Andy in the Cloud

From BBC Basic to Force.com and beyond…


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Infinite Data Scrolling with Apex Cursors Beta

UPDATE: Apex Cursors is now GA and with additional features! This blog is still relevant however so read this first – then head over to Improved Infinite Data Scrolling with the new Apex Pagination Cursors GA.

The infinite scrolling feature of the Lightning Datatable component allows practically an unlimited amount of data to be loaded incrementally as the user scrolls. This is a common web UI approach to load pages faster and without consuming unnecessary amounts of database and compute resources retrieving records some users may not even view. The current recommended approach to retrieve records is to use SOQL OFFSET and LIMIT – however, ironically, this approach is limited to 2,000 max records. Substituting this with the new Apex Cursors feature, as you can see in the screenshot below, we have already gone past this limit! Actually, the limit for Apex Cursors is 50 million records – that said, I would seriously question the sanity of a requirement to load this many! This blog gives an overview of the Apex Cursor feature and how it can be adapted to work with LWC components.

If you want to go ahead and deploy this demo checkout the GitHub repo here. Also please keep in mind that as this is a Beta release – Salesforce does not recommend use in production at this time.

What are Apex Cursors?

If you’re not familiar, the Apex Cursors feature (currently in Beta), it enables you to provide a SOQL statement to the platform and for it to return a means for you to incrementally fetch chunks of records from the result set – this feels similar to the way Batch Apex works – except that it’s much more flexible as you decide when to retrieve the records and, in fact, in any order or chunk size. The standard documentation and much of what you’ll read elsewhere online focuses on using it to drive your own custom Apex async workloads using Apex Queueable as an alternative to Batch Apex – however, because it’s just an Apex API, it can be used for other use cases such as the one featured in this blog.

Usage is simple; first, you create a cursor with Database.getCursor (or getCursorWithBinds) giving your desired SOQL. Then, with the returned Cursor object, call the fetch method with the desired position and count. Unlike Batch Apex, you can actually go back and forth using the position parameter, as this is not an iterator interface. You can also determine the total record size via getNumRecords. Before we dive into the full demo code, let’s use some basic Apex to explore the feature to query 5000 accounts.

Database.Cursor cursor = Database.getCursor(
      'SELECT Id, Name, Industry, Type, BillingCity, Phone 
       FROM Account 
       WHERE Name LIKE \'TEST%\' WITH USER_MODE ORDER BY Name');

System.debug('***** BEFORE FETCH *****');
System.debug('Total Records: ' + cursor.getNumRecords());
System.debug('Limit Queries: ' + Limits.getLimitQueries());
System.debug('Limit Query Rows: ' + Limits.getLimitQueryRows());
System.debug('Limit Aggregate Queries: ' + Limits.getLimitAggregateQueries());
System.debug('Limit Apex Cursor Rows: ' + Limits.getLimitApexCursorRows());
System.debug('Limit Fetch Calls On Apex Cursor: ' + Limits.getLimitFetchCallsOnApexCursor());

List<Account> accounts = cursor.fetch(1, 500);

System.debug('***** AFTER FETCH *****');
System.debug('Accounts Read: ' + accounts.size());
System.debug('Limit Queries: ' + Limits.getLimitQueries());
System.debug('Limit Query Rows: ' + Limits.getLimitQueryRows());
System.debug('Limit Aggregate Queries: ' + Limits.getLimitAggregateQueries());
System.debug('Limit Apex Cursor Rows: ' + Limits.getLimitApexCursorRows());
System.debug('Limit Fetch Calls On Apex Cursor: ' + Limits.getLimitFetchCallsOnApexCursor());

The following code gives us the following debug output:

DEBUG|***** BEFORE FETCH *****
DEBUG|Total Records: 5000
DEBUG|Limit Queries: 100
DEBUG|Limit Query Rows: 50000
DEBUG|Limit Aggregate Queries: 300
DEBUG|Limit Apex Cursor Rows: 50000000
DEBUG|Limit Fetch Calls On Apex Cursor: 10
DEBUG|***** AFTER FETCH *****
DEBUG|Accounts Read: 500
DEBUG|Limit Queries: 100
DEBUG|Limit Query Rows: 50000
DEBUG|Limit Aggregate Queries: 300
DEBUG|Limit Apex Cursor Rows: 50000000
DEBUG|Limit Fetch Calls On Apex Cursor: 10

The findings, at least for Beta, show that retrieving or counting records does not count against the traditional limits for SOQL; all the common ones are still untouched. However, before you get excited, this is not an alternative – it has its own limits! Some of which you can see above, which for the Beta do not seem to be getting updated, see further discussion here. The most important one, however, is not exposed via the Limits class but is documented here, which states you can only create 10,000 cursors per org per day. The other important aspect is that cursors can also span multiple requests, so long as you can find a way to persist them; however, they will get deleted after 48 hours. This is also stated to align with the sister feature Salesforce REST API Cursors.

Using Cursors with LWC Components

Cursors when used in the context of Queueable are persisted in the class state – for LWC components while they don’t give an error – are at time of this Beta not serialisable between the LWC client and the Apex Controller – I suspect for security reasons, so I posted here to confirm. This however is not the end of the story, as we do have other forms of statement management between Apex and LWC, specifically Apex Session cache – as the Apex Controller code below demonstrates.

Update: Since GA, Cursors are now serialisable so can be used directly in LWC without the Cache workaround below. See the main repo attached to this blog for an updated sample. Using Cache meanwhile can still be good solution for sharing Cursor results between users.

public with sharing class ApexCursorDemoController {
    
    @AuraEnabled(cacheable=false)
    public static LoadMoreRecordsResult loadMoreRecords(Integer offset, Integer batchSize) {
        try {
            Database.Cursor cursor = (Database.Cursor) Cache.Session.get('testaccounts');
            if(cursor == null) {
                cursor = Database.getCursor(
                         'SELECT Id, Name, Industry, Type, BillingCity, Phone FROM Account 
                          WHERE Name LIKE \'TEST%\' ORDER BY Name', AccessLevel.USER_MODE);
                Cache.Session.put('testaccounts', cursor);
            }            
            LoadMoreRecordsResult result = new LoadMoreRecordsResult();
            result.records = cursor.fetch(offset, Math.min(batchSize, cursor.getNumRecords() - offset));
            result.offset = offset + batchSize;
            result.totalRecords = cursor.getNumRecords();
            result.hasMore = result.offset < result.totalRecords;
            return result;
        } catch (Exception e) {
            Cache.Session.remove('allaccounts');
            throw new AuraHandledException('Error loading records: ' + e.getMessage());
        }
    }
    
    public class LoadMoreRecordsResult {
        @AuraEnabled public List<Account> records;
        @AuraEnabled public Integer offset;
        @AuraEnabled public Boolean hasMore;
        @AuraEnabled public Integer totalRecords;
    }
}

Because the use of Apex Cursors is purely contained within the Apex Controller the LWC component HTML and JavaScript controller are as per traditional implementation of the DataTable component using the infinite scrolling feature – you can click here to see the code.

