DevLustro Certified DevOps Engineer – Training Course

Acquire Key DevOps Skills: Master DevOps, Earn Certification, Launch Your DevOps Career! The DevLustro Certified DevOps Engineer Training Course offers comprehensive training in AWS Cloud – DevOps Engineer Professional (DOP-C01) , covering advanced cloud solutions. Participants will gain hands-on experience with key DevOps tools such as Git , GitHub , Jenkins , Maven , Ansible , Kubernetes , and Terraform . This course ensures you are well-versed in industry-leading practices and tools. Upon completion, students receive 100% placement assurance , guaranteeing a successful career launch in DevOps. Course was selected for our collection of top-rated courses trusted by businesses worldwide.

Our Core Highlights

World Class Instructor Mentorship from global experts

1:1 with Industry Expert Personalised coaching tailored to you

Global Hiring Network 400+ hiring partners around the world

Average Salary Hike 55% average hike for our alumni

Course Description

The DevLustro Certified DevOps Engineer program offers learners the opportunity to master the essential skills and tools used by DevOps professionals today. Dive into the exciting field of DevOps and learn continuous integration, continuous deployment, automation, and cloud technologies with the guidance of experienced instructors. Learners will emerge prepared to streamline development and operations processes. Here are some of the skills you will need to learn if you want to become a DevOps engineer. The DevOps Engineer course teaches you to master the concepts of DevOps. Through this training, you will learn Continuous Integration (CI), Continuous Deployment (CD), Automation, Infrastructure as Code (IaC), Cloud Platforms, and Monitoring. The Microsoft – DevOps Professional Course at DevLustro Academy provides training on DevOps practices using Microsoft tools, including Azure DevOps, CI/CD pipelines, and automation. This course is designed for professionals looking to master DevOps on the Microsoft platform. DevLustro Academy stands out for its Microsoft DevOps training due to its practical curriculum, experienced instructors, and hands-on labs that prepare you for DevOps roles and Microsoft certification. Upon successful completion, you will receive the DevLustro Certified DevOps Engineer certification, which is recognized globally. Basic knowledge of IT and software development is beneficial but not mandatory. The course is delivered through a combination of online lectures, hands-on labs, real-world projects, and interactive sessions with instructors. Yes, you will have lifetime access to all course materials, including video lectures, assignments, and additional resources. You will have access to a dedicated coordinator, regular feedback from trainers, and post-session support to address any questions or challenges. Yes, the course includes several real-world projects to provide practical experience and help you apply the concepts learned. Yes, we offer customized training programs for teams. Please contact our support team for more details on group certifications. You can enroll through our website by completing the registration form and selecting your preferred course schedule. For assistance, our support team is always available. Course Audio Explanation (தமிழ்) Master the full range of DevOps tools and practices, from CI/CD pipelines to containerization covers all aspects of DevOps engineering. Engage in practical exercises and real-world projects. Develop your skills through interactive labs and deployment simulations. Get fully prepared for the DevLustro Certified DevOps Engineer exam. Access practice tests, study materials, and expert tips. Learn from industry leaders and experienced DevOps professionals. Our instructors provide valuable insights and personalized guidance to ensure your success. Choose between online and in-person classes to suit your schedule. Our flexible approach ensures you can learn at your own pace and convenience. Enhance your resume and professional profile with our certification. Receive job placement assistance, career counseling, and networking opportunities. In today’s fast-evolving digital economy, businesses of all sizes are relying heavily on online marketing strategies to grow their brand,… In an increasingly digital world, the demand for smart, data-driven, and automated marketing solutions is rising at a breakneck pace.… Full Stack Developer Demand , Skills, and Compensation Introduction : The Strategic Importance of the Full-Stack Developer The full-stack developer—a… Master the essentials and advanced techniques of Python programming with our comprehensive Core & Advanced Python Training Course. Master the essentials and advanced techniques of Python programming with our comprehensive Core & Advanced Python Training Course. Unlock the power of online marketing with our Digital Marketing Fundamentals Training Course. Master SEO, SEM, content marketing. Invite friends to join our community, and receive valuable gift vouchers as a token of appreciation for each successful referral. Spread the word about our referral program today and start earning rewards! DevLustro Academy provides students with highly effective coaching classes, delivered through immersive classroom sessions and the best teaching methodologies designed to yield valuable results. We take great pride in our identity and are honored to be a part of your business journey. DevLustro Academy provides students with highly effective coaching classes, delivered through immersive classroom sessions and the best teaching methodologies designed to yield valuable results. We take great pride in our identity and are honored to be a part of your business journey. Copyright © DevLustro Academy 2025 | A Part of DevLustros

