Posts Tagged ‘IronWorker’
IronWorker vs. Google Cloud Run
IronWorker vs. Google Cloud Run: Which One Should You Choose? vs Overview Architecture: IronWorker is an on-demand async task processing tool for container-based workloads. Google Cloud Run lets you run stateless containers that are called upon from HTTP requests. IronWorker relies on the Docker container format. Google Cloud relies on Knative, based on the Kubernetes…
Read MoreCloud Agnostic Architecture Strategies
The landscape of business IT and computing has altered dramatically over the last few years. At least 91% of organizations have adopted the public cloud for a multitude of tasks. Public Cloud refers to cloud computing services such as storage, software, and virtual machines provided by third parties over the internet. Some of the biggest public cloud providers…
Read MoreGoogle Cloud Run Alternatives and Review
Heads up IT professionals! Google Cloud Run is a new cloud computing platform and it is out of Beta that’s hot off the presses from Google, First announced at the company’s Google Cloud Next conference, April 2019 marked its remarkable birth. Google Cloud Run has generated a lot of excitement (and a lot of questions) among both tech journalists and…
Read MoreParallel Asynchronous Processing: Emails & SMS Notifications Best Practices
Emails, texts, and other notifications are critical for engaging with customers. No matter what form they take – alerts, daily summaries, weekly updates, special notices, or monthly newsletters – emails and notifications keep your customers informed, provide them with core services, and help drive revenue. These notifications come in a growing number of formats delivered…
Read MoreSuper Easy Batch Processing with Docker and IronWorker
Batch processing means getting a lot of one type of task done all in one go, saving time, effort and money. There are many ways to do this, but businesses are always hunting for more efficient ways to do more without over-complicating their apps or business tools. Today, we’re going to look at how a user-friendly…
Read MoreEvery Web Application Needs a Background Processing Queue
Every web application has crucial tasks that need to run in the background. They run outside of the main web response loop, but ensure any number of critical jobs gets done to keep the web-based application running smoothly. This means end users enjoy an engaging app experience, without it grinding to a halt every time…
Read MoreWhat is a Docker Image? (And how do you use one with IronWorker?)
Love them or hate them, containers have become part of the infrastructure running just about everything. From Kubernetes to Docker, almost everyone has their version of containers. The most commonly used is still Docker. IronWorker was among the very first to combine serverless management with containers. In this article we will give a high-level overview…
Read MoreWhat is Python Celery?
Celery is an implementation of the task queue concept, one that significantly enhances the end user’s experience. It also benefits developers by saving them time, so that they can focus on what really matters — their ideas and innovations. That is why it remains one of the most popular background job managers in the Python…
Read MorePython Celery Software: Pros & Cons and Reviews
Introduction Python Celery is an open-source project for implementing asynchronous task queues and job queues. If you’re looking for a good Python Celery overview, check out our article “What is Python Celery?”. But now that we’ve discussed how Python Celery works, what about the pros and cons of using Python Celery, or what real users have…
Read MoreCelery vs. IronWorker — Which One Should You Choose?
Vs 5 important differences between Celery vs. IronWorker: Language: Celery runs on Python. IronWorker is “language agnostic.” Performance: IronWorker has far more features than Celery. (It has a better UI too!) Scalability: IronWorker is, hands down, much easier to scale. Price: Celery has an open-source license (this means it’s free!), but it comes with limitations. They…
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