Thoughts and Community Findings

This feature is a welcome, modern addition to Apex and I look forward to the full GA that allows us to use this confidently in a production scenario. Here is a short summary of some usage guidelines to be aware and some very good points already raised by the community in the Apex Previews and Betas group.

  • Cursor Sharing and Security Considerations
    As you can see in the above, user mode is not the default, but is enabled per best practice via use of AccessLevel.USER_MODE. As it is possible (at least for Beta) to share cursors it is important to make sure you consider who/where else you share the cursor as the user and sharing rules could be different. In this case the above code uses the users session cache so its explicitly scoped to the current user only. I suspect (see below) sharing, CRUD and FLS maybe getting re-evaluated anyway on fetch – but just in case (or you explicitly used the system mode, or the default) – this is something to keep in mind. On the flip side, another use case to explore might indeed by that in some cases it might be optimal to have a shared record set evaluated and maintain across a set of users.
  • Partial Cached Results
    The result set appears to be cached when the cursor is created, but I suspect only the Ids since when changing the record field values – changes are seen in the results on refresh. When a record is deleted however it is not returned from the corresponding fetch call – so worth noting the count you ask for when calling fetch may not be what you get back – though the position indexing and total records remains the same. Likewise if you create a record, even if its matches the original criteria it is not returned. These nuances and others are further discussed here – hopefully the GA documentation can formally confirm the behaviours.
  • Ability to Tidy up
    Given the 10k daily limit, while seemingly generous it would be useful to be able to explicitly delete cursors as well. Suggestion posted here.
  • Just because you can show more data – does not mean you should
    What I mean by this – is just because you can now expose more data does not always mean you should – always consider accordingly the fields and rows your users really need as you would any list / data table view your building – in most cases not having any filter is likely to be an anti-pattern. Additionally don’t forget Salesforce has a number of analytical tools that can help users further when moving through large amounts of data.

Additional Resources

Here is a list of useful resources I found:


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Five ways Heroku AppLink Enhances Salesforce Development Capabilities

Over the years through this blog I have enjoyed covering various advancements in Salesforce APIs, Apex, Flow, and more recently, Agentforce. While I have featured Heroku quite a bit – despite it being a Salesforce offering, the reality has been that access to Heroku for a Salesforce developer has felt like plugging in another platform – not just because on the surface its DX is different from SFDX, but because in a more material sense, it has not been integrated with the rest of the platform and its existing tools – in the same way Apex and Flow are. Requiring you to do the integration plumbing before you can access its value.

Now with a new “free” Heroku AppLink add-on, Heroku has now been tangibly integrated by Salesforce into the Salesforce platform – it and code deployed to it even sits under the Setup menu. So now it is finally time to reflect on what Heroku brings to the party!

This blog starts a series on what this new capability means for Salesforce development. Choosing the best tool for the job is crucial for maximizing the holistic development approach the Salesforce platform offers. Apex, Flow, LWC, etc., are still important tools in your toolkit. In my next blog in this series, I’ll share hands-on content, but for now, let’s explore five reasons to be aware of what Heroku and Heroku AppLink can do for Salesforce development:

1. Seamlessly and Securely Attach Unlimited Compute to your Orgs

At times, certain automations or user interactions demand improved response times and/or abiility handle increasing data volumes. While Apex and Flow have a number of options here, they are inherently always constrained by the multi-tenant nature of the core platform that runs their respective logic. The core platform’s first priority is a stable environment for all – thus, largely we see the continued realities of the infamous governor limits. Going beyond some, though not all, of the governor limits that either stop or at least slow things down is now possible – and without leaving the Salesforce family of services.

You can deploy code to Heroku with git push heroku main, which works in much the same way as sf project deploy to upload your code and run it, then you declaratively assign your compute needs, and attach (using the publish command) access to it for use within your Flow, Apex, LWC or Agentforce implementations – across as many orgs as you like using the connect command.

Heroku supports both credit card (pay as you go) and contract billing for compute usage – with the smallest plan at $5 a month already able to run complex and lengthy compute tasks easily – though milage of course varies on usecase.

2. Tap into the worlds most popular languages and frameworks within Salesforce

Salesforce has some history of embracing industry languages such as Node.js for Lightning Web Components and, with that, taps into wider skill set pools, and also commercial and open-source web component libraries. With Heroku AppLink, this is now true for backend logic – and in fact, it extends language support to Python, .NET, Ruby, Java, and many more languages, all with their own rich communities, libraries, and frameworks. Does this mean I am suggesting you port all your Apex code to other languages? No – remember this is a best tool for the job mindset – so if what you need can be better served with existing skills, code, or libraries available in such languages, then with AppLink you can now tap into these while staying within the Salesforce services.

Note: Heroku AppLink provides additional SDK support presently only for Node.js and Python. That said its API is available to any language – and is fully documented. Java samples included with AppLink illustrate how to access the API directly – along with existing Salesforce API libraries.

You may also think that with this flexibility comes more complexity; well, like the rest of Salesforce, Heroku keeps things powerful yet simple. Its buildpacks and simple CLI command git push heroku main remove the heavy lifting of building, deploying, and scaling your code that would otherwise require skills in AWS, GCP, or other platforms – what’s more, Heroku also curates the latest operating system versions, and build tools for you.

3. More power to existing Apex, Flow and Agentforce investments

As we are practicing choosing the best tool for the job – for complex solutions it’s typically not a case of one size fits all – that’s why we have a spectrum of tools to choose from – while one solution, for example, might be mostly delivered through Flow, the most complex parts of it might depend on some code – and thus having interoperability between each approach is important.

Heroku AppLink draws on the use of platform actions – which has over the years become the de facto means to decompose logic/automations – allow reusable logic to be built in code via Apex or declaratively in Flow. Now with Heroku AppLink, you can also effectively write actions in any of the aforementioned languages and also if needed scale that code beyond traditional limits such as CPU timeout and heap – while benefiting from increased execution times.

What is also critical to such code, is user context, so that data access honors the current user, both in terms of their object, field, sharing permissions but also audit information retaining a trail of who did what and when to the data. Thus, Heroku AppLink has the ability to run code in Salesforce “user mode” – much like Apex and Flow – this means the same – your SOQL and DML all operate in this mode – in fact, that’s the default – no need to qualify it as with Apex. This approach follows the industry pattern of the Principle of Least Privilege – there is also a way to selectively elevate permissions as needed using permission sets.

