AWS Certified DevOps Engineer- Professional Certification in Rwanda
Develop top-tier DevOps skills with AWS expertise
24 hours of an AWS-certified training program
Comprehensive course structure with six modules
Work with the latest AWS services such as EC2, Lambda & EKS
Get prepared for the AWS Certified DevOps Engineer - Professional (DOP-C02) exam
Explore hands-on labs and guidance from expert instructors
Flexible learning options designed for busy professionals
Affordable installment options available
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Overview
What our training includes:
- Develop expertise in CI/CD pipeline creation using AWS CodePipeline
- Discover automated testing processes through AWS CodeBuild
- Create and manage software artefacts with AWS CodeArtifact
- Implement deployment methods using AWS CodeDeploy services
- Configure system settings via AWS Systems Manager and OpsWorks
- Learn container orchestration using Amazon ECS and EKS
- Gain the AWS Certified DevOps Engineer – Professional certification
Upcoming sessions
Curriculum
1
Software development lifecycle (SDLC) concepts, phases, and models
2
Pipeline deployment patterns for single- and multi-account environments
3
Configuring code, image, and artifact repositories
4
Using version control to integrate pipelines with application environments
5
Setting up build processes (for example, AWS CodeBuild)
6
Managing build and deployment secrets (for example, AWS Secrets
7
Manager, AWS Systems Manager Parameter Store)
8
Determining appropriate deployment strategies (for example, AWS CodeDeploy)
9
Different types of tests (for example, unit tests, integration tests, acceptance tests, user interface tests, security scans)
10
Reasonable use of different types of tests at different stages of the CI/CD pipeline
11
Running builds or tests when generating pull requests or code merges (for example, CodeBuild)
12
Running load/stress tests, performance benchmarking, and application testing at scale
13
Measuring application health based on application exit codes
14
Automating unit tests and code coverage
15
Invoking AWS services in a pipeline for testing
16
Artifact use cases and secure management
17
Methods to create and generate artifacts
18
Artifact lifecycle considerations
19
Creating and configuring artifact repositories (for example, AWS CodeArtifact, Amazon S3, Amazon Elastic Container Registry [Amazon ECR])
20
Configuring build tools for generating artifacts (for example, CodeBuild, AWS Lambda)
21
Automating Amazon EC2 instance and container image build processes (for example, EC2 Image Builder)
22
Deployment methodologies for various platforms (for example, Amazon EC2, Amazon Elastic Container Service [Amazon ECS], Amazon Elastic
23
Kubernetes Service [Amazon EKS], Lambda)
24
Application storage patterns (for example, Amazon Elastic File System [Amazon EFS], Amazon S3, Amazon Elastic Block Store [Amazon EBS])
25
Mutable deployment patterns in contrast to immutable deployment patterns
26
Tools and services available for distributing code (for example, CodeDeploy, EC2 Image Builder)
27
Configuring security permissions to allow access to artifact repositories (for example, AWS Identity and Access Management [IAM], CodeArtifact)
28
Configuring deployment agents (for example, CodeDeploy agent)
29
Troubleshooting deployment issues
30
Using different deployment methods (for example, blue/green, canary)
1
Infrastructure as code (IaC) options and tools for AWS
2
Change management processes for IaC-based platforms
3
Configuration management services and strategies
4
Composing and deploying IaC templates (for example, AWS Serverless Application Model [AWS SAM], AWS CloudFormation, AWS Cloud Development Kit [AWS CDK])
5
Applying CloudFormation StackSets across multiple accounts and AWS Regions
6
Determining optimal configuration management services (for example, AWS OpsWorks, AWS Systems Manager, AWS Config, AWS AppConfig)
7
Implementing infrastructure patterns, governance controls, and security standards into reusable IaC templates (for example, AWS Service Catalog, CloudFormation modules, AWS CDK)
8
AWS account structures, best practices, and related AWS services
9
Standardizing and automating account provisioning and configuration
10
Creating, consolidating, and centrally managing accounts (for example, AWS Organizations, AWS Control Tower)
