Update PR comments

Signed-off-by: AlvarVG <alvigo92@gmail.com>

Author: AlvarVG

_posts/2026-01-08-measuring-debezium-server-performance-mysql-streaming.adoc

@@ -16,6 +16,10 @@ This post does not aim to compare Debezium Server with Kafka Connect nor to iden
 Instead, it focuses on understanding how Debezium Server behaves under realistic workloads using default configurations, 
 and whether it can sustain real-time change data capture in lightweight architectures.
 
+It is also important to underline that, in this evaluation, the database is not stressed in a fully real-world scenario.
+Conditions such as long-running transactions or other complex workload patterns are not represented,
+as incorporating them would significantly increase the complexity of the test case.
+
 [id=introduction]
 == Introduction
 
@@ -24,15 +28,15 @@ Performance measurement transforms software from a black box into an understanda
 
 'What is not measured cannot be controlled, predicted or reliably improved'
 
-Going beyond sayings and proverbs, we can make the following assertions about performance.
+Going beyond sayings and proverbs, performance measurement provides you with evidence to inform and drive architectural decisions. 
+Specifically, performance testing can help you by providing information that enables you to:
 
-- Validates that the system meets the requirements
-- Identifies bottlenecks and limiting factors
-- Enables predictable scalability
-- Supports data-driven architectural decisions
-- Reduces operational and infrastructure costs
-- Improves reliability and resilience
-- Builds trust with users and stakeholders
+- Validate that the system meets requirements
+- Identify bottlenecks and limiting factors
+- Help ensure predictable scalability
+- Reduce operational and infrastructure costs
+- Deliver improvements in reliability and resilience
+- Build trust with users and stakeholders
 
 [id=debezium-server]
 == Debezium Server
@@ -41,7 +45,7 @@ Apart from performance tests, another great unknown in the CDC community is *Deb
 But let me introduce you to Debezium Server. 
 Debezium Server is a standalone runtime for Change Data Capture that captures database changes using Debezium and delivers them directly to configurable sinks without requiring Kafka or Kafka Connect.
 It addresses a common gap in CDC architectures: situations where Kafka Connect, Kubernetes, or large distributed platforms introduce unnecessary operational complexity. 
-It enables teams to adopt CDC with minimal infrastructure while still benefiting from Debezium’s mature and battle-tested connectors.
+It enables teams to adopt CDC with minimal infrastructure while still benefiting from Debezium’s mature and proven connectors.
 
 [.centered-image.responsive-image]
 ====
@@ -64,9 +68,9 @@ It runs as a single process and although Kafka is not required, it preserves the
 Now that we are familiar with all the components, let us dive into the technical details. 
 
 Starting with the hardware, we have deployed two EC2 machines in AWS of type "c5a.xlarge". Each instance provides 4 vCPUs and 8 GiB of memory, ensuring sufficient resources for both workload generation and CDC processing.
-We have called them Observed and Observer (in order to separate the monitoring load from the machine where Debezium and MySQL are running). In the Observer instance, we have deployed Prometheus, Grafana and YCSB
+We have called these two instances _Observed_ and _Observer_ (in order to separate the monitoring load from the machine where Debezium and MySQL are running). In the Observer instance, we have deployed Prometheus, Grafana and YCSB
 (the software piece generating the load). In the Observed instance, we have a single Kafka container (although it is not really necessary and another software can be used),
-Debezium Server and MySQL. 
+Debezium Server, and MySQL. 
 
 [.centered-image.responsive-image]
 ====
@@ -76,7 +80,7 @@ Debezium Server and MySQL.
 *Benchmarking architecture*
 ====
 
-As described above, we are using some software pieces, most of them are already known, except for YCSB. Yahoo! Cloud Serving Benchmark (YCSB), is a tool created by the Yahoo
+As per the preceding description, we are using several software pieces, most of which are already known, except for Yahoo! Cloud Serving Benchmark (YCSB). The YCSB tool, which was created by the Yahoo
 team and released into open source as of 04/23/2010, developed to evaluate the performance of different cloud serving stores. This is the link to their GitHub project: https://ycsb.site[https://ycsb.site].
 
 If you want to reproduce this scenario, it is quite simple. Go to debezium-performance[ADD_REPO_URL_HERE] repo, clone it and cd into the infrastructure-automation folder and then run terraform apply. 
@@ -120,11 +124,11 @@ And the other ones are the memory consumption in MB throughout the execution. Th
 *Throughput evolution during one execution*
 ====
 
-In another example, we have the Debezium Server throughput during one of the executions. This throughput chart is split into two parts, which comes from YCSB behavior.
+In this example, we see the Debezium Server throughput from another execution of the test. This throughput chart is split into two parts, which comes from YCSB behavior.
 YCSB executions are divided into two phases: an initial load phase that populates the tables, followed by a workload phase that executes the configured mix of operations. This behavior explains the two distinct phases visible in the throughput charts.
 If the first half keeps the throughput at the set level, we consider the execution successful (OK/1), otherwise if something in the process makes it fail we consider it a failed execution (NOK/0).
 
-In the picture below, you can see a detailed view in the second phase of the execution where we are running 300 updates per second and 300 inserts per second. 
+The image that follows shows a detailed view of the second phase of the execution, which runs 300 updates per second and 300 inserts per second. 
 
 [.centered-image.responsive-image]
 ====
@@ -137,8 +141,8 @@ In the picture below, you can see a detailed view in the second phase of the exe
 [id=results-analysis]
 == Results and Analysis
 
-Let me now show you the results. By examining these results, it is possible to gain a clear view of how the system behaves under varying levels of load and
-to identify trends that may not be evident from isolated measurements. But before getting into detailed analysis, you can find the raw results here[ADD_REPO_URL_HERE_RESULTS_FILE]. 
+Let's now examine the results to gain a clear view of how the system behaves under varying levels of load, and
+to identify trends that might not be evident from isolated measurements. If you want to review the detailed analysis, you can view the raw results [ADD_REPO_URL_HERE_RESULTS_FILE]. 
 
 [.centered-image.responsive-image]
 ====
@@ -148,7 +152,7 @@ to identify trends that may not be evident from isolated measurements. But befor
 *Debezium Server streaming results screenshot for MySQL*
 ====
 
-With the image above in mind, let's understand what each of the columns means.
+With the preceding image in mind, let's consider the meaning of each column.
 
 - TABLE_RECORDS: Desired table records we are going to work with in the execution. 
 - TABLE_TARGET_OPS: Desired operations per second we are going to perform during the execution.