From 65775b9fe9fe44049a0f1da2b6b9ffbdb9881d1f Mon Sep 17 00:00:00 2001
From: mjkwiatkowski <mati.rewa@gmail.com>
Date: Sat, 4 Jul 2026 15:55:40 +0200
Subject: feat: finished section 4.4

---
 content/implementation.tex | 14 +++++++++++++-
 1 file changed, 13 insertions(+), 1 deletion(-)

(limited to 'content/implementation.tex')

diff --git a/content/implementation.tex b/content/implementation.tex
index 2395963..0decbc3 100644
--- a/content/implementation.tex
+++ b/content/implementation.tex
@@ -125,7 +125,7 @@ In order to turn it into a \gls{dt}, we have made several design decisions and e
 	      The \code{KafkaMonitor} class implements the generic \code{ComputeMonitor} interface, therefore the new extension follows the other metric exporting options in \code{OpenDC} (\ie follows the implementation for exporting  metrics into \code{.parquet files}).
 	\item \textbf{\code{HTTPClient}}\\
 	      The \code{HTTPClient} offers the necessary functionality to communicate between the \gls{dt} and the datacenter.
-	      We decided to use the HTTP protocol for short, one-off communications between the \gls{dt} and the datacenter, as is common industry practice.
+	      We decided to use the \gls{http} protocol for short, one-off communications between the \gls{dt} and the datacenter, as is common industry practice.
 \end{enumerate}
 
 \section{Python Modules}\label{ss:programming}
@@ -137,7 +137,19 @@ For future work, we envision a system that implements the reference architecture
 
 \begin{enumerate}[label=\textbf{\arabic*.}]
 	\item \textbf{\code{AnalyticsEngine}}\\
+	      The \code{AnalyticsEngine} module is necessary in order to encapsulate the logic of data preprocessing and analysis from monitoring.
+	      This component can contain capabilities for different statistical metrics, subject to \gls{dt}s focus.
+	      In \gls{my_system} \code{AnalyticsEngine} continuously checks whether the incoming datacenter sensor readings exceed different thresholds.
+	      For example, the \code{AnalyticsEngine} is capable of calculating a similarity score $S$ between potential failure distributions and the true failure distribution.
 	\item \textbf{\code{HTTPServer}}\\
+	      The \code{HTTPServer} is crucial for interrupting the operation of the datacenter in order to adjust its operation or offer insights.
+	      It maintains a python \code{Queue} structure.
+	      The \code{Queue} \emph{producer} is the \code{AnalyticsEngine} (\grayCircled{4}).
+	      The \emph{consumer} is the \code{HTTPClient} within \code{OpenDC} (\ie the real datacenter, (\myCircled{2}), (\myCircled{1})).
+	      Both the consumer and producer interact with the \code{Queue} via the network and different HTTP endpoints of \code{HTTPServer}.
 	\item \textbf{\code{MonitoringService}}\\
+	      The \code{MonitoringService} is responsible for interacting with the \code{Redis} key value store.
+	      It contains a \code{while True} Python loop which contains the function call to fetch the latest changes to the \code{Redis} stream.
+	      Upon update, the \code{MonitoringService} informs the \code{AnalyticsEngine} that new data is awaiting \code{AnalyticsEngine} (\grayCircled{6}).
 \end{enumerate}
 
-- 
cgit v1.2.3

