avoiding implementation of a custom micro service for writes to BigQuery.

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Having interacted with several cloud services, GCE stands out to me as more usable than most. The naming and locating of features is a little more intuitive than most I've interacted with, and hinting is also quite helpful. Getting staff up to speed has proven to be overall less painful than others.

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I have never faced a single problem in 4 years.

Google Compute Engine works well for cloud project with lesser geographical audience. It sometimes gives error while everything is set up perfectly. We also keep on check any updates available because that's one reason of site getting down. Google Compute Engine is ultimately a top solution to build an app and publish it online within a few minutes

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It's very fast, can be even better if you use protobuf.

It works great all the time except for occasional issues, but overall, I am very happy with the performance. It delivers on the promise it makes and as per the SLAs provided. Networking is great with a premium network, and AZs are also widespread across geographies. Overall, it is a great infra item to have, which you can scale as you want.

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They have decent documentation, but you need to pay for support. We weren't able to answer all our questions with the documentation and didn't have time to setup support before we needed it so I can't give it a higher rating but I think it tends to be a bit slow unless you're a GCP enterprise support customer.

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• The documentation needs to be better for intermediate users - There are first steps that one can easily follow, but after that, the documentation is often spotty or not in a form where one can follow the steps and accomplish the task. Also, the documentation and the product often go out of sync, where the commands from the documentation do not work with the current version of the product.
• Google support was great and their presence on site was very helpful in dealing with various issues.

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Having used Amazon Web Services SNS & SQS I can say that even if the latter may offer more features, Google Cloud Pub/Sub is easier to use. On the other hand, usage of SNS & SQS as well as documentation and troubleshooting is easier with the AWS solution. Since we are not using GCP only for Pub/Sub the choice depends on other variables.

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Google Compute Engine provides a one stop solution for all the complex features and the UI is better than Amazon's EC2 and Azure Machine Learning for ease of usability. It's always good to have an eco-system of products from Google as it's one of the most used search engine and IoT services provider, which helps with ease of integration and updates in the future.

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You can just plug in consumers at will and it will respond, there's no need for further configuration or introducing new concepts. You have a queue, if it's slow, you plug in more consumers to process more messages: simple as that.

It works really well with other Google Cloud services, making it easy to build scalable solutions across different teams and locations.

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• Increased Efficiency with reliable and Google managed services up all the time wit Disaster Recovery in place as well
• Definitely Lower costs being a cloud based solution and easier to setup
• Faster Project delivery and go to market plan for the business use cases basis this technology at the back end

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• With Google Compute we don't have the overhead of managing our own data centers reducing costs and reducing the staff needed to manage systems.
• As I said earlier, Google's costs are ~1/2 of AWS, so we are able to see a ROI much faster.

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