slayerjain

I wonder about the size comparison between the M1 Ultra and surface area of the equivalent 'Ryzen CPU + Radeon GPU + RAM :D'

Thanks! We are building integrations based on community requests, we'll combine that into a detailed roadmap. Support JS, Java and python is WIP

Thanks for having a look! We already support gRPC clients and gRPC server support is coming soon!

https://github.com/keploy/go-sdk#grpc

Hi HN, I built this because I was tired of writing test cases for my APIs, especially writing mocks for external services or databases.

Would love you to try and provide your feedback.

Fun fact: we use Keploy to test Keploy :D

I just moved from AWS DynamoDB to MongoDB serverless for a project due to the 400KB document size limitation on DynamoDB (as opposed to around 16MB on Mongo). Feeling nervous after reading all the comments.

based on the relative differences between the m1 and the m1 pro/max, and also the comparisons shown by apple to other laptops from the MSI and Razerblade both featuring the RTX 3080.

maybe around next fall

And in the case for the M1 Pro, apple is showing it to be faster than the Lenovo 82JW0012US - which has a RTX 3050ti. so the performance could be between RTX 3050ti - RTX 3060. All of this with insanely low power draw.

Based on the numbers it looks like the M1 Max is in the RTX 3070-3080 performance territory. Sounds like mobile AAA gaming has potential to reach new heights :D

Thanks! Would be awesome if you could try and provide some feedback. Please feel to reach me for any support.

I had this idea while trying out harness.io and its lack of support of flux-like GitOps. You can integrate this api with your CD platform for canary deployments (eg: flux-flagger/Argo) and this would look at your log and metrics data and report abnormal behaviour with your applications. Looking forward to feedbacks, it seems my last post was flagged because the signup button wasn't visible. We've fixed that, and if there's any other difficulties please comment - we'll fix it asap :) Note: We currently only support Linkerd, Istio support is coming soon.

I had this idea while trying to make "AIOps" work with flux on my Kubernetes cluster. You can integrate this api with your CD platform for canary deployments (eg: flagger/Argo) and this would look at your log and metrics data and report abnormal behaviour with your applications.

The API is currently FREE, so please feel free to try and drop a feedback. Looking forward to connecting about your experiences :)

Note: We currently only support Linkerd, Istio support is coming soon.

and what about the M1 unified memory? I'm sorry, I'm not a memory expert :)

That's interesting. I know there's no reference for it being ECC, but do you know for sure it's not ECC?

Since the RAM is packaged into the SOC, and these chips are probably going to be scaled up to high-end workstations, I thought Apple might have done something about ECC memory.

The cat would just eat the mouse, not so much for programming XD

I just got a 16GB M1 MBP, and I can see the HDR option in Youtube even on the inbuilt display. Didn't know that the inbuilt display supported HDR too. I thought HDR was going to be reserved for the future mini-LED displays.

If the graphics performance also get good boosts, mac minis could become a more versatile playstation/xbox alternative! Assuming the games are there of-course.

Maybe they'd launch a more expensive 4 USB-C/Thunderbolt ports model with their more powerful chip (and upto 64/128GB memory) like they did with the earlier MBP13s.

I think MacBook Air is very compelling, and that's why got more screen time. Unless you want to run your system on >60% for extended periods of time - MacBook Air should be great.

Pros: * Amazing chips. Probably more faster than both i9 MacBook Pro 16 and iMac Pros, and GREAT battery life! * Finally better camera and wifi 6 * same price

Cons: * Wont not run all apps in full speed for now (temporary) * Memory expansion is expensive and limited to 16GB (temporary)

Most limitations are temporary, I think these are amazing products unless you want more than 16GB memory.

Yes. The same class desktop counter part (GPU/CPU) are generally faster than their laptop counter parts while remaining cheaper and more versatile

For Hobby projects I'm loving Lambda proxy from AWS Labs. I'm able to use native Golang frameworks like gin/echo without changing anything much and deploying to Lambda + API gateway. This runs for basically free, and is easy to port out.

AWS now also provides native support for deploying 'regular' web apps using lambda + API gateway. I've been using this for my hobby projects - https://github.com/awslabs/aws-lambda-go-api-proxy

Is this solving the same problem as CloudFoundary for K8s? https://github.com/cloudfoundry/cf-for-k8s

What are other docker/k8s based PaaS you've tried?

We allow professionals to take feedback and retain them even after switching companies.

Users also can track their soft-skills progress and also get a public summary profile. It’ll give a deeper look into an individual’s soft-skills than LinkedIn.

Just to clarify this is 200GB per customer.

The problem with multi tenant software is the overall complexity which should also translate to cost . Also releases requires having to keep adding feature flags/config.

I'm a bit afraid that this may lead to a very brittle software/architecture in long term.

In my case specifically, the product is logistics operation management software with different types of users like operations team, drivers, customer support etc. The product automates pickup, routing, delivery of packets etc. So it's an operational heavy product.

This is really awesome! thanks for this :D