What are MuleSoft Data Integration patterns?
Like a hiking trail, patterns based on usage are discovered and created. Patterns often arrive in degrees of perfection. But depending on what business requirements need solutions, they can be optimized or adopted. The business use case can be thought of as an instantiation of the pattern, i.e. use for the generic data movement and handling procedure. Based on business use cases as well as basic integration trends, there are five MuleSoft Data Integration patterns that we have defined and designed templates around.Pattern 1 of MuleSoft Data Integration: MuleSoft migration
MuleSoft migration is the process of transferring a particular collection of data from one device to the other at a point in time. MuleSoft migration involves a source system where the data exists before execution. It’s a criterion that defines the extent of the data to be migrated.
Why are they valuable?
MuleSoft migrations are important to all data systems and are used extensively in every data operating organization. We spend a lot of time producing and preserving data, and MuleSoft migration is crucial to keeping the agnostic data from the tools we use to produce, display and handle it. Without relocation, we will be forced to lose all the data we have accumulated if we choose to change methods. And this will cripple our capacity in the digital world to be productive.
When is it beneficial?
MuleSoft migrations occur most often if you switch from one system to another, move from a system instance to another, or newer system instance. Then spin up a new system that expands the existing infrastructure, back up a dataset, add nodes to database clusters, etc. Moreover, there is substitute hardware for databases, merge systems, and many more.
Pattern 2 for MuleSoft Data Integration: Broadcast
The broadcast can also be referred to as “one-way sync from one to many”. And it is the act of transferring data on a continuous and real-time (or near real-time) basis.
You would need either a broadcast, bi-directional sync, or correlation pattern. If there is a need to keep our data up to date between different systems over time. The difference here is that, like the MuleSoft migration pattern, the broadcast pattern only transfers data in one direction, from the source to the destination. The broadcast pattern is transactional, unlike the MuleSoft migration pattern. These have recently been modified.
Think of broadcasting as a sliding window that catches only those things with field values that have changed since the last time the broadcast was run. Another big difference is how the pattern implementation is constructed. To manage large quantities of data and process several records in parallel and to provide a graceful failure scenario, MuleSoft migration will be tuned. Broadcast patterns are designed to process records as quickly as possible. And they are highly reliable to prevent losing sensitive data in transit. As they are commonly used in mission-critical apps with low human oversight.
Why are they valuable?
If system B wants to know any information that originates or exists in system A in near real-time, the broadcast pattern is extremely useful. For example, you can want to create a monitoring dashboard in real-time, which is the destination of multiple broadcast apps where alerts are received. So that you can know what is going on through multiple systems in real-time. You may want to start fulfilling orders immediately that come from your CRM, online e-shop, or internal tool. Where the delivery system for fulfillment is centralized regardless of which channel the order comes from.
You may want to send a report to a control system every 100 ms of the temperature of your steam turbine. When one of your frequent patients is checked in an emergency department, you may want to broadcast to the patient care system of a general practitioner. There are endless examples of when you want to take an essential piece of information from an originating device. And they relay it as soon as possible after the incident occurs to one or more receiving systems.
When is it beneficial?
The “need” of the broadcast pattern can easily be defined by the following criteria:
- Will Machine B need to be understood as soon as the event occurs?
- Does knowledge need to flow automatically from A to B, without human involvement?
- Does system A need to know what happens in system B with the object- No
The first question will help you determine whether you should use the pattern of MuleSoft migration or broadcast based on how the data needs to be in real-time. Anything less than about an hour would appear to be a trend for broadcasting. There are still exceptions based on data volumes, however. The second issue usually rules out “on-demand” apps, and either a push notification or a scheduled job will trigger broadcast patterns in general. And it will also not have human involvement. The last question will let you know whether the two data sets need to be united so that they are synchronized across two systems, which we call bi-directional synchronization. Different specifications would require different patterns of data synchronization. But the broadcast pattern, in general, is much more versatile in how you can pair the apps. Hence, we would suggest using two broadcast apps over a bi-directional sync application.
Pattern 3 of MuleSoft Data Integration: Bi-Directional Sync
The pattern of incorporation of bi-directional sync data is the act of merging two datasets into two separate systems. So that they act as one while maintaining their need to function as distinct datasets. This type of need for integration comes from using different tools or different frameworks on the same dataset to perform different functions. You can, for instance, have a system for taking and handling orders and a separate customer service system. Then, you can find that these two systems are the best of the breed. And they are rather than a suite that supports all functions. And it has a shared database, it is important to use them.
Why are they valuable?
Depending on the conditions that explain its importance, bi-directional sync maybe both an enabler and a savior. You can use bi-directional sync to optimize the processes if you have two or more separate and separated representations of the same reality. And you have the data representations in both systems far closer to reality. Then reduce the compound cost of having to manually fix the inconsistencies, lack of data, or the effect of letting the inconsistencies remain on your business. This is to a suite that you use an enterprise integration tool like our Anypoint Platform to hand-select and integrate.
When is it beneficial?
The need, or demand, for a bi-directional sync integration app is synonymous with needing to be comprehensive and compatible with object representations of truth. For instance, if you want a single view of your customer, you can manually solve that by giving everyone access to all the systems that reflect a customer’s idea. But listing the fields that need to be accessible for that customer object in those systems. And the systems are the owners is a more elegant and effective solution to the same issue.
Many business systems provide a way of expanding objects so that you can change the data structure of the customer object to include those fields. For example, the status of delivery should be understood by a salesperson, but they do not need to know at which warehouse the delivery is. Similarly, without having to know how much the customer paid for it, the delivery person wants to know the customer’s name that the delivery is for. Bi-directional synchronization helps both of these entities to have a real-time perspective of the same consumer from the point of view they care about.
Conclusion
Data is an incredibly valuable business tool, but control, orchestration, and analysis can often be hard to access. It is not always in a standard format as data travels through systems. MuleSoft Data Integration seeks to rapidly make data agnostic and accessible across the organization so that its constituents can access and manage it. And MuleSoft Data Integration patterns can be generated to standardize the integration process to make the data access much faster. You can learn more about these integrations through MuleSoft online training.