The latest News and Information on DevOps, CI/CD, Automation and related technologies.
To allocate costs or maximize savings? That’s the question many AWS customers will have to answer when formulating their FinOps strategy relating to Savings Plans. If part of your daily routine is finding ways to cut cloud costs, then you know exactly what I’m talking about. Appropriate chargeback reporting is an undeniable necessity for any business, but in this world of uncontrolled rising cloud costs, so is capitalizing on any savings opportunities!
Big features make headlines, but they can be a challenge to deploy without staying dedicated to the finish line. Even the best laid projects can fall victim to time creep as more features are added and the idea gets refined. What’s on paper looks great!
There’s a lot of talk about serverless computing lately, especially with the big tech giants investing in the idea and offering exclusive products built on it. But is it just a buzzword, or does it have the potential to become the next big thing in technology? Cloud computing was once a buzzword, too, one may argue. But that buzzword ended up revolutionizing the whole industry, with 90 percent of companies now using cloud hosting.
Hyperconverged infrastructure (HCI) gives organizations more flexibility and control when building and securing their virtualized on-premises environments. Microsoft’s Azure Stack HCI is an operating system-as-a-service built for HCI backends that lets organizations deploy and manage their virtualized resources alongside any Azure infrastructure they are running.
Get started with Gremlin's Chaos Engineering tools to safely, securely, and simply inject failure into your systems to find weaknesses before they cause customer-facing issues. Think back to the last time you wanted to purchase software for your organization. The software solves real problems and makes your team’s life easier. Then, finance delays or rejects your proposal. What’s going on?
With massive adoption of Kubernetes at enterprises worldwide, we are seeing Kubernetes going to new extremes. On the one hand, Kubernetes is being adopted for workloads at the edge and delivering value beyond the data center. On the other hand, Kubernetes is being used to drive Machine Learning (ML) and high-quality, high-speed data analysis capabilities.