4. Make External Integrations more Secure

Heroku is also known to the wider world as a Paas (Platform-as-a-Service) providing easy to use compute, data and more recently AI services without the infrastructure hassle. This leads to Heroku customers building practically any application or service they desire – again in any language they desire. For example, a web/mobile experience can be hosted along with required data storage – both able to scale to global event needs. Heroku AppLink, joins Heroku Connect to start a family of add-ons that also help such consumer facing or even internal experiences tap into Salesforce org or even Data Cloud data – by effectively managing the connection details securely in one place – elevating the complexity of managing oAuth, JWT, certifications etc.

5. Leverage additional data and AI services

If all your data resides within a Salesforce org or Data Cloud, Heroku AppLink provides an easy to use SDK to make using the most popular APIs easy and even provides a long time favorite of mine, Martin Fowlers, Unit of Work over the relatively complex composite Salesforce APIs to manage multi-object updates within a single transaction.

Beyond this, you can also take advantage of Heroku Postgres to store additional data that does not need to be in the org but needs to be close at hand to your code – likewise attach to data services elsewhere in AWS, DynamoDB for example. Heroku also provides new AI services that provide a set of simple to use AI tooling primitives on top of the latest industry LLM’s. All these Heroku services exist with the same trust and governance as other Salesforce services and thus leveraging them means you don’t have to move data or compute outside of Salesforce if thats something your business is particularly sensitive to.

Summary

Salesforce continues to bring new innovations to its no-code and code tools that are exciting but yet broaden the burden of choice and making the right choice. With Heroku AppLink, this has indeed added to the mix – and expands the classic vs. question – to – when to use Flow vs. Apex vs. Heroku?

I’ve noticed that the Flow vs. Apex debate is still strong at community events this year. When it comes to “code,” whether it’s Apex, Python, Java, or .NET—excluding Triggers, which AppLink doesn’t support—my opinion on no-code versus code remains the same – consider wisely use of one or both accordingly. In respect to coded needs, I still would still generally recommend Apex first, that is unless your project needs align with the points above – then it’s worth further discussion. Ultimately, it’s about finding a suitable mix instead with all three supporting actions, it’s easier to blend and evolve as needed.

As I hinted at the start of this blog, I plan to get into more hands-on blogs on Heroku AppLink and some reflections on ISV usage. Between these, I also have other Apex-related topics I want to explore—such as the new Apex Cursors feature. In the meantime, here below are some useful links about Heroku AppLink available as of the time of this blog.

Thanks for readying, hope it was useful!


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Enhancing Agentforce Output with Rich Text Formatting

I have been working with Agentforce for a while, and as is typically the case, I find myself drawn to platform features that allow extensibility, and then my mind seems to spin as to how to extract the maximum value from them! This blog explores the Rich Text (a subset of HTML) output option to give your agents’ responses a bit more flair, readability, and even some graphical capability.

Agentforce Actions typically return data values that the AI massages into human-readable responses such as, “Project sentiment is good”, “Product sales update: 50% for A, 25% for B, and 25% for C”, “Project performance is exceeding expectations; well done!”. While these are informative, they could be more eye-catching and, in some cases, benefit from more visual alternatives. While we are now getting the ability to use LWC’s in Agentforce for the ultimate control over both rendering and input, Rich Text is a middle-ground approach and does not always require code. All be it perhaps a bit of HTML or SVG knowledge and/or AI assistance is needed – you can achieve results like this in Agentforce chat…

Lets start with a Flow example, as it also supports Rich Text through its Text Template feature. Here is an example of a Flow action that can be added to a topic with instructions to tell the agent to use it when presenting good news to the user, perhaps in collaboration with a project status query action.

In this next example a Flow conditionally assigns and output from multiple Text Templates based on an input of negative, neutral or positive – perhaps used in conjunction with a project sentiment query action.

The Edit Text Template dialog allows you to create Rich Text with the toolbar or enter HTML directly. Its using this option we can enter our smile svg shown below:

<svg xmlns='http://www.w3.org/2000/svg' width='50' height='50'><circle cx='25' cy='25' r='24' fill='yellow' stroke='black' stroke-width='2'/><circle cx='17' cy='18' r='3' fill='black'/><circle cx='33' cy='18' r='3' fill='black'/><path d='M17 32 Q25 38 33 32' stroke='black' stroke-width='2' fill='none' stroke-linecap='round'/></svg>

For a more dynamic approach we can break out into Apex and use SVG once again to generate graphs, perhaps in collaboration with an action that retrieves product sales data.

The full Apex is stored in a Gist here but in essence its doing this:

@InvocableMethod(
   label='Generate Bar Chart' 
   description='Creates a bar chart SVG as an embedded <img> tag.')
public static List<ChartOutput> generateBarChart(List<ChartInput> inputList) {
   ...
   String svg = buildSvg(dataMap);
   String imgTag = '<img src="data:image/svg+xml,' + svg + '"/>';
   return new List<ChartOutput>{ new ChartOutput(imgTag) };
}

When building the above agent, I was reminded of a best practice shared by Salesforce MVP, Robert Sösemann recently, which is to keep your actions small enough to be reused by the AI. This means that I could have created an action solely for product sales that generated the graph. Instead, I was able to give the topic instructions to use the graph action when it detects data that fits its inputs. In this way, other actions can generate data, and the AI can now use the graph rendering independently. As you can see below, there is a separation of concerns between actions that retrieve data and those that format it (effectively those that render Rich Text). By crafting the correct instructions, you can teach the AI to effectively chain actions together.

You can also use Prompt Builder based actions to generate HTML as well. This is something that the amazing Alba Rivas covered very well in this video already. I also captured the other SVG examples used in this Gist here. A word on security here, SVG can contain code, so please make sure to only use SVG content you create or have from a trusted source – of note is that using SVG embedded in an img tag code is blocked by the browser, <img src="data:image/svg+xml,<svg>....</svg>"/>.

Whats next? Well I am keen to explore the upcoming ability to use LWC’s in Agentforce. This allows for control of how you request input from the user and how the results of actions are rendered. Potentially enabling things like file uploads, live status updates and more! Meanwhile check this out from Avi Rai.

Meanwhile, enjoy!


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New Book – Salesforce Platform Enterprise Architecture 4th Edition

It has been nearly 10 years back in 2014 when the first edition of my book Force.com Enterprise Architecture was first published and clearly a lot has moved on since then and not just the platform capabilities. Keeping pace with branding changes resulted in the second edition of the book being called Lightning Platform Enterprise Architecture. This latest 4th edition, Salesforce Platform Enterprise Architecture has probably the most accurate and I hope enduring title! This 4th edition is also nearly twice the size of the first edition, coming in at 681 pages. So much so, its 16 chapters is now split over 4 parts to make digesting the book easier. As is tradition by now, this blog will cover some of latest updates and additions and what to expect in general from the book.

