In June, we were delighted to host our first ever virtual PagerDuty Summit EMEA! Llywelyn Griffith-Swain, SRE Manager, and David Jambor, Head of Systems Engineering at Vodafone, were among our speakers. They outlined Vodafone’s approach to achieving immutable telemetry. David opened the session by defining Vodafone’s strategic goals. “Our vision is to create an engineering-driven culture,” he explained. “We want to empower development teams to be self-sufficient.

Ansible is an open source continuous configuration automation (CCA) tool. You can use it to automate the management of the configuration of host systems. For example: installing and configuring applications, services, security policies; or to perform a wide variety of other administration and configuration tasks.

Client libraries are collections of code that make it easier for developers to write flexible and efficient applications that interface with APIs. Datadog provides client libraries so you can programmatically interact with our API to customize dashboards, search metrics, create alerts, and perform other tasks. We’re pleased to announce that we’ve developed and open-sourced two new client libraries for Java and Go in addition to our existing Ruby and Python libraries.

Kubernetes is a powerful orchestration system, however, it can be really hard to configure its deployment process. Specific apps can help you manage multiple independent resources like pods, services, deployments, and replica sets. Yet, each must be described in the YAML manifest file.

As the Kubernetes ecosystem grows, new technologies are being developed that enable a wider range of applications and use cases. The growth of edge computing has driven a need for some of these technologies to enable the deployment of Kubernetes to low-resource infrastructure to the network edge. In this blog post, we are going to introduce you to one method of deploying k3OS to the edge. You can use this method to automatically register your edge machine to a Rancher instance as a control plane.

Get Better Observability With Machine Learning Anomaly Detection. DevOps teams today are challenged with the rapid growth and complexity of infrastructure. Managing those environments only through static thresholds becomes insufficient, so to address this issue, modern DevOps teams rely on advanced ML/AI algorithms.