DevOps Training
DevelopIntelligence specializes in delivering highly-customized, dedicated, role-based DevOps Training courses to technical teams and organizations.
Instructor-led DevOps Courses
Customized, role-based, expert-led DevOps Training
DevOps is an umbrella term encompassing a variety of interrelated and quickly evolving technologies, as well as a profound culture shift within software companies. DevOps includes a wide variety of tools for configuration management (e.g., Chef, Puppet, and Terraform), containerization (e.g., Docker), cluster management tools (e.g., Kubernetes), continuous integration and deployment (e.g., Jenkins), and virtualization (e.g., VMware).
When they aren’t training for us, our DevOps instructors regularly author technical papers on the evolution of the tools and languages in the field, speak at industry conferences, and contribute to open source projects.
Developer Academy™
For Organizations
Executing a digital transformation or having trouble filling your tech talent pipeline?
Upskilling & Reskilling
For Tech Teams
Need to stay ahead of technology shifts and upskill your current workforce on the latest technologies?
New Hire Development
for Talent Acquisition
Is your engineering new hire experience encouraging retention or attrition?
Learning Strategy
For Tech Learning
Looking for in-the-trenches experiences to level-up your internal learning and development offerings?
Let's Chat
If you are not completely satisfied with your training class, we'll give you your money back.
The Good and Bad on Training Developers
Training Journal sat down with our CEO for his thoughts on what’s working, and what’s not working.
Agile Engineering Fast Track -
Learn how to effectively integrate today’s best software development practices.
Learn about how adopting Agile impacts an organization.
Learn how to effectively estimate for Agile projects.
Learn about an intensive exploration of Agile Testing roles and techniques.
Business Analysis With Agile -
Learn how to effectively capture business requirements for an Agile project.
Learn how to use Agile to develop software.
Certified Agile Practitioner -
Learn the skills to become certified in Agile project management.
Certified Agile Practitioner and Agile Developer Certification -
Learn how to become a Certified Scrum Practitioner and Certified Scrum Developer with hands-on experience.
Certified Agile Product Owner -
Learn how to become a certified and successful Product Owner through in-depth study of Agile, Scrum, and Lean concepts.
Introduction to Agile Development -
Learn about how Agile Development can improve the process of writing software.
Introduction to eXtreme Programming (XP) -
Learn how to successfully implement XP methodology in your organization.
Learn how to use Kanban to enhance and improve your project management.
Introduction to Lean Development -
Learn how to shift to the Lean process.
Introduction to Rational Unified Process -
Learn how the Rational Unified Process can help you be more effective in the development of production-quality software.
Leading the Agile Enterprise with the Scaled Agile Framework™ -
Learn how to use SAFe effectively in an enterprise Agile transformation.
Managing Agile Projects with Scrum and Lean -
Learn about an in-depth exploration of Scrum and Lean through hands-on lab work.
Learn how to enhance Scrum learning with Lean thinking and software engineering practices.
Learn how to train your team to effectively implement Scrum.
Learn how to use Scrum-Kanban tools to improve work flow and agility.
Test-Driven Development (TDD) -
Learn how to define the iterative and quality-focused software development methodology of test-driven development.
Learn how to create user stories as a means of tracking project requirements.
Working With Continuous Integration -
Learn how to adopt a continuous integration mindset to achieve better code quality.
Learn how to effectively create user stories.
Learn how to implement Ansible into your DevOps stack.
Learn a basic understanding of Ansible with hands-on experience to enable its use in managing configuration environments.
Learn to build end-to-end data applications using Microsoft Azure and understand which tools are best suited to certain problems and use-cases.
Learn how to deploy, configure and manage Azure using Chef.
Azure for System Administrators -
Learn how to configure, maintain and monitor Azure Virtual Machines and Virtual Networks.
Learn how to build, deploy, and maintain applications in Azure Cloud.
Learn the philosophy, models, goals, practices and tools being used to move to a DevSecOps culture.
Implementing Microsoft Azure Infrastructure Solutions Certification -
Learn how to pass the "Implementing Microsoft Azure Infrastructure Solutions" certification exam.
Introduction to AI and Machine Learning in Azure -
Learn to implement AI and ML techniques on Azure.
Introduction to Azure for Developers -
Learn how to build, deploy, secure, scale, monitor and maintain applications in Azure Cloud.
Introduction to Azure for Managers -
Learn how to plan and manage cloud team resources more effectively.
Introduction to the Azure Stack and VM Managers -
Learn how to deploy and manage Azure in private data centers.
Microsoft Azure Certification Boot Camp -
Learn the information necessary to pass the Developing Microsoft Azure Solutions Certification Exam.
Working with Big Data on Azure -
Learn how to use Big Data technologies on the Azure cloud.
Learn how to use Chef to automate the configuration, deployment, management and test of server infrastructure.
Learn how to use Chef-specific tools and tactics such as Ohai plugins, Chef handlers, ChefSpec, and Custom Light-Weight Resource Providers (LWRP's).
Introduction to Chef Learning Spike -
Learn how to configure and deploy Chef for server infrastructure.
Learn how to write cookbooks for Chef.
Introduction to ETL Management with Airflow -
Learn how to use Apache Airflow to manage data warehouses.
Learn how to express infrastructure across multiple teams within an enterprise using Terraform.
Working With Continuous Integration -
Learn how to adopt a continuous integration mindset to achieve better code quality.
Learn a comprehensive understanding of Spinnakers features and capabilities in relation to the standard continuous delivery and deployment concepts it supports.