Links: Amazon | Packt Publishing

Motivation and what to expect…

I first came to the platform with a lot of experience and understanding of architecture principles from other platforms, including leveraging platform agnostic patterns such as those of Martin Fowler. Applying patterns to the platform requires some nuance at times, thus this book is about enterprise architecture considerations as applied to the Salesforce Platform and much more in respect to its capabilities that accelerate traditional application development concerns and tasks for you – and can hinder if not considered upfront in your architecture design.

The book dedicates 3 of its 16 chapters to Apex code separation of concerns, how to layout your code, while the rest covers the full spectrum of app concerns such as designing for code and database performance, profiling, testing, data storage design, building apis, extensibility and more and of course how to write much less code by harnessing the declarative aspects. All this is driven throughout the book via a fictitious reference application known as FormulaForce based on Formula1 motor racing – full source is included. Also included are numerous tips and tricks and info blocks pitted among the pages that highlight learnings from my own experiences, and latterly that of the many amazing reviewers.

As good as the platform is at abstracting a huge amount of the complexity of managing and securing modern day applications for you, there is no escaping having to fully understand good architecture principles that would, and do, in most cases apply elsewhere, such as query optimization and indexing.

If you are developing a lot on the Salesforce Platform, have a few years experience and are passionate about creating applications that are enduring and empathetic to the platform itself – this book is for you. Read on for further highlights!

Is it for ISVs or anyone?

This edition is the first to split out the motivations of packaging in respect to internal distribution needs within your own company vs distributing a commercial solution on AppExchange. Regardless of which motivation you fit into, the chapters will callout which bits are relevant vs not. Even if you are not into packaging at all right now, much of the content on Apex, Lightning, Flow, APIs etc is of course agnostic to how you choose to distribute your application. Regardless who you are sharing it with, the book gives you an appreciation of advantages and limits of packaged based distribution and in my view is a key aspect of your overall architecture considerations checklist.

Have the Apex coding patterns evolved given recent features?

The advent of user mode capabilities has had a big impact on the approach taken within the sample application of the book when it comes to using the Apex Enterprise Patterns Library (fflib), specifically in how the Unit of Work and Selector patterns are used when updating and querying for data respectively.

Additionally, the Domain pattern chapter now reflects on how Domain logic, can, if desired allow the developer to split Domain and Trigger logic into separate classes and thus introduces a new pattern (SDCL) to captured this approach. Thats not to say the original model has gone, it is still very much present, but it felt appropriate to include something in the book that reflects how the library usage has also evolved over the years – thanks to my good friend John M. Daniel for pushing for this!

Apply skills in other languages and additional scaling options

A brand new chapter in the book is dedicated to how Heroku and Functions can be used to leverage existing skills or indeed investments in open source or internally for code written in other languages such as Java or Node.js. These technologies also open up further scaling options. The chapter breaks down the approaches using the books sample application as a basis. Thus it continues the Formula1 motor racing theme by introducing Web and API interfaces for race fans and vendors (authentication scenario) to interact with the application backend APIs. Later in the book the integration chapter doubles down further on authoring APIs via OpenAPI standards and how that simplifies integration with the platform.

Lightning Web Components and Lightning Experience expansion

Since the third book, all but one of the Aura components have now been removed as many only existed at the time as workarounds to the lack of LWC enabled integration points. Two large chapters are dedicated to the Lightning framework itself, how it handles separation of concerns, eventing, security and its alignment with the industry Web Component standard. Completing with a section covering the ever expanding possibilities to extend vs build when thinking about your applications user experience, regardless if thats desktop, mobile or driven through the native UIs and tools such as Lightning Pages or Flow. And yes, I still love the Utility Bar integration the most – as you can see from the number of historic posts and tools on the topic here.

APIs, APIs and APIs…

Many years ago a product manager once thanked me for pushing an API strategy internally, since they appreciated first hand as a past buyer that APIs are effectively an insurance policy for buyers when it comes to unexpected feature gaps post or during implementation. Thus several of the chapters highlight the many Salesforce APIs in contextual ways.

Though its not until the integration and extensibility chapter the book really doubles down on building your own application APIs, versioning, naming and design and the value they bring to your fellow developers, customers and/or partner ecosystems. External Services is one of the most impressive aspects of integrating with the Salesforce Platform for me and it was my pleasure to update the book with an updated Heroku based API leveraging OpenAPI to get the full power of the feature – the two are a perfect combo!

And …

This blog is already in danger of becoming chapter size itself, so I will leave it here with the above highlights and before I close share my deepest thanks to this editions reviewers John M. Daniel, Sebastiano Costanzo, Arvind Narasimhan and foreword author Daniel J. Peter.

I will be popping up in the not to distant future in ApexHours (https://www.apexhours.com/) and perhaps other locations to talk in more depth about the book and likely other side topics of interest. I will update this blog as those resources arrive. Thank you all in the meantime, the Salesforce community is the best and remains very close to my heart, enjoy!

AndyInTheCloud

P.S. Suffice to say this 4th edition is an evolution of the prior three books! I would like to also thank the following fine folks for their support as past reviewers and foreword authors!

Past Reviewers and Forewords:
Matt Bingham, Steven Herod, Matt Lacey, Andrew Smith, Rohit Arora, Karanraj Samkaranarayanan, Jitendra Zaa, Joshua Burk, Peter Knolle, John Leen, Aaron Slettenhaugh, Avrom Roy-Faderman, Michael Salem, Mohith Shrivastava and Wade Wegner


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My Top 5 Apex APIs and Bonus

As readers of this blog will already have determined, I love API’s! So when I was approached by the team at 100 Days of Trailhead to share my Top 5 “things” my mind fell to API’s. This is a short blog post because effectively the brief was a 10 minute video! Well ok I ran a bit over in the end so its actually 15 minutes.