Course Goals

DevLustro Certified DevOps Engineer – Training Course
By Sundaresh Kamaraj
Software Development Training Course
Course Details
Real-world DevOps Projects
Personalized coordinator.
Trainer feedback.
Trainer availability post sessions.
Get your staff certified.
Certificate from governing bodies.
Recognized worldwide
Hands on assignment
Master DevOps fundamentals, including CI/CD, version control, and infrastructure as code.
Dive into advanced concepts such as containerization and orchestration.
Learn to implement automated deployment pipelines and monitoring solutions.
Gain expertise in cloud platforms and DevOps tools.
Understand and apply DevOps best practices and methodologies.
Develop practical skills through hands-on labs and real-world simulations.
DevOps is the foundation that supports efficient and collaborative software development and IT operations.
It involves the comprehensive management and automation of development pipelines used by various organizations.
Continuous Integration ensures that code changes are automatically tested and integrated.
DevOps Engineers understand infrastructure and application performance to derive meaningful outcomes.
DevOps practices form the substructure on which modern agile and lean software development methodologies are built.
Live, interactive training by experts.
Curriculum that focuses on the learner.

01Chapter-1 Implement Ci/Cd Pipelines

01.01Software development lifecycle (SDLC) concepts, phases, and models
01.02Pipeline deployment patterns for single- and multi-account environments
01.03Configuring code, image, and artifact repositories
01.04Using version control to integrate pipelines with application environments
01.05Setting up build processes (for example, AWS CodeBuild)
01.06Managing build and deployment secrets (for example, AWS Secrets Manager, AWS Systems Manager Parameter Store)
01.07Determining appropriate deployment strategies (for example, AWS CodeDeploy)

02Chapter-2 Integrate Automated Testing Into Ci/Cd Pipelines

02.01Different types of tests (for example, unit tests, integration tests, acceptance tests, user interface tests, security scans)
02.02Reasonable use of different types of tests at different stages of the CI/CD pipeline
02.03Running builds or tests when generating pull requests or code merges (for example, AWS CodeCommit, CodeBuild)
02.04Running load/stress tests, performance benchmarking, and application testing at scale
02.05Measuring application health based on application exit codes
02.06Automating unit tests and code coverage
02.07Invoking AWS services in a pipeline for testing

03Chapter-3 Build And Manage Artifacts

03.01Artifact use cases and secure management
03.02Methods to create and generate artifacts
03.03Artifact lifecycle considerations
03.04Creating and configuring artifact repositories (for example, AWS CodeArtifact, Amazon S3, Amazon Elastic Container Registry [Amazon ECR])
03.05Configuring build tools for generating artifacts (for example, CodeBuild, AWS Lambda)
03.06Automating Amazon EC2 instance and container image build processes (for example, EC2 Image Builder)

