Search Results for "service"

Kamal offers zero-downtime deploys, rolling restarts, asset bridging, remote builds, accessory service management, and everything else you need to deploy and manage your web app in production with Docker. Originally built for Rails apps, Kamal will work with any type of web app that can be containerized. Kamal seeks to bring the advance in ergonomics pioneered by these commercial offerings to deploying web apps anywhere. Whether that’s low-cost cloud options without the managed-service markup from the likes of Digital Ocean, Hetzner, OVH, etc, or it’s your own colocated bare metal. ...

AWS Deploy Tool is an interactive tooling for the .NET CLI and the AWS Toolkit for Visual Studio that helps deploy .NET applications with minimum AWS knowledge, and with the fewest clicks or commands. It works by analyzing .NET projects and guiding developers to the right AWS service. It then selects the right deployment service, builds and packages your application, and creates the deployment infrastructure. It allows for a quick and easy Proof of concept (POC), smooth graduation to CI/CD, and a gradual ramp-up of AWS knowledge. Get recommendations about the type of computing best suited for your application based on the application type. ...

...It reduces the risk of introducing a new software version in production by gradually shifting traffic to the new version while measuring metrics and running conformance tests. Flagger implements several deployment strategies (Canary releases, A/B testing, Blue/Green mirroring) using a service mesh (App Mesh, Istio, Linkerd, Kuma, Open Service Mesh) or an ingress controller (Contour, Gloo, NGINX, Skipper, Traefik, APISIX) for traffic routing. For release analysis, Flagger can query Prometheus, InfluxDB, Datadog, New Relic, CloudWatch, Stackdriver or Graphite and for alerting it uses Slack, MS Teams, Discord, and Rocket. ...

...The service.serving.knative.dev resource automatically manages the whole lifecycle of your workload. It controls the creation of other objects to ensure that your app has a route, a configuration, and a new revision for each update of the service. Service can be defined to always route traffic to the latest revision or to a pinned revision. The route.serving.knative.dev resource maps a network endpoint to one or more revisions. You can manage the traffic in several ways, including fractional traffic and named routes. The configuration.serving.knative.dev resource maintains the desired state for your deployment. ...

...There’s no central server or database; instead, Hypermind leverages a Distributed Hash Table (DHT) using Hyperswarm to discover peers and maintain approximate counts of active nodes, architected to be a fully decentralized service. Alongside counting nodes, the project also supports ephemeral chat over its mesh network, allowing users to send messages directly to local peers or broadcast via a gossip protocol without storing chat history. The project uses probabilistic data structures like HyperLogLog for efficient estimation of unique peers and provides real-time visualizations and themes for exploring the swarm.

...A Kubernetes application is an application that is both deployed on Kubernetes and managed using the Kubernetes APIs and kubectl (Kubernetes) or oc (OKD) tooling. To be able to make the most of Kubernetes, you need a set of cohesive APIs to extend in order to service and manage your apps that run on Kubernetes. Think of Operators as the runtime that manages this type of app on Kubernetes. The Jaeger Operator can be installed in Kubernetes-based clusters and is able to watch for new Jaeger custom resources (CR) in specific namespaces, or across the entire cluster. There is typically only one Jaeger Operator per cluster, but there might be at most one Jaeger Operator per namespace in multi-tenant scenarios.

Piku is a minimalistic Platform as a Service (PaaS) that enables users to deploy applications to their own servers using simple Git push commands.

...Under the hood it coordinates distributed nodes, tolerating partial failures while continuing to drive toward the target state. By separating deployment recipes from environment specifics, glu encourages repeatable, testable releases for multi-service stacks.