App Engine Flex beta deploy fails

When using gcloud beta app deploy app.development.yml --version development, it fails with [13] Error while processing files.

This same command works fine with gcloud app deploy, I don’t understand what the issue is.

Here is my app.deployment.yml:

service: development-api entrypoint: bundle exec foreman start env: flex runtime: ruby  env_variables:   SECRET_KEY_BASE: "some_secret_key"  beta_settings:   cloud_sql_instances: "cloud_sql_connection"  manual_scaling:   instances: 1 resources:   cpu: 1   memory_gb: 0.5   disk_size_gb: 10  network:   instance_tag: development-api-net   name: nonprod-network   subnetwork_name: nonprod-subnetwork-1  includes:   - credentials.yaml 

Has anyone seen this error before?

Rules and Facts (cyclic ?) definition in an inference engine

I am working on an backwards chaining engine as a school project. Until now, I have mostly done projects in C, and so I decided to try Haskell for that projet. I have read LYAH in order to get started and have begun to implement the representation of rules and facts in my inference engine. So far, this is what I got

module Inference () where  type Op = Bool -> Bool -> Bool type Label = String type Fact = (Label, [Rule]) data Rule = Operation Rule Op Rule           | Fact Fact  eval_fact:: [Label] -> Fact -> Bool eval_fact proved (label,rules) = label `elem` proved || any (eval_rule proved) rules  eval_rule:: [Label] -> Rule -> Bool eval_rule proved (Fact x) = eval_fact proved x eval_rule proved (Operation r op r') =  eval_rule proved r `op` eval_rule proved r' 

The idea being to have some kind of graph where Fact nodes points to Rules nodes, unless the fact is already in a list of known facts.

However, here I encounter the problem of defining my actual facts and rules.

Doing somethings like

let fact_e = ("E", [Fact ("C", [(Operation (Fact ("A", [])) (||) (Fact ("B", [])))])]) 

in ghci in order to represent the rules

C => E A || B => C 

That works. But I don’t really see what direction to go to construct theses rules programmatically. Furthermore, I don’t see how I can handle cyclic rules with that scheme (adding a rule E => A for example).

I have seen that there is ways to define self referencing data structures in haskell with the trick called “Tying the knot” on the Haskell wiki, but I don’t see how (or even if) I should apply that in the present case.

My question is essentially, am I going in the right direction, or do I have it completely backward with that approach ?

P.S : It also seems to me that my code is not as concise as it should be (passing around the [Label] list, repeating eVal_rule proved many times…), but I don’t really know either how to do it in another way.

Googke K8s – Stackdriver Kubernetes Engine Monitoring is enabled but cant see logs in Logs Viewer

Google K8S – Master version 1.13.6-gke.6

On my K8S cluster is Stackdriver Kubernetes Engine Monitoring Enabled, Legacy Stackdriver Logging Disabled, Legacy Stackdriver Monitoring Disabled.

PROBLEM: I get monitoring information in stackdriver dashboards but I cant see logs in google Logs Viewer (also nothing with gcloud logging read “resource.type=k8s_container” to this cluster)

If I switch to Legacy Stackdriver Monitoring and Legacy Stackdriver Logging, it works (with resource.type=container).

Cluster use service with permission (Role editor (owner not help))

  • https://www.googleapis.com/auth/logging.write
  • https://www.googleapis.com/auth/monitoring

Permissions for cluster

  • Stackdriver Logging API – Write Only
  • Stackdriver Monitoring API – Full

On every node runing fluentd-gcp-*

Writing a Descriptive Text Engine

I have a database of people. With the information such as their name, online presence / relevance, and social media accounts, I want to create an engine that will automatically “describe” the person.

For example, if the person tweets about anime a lot, the engine could make the final assumption of “x likes anime.” Or, if they type in all-caps a lot and swear a lot, the engine might assume “x is an ill-tempered individual.”

