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Udemy - Ultimate DevOps to MLOps Bootcamp - Build ML CICD Pipelines (8.2025)

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File Name
Size
01. About this Course/1. Understand the MLOps Project you will Build in the Course.mp4
11 MB
01. About this Course/1. Understand the MLOps Project you will Build in the Course.vtt
9.7 kB
01. About this Course/2. Join RealOps Builders Community on Discord.html
274 B
02. Conceptual Introduction to MLOps/1. M101v2-What-is-MLOps.pdf
2.4 MB
02. Conceptual Introduction to MLOps/1. What is MLOps.mp4
57 MB
02. Conceptual Introduction to MLOps/1. What is MLOps.vtt
29 kB
02. Conceptual Introduction to MLOps/2. M102-Story-of-AI-Infrastructure-Ops.pdf
4.3 MB
02. Conceptual Introduction to MLOps/2. Story of Evolution of MLOps, LLMOps and AgenticAIOps.mp4
308 MB
02. Conceptual Introduction to MLOps/2. Story of Evolution of MLOps, LLMOps and AgenticAIOps.vtt
22 kB
02. Conceptual Introduction to MLOps/3. Comparing Three Approaches to AI.mp4
351 MB
02. Conceptual Introduction to MLOps/3. Comparing Three Approaches to AI.vtt
30 kB
02. Conceptual Introduction to MLOps/3. M103-Understanding-ML-LLM-Agentic-AI.pdf
3.5 MB
02. Conceptual Introduction to MLOps/4. M104-Case-Studies.pdf
3.6 MB
02. Conceptual Introduction to MLOps/4. MLOps Case Studies – Learning from the Pioneers.mp4
124 MB
02. Conceptual Introduction to MLOps/4. MLOps Case Studies – Learning from the Pioneers.vtt
16 kB
02. Conceptual Introduction to MLOps/5. Comparing Devops vs MLOps.mp4
287 MB
02. Conceptual Introduction to MLOps/5. Comparing Devops vs MLOps.vtt
28 kB
02. Conceptual Introduction to MLOps/5. M106-MLOps-vs-DevOps-Understanding-the-Evolution.pdf
2.5 MB
02. Conceptual Introduction to MLOps/6. Emergence of MLOps Engineer.mp4
230 MB
02. Conceptual Introduction to MLOps/6. Emergence of MLOps Engineer.vtt
20 kB
02. Conceptual Introduction to MLOps/6. M105-The-Emergence-of-the-MLOps-Engineer.pdf
2.9 MB
03. Use Case and Environment Setup/1. Module Intro.mp4
66 MB
03. Use Case and Environment Setup/1. Module Intro.vtt
4.2 kB
03. Use Case and Environment Setup/10. Working with Jupyter Notebooks.mp4
68 MB
03. Use Case and Environment Setup/10. Working with Jupyter Notebooks.vtt
8.5 kB
03. Use Case and Environment Setup/11. Download the Lab Guide.html
91 B
03. Use Case and Environment Setup/11. Lab 3 - Environment Setup.pdf
262 kB
03. Use Case and Environment Setup/12. Summary.mp4
75 MB
03. Use Case and Environment Setup/12. Summary.vtt
5.3 kB
03. Use Case and Environment Setup/2. Use Case - House Price Predictor - Regression.mp4
32 MB
03. Use Case and Environment Setup/2. Use Case - House Price Predictor - Regression.vtt
9.7 kB
03. Use Case and Environment Setup/3. Fork and Clone the Repository.html
271 B
03. Use Case and Environment Setup/4. Understanding End to End ML Practices and MLOps.mp4
81 MB
03. Use Case and Environment Setup/4. Understanding End to End ML Practices and MLOps.vtt
27 kB
03. Use Case and Environment Setup/5. Environment Setup Overview.mp4
68 MB
03. Use Case and Environment Setup/5. Environment Setup Overview.vtt
12 kB
03. Use Case and Environment Setup/6. Setting up Docker Podman with Compose.mp4
37 MB
03. Use Case and Environment Setup/6. Setting up Docker Podman with Compose.vtt
6.0 kB
03. Use Case and Environment Setup/7. Launching MLflow for Experiemnt Tracking.mp4
57 MB
03. Use Case and Environment Setup/7. Launching MLflow for Experiemnt Tracking.vtt
9.4 kB
03. Use Case and Environment Setup/8. Understanding the Project Directory and Scaffold.mp4
67 MB
03. Use Case and Environment Setup/8. Understanding the Project Directory and Scaffold.vtt
10 kB
03. Use Case and Environment Setup/9. Setting up Python Virtual Environment with UV.mp4
43 MB
03. Use Case and Environment Setup/9. Setting up Python Virtual Environment with UV.vtt
7.3 kB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/1. Module Intro.mp4
