Handling Nulls in DataWeave with default
Use DataWeave's default keyword to keep common null and missing-value transformations readable, while knowing when explicit conditions are still the better choice.
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The complete collection of Deep Dives, practical tutorials, Quick Reads and engineering notes across Salesforce, MuleSoft, DataWeave, integration, APIs, distributed systems, testing and developer tooling.
Looking specifically for longer-form architecture and production engineering? Explore the 12 curated Deep Dives →
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Filtering Arrays in DataWeave with filter
Practical DataWeave filter examples for selecting records, handling optional values, combining conditions, and keeping filtering separate from transformation logic.
Read article →Flattening Nested Arrays in DataWeave
Practical DataWeave patterns for flattening nested arrays, combining parent and child data, and deciding when flatMap is clearer than map followed by flatten.
Read article →Practical DataWeave groupBy Patterns
Use DataWeave groupBy to turn flat arrays into useful business groupings for aggregation, routing and downstream request construction.
Read article →Grouping Records in DataWeave with groupBy
Learn how DataWeave groupBy turns an array into grouped collections for batching, aggregation, routing, and downstream integration processing.
Read article →DataWeave map vs mapObject: When to Use Each
A quick, practical guide to choosing map or mapObject in DataWeave, with examples for arrays, objects, keys, values, and common transformation mistakes.
Read article →DataWeave map vs mapObject: Choose by Output Shape
Use map when transforming array elements and mapObject when transforming object entries. The desired output shape usually makes the choice obvious.
Read article →Practical DataWeave reduce Patterns
Understand DataWeave reduce through practical examples for totals, object construction, grouping-like transformations, and choosing the right accumulator.
Read article →Removing Null and Empty Fields from JSON in DataWeave
Practical DataWeave patterns for omitting null fields from JSON and deciding whether empty strings, arrays, and objects should also be removed.
Read article →DataWeave Streaming for Large Payloads: What Changes
A practical guide to when DataWeave streaming helps, what sequential access means, and which transformation patterns can accidentally defeat the memory benefit.
Read article →MuleSoft Timeouts: Design the Whole Timeout Budget
A timeout on one connector is not a timeout strategy. Design an end-to-end latency budget across callers, APIs, retries and downstream dependencies.
Read article →MuleSoft Choice Router vs Lookup Table: When Rules Start Growing
Choice Router is excellent for a few clear branches. When routing becomes data-driven, a lookup or configuration model can be easier to maintain.
Read article →MuleSoft Object Store: What to Use It For
A practical introduction to MuleSoft Object Store for watermarks, replay state, tokens, and lightweight application state—and when a database is the better design.
Read article →MuleSoft Parallel For Each vs Batch Processing
A practical guide to choosing Parallel For Each or Batch Processing based on payload size, synchronous completion, memory, concurrency, and record-level recovery needs.
Read article →MuleSoft Rate Limiting vs Spike Control: Different Problems
Rate limits protect consumption over a time window; burst protection addresses sudden traffic. Understand the architectural distinction before choosing an API policy.
Read article →MuleSoft Until Successful: Retry Without Hiding Failure
A practical guide to using MuleSoft Until Successful for bounded synchronous retries, while avoiding retry storms, duplicate effects, and poor recovery design.
Read article →When to Use Salesforce Bulk API 2.0 from MuleSoft
A practical decision guide for choosing Salesforce Bulk API 2.0 instead of record-by-record REST calls when MuleSoft integrations handle larger datasets.
Read article →Salesforce CDC: Read the ChangeEventHeader Before the Payload
Salesforce Change Data Capture consumers should treat ChangeEventHeader as processing metadata, not just jump directly to changed business fields.
Read article →Salesforce CDC Replay IDs Explained
Understand what Salesforce Change Data Capture Replay IDs represent, how they support event recovery, and why they should be treated as opaque stream positions rather than business sequence numbers.
Read article →Salesforce CDC vs Platform Events: Which One Should You Use?
A concise architecture guide to choosing Salesforce Change Data Capture or Platform Events based on whether you need record-change notifications or purpose-built business events.
Read article →Using Salesforce Composite API from MuleSoft
A practical guide to using Salesforce Composite API from MuleSoft when multiple related Salesforce REST operations belong in one request.
Read article →Salesforce External ID vs Record ID in Integrations
Salesforce record IDs identify Salesforce records; external IDs help systems agree on business identity. That difference matters for durable integrations.
Read article →Salesforce Pub/Sub API Flow Control: Request Only What You Can Process
Salesforce Pub/Sub API is pull-based. Use its event-request model as a real backpressure mechanism instead of building an ever-growing consumer backlog.
Read article →Salesforce Upsert with External IDs from MuleSoft
A practical guide to using Salesforce External IDs for idempotent create-or-update integrations from MuleSoft without depending on Salesforce record IDs.
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