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**Amazon Web Services (AWS)** is a secure cloud services platform, offering compute power, database storage, content delivery and other functionality to help businesses scale and grow.

In simple words AWS allows you to do the following things-

1.  Running web and application servers in the cloud to host dynamic websites.

2.  Securely store all your files on the cloud so you can access them from anywhere.

3.  Using managed databases like MySQL, PostgreSQL, Oracle or SQL Server to store information.

4.  Deliver static and dynamic files quickly around the world using a Content Delivery Network (CDN).

5.  Send bulk email to your customers.

Now that you know what you can do with AWS, lets have an overview of various AWS service

# Basic Terminologies

1.  **Region** — A region is a **geographical area**. Each region consists of 2 (or more) availability zones.

2.  **Availability Zone** — It is simply a **data center**.

3.  \*\*Edge Location \*\*— They are **CDN** (Content Delivery Network) **endpoints** for CloudFront.

# Compute

1.  \*\*EC2 (Elastic Compute Cloud) — \*\*These are just the **virtual machines** in the cloud on which you have the OS level control. You can run whatever you want in them.

2.  \*\*LightSail — \*\*If you don’t have any prior experience with AWS this is for you. It **automatically deploys** and manages compute, storage and networking capabilities required to run your applications.

3.  \*\*ECS (Elastic Container Service) — \*\*It is a highly scalable **container service** to allows you to run Docker containers in the cloud.

4.  \*\*EKS (Elastic Container Service for Kubernetes) — \*\*Allows you to use **Kubernetes on AWS** without installing and managing your own Kubernetes control plane. It is a relatively new service.

5.  \*\*Lambda — \*\*AWS’s serverless technology that allows you to run **functions in the cloud**. It’s a huge cost saver as you pay only when your functions execute.

6.  \*\*Batch — \*\*It enables you to easily and efficiently run **batch computing** workloads of any scale on AWS using Amazon EC2 and EC2 spot fleet.

7.  \*\*Elastic Beanstalk — \*\*Allows **automated deployment and provisioning** of resources like a highly scalable production website.

# Storage

1.  \*\*S3 (Simple Storage Service) — \*\*Storage service of AWS in which we can store objects like files, folders, images, documents, songs, etc. It cannot be used to install software, games or Operating System.

2.  \*\*EFS (Elastic File System) — \*\*Provides **file storage** for use with your EC2 instances. It uses NFSv4 protocol and can beused concurrently by thousands of instances.

3.  \*\*Glacier — \*\*It is an extremely low-cost **archival service** to store files for a long time like a few years or even decades.

4.  \*\*Storage Gateway — \*\*It is a virtual machine that you install on your on-premise servers. Your on-premise data can be backed up to AWS providing more durability.

# Databases

1.  \*\*RDS (Relational Database Service) — \*\*Allows you to run **relational databases** like MySQL, MariaDB, PostgreSQL, Oracle or SQL Server. These databases are fully managed by AWS like installing antivirus and patches.

2.  **DynamoDB — It is a highly scalable, high-performance NoSQL database**. It provides single-digit millisecond latency at any scale.

3.  \*\*Elasticache — \*\*It is a way of **caching data** inside the cloud. It can be used to take load off of your database by caching most frequent queries.

4.  \*\*Neptune — \*\*It has been launched recently. It is a fast, reliable and scalable **graph database** service.

5.  \*\*RedShift — \*\*It is AWS’s \*\*data warehousing \*\*solution that can be used to run complex OLAP queries.

# **Migration**

1.  \*\*DMS (Database Migration Service) — \*\*It can be used to **migrate on-site databases** to AWS. It also allows you to migrate from one type of database to another. Eg -from Oracle to MySQL.

2.  **SMS (Server Migration Service)** — It allows you to migrate on-site servers to AWS easily and quickly.

3.  **Snowball** — It is a briefcase sized appliance that can be used to send terabytes of data inside and outside of AWS.

# Networking & Content Delivery

1.  \*\*VPC (Virtual Private Cloud) — \*\*It is simply a data center in the cloud in which you deploy all your resources. It allows you to **better isolate your resources** and secure them.

2.  **CloudFront** -It is AWS’s **Content Delivery Network** (CDN) that consists of Edge locations that cache resources.

3.  **Route53** — It is AWS’s highly available **DNS** (Domain Name System) service. You can register domain names through it.

4.  **Direct Connect** — Using it you can connect your data center to an Availability zone using a high speed dedicated line.

5.  **API Gateway** — Allows you to create, store and manage APIs at scale.

# Developer Tools

1.  **CodeStar** — It is a cloud-based service for creating, managing, and working with software development projects on AWS. You can quickly develop, build, and deploy applications on AWS with an AWS CodeStar project.

2.  **CodeCommit** — It is AWS’s **version control service** that allows you to store your code and other assets privately in the cloud.

3.  **CodeBuild** — It automates the process of **building (compiling)** your code.

4.  **CodeDeploy** — It is a way of **deploying your code** in EC2 instances automatically.

