The latest News and Information on DevOps, CI/CD, Automation and related technologies.
Many organizations use Kubernetes to quickly ship new features and improve the reliability of their services. Rancher enables teams to reduce the operational overhead of managing their cloud-native workloads — but getting continuous visibility into these environments can be challenging. In this post, we’ll explore how you can quickly start monitoring orchestrated workloads with Rancher’s built-in support for Prometheus and Grafana.
I have worked at Virtana for nearly 9 years. During that time, I have had the pleasure to interact with customers, prospects, and partners around the world. The types of conversations I have participated in have dramatically shifted during that time. Back in September 2011, the dialogues were largely focused on Storage Area Network (SAN) infrastructure, and how Virtana could provide performance assurances targeted at this environment. Over time, the conversations have broadened dramatically.
In order to have the most successful deployment, there are a few best practices that software development teams should be mindful of. First, following a continuous delivery approach allows software development teams to release in shorter cycles, so that building, testing, and releasing can be done with greater speed and reduced error rates.
Having a proper backup recovery plan is vital to any organization's IT operation. However, when you begin to distribute workloads across data centers and regions, that process begins to become more and more complex. Container orchestration platforms such as Kubernetes have begun to ease this burden and enabled the management of distributed workloads in areas that were previously very challenging.
In order to have the most successful deployment, there are a few best practices that software development teams should be mindful of. First, following a continuous delivery approach allows software development teams to release in shorter cycles, so that building, testing, and releasing can be done with greater speed and reduced error rates. As stated in an earlier post of ours, you’re doing continuous delivery when: Your software is deployable throughout its lifecycle.
In previous and great articles in here, we already talked about what Cloud is and the types that exist floating above our heads. But today, for a change, we want to focus more on one of its totally forgotten key aspects: Are clouds actually made of childish dreams and cotton candy? No! Just kidding! Today we are going to talk in “Pandora FMS discussions” about what cloud service types there are.
Continuous Integration and Continuous Delivery (CI/CD) delivers services fast, effectively, and accurately. In doing so, CI/CD pipelines have become the mainstay of effective DevOps. But this process needs accurate, timely, contextual data if it’s to operate effectively. This critical data comes in the form of logs and this article will guide you through optimizing logs for CI/CD.
As organizations build out their serverless footprint, they might find themselves managing hundreds or thousands of individual components (e.g., Amazon S3 buckets, Amazon DynamoDB tables, AWS SQS queues) for just a single application. At the same time, performance issues can crop up at any of these points, which means that having access to detailed observability data from your serverless functions is crucial for effective troubleshooting.
