DreamFactory’s Smart Logging Service

Introducing DreamFactory’s Event-Driven Log Service

In DreamFactory 2.3.1 we introduced the Log service supporting Logstash, which allows you to send any log messages to a Logstash service, utilize the power of ELK stack, and get REST API usage data using visual tools like Kibana. However, there was one limitation: the DreamFactory Logstash service wasn’t smart enough to do anything on its own. Continue reading “DreamFactory’s Smart Logging Service”

Wrangling Your Data with Database Functions

One of the fundamental goals of the DreamFactory platform is to make it easy to get the data you want, in the format you want, from the sources you have available. Sometimes the type and/or format of the data in the database isn’t easy to pass to and from a client RESTfully, particularly using JSON or XML payloads. DreamFactory’s database functions support solves this problem. Continue reading “Wrangling Your Data with Database Functions”

DreamFactory 2.4.2 adds logging, SAML, and Azure AD

DreamFactory 2.4.2 is live! This release adds new APIs for SAML and Azure Active Directory, event-driven configuration of the logging service, database function support, usability improvements to the schema manager, and a whole lot more. You can download the 2.4.2 release from Bitnami or GitHub now. Here’s a roundup of 2.4.2 improvements:

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Securely Sharing Your Swagger API Docs with DreamFactory

A common use case is securely sharing your API docs in DreamFactory with other users who aren’t DreamFactory admins. You might need to share specific API endpoints with partners, customers, or other developers. This short tutorial demonstrates how to set up role-based access control to specific API endpoints and easily share a secure link to DreamFactory’s live Swagger API docs. Let’s get started!

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Nurse Call systems for Hospitals and Rest Homes.

John Gilfillan, Software Engineer from Miracle Electronicscreated Nurse Call or Care Call systems for Hospitals and Rest Homes. They wanted a REST API that could interact with their software, as well as to give users the ability to make changes to the system remotely. They run a software application called “Angel” on a P.C. which monitors call points located at the bedside of each Hospital patient or in the home of a Rest Home occupant.  

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Database Table Endpoint Obfuscation Through Custom Scripting

DreamFactory’s power lies in the automatic generation of API endpoints and its standardization. There are times however, where you need something a little more custom, and that’s why we have scripting engines included. Let’s look at a specific use case for custom scripting that we have users ask about a lot.

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Ice Report App: The power of Crowdsourcing

Andrew Jenkins, engineer at Split Rock Software and DreamFactory Community member developed an app called Ice Report. He was looking for a prebuilt system to make information in a database easy to access and handle users in secure way and found DreamFactory. DreamFactory allowed him to build a basic user system with a minimal interface, as well as allow users to submit data for others to view in a quick and easy way.

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Queueing With DreamFactory Scripting

DreamFactory has long supported scripting as a way of allowing users to extend the handling capabilities of existing APIs (i.e. performing actions pre- and post-processing like modifying the request or response), or adding new APIs altogether via scripted services. This has proven to be a very popular feature of DreamFactory, but until release 2.3 it was missing a very big “nice to have”, that being a way to save or queue the scripts to be run at a later time and not take the hit of processing the script at the time of the API call. Thus the advent of queued scripting.

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Virtual Relationships Redux

In the early part of 2016, we introduced a feature called DataMesh, also known as Virtual Relationships, or Virtual Foreign Keys. The idea behind this feature is to allow users to set up “virtual foreign keys” to relate data across tables in the same SQL database where foreign keys did not exist or were not desired, or across different SQL databases altogether. We even allowed relating a SQL database table to a MongoDB collection, opening up a whole new way for a client to retrieve all the data it needed, molded in a way that was easily consumable.

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