11
Applying IAM solutions for multi-account and complex organization structures (for example, SCPs, assuming roles)
12
Implementing and developing governance and security controls at scale (AWS Config, AWS Control Tower, AWS Security Hub, Amazon Detective, Amazon GuardDuty, AWS Service Catalog, SCPs)
13
AWS services and solutions to automate tasks and processes
14
Methods and strategies to interact with the AWS software-defined infrastructure
15
Automating system inventory, configuration, and patch management (for example, Systems Manager, AWS Config)
16
Developing Lambda function automations for complex scenarios (for example, AWS SDKs, Lambda, AWS Step Functions)
17
Automating the configuration of software applications to the desired state (for example, OpsWorks, Systems Manager State Manager)
18
Maintaining software compliance (for example, Systems Manager)
1
Multi-AZ and multi-Region deployments (for example, compute layer, data layer)
2
SLAs
3
Replication and failover methods for stateful services
4
Techniques to achieve high availability (for example, Multi-AZ, multi-Region)
5
Translating business requirements into technical resiliency needs
6
Identifying and remediating single points of failure in existing workloads
7
Enabling cross-Region solutions where available (for example, Amazon DynamoDB, Amazon RDS, Amazon Route 53, Amazon S3, Amazon CloudFront)
8
Configuring load balancing to support cross-AZ services
9
Configuring applications and related services to support multiple
10
Availability Zones and Regions while minimizing downtime
11
Appropriate metrics for scaling services
12
Loosely coupled and distributed architectures
13
Serverless architectures
14
Container platforms
15
Identifying and remediating scaling issues
16
Identifying and implementing appropriate auto scaling, load balancing, and caching solutions
17
Deploying container-based applications (for example, Amazon ECS, Amazon EKS)
18
Deploying workloads in multiple Regions for global scalability
19
Configuring serverless applications (for example, Amazon API Gateway, Lambda, AWS Fargate)
20
Disaster recovery concepts (for example, RTO, RPO)
21
Backup and recovery strategies (for example, pilot light, warm standby)
22
Recovery procedures
23
Testing failover of Multi-AZ and multi-Region workloads (for example, Amazon RDS, Amazon Aurora, Route 53, CloudFront)
24
Identifying and implementing appropriate cross-Region backup and recovery strategies (for example, AWS Backup, Amazon S3, Systems Manager)
25
Configuring a load balancer to recover from backend failure
1
How to monitor applications and infrastructure
2
Amazon CloudWatch metrics (for example, namespaces, metrics, dimensions, and resolution)
3
Real-time log ingestion
4
Encryption options for at-rest and in-transit logs and metrics (for example, client-side and server-side, AWS Key Management Service [AWS KMS])
5
Security configurations (for example, IAM roles and permissions to allow for log collection)
6
Securely storing and managing logs
7
Creating CloudWatch metrics from log events by using metric filters
8
Creating CloudWatch metric streams (for example, Amazon S3 or Amazon Kinesis Data Firehose options)
9
Collecting custom metrics (for example, using the CloudWatch agent)
10
Managing log storage lifecycles (for example, S3 lifecycles, CloudWatch log group retention)
11
Processing log data by using CloudWatch log subscriptions (for example, Kinesis, Lambda, Amazon OpenSearch Service)
12
Searching log data by using filter and pattern syntax or CloudWatch Logs Insights
13
Configuring encryption of log data (for example, AWS KMS)
14
Anomaly detection alarms (for example, CloudWatch anomaly detection)
15
Common CloudWatch metrics and logs (for example, CPU utilization with Amazon EC2, queue length with Amazon RDS, 5xx errors with an
16
Application Load Balancer [ALB])
17
Amazon Inspector and common assessment templates
18
AWS Config rules
19
AWS CloudTrail log events
20
Building CloudWatch dashboards and Amazon QuickSight visualizations
21
Associating CloudWatch alarms with CloudWatch metrics (standard and custom)
22
Configuring AWS X-Ray for different services (for example, containers, API Gateway, Lambda)
23
Analyzing real-time log streams (for example, using Kinesis Data Streams)
24