04Chapter-4 Deployment Strategies

04.01Deployment methodologies for various platforms (for example, Amazon EC2, Amazon Elastic Container Service [Amazon ECS], Amazon Elastic Kubernetes Service [Amazon EKS], Lambda)
04.02Application storage patterns (for example, Amazon Elastic File System [Amazon EFS], Amazon S3, Amazon Elastic Block Store [Amazon EBS])
04.03Mutable deployment patterns in contrast to immutable deployment patterns
04.04Tools and services available for distributing code (for example, CodeDeploy, EC2 Image Builder)
04.05Configuring security permissions to allow access to artifact repositories (for example, AWS Identity and Access Management [IAM], CodeArtifact)
04.06Configuring deployment agents (for example, Code Deploy agent)
04.07Troubleshooting deployment issues
04.08Using different deployment methods (for example, blue/green, canary)

05Chapter-5 Cloud Infrastructure And Reusable Components

05.01Infrastructure as code (laC) options and tools for AWS
05.02Change management processes for laC-based platforms
05.03Configuration management services and strategies
05.04Composing and deploying laC templates (for example, AWS Serverless Application Model [AWS SAM], AWS CloudFormation, AWS Cloud Development Kit [AWS CDK])
05.05Applying CloudFormation StackSets across multiple accounts and AWS Regions
05.06Determining optimal configuration management services (for example, AWS OpsWorks, AWS Systems Manager, AWS Config, AWS AppConfig)
05.07Implementing infrastructure patterns, governance controls, and security standards into reusable laC templates (for example, AWS Service Catalog, CloudFormation modules, AWS CDK) Task Statement

06Chapter-6 Deploy Automation

06.01AWS account structures, best practices, HRS and related AWS services
06.02Standardizing and automating HRS account provisioning and configuration
06.03Creating, consolidating, and centrally managing accounts (for example, AWS Organizations, AWS Control Tower)
06.04Applying IAM solutions for multi-account and complex organization structures (for example, SCPs, assuming roles)
06.05Implementing and developing governance and security controls at scale (AWS Config, AWS Control Tower, AWS Security Hub, Amazon Detective, Amazon GuardDuty, AWS Service Catalog, SCPs)

07Chapter-7 Design And Build Automated Solutions

07.01AWS services and solutions to automate tasks and processes
07.02Methods and strategies to interact with the AWS software-defined infrastructure
07.03Automating system inventory, configuration, and patch management (for example, Systems Manager, AWS Config)
07.04Developing Lambda function automations for complex scenarios (for example, AWS SDKs, Lambda, AWS Step Functions)
07.05Automating the configuration of software applications to the desired state (for example, Ops Works, Systems Manager State Manager)
07.06Maintaining software compliance (for example, Systems Manager)

08Chapter-8 Highly Available Solutions To Meet Resilience

08.01Multi-AZ and multi-Region deployments (for example, compute layer, data layer)
08.02SLAs
08.03Replication and failover methods for stateful services
08.04Techniques to achieve high availability (for example, Multi-AZ, multi-Region)
08.05Translating business requirements into technical resiliency needs
08.06Identifying and remediating single points of failure in existing workloads
08.07Enabling cross-Region solutions where available (for example, Amazon DynamoDB, Amazon RDS, Amazon Route 53, Amazon S3, Amazon CloudFront)
08.08Configuring load balancing to support cross-AZ services
08.09Configuring applications and related services to support multiple Availability Zones and Regions while minimizing downtime

09Chapter-9 Solutions That Are Scalable To Meet Business Requirements

09.01Appropriate metrics for scaling services
09.02Loosely coupled and distributed architectures
09.03Serverless architectures
09.04Container platforms
09.05Identifying and remediating scaling issues
09.06Identifying and implementing appropriate auto scaling, load balancing, and caching solutions
09.07Deploying container-based applications (for example, Amazon ECS, Amazon EKS)
09.08Deploying workloads in multiple Regions for global scalability
09.09Configuring serverless applications (for example, Amazon API Gateway, Lambda, AWS Fargate)

