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How Mule implements message processing for a GIVEN flow is determined by a Flow Processing Strategy. All Mule FLOWS have an implicit processing strategy which Mule applies AUTOMATICALLY: either SYNCHRONOUS or queued-asynchronous. Each of these processing STRATEGIES is optimal for certain flows. 

The different types of Flow Processing Strategies are:

• Synchronous Flow Processing Strategy.
• Asynchronous Flow Processing Strategy.
• Queued Flow Processing Strategy.
• Queued Asynchronous Flow Processing Strategy.
• Custom Processing Strategy.
• Thread Per Processing Strategy.
• Non-blocking Flow Processing Strategy.

The code in MuleSoft be optimized for memory efficiency in the following WAYS:

• One should not save the payload into the flow variable. This is because it is a more memory consuming element.
• The unnecessary part of the document should not be LOADED while processing.
• For highly concurrent SCENARIOS, one should use better database polling.
• Use Dataweave for transformations.

The following are some WAYS to improve the performance of the Mule Application in MuleSoft:

• Put the data VALIDATION at the start of the flow.
• Use Streaming to PROCESS data.
• Save the results of the application and reuse them later.
• Process data asynchronously WHEREVER is possible.

Reliability in Mule MEANS Zero message LOSS. To make this happen, applications must be designed in a way to capture the STATE of a running process/instance, which can be picked up by another running node in the cluster. Reliable messaging is given by built-in support of transactions in transport, if the application uses a transactional transport such as Java Message Service (JMS), Virtual Machine (VM), Database (DB), etc. A reliable messaging pattern is essential when dealing with non-transactional endpoints.

A runtime engine that is used to host and run Mule applications, is CALLED a Mule runtime. This is similar to an APPLICATION server. Mule RUNTIMES can be provisioned either on the premises or also on the cloud. A SINGLE Mule runtime can host SEVERAL Mule applications. Here is the figure representing Mule runtime. 

In Mulesoft, Worker is a dedicated instance of Mule hosted on AWS that is used to run the INTEGRATION applications.

Following are some of the features of WORKERS:

• Capacity: For the purpose of data processing, every worker has a given amount of capacity.
• ISOLATION: Isolation means that every worker runs in a separate container from every other application.
• Manageability: Manageability means that the deployment and management of each worker are done independently.
• Locality: In this feature, every worker runs and is located on a specific worker cloud. 

In Mule, a runtime manager is used for deploying and managing Mule applications. This is DONE on the Mule runtime engine where Mule runtime is running. We can deploy or pause the mule application by using runtime manager. We can also change the runtime VERSION of the application at a given TIME. The WORKER size can be increased or DECREASED as well.

Connectors in Mule are Mule’s ABSTRACTION for sending and receiving data and interacting with various APIS. There are generally 2 forms of connectors in Mule: 

• Transport: This is the most common FORM of connector used in Mule. Like HTTP, transports provide an adaptation layer for a protocol. These are the sources and sinks for data - to get data into and out of flows.
• Cloud connectors: These are typically used to interact with an API. Usually, cloud connectors don’t give endpoints. Instead, they have message PROCESSORS that map to the operations provided in the API. The operations of an API are combined by these cloud connectors. The effect of this is that the initial friction for a developer is greatly reduced.

In Mulesoft studio, the grouping of services (application objects and their attributes) created are CALLED Models. Through this, a USER can START and stop the services inside a GIVEN MODEL.

In Mule, shared resources are common resources that are EXPOSED to all applications DEPLOYED under the same domain. Sharing resources allows different development teams to work in PARALLEL. 

For instance: Connector configurations could be made a reusable resource. These could be shared among all applications deployed.

These shared resources should be defined in the Mule Domain Project. These should then be REFERRED to each of the projects that are meant to use the elements in it. 

MEDIATION is used for PERSONALIZING interactions between DISTRIBUTED applications and service components. The following are the different PRIMITIVES used in Mediation:

• Message Filter
• Type Filter
• Endpoint Lookup
• Service Invoke
• Fan-out
• Fan-in
• XSLT
• BO Map
• Message Element Setter
• DB lookup
• Data Handler
• Custom Mediation
• Header Setters
• Message Logger
• Even Emitter
• Stop
• Fail
• Sub FLOW

• Echo and Log message - These are used to log messages and move them from inbound to OUTBOUND ROUTERS. Inbound Routers means a single event is received via an endpoint and the router controls how and if this event gets routed into the system. Outbound routers mean once a message has been processed by a component an outbound router can be used to determine which components get the RESULT event.
• Bridge Message - This is a passed message from inbound to outbound routers.
• Build Message - These are messages CREATED from fixed or dynamic VALUES.

The different TYPES of variables in MuleSoft are as follows: 

• Flow Variable: This is USED to either set or remove variables that are tied to a particular message in the current flow.
  SYNTAX: #[flowVars.Code]
• Record Variable: This is used for the batch processing flows. Unlike any other variable, these are special variable sets that are used only inside a Batch Job.
  Syntax: #[recordVars.Code]
• Session Variable: This is used to either set or remove variables tied to a particular message for the ENTIRE LIFECYCLE. 
  Syntax: #[sessionVars.Code]

In Mule ESB, a batch job is an element in a mule that splits large messages into records. These records are then PROCESSED asynchronously in a batch job.

Within an application, one can initiate a Batch Job scope, which splits messages into individual records, performs actions upon each record, and then reports on the results and POTENTIALLY PUSHES the processed output to other systems or queues. With this, we can handle large quantities of incoming data from an API into a LEGACY system. We can also synchronize data sets between business applications.

Mule ESB stands for Mule ENTERPRISE Service Bus. Mule ESB makes it easy for the development teams to flexibly connect, access, and exchange data EASILY. This means that even though the application is running into different VMs, the interactions between them are easy. 

Following are some of the FEATURES of Mule ESB:

• MESSAGE Transformation Service
• Set of Service Container
• Web Service Security
• Message ROUTING Service
• Simple drag-and-drop graphical design
• Centralized monitoring and administration

MuleSoft helps in the task of data integration diligently and efficiently. The tools and SERVICES offered by MuleSoft include:

• API Designer: API Designer is a web-based tool that contains a console and a scripting notebook for JavaScript.
• API Manager: API Manager is a management tool that allows ORGANIZATIONS in managing users, traffic, and service level agreements.
• Anypoint Studio: Anypoint Studio is a graphical design environment to build and edit APIs and integrations.
• API PORTAL: This is a portal that offers DEVELOPERS different kinds of documents, tutorials, and code snippets related to APIs.
• API Analytics: API Analytics is an analytics tool that allows a user to track the specifications of an API. This also includes its performance, usage, and reliability. Additionally, it offers a dashboard and charts.

Mule is an open-source enterprise INTEGRATION platform that helps tackle the problems in developing integration applications. Some of the problems that are tackled by Mule include Error handling, Monitoring, Lifecycle and management, Data format, ETC. Thus, with these problems gone, Mule helps FOCUS on the application’s CORE requirements like scalability and efficiency.