Operations | Monitoring | ITSM | DevOps | Cloud

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Kubernetes, Data Science, and Machine Learning

Enabling support for data processing, data analytics, and machine learning workloads in Kubernetes has been one of the goals of the open source community. During this meetup we’ll discuss the growing use of Kubernetes for data science and machine learning workloads. We’ll examine how new Kubernetes extensibility features such as custom resources and custom controllers are used for applications and frameworks integration. Apache Spark 2.3.’s native support is the latest indication of this growing trend. We’ll demo a few examples of data science workloads running on Kubernetes clusters setup by our Kublr platform.

Auvik Use Case #14: Differentiate Your MSP Services With Network Monitoring & Managemen

In a crowded MSP market, you need ways to differentiate yourself from the competition. As former MSP Charles Loves points out, “When you compare MSPs, the look and feel of the offering is often the same. So when the customer tries to compare MSP A, B, and C, what are the real differentiators they can leverage?” You don’t want to end up in a situation where dropping prices is the only way to edge out firms with similar offerings.

Gain Full Visibility into Microservices Architectures Using Kubernetes with Sumo Logic and Amazon EKS

Amazon Elastic Container Service for Kubernetes (Amazon EKS) is a managed service that makes it easyfor you to run Kubernetes on AWS without needing to install and operate your own Kubernetes clusters.

Monitor Amazon EKS with Datadog

Amazon Elastic Container Service for Kubernetes (EKS), the latest addition to the AWS platform, is a cloud-based Kubernetes service that provides features for automated cluster management and maintenance. Whether you are migrating an existing Kubernetes cluster or deploying a new application to Amazon EKS, Datadog can help you monitor your container infrastructure and applications in real time.

Elasticsearch Performance Tuning

Once you have your Elasticsearch running, you’ll likely eventually find that performance starts to suffer over time. This can be due to a variety of factors, including changes in the way you’re using your cluster to how much and what types of data are being sent in. In order to maintain your cluster, you’ll need to set up monitors to alert you to any warning signs so that you can proactively handle available maintenance windows.