another acrolinx item

docs/patterns/gateway-aggregation-content.md

@@ -26,7 +26,7 @@ In the following diagram, the application sends a request to the gateway (1). Th
 - The gateway may introduce a bottleneck. Ensure the gateway has adequate performance to handle load and can be scaled to meet your anticipated growth.
 - Perform load testing against the gateway to ensure you don't introduce cascading failures for services.
 - Implement a resilient design, using techniques such as [bulkheads][bulkhead], [circuit breaking][circuit-breaker], [retry][retry], and timeouts.
-- If one or more service calls takes too long, it may be acceptable to timeout and return a partial set of data. Consider how your application will handle this scenario.
+- If one or more service calls takes too long, it may be acceptable to time out and return a partial set of data. Consider how your application will handle this scenario.
 - Use asynchronous I/O to ensure that a delay at the backend doesn't cause performance issues in the application.
 - Implement distributed tracing using correlation IDs to track each individual call.
 - Monitor request metrics and response sizes.
@@ -43,15 +43,15 @@ Use this pattern when:
 This pattern may not be suitable when:
 
 - You want to reduce the number of calls between a client and a single service across multiple operations. In that scenario, it may be better to add a batch operation to the service.
-- The client or application is located near the backend services and latency is not a significant factor.
+- The client or application is located near the backend services and latency isn't a significant factor.
 
 ## Workload design
 
 An architect should evaluate how the Gateway Aggregation pattern can be used in their workloads's design to address the goals and principles covered in the [Azure Well-Architected Framework pillars](/azure/well-architected/pillars). For example:
 
 | Pillar | How this pattern supports pillar goals |
 | :----- | :------------------------------------- |
-| [Reliability](/azure/well-architected/reliability/checklist) design decisions help your workload become **resilient** to malfunction and to ensure that it **recovers** to a fully functioning state after a failure occurs. | This topology enables you to, amoung other thing, shift transient fault handling from a distributed implementation across clients to a centralized implementation.<br/><br/> - [RE:07 Transient faults](/azure/well-architected/reliability/handle-transient-faults) |
+| [Reliability](/azure/well-architected/reliability/checklist) design decisions help your workload become **resilient** to malfunction and to ensure that it **recovers** to a fully functioning state after a failure occurs. | This topology enables you to, among other things, shift transient fault handling from a distributed implementation across clients to a centralized implementation.<br/><br/> - [RE:07 Transient faults](/azure/well-architected/reliability/handle-transient-faults) |
 | [Security](/azure/well-architected/security/checklist) design decisions help ensure the **confidentiality**, **integrity**, and **availability** of your workload's data and systems. | This topology often reduces the number of touch points a client has with a system, which reduces the public surface area and authentication points. The aggregated backends can stay fully network-isolated from clients.<br/><br/> - [SE:04 Segmentation](/azure/well-architected/security/segmentation)<br/> - [SE:08 Hardening](/azure/well-architected/security/harden-resources) |
 | [Operational Excellence](/azure/well-architected/operational-excellence/checklist) helps deliver **workload quality** through **standardized processes** and team cohesion. | This pattern enables backend logic to evolve independently from clients, allowing you to change the chained service implementations, or even data sources, without needing to change client touchpoints.<br/><br/> - [OE:04 Tools and processes](/azure/well-architected/operational-excellence/tools-processes) |
 | [Performance Efficiency](/azure/well-architected/performance-efficiency/checklist) helps your workload **efficiently meet demands** through optimizations in scaling, data, code. | This design can incur less latency than a design in which the client establishes multiple connections. Caching in aggregation implementations minimizes calls to backend systems.<br/><br/> - [PE:03 Selecting services](/azure/well-architected/performance-efficiency/select-services)<br/> - [PE:08 Data performance](/azure/well-architected/performance-efficiency/optimize-data-performance) |