In the video I cover 5 Apex API’s and a Bonus API at the end. Thank you for 100 Days of Trailhead for asking to contribute and please do check out all the other amazing content they have on their website! You can watch the video below (or link here) and find full source code in this GitHub repository.

https://100daysoftrailhead.com/
/**
 .----------------. 
| .--------------. |
| |   _______    | |
| |  |  _____|   | |
| |  | |____     | |
| |  '_.____''.  | |
| |  | \____) |  | |
| |   \______.'  | |
| |              | |
| '--------------' |
 '----------------' 
 */

//
// Firing Platform Events from Batch Apex
//
public with sharing class Five
    implements Database.Batchable<SObject>, Database.RaisesPlatformEvents {

 .----------------. 
| .--------------. |
| |   _    _     | |
| |  | |  | |    | |
| |  | |__| |_   | |
| |  |____   _|  | |
| |      _| |_   | |
| |     |_____|  | |
| |              | |
| '--------------' |
 '----------------' 

//
// Request Class - Request Id
//
Request reqInfo = Request.getCurrent();
String currentRequestId = reqInfo.getRequestId();


 .----------------. 
| .--------------. |
| |    ______    | |
| |   / ____ `.  | |
| |   `'  __) |  | |
| |   _  |__ '.  | |
| |  | \____) |  | |
| |   \______.'  | |
| |              | |
| '--------------' |
 '----------------' 
 
//
// Request Class - Quiddity
//
switch on Context  {
    when SYNCHRONOUS {
        RequestOrderProcessor = new TriggerOrderProcessing();
    } when BULK_API {
        RequestOrderProcessor = new BulkAPIOrderProcessing();    
    } when else {
        RequestOrderProcessor = new BaseOrderProcessing();
    }
}        

 .----------------. 
| .--------------. |
| |    _____     | |
| |   / ___ `.   | |
| |  |_/___) |   | |
| |   .'____.'   | |
| |  / /____     | |
| |  |_______|   | |
| |              | |
| '--------------' |
 '----------------' 

// 
// Send Notifications
//

Messaging.CustomNotification notification = new Messaging.CustomNotification();
notification.setTitle('Amazing new order ' + newOrder.OrderNumber);
notification.setBody('Check out this new order that has just come in!');
notification.setNotificationTypeId(notificationType.Id);
notification.setTargetId(newOrder.Id);
notification.send(new Set<String> { UserInfo.getUserId()} );


 .----------------. 
| .--------------. |
| |     __       | |
| |    /  |      | |
| |    `| |      | |
| |     | |      | |
| |    _| |_     | |
| |   |_____|    | |
| |              | |
| '--------------' |
 '----------------' 

Opportunity opp = new Opportunity();
opp.addError('Description', 'Error Message!'); 
List<Database.Error> errors = opp.getErrors();
System.assertEquals(1, errors.size());
System.assertEquals('Error Message!', errors[0].getMessage());
System.assertEquals('Description', errors[0].getFields()[0]);

/**
 * 
  ____                        
 |  _ \                       
 | |_) | ___  _ __  _   _ ___ 
 |  _ < / _ \| '_ \| | | / __|
 | |_) | (_) | | | | |_| \__ \
 |____/ \___/|_| |_|\__,_|___/                                             
 */

public class BonusFinalizer implements Finalizer {

    public void execute(FinalizerContext ctx) {


4 Comments

Reducing Field Validation Boilerplate Code

Boilerplate code is code that we repeat often with little or no variation. When it comes to writing field validations in Apex, especially within Apex Triggers there are a number of examples of this. Especially when it comes to checking if a field value has changed and/or querying for related records, which also requires observing good bulkifcathion best practices. This blog presents a small proof of concept framework aimed at reducing such logic made possible in Winter’21 with a small but critical enhancement to the Apex runtime that allows developers to dynamically add field errors. Additionally, for those practicing unit testing, the enhancement also allows test assert such errors without DML!

This is a very basic demonstration of the new addError and getErrors methods.

Opportunity opp = new Opportunity();
opp.addError('Description', 'Error Message!'); 
List<Database.Error> errors = opp.getErrors();
System.assertEquals(1, errors.size());
System.assertEquals('Error Message!', errors[0].getMessage());
System.assertEquals('Description', errors[0].getFields()[0]);

However in order to really appreciate the value these two features bring to frameworks let us first review a use case and the traditional approach to coding such validation logic. Our requirements are:

  1. When updating an Opportunity validate the Description and AccountId fields
  2. If the StageName field changes to “Closed Won” and the Description field has changed ensure it is not null.
  3. If the AccountId field changes ensure that the NumberOfEmployees field on the Account is not null
  4. Ensure code is bulkified and queries are only performed when needed.

The following code implements the above requirements, but does contain some boilerplate code.

// Classic style validation
switch on Trigger.operationType {
    when AFTER_UPDATE {
        // Prescan to bulkify querying for related Accounts
        Set<Id> accountIds = new Set<Id>();
        for (Opportunity opp : newMap.values()) {
            Opportunity oldOpp = oldMap.get(opp.Id);
            if(opp.AccountId != oldOpp.AccountId) { // AccountId changed?
                accountIds.add(opp.AccountId);
            }
        }                
        // Query related Account records?
        Map<Id, Account> associatedAccountsById = accountIds.size()==0 ? 
            new Map<Id, Account>() : 
            new Map<Id, Account>([select Id, NumberOfEmployees from Account where Id = :accountIds]);
        // Validate
        for (Opportunity opp : newMap.values()) {
            Opportunity oldOpp = oldMap.get(opp.Id);
            if(opp.StageName != oldOpp.StageName) { // Stage changed?
                if(opp.StageName == 'Closed Won') { // Stage closed won?
                    if(opp.Description != oldOpp.Description) { // Description changed?               
                        if(opp.Description == null) { // Description null?
                            opp.Description.addError('Description must be specified when Opportunity is closed');
                        }
                    }
                }                                
            }
            if(opp.AccountId != oldOpp.AccountId) { // AccountId changed?
                Account acct = associatedAccountsById.get(opp.AccountId);
                if(acct!=null) { // Account queried?
                    if(acct.NumberOfEmployees==null) { // NumberOfEmployees null?
                        opp.AccountId.addError('Account does not have any employees');
                    }    
                }
            }
        }
    }
}               

Below is the same validation implemented using a framework built to reduce boilerplate code.

SObjectFieldValidator.build()            
  .when(TriggerOperation.AFTER_UPDATE)
    .field(Opportunity.Description).hasChanged().isNull().addError('Description must be specified when Opportunity is closed')
      .when(Opportunity.StageName).hasChanged().equals('Closed Won')
    .field(Opportunity.AccountId).whenChanged().addError('Account does not have any employees')
      .when(Account.NumberOfEmployees).isNull()
  .validate(operation, oldMap, newMap);

The SObjectFieldValidator framework uses the Fluent style design to its API and as such allows the validator to be dynamically constructed with ease. Additionally configured instances of it can be passed around and extended by other code paths and modules with the validation itself to be performed in one pass. The framework also attempts some smarts to bulkify queries (in this case related Accounts) and only do so if the target field or related fields have been modified – thus ensuring optimal processing time. The test code for either approaches can of course be written in the usual way as shown below.

