Overhead | Tower defense game , National finalist | Game Engine library

I am trying to understand the example with incorrect sync code from The Go Memory Model.

Double-checked locking is an attempt to avoid the overhead of synchronization. For example, the twoprint program might be incorrectly written as:

I'm developing internal messaging protocol that is based on TCP. Everything works, but I want to add tests to it.

It is possible to test serialization/deserialization with MemoryStream, but I can't find a way to test this thing as whole - with contiguous message interchange, because MemoryStream "ends" after reading first message.

The question: Is there a stream that behaves like NetworkStream (duplex, ends only when other end closed, can't seek) in base library or any nuget package?

Currently I can start 2 TcpClients and use them, but I think it have too much overhead for tests especially when there's hundreds of tests running simultaneously

I'm running gitlab-ce on-prem with min.io as a local S3 service. CI/CD caching is working, and basic connectivity with the S3-compatible minio is good. (Versions: gitlab-ce:13.9.2-ce.0, gitlab-runner:v13.9.0, and minio/minio:latest currently c253244b6fb0.)

Is there additional configuration to differentiate between job-artifacts and pipeline-artifacts and storing them in on-prem S3-compatible object storage?

In my test repo, the "build" stage builds a sparse R package. When I was using local in-gitlab job artifacts, it succeeds and moves on to the "test" and "deploy" stages, no problems. (And that works with S3-stored cache, though that configuration is solely within gitlab-runner.) Now that I've configured minio as a local S3-compatible object storage for artifacts, though, it fails.

There is a Java 11 (SpringBoot 2.5.1) application with simple workflow:

1. Upload archives (as multipart files with size 50-100 Mb each)
2. Unpack them in memory
3. Send each unpacked file as a message to a queue via JMS

When I run the app locally java -jar app.jar its memory usage (in VisualVM) looks like a saw: high peaks (~ 400 Mb) over a stable baseline (~ 100 Mb).

When I run the same app in a Docker container memory consumption grows up to 700 Mb and higher until an OutOfMemoryError. It appears that GC does not work at all. Even when memory options are present (java -Xms400m -Xmx400m -jar app.jar) the container seems to completely ignore them still consuming much more memory.

So the behavior in the container and in OS are dramatically different. I tried this Docker image in DockerDesktop Windows 10 and in OpenShift 4.6 and got two similar pictures for the memory usage.

Dockerfile

I'm learning that Golang channels are actually slower than many alternatives provided by the language. Of course, they are really easy to grasp but because they are a high level structure, they come with some overhead.

Reading some articles about it, I found someone benchmarking the channels here. He basically says that the channels can transfer 10 MB/s, which of course must be dependant on his hardware. He then says something that I haven't completely understood:

If you just want to move data quickly using channels then moving it 1 byte at a time is not sensible. What you really do with a channel is move ownership of the data, in which case the data rate can be effectively infinite, depending on the size of data block you transfer.

I've seen this "move ownership of data" in several places but I haven't seen a solid example illustrating how to do it instead of moving the data itself.

I wanted to see an example in order to understand this best practice.

I have about 200 records that I need to write frequently to DynamoDB and I'm trying to see if the BatchWriteItem saves any overhead in terms of WCU versus iterating PutItem 200 times. Other than the number of network requests sent, does BatchWriteItem lower the amount of WCU used?

Suppose a class myClass has two method definitions _call1 and _call2, but only one of them should be used depending on a parameter passed when the object is instantiated, and a specific alias call is given for the chosen method. How to program this? A minimum example is shown below.

The reason behind this code is that I would like to avoid the overhead of having an if-else statement with two possible returns inside a single call method. Another option would be to create two different possible classes based on cond_param, but I'd rather avoid that.

Since the node v10 changes to Cloud Functions, one thing that we've come to accept is a default storage bundle within our GCP of which accrues a cost of ~$0.03 a month. It is believed to be Docker cache files that store the Cloud Functions, Node Modules, and Hosting Revisions.

But on an almost empty project, how can you have 535MB in storage when the source is only 83MB total?

• no hosting
• 2 cloud functions

What are the contents of the Files? is it overhead for the revision history? is there any reasonable way to minimize it? I get asked these questions many times and I do not have an answer that I feel comfortable with.

I have a callable struct Foo defined as