Operations | Monitoring | ITSM | DevOps | Cloud

Surely you may have at one time or another received an email warning of an outstanding invoice, a parcel shipment that you did not expect or a warning from the bank about suspicious activity in your account. These messages usually adopt an alarming tone and provide you with a link to a website that you must visit right away to verify your personal information or to complete payment information. Caution! This is a “phishing” attempt, one of the most popular scam methods on the Internet!

In this blog series, we’ll explore how Cribl Stream can leverage your existing cross-domain solution (CDS) to easily collect and send your log and metric data between disparate security domains or across air-gapped networks. The goal is to retain as much fidelity of the data as possible, deduplicating processes and simplifying management efforts.

Canonical is proud to announce that we have joined the Sylva project of Linux Foundation Europe as a General Member. We aim to bring our open source infrastructure solutions to Sylva and contribute to the project’s goal of providing a platform to validate cloud-native telco functions.

Data is everywhere, not just in large centralised data centres, but in smaller outposts, like retail outlets, remote or branch offices, filming locations and even cars. Use cases for edge storage include local processing, content collaboration that cannot take place with high network latency, and for ingest – where locally created content is captured, protected and then made available to other systems.

On Dec. 5, 2013, Torkel Ödegaard made the first commit in GitHub for a personal project that would become Grafana. “It’s hard to believe it’s been 10 years since Torkel launched Grafana, growing from a small man with a big dream to becoming the most popular data visualization software in the world,” says Grafana Labs co-founder and CEO Raj Dutt. “The Story of Grafana” chronicles that meteoric journey.

New Kafka topics catalog in Aiven for Apache Kafka brings a topic-centric view of your Kafka environment directly to the Aiven console.

Whether or not you made the journey to this year’s re:Invent, there’s always a variety of great announcements lost amid an action-packed week of keynotes, breakouts, expo hall demos, and networking sessions. No need to worry—we’re always happy to be a big part of the re:Invent experience and share our observations with you.

On-call scheduling is tricky. Like, really tricky. It was one of the scariest parts when we decided to build a modern alerting system earlier this year. We knew we couldn't cut any corners on Day One of our release because it needed to be a fully loaded feature for someone to realistically use our product (and replace an incumbent). This meant including windowed restrictions, coverage requests, and simple to complex rotations.

Get a dedicated internet solution with all the benefits of Megaport’s scalable network fabric in just 60 seconds.

There is more data available to us than ever. Storing this data is important — but deciding on the right type of data storage solution is not so clear. This article explores two primary types of big data storage: data lakes and data warehouses. We’ll examine the benefits of each, then discuss the key differences between a data lake and a data warehouse, so you can decide on the best approach for your business.