clojure-news-feed VS proposals

Your question is interesting to me. As a software architect, I study various tech stacks and programming languages. I concentrate mostly on open source and microservice architectures. I usually start with implementing the same feature identical rudimentary news feed microservice. Over time you start to see the similarities and differences between the various implementations. I blog about this over at https://glennengstrand.info and the source code can be found in https://github.com/gengstrand/clojure-news-feed

You are looking for a decision on what programming language and tech stack to learn next based on career mobility. Here are some questions to consider.

What kind of company are you most interested in working for? Think about the size of the company. Is it in a growth market or is profitability more important? Is it a technology company? Does the CEO view technology as a profit center or a cost center? Do they have a CTO? If they do, then who does the CTO report to, the CEO, the CIO, or the COO?

What kinds of programming languages and tech stacks are on the career pages for the kinds of companies that you are most interested in? Different kinds of companies tend to cluster around different tech stacks. There are other factors to filter for such as how deeply do they embrace remote work or commute distance to where you currently live or are willing to move to.

These are lagging indicators. They are going to be more accurate than leading indicators but that also might indicate that whatever you learn next based on these factors might have a shorter shelf life.

Finally, you should ask yourself what about your current programming language do you like? Try to pick something that you would also like. The Go programming language was originally invented as a better C and is enjoying some marketability right now. Maybe that would be something to look at.

I have a github repo where I implement a feature identical microservice in various tech stacks. I started that repo with a Clojure version that used community provided wrappers. See https://github.com/gengstrand/clojure-news-feed/blob/master/... as an example of calling Cassandra. Recently, I added another implementation with Clojure that just called the Java drivers directly. See https://github.com/gengstrand/clojure-news-feed/blob/master/... for that version of the same call. In the end, I decided to forego wrappers and make the calls directly because you end up with fewer dependencies and are more likely to be able to use latest versions of everything.

I have been exposed to many different tech stacks over the years. This https://github.com/gengstrand/clojure-news-feed repo contains the code used to evaluate thirteen different stacks which is what I can share publicly. What I can say is that the best choice of tech stack depends on what is being called for. Is this for an early stage startup or an intrepreneurial greenfield project? Is this for an MVP or just the next component in an already formalized microservice architecture? What are the skillsets of the developers that you will have access to? Have you reached agreement that you can throw it all away and start over or are you expected to have to live with the choice of tech stack for the life of the product? Are you mobile first? These are all important questions that very much shape the decision.

Check out temporal.io open source project. It was built at Uber for large scale business-level processes. So any data pipelines are low-rate use cases by definition.

With KuFlow it is also possible to work with serverless workflows apart from Temporal.io, we explain it in this blog entry, but in summary, almost as a no-code tool, the correct use It would be a rather low-code tool; in just a matter of minutes with our drag-and-drop tool, you can have a workflow that interacts with one or more users of the organization.

Otherwise you may want to look into Kafka or Fluvio to ensure that task runs at least once. If you're doing something like batch operations as a background task, Temporal is another great option.

The runtime is developed using Temporal, which is one of the main tools that we are currently using at KuFlow. Thanks to, all the workflow executions are robust: your application will be durable, reliable, and scalable.

Hmmm I got confused by the name. I thought it's related to https://temporal.io/

Have you looked at temporal.io open source platform? It uses event sourcing as an implementation detail. But it greatly simplifies the user experience compared to "raw event sourcing."

Rewrite Airflow on top of temporal.io. This way, you get unlimited scalability and very high reliability out of the box and would be able to innovate on the features that matter for DE.

Hi all, founder @ Retool here. Over the past year, we’ve been working on Retool Workflows; a fast way for engineers to automate tasks with code. We started building the product because we ourselves (as developers) were looking for something in-between writing cron jobs (which involves a lot of boilerplate) and Zapier (which oftentimes isn’t customizable enough, since it doesn’t _really_ support writing code).

Workflows is a code-first automation tool: you’re _expected_ to write code, but we handle all the boilerplate for you. For example: out-of-the-box integration with 80+ resources (you probably don’t want to be trying to figure out OAuth 2.0 with Salesforce!), monitoring and observability (so you can see the output of every run in the past, and immediately be notified if something goes wrong), and permissions (e.g. some Okta groups can see the outputs of Workflows, but can’t change the code itself).

Right now, the product is cloud-only, but we’re hard at work at an on-prem, self-hosted version (in a Docker image). If you’re interested in that version, feel free to email us at [email protected]. We aim to get it out in the next few weeks. Self-hosted Retool is responsible for a large portion of our usage today, and we’re excited to be supporting Workflows too.

All Retool plans now include 1GB of Workflows throughput, which we think is quite generous (80% of active Workflows users are below 1GB). We don’t bill by run at all, so you’re welcome to run as many workflows as you want.

We use a bunch of interesting technology for Workflows; we are, for example, using Temporal (https://temporal.io/) under the hood. That’s something we’re going to be writing a blog post about later. (We’ve been hard at work on the launch, hah.)

In such a diverse world, it would be boring to have a single way of doing things. That's why at KuFlow we support different ways to implement the logic of our processes and tasks. And in this post, we will talk about one of them, the orchestration through Temporal, which gives us a powerful way to manage our workflows.