Skip to content
View tallgray's full-sized avatar

Block or report tallgray

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
tallgray/README.md

Hi 👋, I'm Glenn

I am passionate about development platforms

DevOps Model

According to Amazon AWS, "DevOps is the combination of cultural philosophies, practices, and tools that increases an organization’s ability to deliver applications and services at high velocity."

DevOps follows specific practices that include:

  • Continuous Integration
  • Continuous Delivery
  • Microservices
  • Infrastructure as Code
  • Monitoring and Logging
  • Communication and Collaboration

These practices can further be categorized into functions that work to align the practices into a coherent organizational process flow:

  1. Infrastructure automation
  2. Configuration management
  3. Deployment automation
  4. Version control
  5. Performance management
  6. Log management
  7. Monitoring
  8. Security and compliance

Ultimately, the success of the DevOps approach relies upon the importance of automation:

Automation is a fundamental principle in DevOps practices. It starts from code generation on developers' machines and extends to monitoring applications and systems in production. Regardless of unique business operational practices, automation is crucial for achieving speed, consistency, accuracy, reliability, and increased delivery frequency. The actual implementation of DevOps practices relies on the tools used to perform them. These tools align with the function categories, and some can even satisfy multiple categories.

Here are examples of tools that support various DevOps function categories:

  • Infrastructure Automation: Terraform, AWS CloudFormation, Google Cloud Deployment Manager, Azure Resource Manager
  • Configuration Management: Ansible, Chef, Puppet, SaltStack
  • Deployment Automation: Jenkins, CircleCI, GitLab CI/CD, Travis CI
  • Version Control: Git, GitHub, GitLab, Bitbucket
  • Performance Management: New Relic, Dynatrace, AppDynamics, Datadog
  • Log Management: ELK Stack (Elasticsearch, Logstash, Kibana), Splunk, Graylog, Sumo Logic
  • Monitoring: Prometheus, Nagios, Zabbix, Datadog
  • Security and Compliance: SonarQube, OWASP ZAP, Nessus, HashiCorp Vault

It's important to note that there are many tools available in each category, and the choice of tool depends on specific requirements, preferences, and the technology stack being used. Proper implementation of these tools enhances productivity and enables efficient DevOps workflows across large teams and extensive IT infrastructures, leading to the delivery and security of applications and services.

Connect with me:

tallgray tallgray

Languages and Tools:

Ansible Terraform Docker Kubernetes NodeJS Python AWS GitHub Postman

Popular repositories Loading

  1. tallgray tallgray Public

  2. ansible ansible Public

    End-to-end automation to configure systems, deploy software, and orchestrate advanced workflows.

    Dockerfile

  3. terraform terraform Public

    HCL

  4. MeanStack MeanStack Public

    Real-World Case Study: A Practical Blueprint for Streamlined Software Development

    JavaScript

  5. MernStack MernStack Public

    Forked from david4473/MERN_application

    A Practical Blueprint for MongoDB, Express.js, React, and Node.js applications.

    JavaScript

  6. CreateResumeWebsiteInS3WithCloudFormation CreateResumeWebsiteInS3WithCloudFormation Public

    How to create a static RESUME website and deploy it to Amazon S3 using AWS CloudFormation.