dtm
proposals
dtm | proposals | |
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20 | 60 | |
5,149 | 63 | |
- | - | |
9.8 | 4.2 | |
about 2 years ago | 8 days ago | |
Go | ||
BSD 3-clause "New" or "Revised" License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
dtm
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How to reliably sync 2 application databases
- using a distributed transaction framework (like https://github.com/dtm-labs/dtm)
- Examples code for DTM Saga
- dtm 1.15.1 Released – A lightweight workflow engine to orchestrate micro-services for distributed transactions.
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Use workflow to handle distributed transactions
But in this article, we introduce a workflow pattern in github.com/dtm-labs/dtm. Under this pattern, a mixture of XA, SAGA and TCC can be applied to different branches in a single distributed transactions, allowing users to customize most of the contents of a distributed transaction, providing great flexibility.
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How to elegantly implement a multi-database outbox pattern
The open source distributed transaction framework https://github.com/dtm-labs/dtm has a two-stage message pattern inside that handles this problem very well. The following is an example of the use of an interbank transfer operation.
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How to Manage Anomalies in Saga Pattern in Microservices
The above Sub-transaction Barrier technique, when used in conjunction with the distributed transaction framework https://github.com/dtm-labs/dtm, has been made available in several language SDKs, with the following example code in Go.
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Building financial integration with Cadence in doordash
Maybe you can take a look at github.com/dtm-labs/dtm which provide built-in TCC pattern
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Understanding XA Transactions With Practical Examples in Go
Distributed XA transactions can solve the above business problem. This article presents a solution based on dtm-labs/dtm. DTM is a popular distributed transaction framework which supports XA, Saga, OutBox, and TCC patterns.
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dtm 1.13.5 Released – A distributed transaction framework that supports saga, tcc, xa, outbox patterns.
Github: https://github.com/dtm-labs/dtm
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How to Implement a Distributed Transaction Across Mysql, Redis, and Mongo
This article gives an example of implementing a distributed transaction across multiple store engines, Mysql, Redis and Mongo. This example is based on the Distributed Transaction Framework https://github.com/dtm-labs/dtm and will hopefully help to solve your problems in data consistency across microservices.
proposals
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Is there an alternative for Airflow for running thousands of dynamic tasks?
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.
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KuFlow as a Temporal.io-based Workflow Orchestrator
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.
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How to handle background jobs in Rust?
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.
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No-code or Workflow as code? Better both
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.
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Temporal Programming, a new name for an old paradigm
Hmmm I got confused by the name. I thought it's related to https://temporal.io/
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Possible innovations in Event Sourcing frameworks.
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."
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After Airflow. Where next for DE?
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.
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Show HN: Retool Workflows – Cronjobs, but better
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.)
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How KuFlow supports Temporal as a worfkows engine for our processes?
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.
- Library for manage tasks when make a workflow automation.
What are some alternatives?
Seata - :fire: Seata is an easy-to-use, high-performance, open source distributed transaction solution.
conductor - Conductor is a microservices orchestration engine.
go-cache - An in-memory key:value store/cache (similar to Memcached) library for Go, suitable for single-machine applications.
temporalite-archived - An experimental distribution of Temporal that runs as a single process
temporal - Temporal service
zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
bolt
seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
InfluxDB - Scalable datastore for metrics, events, and real-time analytics
kubemq-community - KubeMQ is a Kubernetes native message queue broker
cockroach - CockroachDB - the open source, cloud-native distributed SQL database.
nextjs-cron - Cron jobs with Github Actions for Next.js apps on Vercel▲