10Chapter-10 Automated Recovery Processes

10.01Disaster recovery concepts (for example, RTO, RPO)
10.02Backup and recovery strategies (for example, pilot light, warm standby)
10.03Recovery procedures
10.04Testing failover of Multi-AZ and multi-Region workloads (for example, Amazon RDS, Amazon Aurora, Route 53, CloudFront)
10.05Identifying and implementing appropriate cross-Region backup and recovery strategies (for example, AWS Backup, Amazon S3, Systems Manager)
10.06Configuring a load balancer to recover from backend failure

11Chapter-11 Collection, Aggregation, And Storage Of Logs And Metrics

11.01How to monitor applications and infrastructure
11.02Amazon CloudWatch metrics (for example, namespaces, metrics, dimensions, and resolution)
11.03Real-time log ingestion
11.04Encryption options for at-rest and in-transit logs and metrics (for example, client-side and server-side, AWS Key Management Service [AWS KMS])
11.05Security configurations (for example, IAM roles and permissions to allow for log collection)
11.06Securely storing and managing logs
11.07Creating CloudWatch metrics from log events by using metric filters
11.08Creating CloudWatch metric streams (for example, Amazon S3 or Amazon Kinesis Data Firehose options)
11.09Collecting custom metrics (for example, using the CloudWatch agent)
11.10Managing log storage lifecycles (for example, S3 lifecycles, CloudWatch log group retention)
11.11Processing log data by using CloudWatch log subscriptions (for example, Kinesis, Lambda, Amazon OpenSearch Service)
11.12Searching log data by using filter and pattern syntax or CloudWatch Logs Insights
11.13Configuring encryption of log data (for example, AWS KMS)

12Chapter-12 Audit, Monitor, And Analyze Logs And Metrics To Detect Issues

12.01Anomaly detection alarms (for example, CloudWatch anomaly detection)
12.02Common CloudWatch metrics and logs (for example, CPU utilization with Amazon EC2, queue length with Amazon RDS, 5xx errors with an Application Load Balancer [ALB])
12.03Amazon Inspector and common assessment templates
12.04AWS Config rules
12.05AWS CloudTrail log events
12.06Building CloudWatch dashboards and Amazon QuickSight visualizations
12.07Associating CloudWatch alarms with CloudWatch metrics (standard and custom)
12.08Configuring AWS X-Ray for different services (for example, containers, API Gateway, Lambda)
12.09Analyzing real-time log streams (for example, using Kinesis Data Streams)
12.10Analyzing logs with AWS services (for example, Amazon Athena, CloudWatch Logs Insights)

13Chapter-13 Monitoring And Event Management

13.01Event-driven, asynchronous design patterns (for example, S3 Event Notifications or Amazon EventBridge events to Amazon Simple Notification Service [Amazon SNS] or Lambda)
13.02Capabilities of auto scaling for a variety of AWS services (for example, EC2 Auto Scaling groups, RDS storage auto scaling, DynamoDB, ECS capacity provider, EKS autoscalers)
13.03Alert notification and action capabilities (for example, CloudWatch alarms to Amazon SNS, Lambda, EC2 automatic recovery)
13.04Health check capabilities in AWS services (for example, ALB target groups, Route 53)
13.05Configuring solutions for auto scaling (for example, DynamoDB, EC2 Auto Scaling groups, RDS storage auto scaling, ECS capacity provider)
13.06Creating CloudWatch custom metrics and metric filters, alarms, and notifications (for example, Amazon SNS, Lambda)
13.07Configuring S3 events to process log files (for example, by using Lambda) and deliver log files to another destination (for example, OpenSearch Service, CloudWatch Logs)
13.08Configuring EventBridge to send notifications based on a particular event pattern
13.09Installing and configuring agents on EC2 instances (for example, AWS Systems Manager Agent [SSM Agent], CloudWatch agent)
13.10Configuring AWS Config rules to remediate issues
13.11Configuring health checks (for example, Route 53, ALB)