Analyzing logs with AWS services (for example, Amazon Athena, CloudWatch Logs Insights)
25
Event-driven, asynchronous design patterns (for example, S3 Event Notifications or Amazon EventBridge events to Amazon Simple Notification Service [Amazon SNS] or Lambda)
26
Capabilities 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)
27
Alert notification and action capabilities (for example, CloudWatch alarms to Amazon SNS, Lambda, EC2 automatic recovery)
28
Health check capabilities in AWS services (for example, ALB target groups, Route 53)
29
Configuring solutions for auto scaling (for example, DynamoDB, EC2 Auto Scaling groups, RDS storage auto scaling, ECS capacity provider)
30
Creating CloudWatch custom metrics and metric filters, alarms, and notifications (for example, Amazon SNS, Lambda)
31
Configuring S3 events to process log files (for example, by using Lambda) and deliver log files to another destination (for example, OpenSearch Service, CloudWatch Logs)
32
Configuring EventBridge to send notifications based on a particular event pattern
33
Installing and configuring agents on EC2 instances (for example, AWS Systems Manager Agent [SSM Agent], CloudWatch agent)
34
Configuring AWS Config rules to remediate issues
35
Configuring health checks (for example, Route 53, ALB)
1
AWS services that generate, capture, and process events (for example, AWS Health, EventBridge, CloudTrail)
2
Event-driven architectures (for example, fan out, event streaming, queuing)
3
Integrating AWS event sources (for example, AWS Health, EventBridge, CloudTrail)
4
Building event processing workflows (for example, Amazon Simple Queue Service [Amazon SQS], Kinesis, Amazon SNS, Lambda, Step Functions)
5
Fleet management services (for example, Systems Manager, AWS Auto Scaling)
6
Configuration management services (for example, AWS Config)
7
Applying configuration changes to systems
8
Modifying infrastructure configurations in response to events
9
Remediating a non-desired system state
10
AWS metrics and logging services (for example, CloudWatch, X-Ray)
11
AWS service health services (for example, AWS Health, CloudWatch, Systems Manager OpsCenter)
12
Root cause analysis
13
Analyzing failed deployments (for example, AWS CodePipeline, CodeBuild, CodeDeploy, CloudFormation, CloudWatch synthetic monitoring)
14
Analyzing incidents regarding failed processes (for example, auto scaling, Amazon ECS, Amazon EKS)
1
Appropriate usage of different IAM entities for human and machine access (for example, users, groups, roles, identity providers, identity-based policies, resource-based policies, session policies)
2
Identity federation techniques (for example, using IAM identity providers and AWS IAM Identity Center)
3
Permission management delegation by using IAM permissions boundaries
4
Organizational SCPs
5
Designing policies to enforce least privilege access
6
Implementing role-based and attribute-based access control patterns
7
Automating credential rotation for machine identities (for example, Secrets Manager)
8
Managing permissions to control access to human and machine identities (for example, enabling multi-factor authentication [MFA], AWS Security Token Service [AWS STS], IAM profiles)
9
Network security components (for example, security groups, network ACLs, routing, AWS Network Firewall, AWS WAF, AWS Shield)
10
Certificates and public key infrastructure (PKI)
11
Data management (for example, data classification, encryption, key management, access controls)
12
Automating the application of security controls in multi-account and multi-Region environments (for example, Security Hub, Organizations, AWS Control Tower, Systems Manager)
13
Combining security controls to apply defence 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)
14
Automating the discovery of sensitive data at scale (for example, Amazon Macie)
15
Encrypting data in transit and data at rest (for example, AWS KMS, AWS CloudHSM, ACM)
16
Security auditing services and features (for example, CloudTrail, AWS Config, VPC Flow Logs, CloudFormation drift detection)
17
AWS services for identifying security vulnerabilities and events (for example, GuardDuty, Amazon Inspector, IAM Access Analyzer, AWS Config)
18
Common cloud security threats (for example, insecure web traffic, exposed AWS access keys, S3 buckets with public access enabled or encryption disabled)
