Are you tired of relying on Directed Acyclic Graphs (DAGs) for your workflow orchestration? Consider transitioning from Apache Airflow to Temporal. With a focus on scalability and fault tolerance, Temporal is the perfect solution for complex workflows. Migrating from Airflow to Temporal can improve error handling and even solve looming tech debt.
Deploying an updated version of Temporal workflow code can result in errors if there are non-deterministic changes to the code. Determinism is verified during the “replay“ process that rebuilds the last known state of an ongoing workflow in order to continue its execution. Rebuilding execution state enables Temporal to support long-sleeping workflows and reliably relocate workflow executions to another worker when one crashes.
Using cloud services is standard practice for most backend application architectures. When using cloud services, it is important to understand and control what data is leaving your network and being sent to the cloud. Temporal Cloud has great options available to ensure that data sent to and from the cloud is securely encrypted. This post will showcase how Temporal Cloud might interact with your infrastructure by default and how you can customize Temporal to prevent any user or business-related data from being sent to the cloud.
Managing your own Temporal cluster is a daunting task. Between the four core services, the myriad of metrics to monitor, and a separate persistence service, it's a sizeable undertaking for any team. This post begins a new series that will review the work involved in hosting Temporal yourself and try to demystify it.
Bitovi’s Backend Consulting team has had the pleasure of working with Temporal for several different use cases over the last few years. Temporal has greatly simplified complex distributed systems and helped our team focus more on achieving business goals and to spend less time handling errors, among many other things. Temporal isn’t a silver bullet, but it is helpful in a variety of different situations.
A skill our Node.js Consulting team practices often is the process of breaking down new product requirements into actionable technical requirements. This is one of the most critical capabilities for a developer to learn in order to help their organization swiftly deliver new features to their users. In this post, we’ll talk through the process we use on our projects.
Lots of things change year over year, especially in backend development. GraphQL, as well as Node.js, are no exception! We’ll cover some background context for the changes leading up to 2023 and then highlight the most relevant changes that happened last year. Without further ado, let’s hop in!