5.  **CodePipeline** — Allows you to keep track of different steps in your deployment like **building, testing, authentication,** and deployment on development and production environments.

6.  **Cloud9** —It is an **IDE** (Integrated Development Environment) for writing, running, and debugging code in the cloud.

7.  **X-Ray** — It makes it easy for developers to **analyze the behavior** of their distributed applications by providing request tracing, exception collection, and profiling capabilities.

#

![](/images/1\_1S-Iwvkh_TRNuMHjDgavBw.png)

Management Tools

1.  **CloudWatch** — It can be used to **monitor AWS environments** like CPU utilization of EC2 and RDS instances and trigger alarms based on different metrics.

2.  **CloudFormation** — It is a way of **turning infrastructure into the cloud**. You can use templates to provision a whole production environment in minutes.

3.  **CloudTrail** — A way of **auditing AWS resources**. It logs all changes and API calls made to AWS.

4.  **OpsWorks** — It helps in automating **Chef deployments** on AWS.

5.  **Config** — It monitors your environment and notifies you when you break certain **configurations**.

6.  \*\*Service Catalog \*\*— For larger enterprises, helps to authorize which services will be used and which won’t be.

7.  **Trusted Advisor** — Gives you recommendations on how to do cost optimizations, and secure your environment.

8.  **AWS Auto Scaling** — Allows you to **automatically scale** your resources up and down based on CloudWatch metrics.

9.  \*\*Systems Manager \*\*— Allows you to **group your resources**, so you can quickly gain insights, identify issues and act on them.

10. **Managed Services**—It provides ongoing management of your AWS infrastructure so you can focus on your applications.

# Analytics

1.  **Athena** — Allows you to run\*\* SQL queries on your S3 bucket\*\* to find files.

2.  \*\*EMR (Elastic Map Reduce) \*\*— It is used for **big data processing** like Hadoop, Apache Spark, and Splunk, etc.

3.  **CloudSearch** — It can be used to create a fully managed **search engine** for your website.

4.  **ElasticSearch** — It is similar to CloudSearch but gives you more features like application monitoring.

5.  **Kinesis** — A way of streaming and **analyzing real-time** data at massive scale. It can store TBs of data per hour.

6.  **Data Pipeline** — Allows you to **move data** from one place to another. Eg: from S3 to DynamoDB or vice versa.

7.  **QuickSight** —A business analytics tool that allows you to **create visualizations** in a rich dashboard for data in AWS. Eg: for S3, DynamoDB, etc.

8.  **Glue** — It is a fully managed **ETL (extract, transform, and load) service** that makes it simple and cost-effective to categorize your data, clean it, enrich it, and move it reliably between various data stores.

# Security, Identity, and Compliance

1.  **IAM (Identity and Access Management)** — Allows you to manage users, assign policies, create groups to manage multiple users.

2.  **Inspector** — It is an agent that you install on our virtual machines, which then **reports any security vulnerabilities**.

3.  **Certificate Manager** — It gives free **SSL certificates** for your domains that are managed by Route53.

4.  **Directory Service** — A way of using your **company’s account to log in** to AWS.

5.  **WAF (Web Application Firewall)** — Gives you \*\*application-level protection \*\*and blocks SQL injection and cross-site scripting attacks.

6.  **CloudHSM** — It helps you meet corporate, contractual, and regulatory compliance requirements for data security by using **dedicated Hardware Security Module** (HSM) appliances within the AWS Cloud.

7.  \*\*Cloud Directory \*\*— It enables you to build flexible, cloud-native directories for **organizing hierarchies of data** along multiple dimensions.

8.  **KMS (Key Management Service)** — It is a managed service that makes it easy for you to create and control the **encryption keys** used to encrypt your data.

9.  **Organizations** — It allows you to **create groups of AWS accounts** that you can use to more easily manage security and automation settings.

10. **Shield** — A managed\*\* DDoS (Distributed Denial of Service) protection\*\* service that safeguards web applications running on AWS.

11. **Artifact** — It is the place where you can get all your **compliance certifications**.

12. **Macie** — A data visibility security service that helps classify and **protect** your sensitive and **business-critical content**.

13. **GuardDuty** —Provides **intelligent threat detection** to protect your AWS accounts and workloads

# Application Services

1.  **Step Functions** — A way of visualizing what’s going inside your application and what different microservices it is using.

2.  **SWF (Simple Workflow Service)** — A way of coordinating both automated tasks and human-led tasks.

3.  **SNS (Simple Notification Service)** — Can be used to send you notifications in the form of email and SMS regarding your AWS services. It is a push-based service.

4.  **SQS (Simple Queue Service)** — The first service offered by AWS. It can be used to **decouple your applications**. It is a pull-based service.

5.  **Elastic Transcoder** — Changes a video’s format and resolution to support different devices like tablets, smartphones, and laptops of different resolutions.

# Mobile Services

1.  \*\*Mobile Hub \*\*— Allows you to add, configure and design features for mobile apps. It is a **console for mobile app development**.