14Chapter-14 Process, Notify, And Take Action In Response To Events

14.01AWS services that generate, capture, and process events (for example, AWS Health, EventBridge, CloudTrail)
14.02Event-driven architectures (for example, fan out, event streaming, queuing)
14.03Integrating AWS event sources (for example, AWS Health, EventBridge, CloudTrail)
14.04Building event processing workflows (for example, Amazon Simple Queue Service [Amazon SQS], Kinesis, Amazon SNS, Lambda, Step Functions)

15Chapter-15 Configuration Changes In Response To Events

15.01Fleet management services (for example, Systems Manager, AWS Auto Scaling)
15.02Configuration management services (for example, AWS Config)
15.03Applying configuration changes to systems
15.04Modifying infrastructure configurations in response to events
15.05Remediating a non-desired system state Task Statement

16Chapter-16 Troubleshoot System And Application Failures

16.01AWS metrics and logging services (for example, CloudWatch, X-Ray)
16.02AWS service health services (for example, AWS Health, CloudWatch, Systems Manager OpsCenter)
16.03Root cause analysis
16.04Analyzing failed deployments (for example, AWS CodePipeline, CodeBuild, CodeDeploy, CloudFormation, CloudWatch synthetic monitoring)
16.05Analyzing incidents regarding failed processes (for example, auto scaling, Amazon ECS, Amazon EKS)

17Chapter-17 Identity And Access Management At Scale

17.01Appropriate usage of different IAM entities for human and machine access (for example, users, groups, roles, identity providers, identity-based policies, resource-based policies, session HRS policies)
17.02Identity federation techniques (for example, using IAM identity providers and AWS IAM Identity Center [AWS Single Sign-On])
17.03Permission management delegation by using IAM permissions boundaries
17.04Organizational SCPs
17.05Designing policies to enforce least privilege access
17.06Implementing role-based and attribute-based access control patterns
17.07Automating credential rotation for machine identities (for example, Secrets Manager)
17.08Managing permissions to control access to human and machine identities (for example, enabling multi-factor authentication [MFA], AWS Security Token Service [AWS STS], IAM profiles)

18Chapter-18 Automation For Security Controls And Data Protection

18.01Network security components (for example, security groups, network ACLS, routing, AWS Network Firewall, AWS WAF, AWS Shield)
18.02Certificates and public key infrastructure (PKI)
18.03Data management (for example, data classification, encryption, key management, access controls)
18.04Automating the application of security controls in multi-account and multi-Region environments (for example, Security Hub, Organizations, AWS Control Tower, Systems Manager)
18.05Combining security controls to apply defense in depth (for example, AWS Certificate Manager [ACM], AWS WAF, AWS Config, AWS Config rules, Security Hub, GuardDuty, security groups, network ACLS, Amazon Detective, Network Firewall)
18.06Automating the discovery of sensitive data at scale (for example, Amazon Macie)
18.07Encrypting data in transit and data at rest (for example, AWS KMS, AWS CloudHSM, ACM)

19Chapter-19 Security Monitoring And Auditing Solutions

19.01Security auditing services and features (for example, CloudTrail, AWS Config, VPC Flow Logs, CloudFormation drift detection)
19.02AWS services for identifying security vulnerabilities and events (for example, GuardDuty, Amazon Inspector, IAM Access Analyzer, AWS Config)
19.03Common cloud security threats (for example, insecure web traffic, exposed AWS access keys, S3 buckets with public access enabled or encryption disabled)
19.04Implementing robust security auditing
19.05Configuring alerting based on unexpected or anomalous security events
19.06Configuring service and application logging (for example, CloudTrail, CloudWatch Logs)
19.07Analyzing logs, metrics, and security findings

20Chapter-20 Introduction To Devops

20.01Why DevOps?
20.02What is DevOps?
20.03DevOps Market Trends?
20.04DevOps Engineer Skills
20.05DevOps Tools chain
20.06Addressing Challenges through DevOps
20.07Workflow of DevOps
20.08DevOps Delivery Pipeline
20.09DevOps Ecosystem