66 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/1. Module Intro.vtt
4.5 kB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/10. Download the Lab Guide.html
85 B
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/10. Lab 4 - From Data to Model.pdf
146 kB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/11. Module Summary.mp4
71 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/11. Module Summary.vtt
4.3 kB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/2. Learning Data Engineering.mp4
117 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/2. Learning Data Engineering.vtt
18 kB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/3. Experimental Data Analysis.mp4
82 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/3. Experimental Data Analysis.vtt
11 kB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/4. Understaing Feature Engineering Concepts.mp4
28 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/4. Understaing Feature Engineering Concepts.vtt
7.7 kB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/5. Building New Features for House Price Predictor.mp4
60 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/5. Building New Features for House Price Predictor.vtt
6.7 kB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/6. Preparing for Model Experimentation.mp4
56 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/6. Preparing for Model Experimentation.vtt
7.8 kB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/7. Data Splitting with x_train, y_train, x_test, y_test.mp4
51 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/7. Data Splitting with x_train, y_train, x_test, y_test.vtt
6.3 kB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/8. Defining Algorithms and Hyperparameter Grids.mp4
62 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/8. Defining Algorithms and Hyperparameter Grids.vtt
7.4 kB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/9. Running Model Experiments to find the Best Model and Hyperparamters.mp4
106 MB
04. From Data to Models - Understanding Data Science with Feature Engineering and Ex/9. Running Model Experiments to find the Best Model and Hyperparamters.vtt
12 kB
05. Bonus Understanding the Core ML Algorithms/1. Module Intro.mp4
16 MB
05. Bonus Understanding the Core ML Algorithms/1. Module Intro.vtt
928 B
05. Bonus Understanding the Core ML Algorithms/2. Linear Regression.mp4
50 MB
05. Bonus Understanding the Core ML Algorithms/2. Linear Regression.vtt
6.8 kB
05. Bonus Understanding the Core ML Algorithms/3. Logistic Regression.mp4
27 MB
05. Bonus Understanding the Core ML Algorithms/3. Logistic Regression.vtt
4.1 kB
05. Bonus Understanding the Core ML Algorithms/4. Decision Tree.mp4
28 MB
05. Bonus Understanding the Core ML Algorithms/4. Decision Tree.vtt
5.5 kB
05. Bonus Understanding the Core ML Algorithms/5. Random Forest.mp4
39 MB
05. Bonus Understanding the Core ML Algorithms/5. Random Forest.vtt
6.4 kB
05. Bonus Understanding the Core ML Algorithms/6. Support Vector Machine (SVM).mp4
25 MB
05. Bonus Understanding the Core ML Algorithms/6. Support Vector Machine (SVM).vtt
2.9 kB
05. Bonus Understanding the Core ML Algorithms/7. Neural Networking.mp4
45 MB
05. Bonus Understanding the Core ML Algorithms/7. Neural Networking.vtt
6.6 kB
05. Bonus Understanding the Core ML Algorithms/8. Boosting Algorithms (XGBoost, LightGBM etc.).mp4
85 MB
05. Bonus Understanding the Core ML Algorithms/8. Boosting Algorithms (XGBoost, LightGBM etc.).vtt
10 kB
05. Bonus Understanding the Core ML Algorithms/9. Module Summary.mp4
30 MB
05. Bonus Understanding the Core ML Algorithms/9. Module Summary.vtt
1.8 kB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/1. Module Intro.mp4
66 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/1. Module Intro.vtt
3.9 kB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/10. Download the Lab Guide.html
74 B