DevOps on Amazon Web Services (AWS) -
Learn the DevOps practice on AWS and a holistic view on DevOps implementation on the cloud platform using tools like Jenkins, Ansible, and Terraform.
Learn the philosophy, models, goals, practices and tools being used to move to a DevSecOps culture.
Learn about the key concepts and components of a DevOps environment.
Learn to publish to Nexus for easier distribution.
Learn how to utilize Docker for distributed apps.
Introduction to Docker Learning Spike -
Learn the basics about systems and application design using Docker.
Introduction to Elasticsearch -
Learn the key concepts required to adopt Elasticsearch.
Learn how to work with ElasticSearch.
Learn how to use the ELK stack.
Learn how to leverage the advanced parts of Git.
Understanding of Git, Github, Gitlab & Bitbucket -
Learn the details and advanced usage of Git and review the Cloud-based tools and repositories.
Learn how Bitbucket can make teams more productive.
Learn how to adopt and use Git to manage your source control.
Learn how to utilize GitLab to manage the software development lifecycle.
Building Chatbots Using Google Dialogflow -
Learn how to build a Chatbot on Google Cloud and deploy it standalone as well as on Facebook Messenger.
Google Cloud for Data Analysts -
Learn how to perform insightful and responsive data analysis at scale and delight the consumers of the analysis with effective data visualizations.
Google Cloud for Data Engineers -
Learn to build systems on Google Cloud to store and process batch or streaming data.
Google Cloud for Data Scientists -
Learn how to create and deploy high-performance data science and machine learning systems on Google Cloud for regression and classification use cases leveraging both structured and unstructured datasets.
Learn to create and deploy software on Google Cloud to have secure and stable applications.
Learn a technical overview of Google Cloud and its capabilities in the areas of Information Technology (IT) infrastructure, operations, Big Data, and Machine Learning.
Intermediate Google Cloud For Data Analysts -
Learn how to analyze large scale, distributed, and real-time datasets with MapReduce and Apache Beam based capabilities of Google Cloud and practice identification and analysis of effective data features for predictive analytics with BigQuery ML and TensorFlow.
Intermediate Google Cloud for Data Engineers -
Learn how to use data engineering on Google Cloud to build specialized data pipelines for large scale streaming data analytics, machine learning, and recommendation systems.
Intermediate Google Cloud For Data Scientists -
Learn how to implement statistical and machine learning models using TensorFlow, for example for recommendation engines, and how to improve their performance based on the students’ understanding of underlying mathematical principles.
Intermediate Google Cloud for Developers -
Learn how to utilize advanced processes and practices for the platform to improve function and security.
Learn to use Google's BigQuery to explore and gain insights from large datasets.
Introduction to Cloud Computing -
Learn about the different cloud providers and what they offer.
Introduction to the Google App Engine -
Learn how to use Java to set up a project with the Google App Engine and integrate it with other Google Cloud services.
Moving to a Hybrid Cloud for Managers Adding Google Cloud -
Learn how to develop a platform-based infrastructure using Google Cloud.
Learn the fundamental skills needed to manage large scale infrastructure with SaltStack on major cloud providers (AWS, Google Cloud and Azure).
Learn how to enable continuous integration in a distributed environment with Jenkins.
Learn how to install, configure, and administer Jenkins.
Working With Continuous Integration -
Learn how to adopt a continuous integration mindset to achieve better code quality.
Learn how to enable continuous integration with Jenkins.
Learn the essentials of Atlassian JIRA.
Learn the essentials of JIRA.
Learn how to create and configure Kubernetes clusters.
Learn the skills required to build, store, and deploy containers using Docker and Kubernetes.
Learn a deeper dive into Kubernetes architecture, concepts, and container management.
Learn about the key operations and configurations utilized when using Kubernetes to automate, deploy, and manage containerized applications.
Learn a comprehensive understanding of Helm and how to use it to package and manage Kubernetes workloads.
Learn how to automate an Information Technology (IT) infrastructure utilizing Puppet.
Learn advanced techniques for managing data and tuning models.
Learn how to become an expert at creating high-throughput, multithreaded, network oriented programs written in Python.
Applied Data Science & Machine Learning -
Learn intermediate data analysis techniques and how programming languages can be used to further analyze data.
Building a Recommendation Engine Using Python -
Learn to design, implement and evaluate various recommendation engines.
Learn how to mature programming knowledge.
Introduction to Data Science & Machine Learning -
Learn how data can be gathered to improve the overall needs of the business.
Introduction to Graphics Processing -
Learn a working knowledge of graphics processing practices within Machine Learning using CUDA, PyCuda, OpenCL, Vulkan, and Tensorflow.
Introduction to Machine Learning -
Learn various Machine Learning algorithms to evaluate and productize models.
Learn how to create basic programs using Python.
Learn how to develop simple programs using fundamental Python concepts.
Learn both R and Python programming languages by providing comparisons and recommendations between both.
Learn the knowledge and use cases for software engineers to transition to Machine Learning for Search.
MongoDB for Python Developers -
Learn how to use MongoDB with Python.
Learn how to use Python to explore and analyze data, run basic regression models, visualize data, and apply some basic machine learning models to data.
Learn how to implement statistical and machine learning models using PyTorch and how to improve their performance based on an understanding of underlying mathematical principles.
Software Engineering in Python -
Learn software engineering techniques using Python.
Learn how to use Splunk
Site Reliability Engineering (SRE) -
Learn to incorporate the principles of SRE into practice.
Introduction to Vagrant Learning Spike -
Learn how to use the essentials of Vagrant.
Learn an in-depth understanding of monitoring via Zabbix.
