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AWS Cloud Engineering Concepts

Step-by-step explanations, real-world issues, and simplified understanding. Master every angle — from foundational concepts to real-world troubleshooting.

What we cover

CloudWatch, CloudTrail, and Config - Monitoring, Auditing, and ComplianceEventBridge - Event-Driven Architecture at ScaleCloudFormation and SSM - Infrastructure as Code and Systems ManagementAWS Cost Explorer, Savings Plans, and Cost OptimisationAWS Machine Learning Services - AI Without Building ModelsAWS Batch, Outposts, and Hybrid Compute - Running Jobs and Extending AWSSES, Pinpoint, and Communication Services - Email, SMS, and Multi-Channel

7 Subtopics

Interactive guides & progressions

8 Articles

In-depth technical readings

3 FAQs

Common questions answered

AWS DevOps, Cost, and Machine Learning

Master CloudWatch, CloudTrail, CloudFormation, Cost Explorer, SageMaker, and AWS Batch — operating, automating, and optimising production AWS infrastructure.

Operating AWS at scale without proper observability and cost controls leads directly to runaway spend and blind spots during incidents. This pillar ties together the monitoring, automation, and financial governance tools that mature engineering teams check daily, alongside AWS's managed ML tooling for teams building on top of the same infrastructure.

What This Pillar Covers

  • CloudWatch and CloudTrail — metrics, alarms, log groups, and API audit trails for incident forensics
  • CloudFormation — Infrastructure as Code, stacks, change sets, and drift detection
  • Cost Explorer and AWS Budgets — cost allocation tags, anomaly detection, and Savings Plans
  • AWS Batch — managed job queues, compute environments, and array jobs for large-scale processing
  • SageMaker — training jobs, model endpoints, and MLOps pipelines

Who This Is For

DevOps engineers responsible for observability and cost governance, and platform teams supporting data science workloads who need SageMaker and Batch to coexist cleanly with production infrastructure spend.

Learning Progression
1

CloudWatch, CloudTrail, and Config - Monitoring, Auditing, and Compliance

Monitor AWS infrastructure with CloudWatch metrics and alarms, audit every API call with CloudTrail, and enforce compliance rules with AWS Config.

2

EventBridge - Event-Driven Architecture at Scale

Build event-driven architectures with EventBridge rules, custom event buses, Schema Registry, and EventBridge Pipes to connect AWS services without glue code.

3

CloudFormation and SSM - Infrastructure as Code and Systems Management

Define AWS infrastructure as code with CloudFormation templates, manage servers without SSH using SSM Session Manager, and automate patching with Patch Manager.

4

AWS Cost Explorer, Savings Plans, and Cost Optimisation

Analyse and reduce AWS spend with Cost Explorer, Savings Plans, Reserved Instances, Cost Anomaly Detection, and smart networking cost decisions.

5

AWS Machine Learning Services - AI Without Building Models

Add AI capabilities to applications using AWS pre-built ML services — Rekognition, Transcribe, Polly, Translate, Comprehend, Lex, Kendra, Textract, and SageMaker.

6

AWS Batch, Outposts, and Hybrid Compute - Running Jobs and Extending AWS

Run large-scale batch jobs with AWS Batch, extend AWS infrastructure to your data center with Outposts, and integrate SaaS data with AppFlow.

7

SES, Pinpoint, and Communication Services - Email, SMS, and Multi-Channel

Send transactional email with SES, run multi-channel marketing campaigns with Pinpoint, and understand when each communication service is the right tool.

Frequently Asked Questions

What does the AWS DevOps, Cost, and Machine Learning concept cover?

AWS DevOps, Cost, and Machine Learning covers a variety of key topic guides, including: CloudWatch, CloudTrail, and Config - Monitoring, Auditing, and Compliance, EventBridge - Event-Driven Architecture at Scale, CloudFormation and SSM - Infrastructure as Code and Systems Management, AWS Cost Explorer, Savings Plans, and Cost Optimisation, AWS Machine Learning Services - AI Without Building Models, AWS Batch, Outposts, and Hybrid Compute - Running Jobs and Extending AWS, SES, Pinpoint, and Communication Services - Email, SMS, and Multi-Channel. Master CloudWatch, CloudTrail, CloudFormation, Cost Explorer, SageMaker, and AWS Batch — operating, automating, and optimising production AWS infrastructure.

How does AWS DevOps, Cost, and Machine Learning relate to the AWS Cloud Engineering hub?

AWS DevOps, Cost, and Machine Learning is a core learning conceptual pillar mapped within the AWS Cloud Engineering engineering hub of the DevOps Network.

Are these DevOps concepts free to learn?

Yes, all lessons, visual roadmaps, and guides on DevOps Network are 100% free with no paywalls or sign-up gates for learning content.

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