We used the solution for integrations. I worked for a company that did international freight integrations, and we had to integrate with a system called CargoWise to help our customers track their containers and shipments. We used Temporal workflows to pull in data and keep everything in sync.

The solution's most valuable feature is its ability to fix things quickly. Suppose there's a bug in the code and the workflow you created in Temporal breaks in production. If we lose that data, the system will be out of sync. With Temporal, you can create and push a patch to production so that the workflow will retry automatically, and you won't lose any data.

We previously faced issues with the solution's patch system. We had to create the patch and put a condition on the code to check if the workflow was patched or not. Then, we needed to push another change to get rid of that patch.

I used Temporal on my previous job for seven to eight months.

In our case, the solution's scalability was pretty good. We used the Temporal Cloud service. Temporal gives you the option to either host it yourself or pay for the service, and we paid for Temporal Cloud. We also had our workers running on Kubernetes. It was pretty good. We had to scale it up a few times, but it just worked fine.

I rate the solution’s scalability an eight out of ten.

We contacted the technical support team many times to ask questions and get help, and they were very good at responding.

The solution's initial setup was straightforward, but setting up the tokens on Temporal Cloud was difficult. You had to create this token, and they have docs on it. You can install a Docker container that will create a token for you, but it's not production-ready. We had a couple of issues getting that going. However, it was fine after we learned it.

Temporal is worth the money.

One of the reasons we wanted to change to Temporal was to cut costs because our AWS bill was really, really high. We migrated all of our integrations to use Temporal workflows. The savings weren't as big as we initially expected, but they were pretty great from a developer's perspective.

You need to be a software developer or a software engineer to use Temporal. Other than that, its documentation is pretty good. It is a pretty new product. We found it online when we first started working with it. When we thought it would fit our needs, we read the docs and started building the workflows, and it worked.

I would recommend the solution to other users because it's a really good tool. Temporal gets rid of the need to worry about a bunch of things. When coding, I felt like I could focus on the integration itself, and I didn't have to worry that much about making sure things didn't break.

Suppose you have an integration, and you're building it all by yourself. If something breaks in a microservice, the other microservice needs to be ready, and everything needs to be ready to support that error without losing any data. Using Temporal got rid of a lot of that complication.

Overall, I rate the solution a nine out of ten.

We use Temporal in our company to create child components and complete workflows that are dependent on each other. We also use it for child workflows and employee task orientation.

The most valuable thing about Temporal is that we can create multiple and child workflows. We can segregate work as we want, which is good for work organization. It's also easy to maintain. We're trying to generate and fill PDF forms with custom data, including digital signatures. We call AWS and do all activities through Temporal, like calling and saving data in buckets. We do this because we have a lot of load, with multiple users requesting data. We have two types of users: admin and customer. The admin creates forms, and employees or customers fill them out. When admin gets a form, it's stored in Temporal.

We convert RSA files to PKCS format for integration and have configuration settings. Many libraries help integrate the tool, making it easy to implement in Java and Python.

One issue is that we don't have enough resources in the community to get answers when we face problems. We once had a cross-cluster persistence issue, which we solved using different keys. I think Temporal is good right now, but I'm part of the community and will let you know if I think of any improvements.

We use the cloud version of Temporal. They provide a key that we insert in our files to execute functionality. Our certificate expires in one year, which can cause issues in the product. It would be beneficial if the certificate expiry timeline could be extended to two or three years, as changing it every year is challenging.

One issue is that workflows without an expiry time can run indefinitely, overloading the server. It would be helpful to have a default timeline that automatically deletes or removes workflows after a month.

I have been working with the product for a year.

The tool doesn't have any performance issues.

The solution's scalability is high.

I haven't contacted support yet.

Before Temporal, we tried to implement Kafka, but Temporal was better suited to our use cases. We evaluated Kafka but decided to go with Temporal.

The initial setup can be tough for beginners as it's not like simple coding languages. You must understand how functions work, including small things like run methods. I followed the personal document. Three to four people were involved in the deployment. Deployment locally can take one or two days, including all activity checks and finalizing components.

I rate the overall solution a nine out of ten.

We have multiple products and wanted to use Temporal because different business logic was better suited to different programming languages, such as Java and Python. We needed a unified solution to handle this diversity. Netflix, one of our clients, introduced us to Temporal.

We set up an on-premise Temporal server, with Temporal handling the initial setup in our Kubernetes cluster. Another team implemented additional security measures on top of Temporal to enhance security. We developed our authentication system and library to integrate with multiple role-based access control systems.

We use Temporal primarily for orchestration. We deploy products across AWS Cloud, Azure, and on-premise data centers. Temporal helps us centralize the orchestration process. We use the Temporal SDK to implement our workflows and workers in our Kubernetes cluster. Based on user requests from a centralized portal, we trigger workflows, which drive multiple tasks sequentially or concurrently to deliver the desired outcomes.