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/10. Lab 5 - Containerize and Deploy the Model with Streamlit App.pdf
220 kB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/11. Summary.mp4
86 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/11. Summary.vtt
5.8 kB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/2. Handover from Data Scientist to ML Engineer MLOps.mp4
30 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/2. Handover from Data Scientist to ML Engineer MLOps.vtt
8.6 kB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/3. Running Feature Engineering and Preprocessing Jobs.mp4
45 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/3. Running Feature Engineering and Preprocessing Jobs.vtt
6.2 kB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/4. Building and Training Final Model with Configs from Data Scientists.mp4
52 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/4. Building and Training Final Model with Configs from Data Scientists.vtt
7.5 kB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/5. Wrapping the Model with FastAPI with Streamlit Client Apps.mp4
78 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/5. Wrapping the Model with FastAPI with Streamlit Client Apps.vtt
9.0 kB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/6. Writing Dockerfile to package Model with FastAPI Wrapper.mp4
117 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/6. Writing Dockerfile to package Model with FastAPI Wrapper.vtt
22 kB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/7. Debugging and Fixing Image Failures, Launch and Validate FastAPI.mp4
96 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/7. Debugging and Fixing Image Failures, Launch and Validate FastAPI.vtt
13 kB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/8. Packaging and testing Streamlit App.mp4
68 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/8. Packaging and testing Streamlit App.vtt
11 kB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/9. Packaging and Model Serving Infra with Docker Compose.mp4
103 MB
06. Packaging Model along with FastAPI Wrapper and Streamlit with Containers/9. Packaging and Model Serving Infra with Docker Compose.vtt
18 kB
07. Setting up MLOps CI Workflow with GitHub Actions/1. Moule Intro.mp4
58 MB
07. Setting up MLOps CI Workflow with GitHub Actions/1. Moule Intro.vtt
3.6 kB
07. Setting up MLOps CI Workflow with GitHub Actions/10. Download the Lab Guide.html
85 B
07. Setting up MLOps CI Workflow with GitHub Actions/10. Lab 6 - MLOps CI PipelineWorkflow with GitHub Actions.pdf
1.1 MB
07. Setting up MLOps CI Workflow with GitHub Actions/11. Summary.mp4
54 MB
07. Setting up MLOps CI Workflow with GitHub Actions/11. Summary.vtt
3.4 kB
07. Setting up MLOps CI Workflow with GitHub Actions/2. DAGs, GitHub Actions and our MLOps CI Workflow.mp4
53 MB
07. Setting up MLOps CI Workflow with GitHub Actions/2. DAGs, GitHub Actions and our MLOps CI Workflow.vtt
18 kB
07. Setting up MLOps CI Workflow with GitHub Actions/3. Understanding GitHub Actions Syntax.mp4
58 MB
07. Setting up MLOps CI Workflow with GitHub Actions/3. Understanding GitHub Actions Syntax.vtt
11 kB
07. Setting up MLOps CI Workflow with GitHub Actions/4. Writing an executung out first GitHub Actions Workflow.mp4
119 MB
07. Setting up MLOps CI Workflow with GitHub Actions/4. Writing an executung out first GitHub Actions Workflow.vtt
16 kB
07. Setting up MLOps CI Workflow with GitHub Actions/5. Adding Data and Feature Engineering Steps with Model Training.mp4
56 MB
07. Setting up MLOps CI Workflow with GitHub Actions/5. Adding Data and Feature Engineering Steps with Model Training.vtt
6.1 kB
07. Setting up MLOps CI Workflow with GitHub Actions/6. Model Training Step with MLFlow for Tracking.mp4
79 MB
07. Setting up MLOps CI Workflow with GitHub Actions/6. Model Training Step with MLFlow for Tracking.vtt
7.5 kB
