Operations | Monitoring | ITSM | DevOps | Cloud

Scaling based on the number of messages in an Azure Service Bus queue

One of the most notable advantages of the Cloud is the ability to scale resources to meet demand. We then scale out or up when the demand increases, and we scale in or down when the demand decreases. For the record, scaling out / in refers to increasing or decreasing the number of instances of a given resource, whereas scaling up / down refers to increasing or decreasing the capacity (CPU, Ram, Disk, I/O performance) or a given instance.

Don't Miss Out: Highlights from DevOps Cloud Days 2022

If you didn’t attend our recently concluded DevOps Cloud Days online conference, you missed a learning event that those who did called “fantastic” and “meaningful.” In written feedback, developers, operations staff, and security admins who attended described the presentations as “powerful,” “inspiring” and “excellent.” Fortunately, it wasn’t your last chance to share that fruitful experience with us.

Delivering Better Service Experiences with AI-Powered Agents

For the last two years, it’s an understatement to say we’ve witnessed big shifts in the relationship between most employees and their work environment. Many of us saw our work experience transform seemingly overnight into predominately a digital one as working from home became the ‘new normal.’

5 Ways To Increase Engineering Velocity Without Skyrocketing Costs

It's something you know. Those who rely on or offer Software-as-a-Service (SaaS) solutions are under constant pressure to innovate. Often, this means quickly building new features and releasing them more frequently. Staying on budget and on time is also critical for staying competitive. Likewise, SaaS providers should also offer customers cost-effective solutions to their technology challenges. But that’s not all. You must also always release quality code that provides seamless user experiences.

From eBPF to CI/CD: 12 emerging trends in observability

As businesses accelerate digital transformations and cloud adoption to better serve customers and employees in the face of the global pandemic, operational complexity has also mounted. To untangle these complexities and enable executive visibility into IT ecosystem , business leaders are increasingly looking to observability solutions as a strategic investment.

The Power of Shipa CNAMEs

As a software engineer, I admit I am not the best at networking. Can’t connect to your app for some reason, one going joke is to “always blame DNS” e.g the Domain Name System. My personal DNS experience is usually editing a few records for my personal blog and connecting a few tools and that is it. Thanks to distributed systems, had to learn all about SRV records and some more DNS concepts.

How a company saved 32k hours of IT support and $1.6M on their Windows Migration

A Windows migration is like taking out the trash–you can always delay it, but you’ll have to do it at some point (and you’ll be so happy once it’s done). Unlike taking out the trash, however, the risk of failure throughout the entire migration process is extremely high, especially when you consider all the moving parts.

UK Companies to Test Four-Day Work Week

Beginning in June, at least 30 companies in the United Kingdom will take part in a pilot of a four-day work week. Employees at these companies will work 32 hours per week rather than the standard 40, with no changes to their compensation or benefits. As the program progresses over a six-month trial period, researchers will analyze its effects on employee productivity, along with other variables including employee wellbeing and the environmental impact.

Getting Started with the InfluxDB API

This article was written by Nicolas Bohorquez. Scroll below for the author’s picture and bio. Time series databases, like InfluxDB, index data by time. They are very efficient at recording constant streams of data, like server metrics, application monitoring data, sensor reports, and any data containing a timestamp. Data in a time series database is always written with the most recent data values but with the previous values not updated.