Jean  Glover

Jean Glover

1619308800

How Open Data Hub Speeds AI Development and Fixed a Kubernetes Bottleneck

Many companies wonder how to properly apply AI/ML tools to their work and line of business applications. One good way to find such an application’s use is to take a gander at what the rest of the business world is doing with machine learning, and attempt to find a location inside your organization where it could be applied.

As an example, much has been made of the Netflix recommendation engine, which was the product of a public $1 million algorithm challenge. The resulting feature helps millions of Netflix subscribers navigate an enormous library of shows and movies. That increases user enjoyment of the platform, and helps the service to become more useful to the use.

How can this recommendation engine model be applied to your business? How is it applied to our own business, here at Red Hat? We have some top minds working on these machine learning applications, and in the process we’ve discovered some interesting things about the open source projects that fuel the Red Hat OpenShift Platform.

#kubernetes

What is GEEK

Buddha Community

How Open Data Hub Speeds AI Development and Fixed a Kubernetes Bottleneck
Christa  Stehr

Christa Stehr

1602964260

50+ Useful Kubernetes Tools for 2020 - Part 2

Introduction

Last year, we provided a list of Kubernetes tools that proved so popular we have decided to curate another list of some useful additions for working with the platform—among which are many tools that we personally use here at Caylent. Check out the original tools list here in case you missed it.

According to a recent survey done by Stackrox, the dominance Kubernetes enjoys in the market continues to be reinforced, with 86% of respondents using it for container orchestration.

(State of Kubernetes and Container Security, 2020)

And as you can see below, more and more companies are jumping into containerization for their apps. If you’re among them, here are some tools to aid you going forward as Kubernetes continues its rapid growth.

(State of Kubernetes and Container Security, 2020)

#blog #tools #amazon elastic kubernetes service #application security #aws kms #botkube #caylent #cli #container monitoring #container orchestration tools #container security #containers #continuous delivery #continuous deployment #continuous integration #contour #developers #development #developments #draft #eksctl #firewall #gcp #github #harbor #helm #helm charts #helm-2to3 #helm-aws-secret-plugin #helm-docs #helm-operator-get-started #helm-secrets #iam #json #k-rail #k3s #k3sup #k8s #keel.sh #keycloak #kiali #kiam #klum #knative #krew #ksniff #kube #kube-prod-runtime #kube-ps1 #kube-scan #kube-state-metrics #kube2iam #kubeapps #kubebuilder #kubeconfig #kubectl #kubectl-aws-secrets #kubefwd #kubernetes #kubernetes command line tool #kubernetes configuration #kubernetes deployment #kubernetes in development #kubernetes in production #kubernetes ingress #kubernetes interfaces #kubernetes monitoring #kubernetes networking #kubernetes observability #kubernetes plugins #kubernetes secrets #kubernetes security #kubernetes security best practices #kubernetes security vendors #kubernetes service discovery #kubernetic #kubesec #kubeterminal #kubeval #kudo #kuma #microsoft azure key vault #mozilla sops #octant #octarine #open source #palo alto kubernetes security #permission-manager #pgp #rafay #rakess #rancher #rook #secrets operations #serverless function #service mesh #shell-operator #snyk #snyk container #sonobuoy #strongdm #tcpdump #tenkai #testing #tigera #tilt #vert.x #wireshark #yaml

 iOS App Dev

iOS App Dev

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Houston  Sipes

Houston Sipes

1600992000

Did Google Open Sourcing Kubernetes Backfired?

Over the last few years, Kubernetes have become the de-facto standard for container orchestration and has also won the race against Docker for being the most loved platforms among developers. Released in 2014, Kubernetes has come a long way with currently being used across the entire cloudscape platforms. In fact, recent reports state that out of 109 tools to manage containers, 89% of them are leveraging Kubernetes versions.

Although inspired by Borg, Kubernetes, is an open-source project by Google, and has been donated to a vendor-neutral firm — The Cloud Native Computing Foundation. This could be attributed to Google’s vision of creating a platform that can be used by every firm of the world, including the large tech companies and can host multiple cloud platforms and data centres. The entire reason for handing over the control to CNCF is to develop the platform in the best interest of its users without vendor lock-in.

#opinions #google open source #google open source tools #google opening kubernetes #kubernetes #kubernetes platform #kubernetes tools #open source kubernetes backfired

Ian  Robinson

Ian Robinson

1624434960

Using AI and Big Data in Anti-ransomware Development

Recently, the internet watchdog from South Korea has surfaced a roadmap to develop an anti-ransomware system. This development will be backed by big data and AI.

What is Ransomware?

Ransomware is best famously described as a type of hacking attack. This allows a hacker to control target computers or servers. It encrypts all the files inaccessible without a decryption key. The criminal activities are aimed at soliciting ransom money. Hackers, at the time, leave the system infected and useless. KISA says that when ransomware takes control of a computer network of a private network, the hacker file takes control of the main server.

#artificial intelligence #big data #using ai and big data in anti-ransomware development #anti-ransomware development #ai and big data #ai

Gerhard  Brink

Gerhard Brink

1620629020

Getting Started With Data Lakes

Frameworks for Efficient Enterprise Analytics

The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.

This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.

Introduction

As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).


This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.

#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management