Search Results for "microservices"
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Showing 10 open source projects for "microservices"
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Zeebe
Distributed Workflow Engine for Microservices Orchestration
Automate processes at scale with unprecedented performance and resilience. Zeebe is the workflow and decision engine that powers Camunda Platform 8. Zeebe’s cloud-native design provides the performance, resilience, and security enterprises need to future-proof their process orchestration efforts. Zeebe distributes data across all brokers in a cluster with storage directly on the server filesystem. If one broker goes down, another can replace it with no data loss. This pre-configured... -
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POCO
Cross-platform C++ libraries for building network applications
The POCO C++ Libraries are powerful cross-platform C++ libraries for building network- and internet-based applications that run on desktop, server, mobile, IoT, and embedded systems. Whether building automation systems, industrial automation, IoT platforms, air traffic management systems, enterprise IT application and infrastructure management, security and network analytics, automotive infotainment and telematics, financial or healthcare, C++ developers have been trusting the POCO C++... -
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Helidon
Java libraries for writing microservices
Helidon is a cloud-native, open‑source set of Java libraries for writing microservices that run on a fast web core powered by Netty. Helidon Níma is the first Java microservices framework based on virtual threads. Helidon is designed to be simple to use, with tooling and examples to get you going quickly. Since Helidon is simply a collection of Java libraries running on a fast Netty core, there is no extra overhead or bloat. Helidon supports MicroProfile and provides familiar APIs like JAX-RS... -
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Go kit
A standard library for microservices
Go is a lovely little language that's perfectly suited to writing microservices. Go kit fills in the gaps left by the otherwise excellent standard library, giving your team the confidence to adopt Go throughout your stack. Adopting microservices means building a distributed system, and that comes with a lot of challenges. Go kit provides guidance and solutions for most of the common operational and infrastructural concerns. Allowing you to focus your mental energy on your business. You know... -
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Go gRPC Middleware
Golang gRPC Middlewares: interceptor chaining, auth, logging, retries
gRPC Go has support for "interceptors", i.e. middleware that is executed either on the gRPC Server before the request is passed onto the user's application logic, or on the gRPC client either around the user call. It is a perfect way to implement common patterns: auth, logging, tracing, metrics, validation, retries, rate limiting, and more, which can be great generic building blocks that make it easy to build multiple microservices. Especially for observability signals (logging, tracing... -
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Pedestal
The Pedestal Server-side Libraries
.... Applications must respond with immediate feedback even while some back-end communication goes on. Pedestal makes it easy to deliver server-sent events and asynchronous updates. Pedestal works with a huge variety of containers and deployment options. Deploy applications or microservices on unikernels, Docker containers, or JAR files. Pedestal supports Tomcat, Jetty, Immutant (with Undertow), Vert.x, nginx, and Netty. -
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k8s-graceful-shutdown
The library provides the resources to implement graceful shutdown
The library provides the resources to implement a graceful shutdown with Kubernetes. When running microservices in Kubernetes. We need to handle the termination signals emitted by Kubernetes. The simple app shown above, adds a graceful shutdown period of 5 seconds after which the hook, which takes care of closing the server with the help of our shutdown functionality, gets triggered. Upon sending a SIGINT or SIGTERM signal, the user can see that a grace period of 5 seconds after which a waiting... -
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Polly
A .NET resilience and transient-fault-handling library for policies
..., spikes in load, all challenge 100% reliability. Polly helps you navigate the unreliable network. By providing resilience strategies in fluent-to-express policies such as Retry, WaitAndRetry, and CircuitBreaker, Polly can help you reduce fragility, and keep your systems and customers connected. Example usages are fault-tolerance for any distributed systems and inter-process calls, such as WCF, RESTful calls between microservices, calls to cloud services, Internet of Things connectivity, etc. -
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Lagom
Reactive Microservices for the JVM
The opinionated microservices framework for moving away from the monolith. Lagom helps you decompose your legacy monolith and build, test, and deploy entire systems of Reactive microservices. Lagom is an open source framework for building systems of Reactive microservices in Java or Scala. Lagom builds on Akka and Play, proven technologies that are in production in some of the most demanding applications today. Lagom's integrated development environment allows you to focus on solving business... -
Holistically view your business data within a single solution.BrightGauge, a ConnectWise solution, was started in 2011 to fill a missing need in the small-to-medium IT Services industry: a better way to manage data and provide the value of work to clients. BrightGauge Software allows you to display all of your important business metrics in one place through the use of gauges, dashboards, and client reports. Used by more than 1,800 companies worldwide, BrightGauge integrates with popular business solutions on the market, like ConnectWise, Continuum, Webroot, QuickBooks, Datto, IT Glue, Zendesk, Harvest, Smileback, and so many more. Dig deeper into your data by adding, subtracting, multiplying, and dividing one metric against another. BrightGauge automatically computes these formulas for you. Want to show your prospects how quick you are to respond to tickets? Show off your data with embeddable gauges on public sites.
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10
Functional, Data Science Intro To Python
[tutorial]A functional, Data Science focused introduction to Python
The first section is an intentionally brief, functional, data science-centric introduction to Python. The assumption is a someone with zero experience in programming can follow this tutorial and learn Python with the smallest amount of information possible. The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, command line tools, recommendation engines, Sentiment Analysis and Cloud Computing.
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