// Given
Account relatedAccount = new Account(Name = 'Test', NumberOfEmployees = null);        
insert relatedAccount;
Opportunity opp = new Opportunity(Name = 'Test', CloseDate = Date.today(), StageName = 'Prospecting', Description = 'X', AccountId = null);
insert opp;
opp.StageName = 'Closed Won';
opp.Description = null;
opp.AccountId = relatedAccount.Id;
// When
Database.SaveResult saveResult = Database.update(opp, false);
// Then
List<Database.Error> errors = saveResult.getErrors();
System.assertEquals(2, errors.size());
System.assertEquals('Description', errors[0].getFields()[0]);
System.assertEquals('Description must be specified when Opportunity is closed', errors[0].getMessage());
System.assertEquals('AccountId', errors[1].getFields()[0]);
System.assertEquals('Account does not have any employees', errors[1].getMessage());

While you do still need code coverage for your Apex Trigger logic, those practicing unit testing may prefer to leverage the ability to avoid DML in order to assert more varied validation scenarios. The following code is entirely free of any SOQL and DML statements and thus better for test performance. It leverages the ability to inject related records rather than allowing the framework to query them on demand. The SObjectFieldValidator instance is constructed and configured in a separate class for reuse.

// Given
Account relatedAccount = 
    new Account(Id = TEST_ACCOUNT_ID, Name = 'Test', NumberOfEmployees = null);
Map<Id, SObject> oldMap = 
    new Map<Id, SObject> { TEST_OPPORTUNIT_ID => 
        new Opportunity(Id = TEST_OPPORTUNIT_ID, StageName = 'Prospecting', Description = 'X', AccountId = null)};
Map<Id, SObject> newMap = 
    new Map<Id, SObject> { TEST_OPPORTUNIT_ID => 
        new Opportunity(Id = TEST_OPPORTUNIT_ID, StageName = 'Closed Won', Description = null, AccountId = TEST_ACCOUNT_ID)};
Map<SObjectField, Map<Id, SObject>> relatedRecords = 
    new Map<SObjectField, Map<Id, SObject>> {
        Opportunity.AccountId => 
            new Map<Id, SObject>(new List<Account> { relatedAccount })};
// When
OpportunityTriggerHandler.getValidator()
  .validate(TriggerOperation.AFTER_UPDATE, oldMap, newMap, relatedRecords); 
// Then
List<Database.Error> errors = newMap.get(TEST_OPPORTUNIT_ID).getErrors();
System.assertEquals(2, errors.size());
System.assertEquals('AccountId', errors[0].getFields()[0]);
System.assertEquals('Account does not have any employees', errors[0].getMessage());
System.assertEquals('Description', errors[1].getFields()[0]);
System.assertEquals('Description must be specified when Opportunity is closed', errors[1].getMessage());

Finally it is worth noting that such a framework can of course only get you so far and there will be scenarios where you need to be more rich in your criteria. This is something that could be explored further through the SObjectFieldValidator.FieldValidationCondition base type that allows coded field validations to be added via the condition method. The framework is pretty basic as I really do not have a great deal of time these days to build it out more fully, so totally invite anyone interested to take it further.

Enjoy!


7 Comments

Apex Process Orchestration and Monitoring with Platform Events

When it comes to implementing asynchronous workloads in Apex developers have a number of options such as Batch Apex and Queueable, each can be driven by user or system driven actions. This blog focuses on some of the more advanced aspects of implementing async workloads using Platform Events and Apex.

In comparison to other approaches, implementing asynchronous workloads using Platform Events offers two unique features. The first helps you better dynamically calibrate and manage resources based on data volumes to stay within limits, while the second feature provides automatic retry capabilities when errors occur. Lastly I want to highlight an approach I used to add some custom realtime telemetry to the workload using Platform Events.

Side Note: Before getting into the details, the goal of this blog is not to say one async option is better than another, rather to highlight the above features further so you can better consider your options. I also include a short comparison at the end of this blog with Batch Apex.

Business Scenario

Lets imagine the following scenario to help illustrate the use of the features described below:

  • Business Process
    Imagine that your business is processing Invoice generation on the platform and that the Orders that drive this arrive and are updated constantly.
  • Continuous Processing
    In order to avoid backlogs or spikes of invoices being processed, you want to maintain a continuous flow of the overall process. For this you create a Platform Event called Generate Invoice. This event can easily be sent by an admin / declarative builders who have perhaps setup some rules on the Orders object using Process Builder.
  • Resource Management
    Orders arrive in all shapes and sizes, meaning the processing required to generate Invoices can also vary when you consider variables such as number of order lines, product regional discounts, currencies and tax rules etc. Processing each one at time per execution context is an obvious way to maximize use of available resources and is certainly an option, but if resources allow, processing multiple invoices in one execution context is more efficient.

Below is what the Generate Invoice Platform Event looks like, it simply has a reference to the Order Id (though it could equally reference an External Id on the Order object).

For the purposes of this blog we are not focusing on how the events are sent / published. You can publish events using programatic API’s on or off platform or using one of the platforms declarative tools, there are in fact many ways to send events. For this blog we will just use a basic Apex snippet to generate the events as shown below.

List&lt;GenerateInvoice__e&gt; events = new List&lt;GenerateInvoice__e&gt;();
for(Order order : 
       [select Id from Order 
          where Invoiced__c != true 
          order by OrderNumber asc]) {
   events.add(new GenerateInvoice__e(OrderId__c = order.Id));
}
EventBus.publish(events);        

Here is a basic Apex handler for the above Platform Event that delegates the processing to another Apex class:

trigger GenerateInvoiceSubscriber on GenerateInvoice__e (after insert) {
    Set&lt;Id&gt; orderIds = new Set&lt;Id&gt;();
    for (GenerateInvoice__e event : Trigger.New) {
        orderIds.add(event.OrderId__c);
    }
    OrderService.generateInvoices(orderIds);
}

Processing Chunks of Events and Handling Retries

The following diagram highlights how a more advanced version of the above Apex handler can be used to optimally work within the limits to process chunks of Orders based on their size/complexity and also retry those that result in some errors along the way.

In order to orchestrate things this way you need to use some Apex API’s in your handler logic to let the platform know a few things. At the end of this blog I also share how I added telemetry to better visualize this along with a video. So don’t worry at this juncture if its not 100% clear how what you are seeing below is possible, just keep reading and watching!

Controlling how many Events are passed to your handler

Imagine the above code snippet published 1000 events. The platform docs state that it can pass up to a maximum of 2000 events to an Apex event handler at once, meaning the above will be invoked once. If you have been on the platform a while you will know that 200 (not 2000) is common number used to expressed a minimum number of records you should use when testing Apex Triggers and general bulkkification best practice. So why 2000 in the case of platform event handlers? Well the main aim of the platform is to drain the Platform Event message queue quickly and so it attempts to give the handler as much as possible, just in case it can process it.

As we have set out in our scenario above, Orders can be quite variable in nature and thus while a batch of 1000 orders with only a few order lines might be possible within the execution limits, include few orders in that batch with 100’s or a few thousand line items and its more likely you will hit CPU or heap limits. Fortunately, unlike Batch Apex, you get to control the size of each individual chunk. This is done by effectively giving some of the 1000 block of events passed to your handler back to the platform to pass back in a separate handler invocation where the limits are reset.