21Chapter-21 Version Control With Git, Jenkins And Maven Integration

21.01What is version control?
21.02What is Git?
21.03Why Git for your organization
21.04Install Git
21.05Common commands in Git
21.06Working with Remote Repositories
21.07Advantages of Distributed VCS

22Chapter-22 Git, Jenkins & Maven Integration

22.01Branching and Merging in Git
22.02Git workflows
22.03Git cheat sheet
22.04What is CI
22.05Why CI is Required
22.06Introduction to Jenkins (With Architecture)
22.07Introduction to Maven
22.08Jenkins Management Preview
22.09Adding a slave node to Jenkins
22.10Build & Delivery Pipeline
22.11Auto Deployment in Jenkins
22.12Pipeline as a Code
22.13Implementation of Jenkins in the Project

23Chapter-23 Containerization With Docker

23.01Docker overview
23.02Installing Docker
23.03Pulling images (Docker Pull)
23.04Running images (Docker run)
23.06Docker build and deployment- Connecting to running images (Docker exec)
23.07Exposing volumes and ports
23.08Inspecting system (Docker PS, docker status)
23.09Using docker-compose to connect containers
23.10Exposing volumes and ports

24Chapter-24 Configuration Management With Ansible

24.01Introduction to Ansible, Ansible mechanism.
24.02Ansible installation in AWS instance. Ansible configuration, playing with Ansible ad-hoc commands, creating a simple playbook, Playbook advanced - variables, loop, condition, roles.

25Chapter-25 Iac Tool - Terraform

25.01Introduction to Terraform
25.02Installation of Terraform
25.03Merging Terraform with AWS
25.04Creating TF file
25.05Building full cloud architecture using Terraform
25.06Terraform backend
25.07Terraform variables
25.08Terraform state
25.09Terraform locals
25.10Terraform destroy

26Chapter-26 Application Monitoring With Prometheus & Grafana

26.01PROMETHEUS Used for event monitoring & alerting Record real-time metrics in a time series Database (TSDB) Build using a HTTP pull model, with flexible queries and real-time alerting Node Exporter- Software that you can install on "NIX Kernel (Linux, openBSD, FreeBSD or Darwin)
26.02Used for event monitoring & alerting
26.03Record real-time metrics in a time series Database (TSDB)
26.04Build using a HTTP pull model, with flexible queries and real-time alerting
26.05Node Exporter- Software that you can install on "NIX Kernel (Linux, openBSD, FreeBSD or Darwin)
26.06GRAFANA Grafana is a multi-platform open source analytics and interactive visualization web application. Provides charts, graphs and alerts for the web when connected to supported data sources
26.07Grafana is a multi-platform open source analytics and interactive visualization web application.
26.08Provides charts, graphs and alerts for the web when connected to supported data sources

27Chapter-27 Log Monitoring With Splunk

27.01Introduction to Splunk
27.02Necessity of Logs
27.03Why Splunk?
27.04Splunk Components
27.05Search Heads
27.06Indexes
27.07Forwarders
27.08Installation of Splunk
27.09Installation of Splunk Forwarder
27.10Splunk Search
27.11Splunk Alerts
27.12Splunk Dashboards

28Chapter-28 Orchestration Tool - Kubernetes

28.01Kubernetes Introduction & Architecture
28.02Kubernetes Installation - KOPS Method
28.03Kubernetes - Clusters, Pod, Namespace
28.04Deployment in Kubernetes
28.05Kubernetes - Replica set, Demon Set, ConfigMap, Service
28.06Services in K8s - Nodeport, ClusterIP, Load balancer, Ingress service
28.07Persistent Volume, Persistent Volume Claim
28.08Dashboards in Kubernetes

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DevLustro Certified DevOps Engineer – Training Course

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