Temporal solved a major problem for us. Implementing a saga pattern or a workflow management system traditionally requires handling many aspects beyond business logic. These include retry mechanisms, rollback mechanisms, logging, monitoring execution status, and features for pausing or resuming workflow execution. Temporal provides all these features by default, allowing us to focus solely on our business logic while Temporal manages the rest.

The network should consider adding a basic authentication system to Temporal, such as JWT token-based authentication. Temporal doesn’t include these features by default, and while Temporal Cloud might offer them, on-premise users have to build their security systems. This is an area where there is room for improvement.

Temporal terminology can be confusing for new users. A more user-friendly approach or improved documentation could help ease the learning curve. The current documentation often requires users to piece together information from various sources, including existing implementations from other organizations or direct developer support. The documentation needs a significant update. Not all necessary information is available online, and community support is limited. For instance, our security team implemented certain features a year ago, but it included relevant information in their documentation. Improved documentation and better community support would greatly benefit users working with Temporal.

I have been using Temporal for the last one and a half years.

While Temporal is generally stable, improvements could be made in some areas. Temporal UI provides information on execution status; it only shows the latest state and not the history of previous attempts or failures. This limits our ability to diagnose issues without setting up a separate logging system in tools like Splunk or Elasticsearch.

The traceback provided by Temporal isn’t always helpful when working with core areas such as interceptors. For instance, verifying if tokens are correctly attached to headers and linked with requests is difficult.

Another challenge is with SDKs. Temporal uses different approaches depending on the language: for Go and Java, it provides native SDKs, while for Python and TypeScript, it uses a Rust core with wrappers. This division makes it difficult to trace issues in the Rust core from Python or TypeScript, creating a barrier to debugging and development.

I rate the solution’s stability a seven out of ten.

From a scalability perspective, Temporal excels. It allows us to spawn multiple workers and handles task distribution across them efficiently. We don’t need to worry much about load balancing. We build and launch as many containers as needed, pointing to the same Temporal server. Its server is a load balancer and a queue system, making it highly effective for scalable applications.

It would be beneficial if Temporal could simplify scalability by allowing workers to spawn multiple processes within a single container based on a specified number rather than deploying multiple containers. This approach would streamline scalability and reduce the need for additional management from the Jenkins side.

We have around ten to twelve services running on the top of Temporal.

I rate the solution’s scalability an eight out of ten.

We did not find any dedicated support. We had to either raise concerns in their forum or connect to the Slack channel of Temporal and raise concerns in the appropriate channel, such as the Python SDK channel, for Python-related issues.

They operate in US time zones, and since I am in the Indian time zone, I have to wait until they are online to receive assistance. The support is text-based only, and there is often a delay.

Suppose you have multiple technologies across your portfolio and want to implement business logic. In that case, it’s better to use technologies like Temporal instead of converting all the business logic to a single language. If you’re starting from scratch and the business logic is simple without complex scenarios, using Temporal from the beginning might not make sense because it can be complex and requires heavy infrastructure, which increases costs. Temporal may not be recommended for small-scale projects, but it could be a good fit for larger scales where you’ve already implemented many things in different languages.

Overall, I rate the solution an eight out of ten.

Temporal serves as an orchestration manager for our Mac platform. It allows us to view and manage all the workflows within the application, providing a framework for implementing these workflows efficiently. Temporal itself doesn't store data; our AWS setup handles storage and other functionalities. Temporal offers a platform for orchestration management and provides SDK tools.

Temporal serves as an Orchestration Manager for our microservices architecture. It automates the communication and actions between multiple microservices. With Temporal, we can track workflows' progress, identify failures, and retry actions as needed. It eliminates the need for each microservice. Previously, we had a dedicated microservice for orchestration, but Temporal replaced it seamlessly.

Temporal provides visibility into workflow progress and analytics andsupports scheduled tasks with customizable settings, making it very convenient.

There are areas where Temporal could improve. For instance, calling multiple microservices with Temporal introduces latency due to workflow registration and analytics overhead.

I have been using Temporal for the past year.

I haven't experienced any stability issues or bugs with Temporal. It has been stable and reliable throughout my use, up to version 1.5.

I once contacted Temporal's support team regarding a certificate issue, but it was our mistake. Overall, I was satisfied with the support.

The initial installation and setup of Temporal was straightforward. We needed to generate a certificate and private key, making the process very simple.

If someone asked me whether they should use Temporal for the first time, I'd say it depends on their customer base. If they have few customers, RabbitMQ might be a better choice. However, if they have many customers or an event-driven system, Temporal would be easier to manage and track. For a beginner joining our team, learning Temporal might initially have a moderatelearning curve, but once you get the hang of it, it becomes pretty easy to understand.

I would rate Temporal nine out of ten because it's the best workflow manager I've used.The one-point deduction is mainly for potential improvements and the latency issue that can sometimes occur.