Below is some basic code that illustrates how you might go about pre-scanning the Orders to determine complexity (by number of lines) and thus dynamically calibrating how many of the events your code can really process within the limits. The orderIds list that is passed to the service class is reset with the orders that can be processed. The key part here is the use of the setResumeCheckpoint method that tells the platform where to resume from after this handler has completed its processing.

trigger GenerateInvoiceSubscriber on GenerateInvoice__e (after insert) { 

    // Determine number overall order lines to process 
    //   vs maximum within limits (could be config)
    Integer maxLines = 40000;
    Set&lt;Id&gt; orderIds = new Set&lt;Id&gt;();
    for (GenerateInvoice__e event : Trigger.New) {
        orderIds.add(event.OrderId__c);
    }
    Map&lt;Id, Integer&gt; lineCountByOrderId = 
        new OrdersSelector().selectLineCountById(orderIds);

    // Bulkify events passed to the OrderService
    orderIds = new Set&lt;Id&gt;();
    Integer lineCount = 0;
    for (GenerateInvoice__e event : Trigger.New) {
        orderIds.add(event.OrderId__c);
        EventBus.TriggerContext.currentContext().setResumeCheckpoint(event.ReplayId);
        lineCount = lineCount + lineCountByOrderId.get(event.OrderId__c);
        if(lineCount&gt;maxLines) { 
            break;
        }
    }

    OrderService.generateInvoices(orderIds);
}

You can read more about this approach in the formal documentation here.

Implementing Retry Logic

There are a number of reasons errors can occur when your handler code is running. For errors that represent transient situations, such as timeouts and row locks for example, you would normally have to ask the user to retry (via email or notification) or utilize a dynamically scheduled job to retry. With Platform Event handlers in Apex, when the system RetryableException is thrown the Platform will automatically retry a batch events after period of time, up to 9 times (the batch sizes may vary between attempts). It is generally recommended that you do not let your code retry above 6, since when the maximum is reached the platform deactivates the handler/trigger.

The following code is basic illustration of how to use this facility and track the number of retries before reaching the max. In this example if the soft maximum is reached the events are effectively just lost in this case or if needed you can write them to a staging custom object for resubmission or just simply have some code such as the above scan for unprocessed Orders and resubmit events.

    // Invoke OrderService, support retries
    try {
        OrderService.generateInvoices(orderIds);
    } catch (Exception e) {
        // Only retry so many times, before giving up (thus avoid disabling the trigger)
        if (EventBus.TriggerContext.currentContext().retries &lt; 6) {
            throw new EventBus.RetryableException(e.getMessage());
        }
        // In this case its ok to let the events drain away... 
        //   since new events for unprocessed Orders can always be re-generated
    }    

Using Platform Events to monitor activity

I used Platform Events to publish telemetry about the execution of the above handlers, by creating another Platform Event called Subscriber Telemetry and used a Lightning Web Component to monitor the events in realtime. Because Platform Events can be declared as being outside the standard Apex Transaction they are sent immediately using the “Publish Immediately” setting, they are sent even if an error occurs.

To publish to this event I simply added the following snippet of code to the top of my handler.

// Emit telemetry
EventBus.publish(
    new SubscriberTelemetry__e(
        Topic__c = 'GenerateInvoice__e', 
        ApexTrigger__c = 'GenerateInvoiceSubscriber',
        Position__c = 
           [select Position from EventBusSubscriber
              where Topic = 'GenerateInvoice__e'][0].Position,
        BatchSize__c = Trigger.new.size(),
        Retries__c = EventBus.TriggerContext.currentContext().retries,
        LastError__c = EventBus.TriggerContext.currentContext().lastError));

The following video shows me clicking a button to publish a batch of 1000 events, then monitoring the effects on my chunking logic and retry logic. The video actually includes me fixing some data errors in order to highlight the retry capabilities. The errors shown are contrived by some deliberately bad code to illustrate the retry logic, hence the fix to the Order records looks a bit odd, so please ignore that. Finally note that the platform chose to send my handler 83 events first then larger chunks thereafter, but in other tests I got 1000 events in the first chunk.

Batch Apex vs Platform Events

Batch Apex also provides a means to orchestration sequentially the processing of records in chunks, so I thought I would end here with a summary of some of the other differences. As you can see one of the key ones to consider is the user identity the code runs as. This is not impossible to workaround in the platform event handler case, but requires some coding to explicitly set the OwnerId field on records if that information is important to you. Overall though I do feel that Platform Events offers some useful options for switching to a more continuous mode of operation vs batch, so long as your aware of the differences this might be a good fit for you.

Side Note: For Apex Queueable handlers you will soon have the option to implement so called Transaction Finalizers that allow you to implement retry or logging logic.


3 Comments

The Third Edition

bookI’m proud to announce the third edition of my book has now been released. Back in March this year I took the plunge start updates to many key areas and add two brand new chapters. Between the 2 years and 8 months since the last edition there has been several platform releases and an increasing number of new features and innovations that made this the biggest update ever! This edition also embraces the platforms rebranding to Lightning, hence the book is now entitled Salesforce Lightning Platform Enterprise Architecture.

You can purchase this book direct from Packt or of course from Amazon among other sellers.  As is the case every year Salesforce events such as Dreamforce and TrailheaDX this book and many other awesome publications will be on sale. Here are some of the key update highlights:

  • Automation and Tooling Updates
    Throughout the book SFDX CLI, Visual Studio Code and 2nd Generation Packaging are leverage. While the whole book is certainly larger, certain chapters of the book actually reduced in size as steps previously reflecting clicks where replaced with CLI commands! At one point in time I was quite a master in Ant Scripts and Marcos, they have also given way to built in SFDX commands.
  • User Interface Updates
    Lightning Web Components is a relative new kid on the block, but benefits greatly from its standards compliance, meaning there is plenty of fun to go around exploring industry tools like Jest in the Unit Testing chapter. All of the books components have been re-written to the Web Component standard.
  • Big Data and Async Programming
    Big data was once a future concern for new products, these days it is very much a concern from the very start. The book covers Big Objects and Platform Events more extensibility with worked examples, including ingest and calculations driven by Platform Events and Async Apex Triggers. Event Driven Architecture is something every Lightning developer should be embracing as the platform continues to evolve around more and more standard platforms and features that leverage them.
  • Integration and Extensibility
    A particularly enjoyed exploring the use of Platform Events as another means by which you can expose API’s from your packages to support more scalable invocation of your logic and asynchronous plugins.
  • External Integrations and AI
    External integrations with other cloud services are a key part to application development and also the implementation of your solution, thus one of two brand new chapters focuses on Connected Apps, Named Credentials, External Services and External Objects, with worked examples of existing services or sample Heroku based services. Einstein has an ever growing surface area across Salesforce products and the platform. While this topic alone is worth an entire book, I took the time in the second new chapter, to enumerate Einstein from the perspective of the developer and customer configurations. The Formula1 motor racing theme continued with the ingest of historic race data that you can run AI over.
  • Other Updates
    Among other updates is a fairly extensive update to the CI/CD chapter which still covers Jenkins, but leverages the new Jenkins Pipeline feature to integrate SFDX CLI. The Unit Testing chapter has also been extended with further thoughts on unit vs integration testing and a focus on Lightening Web Component testing.

