Cron jobs in Node.js

medium.com – Every developer sooner or later faces a problem on how to deal with cron jobs. The list of cron jobs use-cases is enormous: cache invalidation, reports generation, refreshing data from external…
Quelle: news.kubernauts.io

Intro to Kf: Cloud Foundry apps on Kubernetes

While many companies are writing brand-new Kubernetes-based applications, it’s still quite common to find companies who want to migrate existing workloads. A common source platform for these applications is Cloud Foundry. However, getting an existing Cloud Foundry application running on Kubernetes can be non-trivial, especially if you want to avoid making code changes in your applications, or taking on big process changes across teams. That is, if you’re not using Kf to do a lot of that heavy lifting for you. Kf is a Google Cloud service that allows you to easily move existing Cloud Foundry workloads to Kubernetes with minimal disruption to your existing processes. Kf features a command line interface (CLI) also named kf, that replaces the existing Cloud Foundry cf command line utility. The kf CLI implements the most commonly used cf functionality, including the ability to manage bindings, services, apps, routes and more. For example, to deploy an existing application you would simply issue the kf push command. On the server side Kf is built on several open source technologies. In some cases these technologies are also the Google Cloud implementation. For instance GKE is our managed Kubernetes offering,  and provides the platform for managing and running the applications. Routing and ingress is handled by Anthos Service Mesh, Google Cloud’s managed Istio-based service mesh. Finally, Tekton provides on-cluster build functionality for Kf. Developers don’t have to worry about any of those technologies, as Kf abstracts them away.Kf primitives such as spaces, bindings and services are implemented as custom Kubernetes resources and controllers. The custom resources effectively serve as the Kf API and are used by the kf CLI to interact with the system. The controllers use Kf’s CRDs to orchestrate the other components in the system.The beauty of this approach is that developers who are familiar with existing workflows can largely replicate those workflows with the kf CLI. On the other hand, platform operators who are more familiar with Kubernetes can use kubectl to interact with the CRDs and controllers. For instance if you wanted to list the apps running on your Kf cluster you could issue either of the following commands:Notice that CF / Kf spaces get mapped one to one to Kubernetes namespaces.To get a list of all the custom resources you can examine the api-resources in the kf.dev API group.With Kf developers can continue to work with a familiar interface and platform operators can use declarative Kubernetes practices and tooling such as Anthos Config Management to manage the cluster. It’s really the best of both worlds if you’re looking to manage your existing Cloud Foundry applications on Kubernetes. If you’d like to learn more about Kf check out the video I just released on YouTube.  It reviews some of the concepts discussed here, and includes a short demo. If you’d like to get hands on, try the quick start. And, of course, you can always read the documentation.Related ArticleApplication modernization isn’t easy. But we can make it easier.Migrating and modernizing applications and moving to the cloud can be a fun and interesting challenge, but it’s seldom “easy”. Here are f…Read Article
Quelle: Google Cloud Platform

Changes to Docker Hub Autobuilds

As many of you are aware, it has been a difficult period for companies offering free cloud compute [1]. Unfortunately, Docker’s Autobuild service has been targeted by the same bad actors, so today we are disappointed to announce that we will be discontinuing Autobuilds on the free tier starting from June 18, 2021. 

In the last few months we have seen a massive growth in the number of bad actors who are taking advantage of this service with the goal of abusing it for crypto mining. For the last 7 years we have been proud to offer our Autobuild service to all our users as the simplest way to set up CI for containerized projects. As well as the increased cost of running the service, this type of abuse periodically impacts performance for paying Autobuild users and induces many sleepless nights for our team

In April we saw the number of build hours spike 2X our usual load and by the end of the month we had already deactivated ~10,000 accounts due to mining abuse The following week we had another ~2200 miners spin up.

As a result of this we have made the hard choice to remove Autobuilds from our free plan as a mitigation for this abuse. While making these changes is never an easy choice, we’ve also continued to focus on making meaningful improvements to the performance of Autobuilds, including:

Increasing the number of parallel builds to 5 for Pro and 15 for Team.Increase the build instance types, so you get a beefier machine to build on!Changed Autobuild to take advantage of BuildKit by default for improved build performance.

All of these improvements should see a faster and more stable build experience with lower queue times. If that sounds good and you are a free user who <3’s their Autobuilds, we are offering 20% off Docker Pro and Team for new and returning subscriptions through June 18, 2021 so you can continue using that Autobuild goodness.

If you’re part of the Docker Open Source program, and currently leveraging Autobuilds as part of a Free plan, we want to continue supporting you and we will be reaching out to make sure you will not be impacted by this change.   

We really appreciate your support and the community’s understanding as the whole industry battles against these abusive few. We want to keep providing awesome and magical services and hope we can find a better solution with everyone going forward.
The post Changes to Docker Hub Autobuilds appeared first on Docker Blog.
Quelle: https://blog.docker.com/feed/

Die Amazon-SageMaker-Modell-Registry unterstützt jetzt das Rollback von bereitgestellten Modellen

Amazon SageMaker Pipelines ist der erste speziell entwickelte Service für kontinuierliche Integration und kontinuierliche Bereitstellung für maschinelles Lernen (ML). Mit diesem Service können Kunden nun die letzte vom Kunden genehmigte Version von ML-Modellen, die an von SageMaker bereitgestellten Endpunkten bereitgestellt wurden, auf eine frühere vom Kunden genehmigte Version des Modells zurücksetzen. Kunden können nun den Status der bereitgestellten Modellpaketversion in der Modell-Registry von „Genehmigt“ in „Abgelehnt“ ändern. Dadurch wird die CI/CD-Pipeline für die Modellbereitstellung ausgelöst, um die aktuelle Version des am SageMaker-Endpunkt bereitgestellten Modells auf die letzte vorherige Version des Modells zurückzusetzen, die für die Bereitstellung freigegeben wurde.
Quelle: aws.amazon.com

AWS Security Hub fügt dem Foundational-Security-Best-Practices-Standard 16 neue Kontrollen für eine verbesserte Überwachung des Cloud-Sicherheitsniveaus hinzu

AWS Security Hub hat 16 neue Kontrollen für den Foundational Security Best Practice Standard eingeführt, um die Überwachung des Cloud-Sicherheitsniveaus für Kunden zu verbessern. Diese Kontrollen überprüfen vollautomatisch die bewährten Sicherheitsverfahren für Amazon API Gateway (APIGateway.2, APIGateway.3), AWS Elastic Beanstalk (ElasticBeanstalk.1, ElasticBeanstalk.2), Amazon RDS (RDS.12, RDS.13, RDS.14 ), Amazon EC2 (EC2.15, EC2.16), AWS CloudTrail (CloudTrail.4, CloudTrail.5), Amazon Redshift (Redshift.7), AWS Lambda (Lambda.4), AWS Secrets Manager (SecretsManager.3, SecretsManager.4) und AWS Web Application Firewall (WAF.1). Sofern Sie Security Hub so eingestellt haben, dass neue Kontrollen automatisch aktiviert werden und Sie bereits AWS Foundational Security Best Practices verwenden, sind diese Kontrollen standardmäßig aktiviert. Security Hub unterstützt jetzt 131 Sicherheitskontrollen zur automatischen Überprüfung Ihres Sicherheitsniveaus in AWS.
Quelle: aws.amazon.com