DevOps Life Cycle Approach and Tools

Please refer the diagram below for DevOps Life Cycle stages and tools probably be used. This may not be exhaustive list of tools, but covered important ones. Tools are mixture of open source as well vendor provided

1. Continuous Integration, Continuous Delivery/Deployment (CI/CD) Framework:

This controls all the stages in DevOps life cycle by integrating various tools, services and orchestrate them to automate the entire process.

2. Application Life Cycle Management (ALM) & Development:

  • Planning, Execution, Issue Tracking – Feature, Story and Backlogs creations and documentation of the products or projects.Also tracking issuesfrom development as well as rollouts.
  • Development – Feature development and implementation.
  • Version control, source code management.

3. Build & Package:

  • Build process can run in multiple times and package creation can happen at logical stage.
  • Collect all code and related objects, compile and resolve the dependencies. Build executable binary code.
  • Execute unit tests.
  • If the build and unit tests are successful, create packages out of build process with proper versioning and tagline for ease of management. This will help promote or rollback the environment.

4. Test Coverage:

  • Test all the source code, objects and packages before releasing to various environment.
  • Create test cases to automate and perform continuous testing.
  • Create test data and measure data efficiency.
  • Generate test report automatically.

5. Configuration & Provisioning:

  • Handles release planning, scheduling and controlling the software builds and packages across environments.
  • Handles creating servers and infrastructure, configurations of the same and managing.

6. Monitoring & Logging:

  • Monitor deployed applications, infrastructure, services etc. for performance,anomalies etc.
  • Capture and also log all the required metrics and report for easy analysis and dashboard

More Blogs

Demystifying Vector Databases: Unleashing the Power of High-Dimensional Data

A vector data store is a specialized database designed to store high-dimensional embedding representations of diverse data types, including audio, video, images, text, and more. One of its core functionalities is the ability to efficiently search for vectors within the store that closely resemble a given query vector.
Vector stores streamline the process of storing embeddings and conducting similarity searches among these vectors, simplifying the management and retrieval of high-dimensional data representations.

Read more

Enhancing Customer Experience with GenAI Applications

In this blog, we will explore the creation of GenAI applications that significantly enhance the customer experience by leveraging OpenAI’s Large Language Models (LLMs) through their APIs, as well as key AWS services like Amazon Kendra, AWS Transcribe, and AWS Polly. Additionally, we’ll discuss the pivotal role of AWS S3 and In-Memory Cache for storing indexed data, chat history, and serving the GenAI application’s various functions

Read more

Evolution of Application Integration and API First Approach

Over time, the landscape of application integration has undergone significant changes. We’ve moved from integration within Mainframes to traditional file-based communication to more advanced methods.

In the ever-evolving digital landscape, APIs (Application Programming Interfaces) have become a crucial component in various domains, including e-commerce, banking, social platforms, and enterprise applications, enabling seamless communication between software components and services.

Read more
Contact us

Partner with us for Comprehensive IT

We’re happy to answer any questions you may have and help you determine which of our services best fit your needs.

Your benefits:
What happens next?

We Schedule a call at your convenience 


We do a discovery and consulting meeting 


We prepare a proposal 

Schedule Consultation