Operations | Monitoring | ITSM | DevOps | Cloud

Hello, fellow data enthusiasts and Google Colab aficionados! Today, we're going to explore how to monitor your Google Colab instances using Netdata. Colab is a fantastic platform for running Notebooks, developing ML models, and other data science and analytics tasks. But have you ever wondered how your Colab instance is performing under the hood? That's where Netdata comes into play!

Introducing Netdata's Demo Space, a quick and easy way to experience monitoring environments before you set them up yourself. At Netdata, we are always striving to provide the best monitoring experience for our users. We understand that adopting a new monitoring solution can sometimes be challenging, especially when you're unsure of how it will fit your specific environment. That's why we're excited to announce the Netdata Demo Space!

Everyone knows that MicroK8s is an extremely lightweight, extensible, reliable, CNCF-compliant distribution of Kubernetes. What you didn’t know until now is that it is even easier to install and manage as part of your AWS marketplace experience. First, a quick reminder of why MicroK8s is great: What is new is that MicroK8s is now available on the AWS marketplace, combining all of MicroK8s advantages with the convenience of AWS.

In this live stream, Sidd Shah and I discuss how Cribl Stream can empower Security Operations Admins to make the most of their CrowdStrike FDR data. They address the challenges faced by CrowdStrike customers, who generate a vast amount of valuable data each day but struggle to leverage it fully due to complexity and size.

Storage is vital to any software used to solve a business problem. This is because the data must be preserved or stored in any storage before/after/during the processing of data in software. The storage account is an Azure storage offering to store data in different forms based on the requirements. This article discusses Azure Storage cost optimization and how Serverless360 helps focuses on optimizing the cost spent on Azure storage accounts.

IBM zSystems run on some of the fastest processors. IBM zSystems are used for maximum speed and volume of data transactions, mainly in the banking, health care, airline, and retail sector. These markets need to rely on seven nines (99.99999%) of availability and performance of their systems, as they are the backbone of the entire business.

Today’s enterprises aspire to achieve IT process automation to help manage their infrastructure more efficiently and effectively. An AIOps platform like SL1 from ScienceLogic makes IT automation possible by discovering all devices, configuration, ingesting data from all resources, and creating an operational data lake populated with accurate and timely data. That data ensures the best possible result when automating simple, repetitive tasks.

What’s the right way to manage growing volumes of enterprise data, while providing the consistency, data quality and governance required for analytics at scale? Is centralizing data management in a data lake the right approach? Or is a distributed data mesh architecture right for your organization? When it comes down to it, most organizations seeking these solutions are looking for a way to analyze data without having to move or transform it via complex extract, transform and load (ETL) pipelines.

Azure Data Lake Storage (ADLS) is a highly scalable and cost-effective storage solution provided by Microsoft Azure for big data analytics. ADLS can handle structured and unstructured data, making it a popular choice for businesses looking to optimize their cloud storage management. In this article, we will provide a comprehensive analysis of the key factors that impact costs in Azure Data Lake Storage.