07. Setting up MLOps CI Workflow with GitHub Actions/7. Adding Image Build and Publish Step with Docker.mp4
53 MB
07. Setting up MLOps CI Workflow with GitHub Actions/7. Adding Image Build and Publish Step with Docker.vtt
7.2 kB
07. Setting up MLOps CI Workflow with GitHub Actions/8. Configurating Registry Token and publishing Image to DockerHub.mp4
65 MB
07. Setting up MLOps CI Workflow with GitHub Actions/8. Configurating Registry Token and publishing Image to DockerHub.vtt
8.5 kB
07. Setting up MLOps CI Workflow with GitHub Actions/9. Modular, Multi Stage MLOps CI Workflow Pipeline.mp4
152 MB
07. Setting up MLOps CI Workflow with GitHub Actions/9. Modular, Multi Stage MLOps CI Workflow Pipeline.vtt
18 kB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/1. Module Intro.mp4
42 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/1. Module Intro.vtt
2.3 kB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/10. Easy way to Generate Kubernetes Manifets and YAML.mp4
32 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/10. Easy way to Generate Kubernetes Manifets and YAML.vtt
8.0 kB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/11. Download the Lab Guide.html
86 B
08. Building Scalable Prod Inference Infrastructure with Kubernetes/11. Lab 7 - Deploying to Kubernetes.pdf
52 kB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/12. Summary.mp4
42 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/12. Summary.vtt
2.4 kB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/2. Designing Scalable Infrastructure for Model Inference.mp4
18 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/2. Designing Scalable Infrastructure for Model Inference.vtt
5.9 kB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/3. Introduction to Kubernetes for Machine Learning.mp4
47 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/3. Introduction to Kubernetes for Machine Learning.vtt
14 kB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/4. Kubernetes Core Concepts - Pods, Deployments and Services.mp4
40 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/4. Kubernetes Core Concepts - Pods, Deployments and Services.vtt
12 kB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/5. Simplest way to build a 3 Node Kubernetes Cluster with KIND.mp4
71 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/5. Simplest way to build a 3 Node Kubernetes Cluster with KIND.vtt
12 kB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/6. Deploying Streamlit Frontent App with Kubernetes.mp4
90 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/6. Deploying Streamlit Frontent App with Kubernetes.vtt
16 kB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/7. Exposing the Streamlit App with Kubernetes NodePort Service.mp4
44 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/7. Exposing the Streamlit App with Kubernetes NodePort Service.vtt
8.2 kB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/8. Creating Deployment Service for the Model wrapped in FastAPI.mp4
48 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/8. Creating Deployment Service for the Model wrapped in FastAPI.vtt
8.0 kB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/9. Connecting Streamlit with Model using Kubernetes native DNS Based Service Discov.mp4
87 MB
08. Building Scalable Prod Inference Infrastructure with Kubernetes/9. Connecting Streamlit with Model using Kubernetes native DNS Based Service Discov.vtt
13 kB
09. Monitoring and Autoscaling a ML Model/1. Module Intro.mp4
30 MB
09. Monitoring and Autoscaling a ML Model/1. Module Intro.vtt
1.7 kB
09. Monitoring and Autoscaling a ML Model/10. AI Based Troubleshooting Monitoring with ChatGPT.mp4
91 MB
09. Monitoring and Autoscaling a ML Model/10. AI Based Troubleshooting Monitoring with ChatGPT.vtt
11 kB
09. Monitoring and Autoscaling a ML Model/11. Running Load Test and Analysing Autoscaling.mp4
75 MB
09. Monitoring and Autoscaling a ML Model/11. Running Load Test and Analysing Autoscaling.vtt