19
Implementing robust security auditing
20
Configuring alerting based on unexpected or anomalous security events
21
Configuring service and application logging (for example, CloudTrail, CloudWatch Logs)
22
Analyzing logs, metrics, and security findings
Meet your Trainer
Our Trainer
Learners Point has a reputation for high-quality training that makes a difference in people's lives. We undertake a practical and innovative approach to working closely with businesses to improve their workforce. Our expertise is wide-ranging with ample support from our expert trainers who are globally recognized and hold a diverse set of experiences in their field of expertise. We are proud of our instructors who take ownership of our distinctive and comprehensive training methodologies, help our students imbibe those with ease, and accomplish gracefully.
We at Learners Point believe in encouraging our students to embark upon a journey of lifelong learning and self-development, with the aid of our comprehensive and distinctive courses tailored to current market trends. The manifestation of our career-oriented approach is what we assure through a pleasant professional enriched environment with cutting-edge technology, and an outstanding while highly acknowledged training staff that uses up-to-date methodologies and quality course material. With our aim to mold professionals to be future leaders, our industry expert trainers provide the best in town mentorship to our students while endowing them with the thirst for knowledge and inspiring them to strive for professional and human excellence.
Learning Outcomes
Once you complete the training, you will be able to:
1
Streamline CI/CD workflows using AWS CodePipeline, CodeBuild, and CodeDeploy for efficient releases
2
Build skills in managing containers with Amazon ECS and EKS for scalable deployment
3
Deploy Infrastructure as Code (IaC) using tools like AWS CloudFormation, SAM, and CDK
4
Obtain practical knowledge in monitoring and logging automation with CloudWatch and AWS X-Ray
5
Craft automated recovery strategies for multi-region and multi-AZ workloads using AWS services
6
Establish secure AWS architectures with IAM, encryption practices, and compliance tools like Security Hub
Learners Point Certificate
Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.
Prerequisites
To apply for the AWS Certified DevOps Engineer – Professional Course in Rwanda, candidates should have the following skills:
- 2+ years of experience in provisioning, operating, and managing AWS environments
- Knowledge of coding in at least one high-level programming language
- Skills in creating highly automated systems
- Understanding of modern development methods and operational processes
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Frequently asked questions
The AWS Certified DevOps Engineer- Professional Certification in Rwanda is designed for professionals to teach them crucial skills like automating deployments, managing infrastructure, and applying DevOps practices on AWS. This certification can boost their career growth and unlock new opportunities for high-paying roles.
DevOps roles are suitable for system admins, QA testers, IT professionals, and even project managers who know collaboration, automation, and delivery pipelines. So it can be said that it is not only for software developers.
AWS Certified DevOps Engineer credential improves your credibility, opens up new opportunities, and showcases your expertise in managing automation and deployment on AWS. Employers look for those professionals who have AWS certification with the required skill set.
Here is the following set of skills you will learn during this course:
- Automating CI/CD pipelines
- Managing infrastructure as code
- Monitoring and logging systems
- Handling containerized deployments
- Implementing security and compliance on AWS
To enrol in the AWS Certified DevOps Engineer Professional Training in Oman, interested professionals will need to fulfil the eligibility criteria, which include:
- More than two years of experience in AWS environment management
- Proficiency in at least one high-level programming language
- Skilled in developing highly automated systems
- Familiar with current development methodologies and operational procedures
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