The above is just highlights for this third edition, you can see a full table of contents here. A massive thanks to everyone involving for providing the inspiration and support for making this third edition happen! Enjoy!


57 Comments

Getting your users attention with Custom Notifications

customnotificationsummaryGetting your users attention is not always easy, choosing how, when and where to notify them is critical. Ever since Lightning Experience and Salesforce Mobile came out the notification bell has been a one stop shop for Chatter and Approval notifications, regardless if you are on your desktop or your mobile device.

In beta release at time of writing is a new platform feature known as Notification Manager that allows you to send your own custom notifications to your users for anything your heart desires from the very same locations, even on a users mobile device! This blog dives into this feature and how you can integrate it into your creations regardless if you are a admin click coder, Apex developer or REST API junkie.

Getting Started

The first thing you need to do is define a new Notification Type under the Setup menu. This is a simple process that involves giving it a name and deciding what channels you want the notification to go out on, currently user desktop and mobile devices.

notificationstypes

Once this has been done you can use the new Send Custom Notification action in Process Builder or Flow. This allows you to define the title and body of your notification, along with the target recipients (users, groups, queues and more) along the target record that determines the record the user sees when they click/tap the notification. The following screenshot shows an example of such an Action in Process Builder:-

opportunitycustomnotification

notificationoppty.png

Basically that is all there is to it! You will have in a few clicks empowered yourself with the ability to reach out to not only your users desktop but the actual mobile device notification experience on each of the their mobile devices!  You didn’t have to learn how to write a mobile app, figure out how to do mobile notifications, register things with Google or Apple. I am honestly blown away at how easy and powerful this is!

So it is pretty easy to to send notifications this way from Process Builder processes driven by record updates from the user and also reference field values to customize the notification text. However in the ever expanding world of Platform Events, how do we send custom notifications based on Platform Events?

Sending Custom Notifications for Batch Apex Job Failures

One of my oldest and most popular blog posts discussed design best practices around Batch Apex jobs. One of the considerations it calls out is how important it is to route errors that occur in the background back to the user. Fast forward a bit to this blog, where I covered the new BatchApexError Platform Event as a means to capture and route batch errors (even uncatchable exceptions) in near realtime. It also describes strategy to enabled users to retry failed jobs. What it didn’t really solve, is letting them know something had gone wrong without them checking a custom tab. Let’s change that!

Process Builder is now able to subscribe to the standard BatchApexErrorEvent and thus enables you as an admin to apply filter and routing logic on failed batch jobs. When combined with custom notifications those errors can now be routed to users devices and/or desktops in realtime. While Process Builder can subscribe to events it does have some restrictions on what it can do with the event data itself. Thus we are going to call an autolaunch Flow from Process Builder to actually handle the event and send the custom notification from within Flow. If you are reading this wondering if your Apex code can get in on the action, the answer is yes (ish), more on this later though. The declarative solution utilizes one Process Builder process and two Flows. The separation of concerns between them is shown in the diagram below:-

batchapexeventtonotificationarch

Let’s work from the bottom to the top to understand why I decided to split it up this way. Firstly, SendCustomNotification is a Sub Flow (callable by other Flows) and is a pretty simple wrapper around the new Send Custom Notification action shown above. You can take a closer look at this later through the sample code repository here.

SendCustomNotification

Next the BatchApexErrorPlatformEventHandler Flow defines a set of input variables that are populated from the Process Builder process. These variables match the fields and types per the definition of the Batch Apex Error Event here. The only other thing it does is add the Id of the user that generated the event (aka the user who submitted the failed job) to the list of recipients passed to the SendCustomNotification sub flow above. This could also be a Group Id if you wanted to send the notification further.

batchapexeventhandlerflow.png

Lastly, in the screenshot below you see the Process Builder that subscribes to the Batch Apex Error Event and maps the event field values to the input variables exposed from BatchApexErrorPlatformEventHandler Flow via the EventReference. The example here is very simple, but you can now imagine how you can add other filter criteria to this process that allows you to inspect which Batch Apex job failed and route and/or adjust messaging in the notifications accordingly, all done declaratively of course!

batchapexerrorfrompb.png

NOTE: It is not immediately apparent in all cases that you can access the event fields from Process Builder, since the documentation states them as not supported within formulas. I want to give a shout out to Alex Edelstein PM for Flow for clarifying that it is possible! Check out his amazing blog around all things Flow here. Finally note that Process Builder requires an Object to map the incoming event to. In this case I mapped to a User record using the CreatedById field on the event.

Sending Custom Notifications from Code

The Send Custom Notification action is also exposed via the Salesforce Action REST API defined here (hint hint for Doug Ayers Mass Action tool to support it). You can of course attempt to call this REST API via Apex as well. While there is currently no native Apex Action API, it turns out calling the above SendCustomNotification Flow from Apex works pretty well meanwhile. I have written a small wrapper around this technique to make it a little more elegant to perform from Apex and it also serves to abstract away this hopefully temporary workaround for Apex developers.

new CustomNotification()
    .type('MyNotificationType')
    .title('Fun Custom Notification')
    .body('Custom Notifications are Awesome!')
    .sendToCurrentUser();

The following Apex code results in this notification appearing on your device!

funfromapexnotification.png

This CustomNotification helper class is included in the sample code for this blog and leverages another class I wrote that wraps the native Apex Flow API. I used this wrapper because it allowed me to mock the actual Flow invocation since there is no way as far as I can see to assert the notification was actually sent.

NOTE: When sending custom notifications via declarative tools and/or via code I did confirm in my testing that they are included in the current transaction. Also I recommend you always avoid calling Flow in loops in your Apex code, instead make your Flows take list variables (aka try to bulkify Flows called from Apex). Though not shown in the Apex above, the wrapped Flow takes a list of recipients.

Summary

You can find all the code for this blog in sample code repository here. So there you have it, custom mobile and desktop notifications sent from Process Builder, Flow, Apex and REST API. Keep in mind of course at time of writing this is a Beta feature and thus read the clause in the documentation carefully. Now go forth and start thinking of all the areas you can enable with this feature!

P.S. Check out another new cool feature called Lightning In-App Guidance.