Theoretically, how could I go upon structuring this? This is how I see it going:

  1. Find common entries or keywords in search engine results or social media results (for example, the person frequently tweets or is featured in links from “iloveanime.com”)
  2. Collate these entries and somehow weigh them against the websites’ actual keywords (for example, iloveanime.com being “anime”). This way if the person tweets iloveanime.com a lot, we don’t accidentally assume they like politics, and the engine knows what the website is for.
  3. Generate a phrase based on keyword relevance. (For example, “iloveanime.com” appears greater than or equal to x amount of times, the category is “anime” so category = topic, and perhaps the person says “love” or “awesome” quite a lot in their tweets. So we say “x likes topic.”)

I don’t know if that makes sense or not. Please, add suggestions or critique my current idea of how to do this. There might be an easier way I don’t know of.

Forcing search engine to display stock quote in Chrome

Is there a way (extension, tag) to input a stock ticker into the Google Chrome search bar and return the relevant yahoo finance/ google finance/bloomberg page for a stock?

Most of the time google is very good about showing a finance card but there are numerous tickers (KORS) comes to mind where the finance card doesn’t show up at all.

Search Engine Optimization. The Starter Guide for $2

This document first began as an effort to help teams within Google, but we thought it’d be just as useful to webmasters that are new to the topic of search engine optimization and wish to improve their sites’ interaction with both users and search engines. Although this guide won’t tell you any secrets that’ll automatically rank your site first for queries in Google (sorry!), following the best practices outlined below will make it easier for search engines to crawl, index and understand your content. Search engine optimization is often about making small modifications to parts of your website. When viewed individually, these changes might seem like incremental improvements, but when combined with other optimizations, they could have a noticeable impact on your site’s user experience and performance in organic search results. You’re likely already familiar with many of the topics in this guide, because they’re essential ingredients for any web page, but you may not be making the most out of them. Even though this guide’s title contains the words “search engine”, we’d like to say that you should base your optimization decisions first and foremost on what’s best for the visitors of your site. They’re the main consumers of your content and are using search engines to find your work. Focusing too hard on specific tweaks to gain ranking in the organic results of search engines may not deliver the desired results. Search engine optimization is about putting your site’s best foot forward when it comes to visibility in search engines, but your ultimate consumers are your users, not search engines. Your site may be smaller or larger than our example site and offer vastly different content, but the optimization topics we discuss below should apply to sites of all sizes and types. We hope our guide gives you some fresh ideas on how to improve your website, and we’d love to hear your questions, feedback, and success stories in the Google Webmaster Help Forum.

by: oforce500
Created: —
Category: Onsite SEO & Research
Viewed: 90


Make SEO Package And higher on the search engine rankings for $45

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How would one log into an AWS User Pool from Unreal Engine?

I’m very, very new to the networking and AWS side of things, but experimenting a bit with some concepts. I was wondering if anyone had suggestions for the following use case. I’m in an experimental capacity at the moment, so these atypical practices have their reasons. Anyway, thanks for any guidance y’all can provide!

  1. A person in Unreal enters some credentials, e.g., “username” and “password.”
  2. I verify that in AWS with a Cognito User Pool and provide them with an access token. Optionally, maybe I access IAM/Cognito directly to log into a User Pool identity.
  3. Upon verifying that request, I serve them links to download content, e.g., from S3. The links could have further verification with tokens and such.

My initial plan was to send some HTTP(S) requests to Lambda functions, but Lambda doesn’t appear to support Authenticating a user by receiving credentials. I could be totally crazy of course, and may have just missed that part of the documentation.

So, I suppose my questions are: from Unreal Engine, what would the best way be for simply submitting user credentials and receiving a token in return? And, once I have that token, what’s the best way to then route that token and user pool to an S3 bucket for downloading some special content? I feel like making some serverless web app with no front-end as a surrogate for Unreal requesting just two things would be super overkill. But maybe y’all feel differently, and I’m open to suggestions.

Thanks! Definitely expect some follow-up questions as I’m quite new to the AWS space, heh. If this is an inappropriate venue for questions like this, I’m happy to close the thread and go elsewhere.