10 kB
09. Monitoring and Autoscaling a ML Model/12. CPU Based Auto Scaling with KEDA.mp4
78 MB
09. Monitoring and Autoscaling a ML Model/12. CPU Based Auto Scaling with KEDA.vtt
12 kB
09. Monitoring and Autoscaling a ML Model/13. Adding a Verticle Pod Autoscaler (VPA).mp4
92 MB
09. Monitoring and Autoscaling a ML Model/13. Adding a Verticle Pod Autoscaler (VPA).vtt
14 kB
09. Monitoring and Autoscaling a ML Model/14. Lab - Setting up Monitoring with Prometheus and Grafana.html
79 B
09. Monitoring and Autoscaling a ML Model/14. Lab 8 - Setting up Model Monitoring.pdf
947 kB
09. Monitoring and Autoscaling a ML Model/15. Lab - Setting up ML Autoscaling.html
89 B
09. Monitoring and Autoscaling a ML Model/15. Lab 9 - Autoscaling Models.pdf
181 kB
09. Monitoring and Autoscaling a ML Model/16. Summary.mp4
50 MB
09. Monitoring and Autoscaling a ML Model/16. Summary.vtt
2.8 kB
09. Monitoring and Autoscaling a ML Model/2. Project Spec.mp4
6.7 MB
09. Monitoring and Autoscaling a ML Model/2. Project Spec.vtt
3.3 kB
09. Monitoring and Autoscaling a ML Model/3. Installing Prometheus and Grafana with Helm.mp4
57 MB
09. Monitoring and Autoscaling a ML Model/3. Installing Prometheus and Grafana with Helm.vtt
7.9 kB
09. Monitoring and Autoscaling a ML Model/4. Exploring Monitoring Metrics with Grafana and Prometheus.mp4
76 MB
09. Monitoring and Autoscaling a ML Model/4. Exploring Monitoring Metrics with Grafana and Prometheus.vtt
10 kB
09. Monitoring and Autoscaling a ML Model/5. Adding Instrumentation for FastAPI along with Custom Dashboard.mp4
103 MB
09. Monitoring and Autoscaling a ML Model/5. Adding Instrumentation for FastAPI along with Custom Dashboard.vtt
13 kB
09. Monitoring and Autoscaling a ML Model/6. Automatic Capacity Scaling Concepts.mp4
34 MB
09. Monitoring and Autoscaling a ML Model/6. Automatic Capacity Scaling Concepts.vtt
4.5 kB
09. Monitoring and Autoscaling a ML Model/7. Installing KEDA and Configuring Resource Spec.mp4
43 MB
09. Monitoring and Autoscaling a ML Model/7. Installing KEDA and Configuring Resource Spec.vtt
5.9 kB
09. Monitoring and Autoscaling a ML Model/8. Configuring Scaled Objects with KEDA.mp4
61 MB
09. Monitoring and Autoscaling a ML Model/8. Configuring Scaled Objects with KEDA.vtt
8.9 kB
09. Monitoring and Autoscaling a ML Model/9. Getting started with Load Testing Model Inference.mp4
65 MB
09. Monitoring and Autoscaling a ML Model/9. Getting started with Load Testing Model Inference.vtt
8.4 kB
10. GitOps Based Deployments for MLLLM Apps/1. Module Intro.mp4
15 MB
10. GitOps Based Deployments for MLLLM Apps/1. Module Intro.vtt
705 B
10. GitOps Based Deployments for MLLLM Apps/2. GitOps Concepts.mp4
23 MB
10. GitOps Based Deployments for MLLLM Apps/2. GitOps Concepts.vtt
6.1 kB
10. GitOps Based Deployments for MLLLM Apps/3. GitOps Pricinple 2 Start Revision Controling the Code.mp4
47 MB
10. GitOps Based Deployments for MLLLM Apps/3. GitOps Pricinple 2 Start Revision Controling the Code.vtt
7.7 kB
10. GitOps Based Deployments for MLLLM Apps/4. GitOps Principle 4 Setup a Agent - ArgoCD.mp4
43 MB
10. GitOps Based Deployments for MLLLM Apps/4. GitOps Principle 4 Setup a Agent - ArgoCD.vtt
5.3 kB
10. GitOps Based Deployments for MLLLM Apps/5. Overview of Argo Application CRD.mp4
57 MB
10. GitOps Based Deployments for MLLLM Apps/5. Overview of Argo Application CRD.vtt
6.5 kB
10. GitOps Based Deployments for MLLLM Apps/6. Continuous Delivery with ArgoCD Applications.mp4
116 MB
10. GitOps Based Deployments for MLLLM Apps/6. Continuous Delivery with ArgoCD Applications.vtt
14 kB
10. GitOps Based Deployments for MLLLM Apps/7. End to End CI and CD Pielines for ML App.mp4
303 MB
10. GitOps Based Deployments for MLLLM Apps/7. End to End CI and CD Pielines for ML App.vtt
27 kB
10. GitOps Based Deployments for MLLLM Apps/8. Summary.mp4
64 MB
10. GitOps Based Deployments for MLLLM Apps/8. Summary.vtt
3.8 kB