Operations | Monitoring | ITSM | DevOps | Cloud

We’re happy to announce that with the upcoming release of Splunk App for Data Science and Deep Learning (DSDL) 5.1.1 we’re significantly overhauling the build process for containers in DSDL. More and more customers are adopting DSDL for some of their most complex and advanced workloads. In this newest release, we’re making the process of deploying, building and maintaining containers for DSDL more modular, more secure, more robust, and more scalable as well as adding some new features!

Stop me if you’ve heard this one before: you just pushed and deployed your latest change to production, and it’s rolling out to your Kubernetes cluster. You sip your coffee as you wrap up some documentation when a ping in the ops channel catches your eye—a sales engineer is complaining that the demo environment is slow. Probably nothing to worry about, not like your changes had anything to do with that… but, minutes later, more alerts start to fire off.

In the swiftly evolving tech world, the need for agile and efficient development processes is paramount. This was the essence of our enlightening event, "Creating Ephemeral Environments for CI/CD Pipelines with Kubernetes," which garnered an impressive turnout of over 650 attendees. The event, now available on Youtube, focused on the transformative potential of ephemeral environments in modern CI/CD pipelines.

Since 2020, I’ve been working on an Express (Node.js framework) application to power viewer interactions and events that happen whilst I’m streaming live coding on Twitch — my Twitch bot. Since using Sentry for error monitoring and crashes using the Sentry Node SDK, I’ve already squashed quite a few bugs that were entirely a result of my own terrible code.

Any existing InfluxDB user will notice that InfluxDB underwent a transformation with the release of InfluxDB 3.0. InfluxDB v3 provides 45x better write throughput and has 5-25x faster queries compared to previous versions of InfluxDB.

Cloud computing has revolutionized the technology landscape, increasing deployment velocity exponentially. Organizations leverage cloud technologies to improve availability, drive innovation, enhance agility, and streamline operations. However, a one-size-fits-all approach to cloud technologies doesn't always meet the diverse needs of modern enterprises.

Application Programming Interfaces, or APIs, are rules and protocols that allow one software application to interact with another, and can be found everywhere in today's digital ecosystem. From the weather app on your smartphone pulling data from a remote server to provide real-time weather information, to the payment gateway service that processes your online purchases, APIs facilitate the seamless flow of data and services.

Remote access software has risen to prominence as a vital tool, enabling organizations to bridge geographical distances and empower remote workforces. However, as businesses embrace the convenience and flexibility that remote access solutions offer, they are also confronted with an essential consideration: understanding the true cost of remote access software. In this article, we embark on a comprehensive exploration of the financial dimensions surrounding remote access solutions.

Kubernetes, often abbreviated as K8s, has revolutionised the way we manage containerized applications. It provides a robust platform for orchestrating and managing containers at scale. One of the key features that sets Kubernetes apart is its powerful metadata system, which includes labels and annotations. In this blog post, we’ll take a comprehensive look at how labels and annotations work in Kubernetes and how you can leverage them to enhance the management of your applications.

MLflow is an open source platform, used for managing machine learning workflows. It was launched back in 2018 and has grown in popularity ever since, reaching 10 million users in November 2022. AI enthusiasts and professionals have struggled with experiment tracking, model management and code reproducibility, so when MLflow was launched, it addressed pressing problems in the market. MLflow is lightweight and able to run on an average-priced machine.