2.  **Cognito** — Allows your users to **signup using social** identity providers.

3.  **Device Farm** — Enables you to improve quality of apps by quickly **testing** on hundreds of mobile devices.

4.  **AWS AppSync** —It is an enterprise level, fully managed \*\*GraphQL service \*\*with real-time data synchronization and offline programming features.

5.  **Mobile Analytics** — Allows to simply and cost effectively analyze mobile data.

# Business Productivity

1.  **Alexa for Business** — It lets you empower your organization with voice, using Alexa. Allows you to\*\* build custom voice skills \*\*for your organization.

2.  **Chime** — Can be used for online meeting and video conferencing.

3.  **WorkDocs** — Helps to store documents in the cloud

4.  **WorkMail** — Allows you to send and receive business emails.

# Desktop & App Streaming

1.  **WorkSpaces** — It is a **VDI** (Virtual Desktop Infrastructure). Allows you to use remote desktops in the cloud

2.  **AppStream 2.0 — A way of streaming desktop applications** to your users in the web browser. Eg: Using MS Word in Google Chrome.

# Artificial Intelligence

1.  **Lex** — Allows you to quickly build **chatbots.**

2.  **Polly** — AWS’s **text-to-speech** service. You can create audio versions of your notes using it.

3.  **Machine learning** — You just have to give your dataset and target variable and AWS will take care of training your model.

4.  **Rekognition** — AWS’s **face recognition** service. Allows you to recognize faces and object in images and videos.

5.  **SageMaker** — Helps you to build, train and deploy machine learning models at any scale.

6.  **Comprehend** — It is a **Natural Language Processing** (NLP) service that uses machine learning to find insights and relationships in text. It can be used for sentiment analysis.

7.  **Transcribe** — It is the opposite of Polly. It is AWS’s **speech-to-text** service that provides that provides high-quality and affordable transcriptions.

8.  **Translate** — It is **like Google Translate** and allows you to translate text in one language to another.

# AR & VR (Augmented Reality & Virtual Reality)

1.  **Sumerian** — It is a set of tools for creating high-quality virtual reality (VR) experiences on the web. You can quickly create interactive 3D scenes and publish it as a website for users to access.

# Customer Engagement

1.  **Amazon Connect** — Allows you to create a **customer care center** in the cloud.

2.  **Pinpoint** — It is **like Google analytics** for mobile applications. It helps you to understand users and engage with them.

3.  **SES (Simple Email Service)** — Allows you to **send bulk emails** to your customers at an extremely low price.

# Game Development

1.  **GameLift** — It is a service managed by AWS that can used to **host dedicated game servers**. It seamlessly scales without taking your game offline.

# Internet of Things

1.  **IoT Core**— It is a managed cloud platform that lets connected devices — cars, light bulbs, sensor grids, and more — easily and securely interact with cloud applications and other devices.

2.  \*\*IoT Device Management \*\*— Allows you to manage your IoT devices at any scale.

3.  **IoT Analytics** — Can be used to perform analysis on data collected by your IoT devices.

4.  **Greengrass** — Lets your IoT devices to process the locally generated data while advantage of AWS services.

5.  **Amazon FreeRTOS** — It is a real-time operating system for microcontrollers that makes it easy to securely connect IoT devices locally or to the cloud.

Now, that was a whole lot to cover but if you read it, Kudos!

Having an overview of these services helps you to understand the power of cloud computing.

Kubernetes brings significant agility, automation and optimization to the DevOps environment. It will be a catalyst for DevOps to break existing silos and evolve as a strategic function enabling business outcomes.


Whether you are looking to learn about AWS for your career or for your interest, I believe you will find this article helpful.

Let’s get Started!

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Will DevOps survive in a Kubernetes world? The short answer is, no. But don’t sound the death knell for DevOps just yet.

Kubernetes (K8s) is the [core engine of a containerized platform as a service](https://kubernetes.io/) (PaaS). When enterprises use PaaS, they offload the operations (ops) functions to a PaaS provider as a way of automating repetitive tasks. Kubernetes introduces greater flexibility and automation. However, optimization of K8s requires declaration and configuration effort.

Where, then, does that leave DevOps as we know it?


![](https://preview--next-js-9111b.stackbit.dev/\_static/app-assets/images/Why_DevOps_and_Kubernetes_Are\_-a_Perfect_Match.png)


## Kubernetes Adoption

All enterprises today are embracing digital transformation for continued growth and to gain a competitive edge. Cloud-native technologies such as Kubernetes, provide the automation, visibility and control necessary to manage applications at scale and high innovation velocity.

Kubernetes provides [constructs and capabilities](https://containerjournal.com/topics/container-ecosystems/kubernetes-changing-the-game-for-enterprise-containerization/) in which operational functions such as managing, monitoring, updating and upgrading a cluster; scaling pods in or out; and managing resource handling are now done through code.

Kubernetes allows users to configure their desired state for a deployment. Kubernetes controllers continuously check the state of a deployment and attempt to get it from the current state to the desired state. Tasks such as rollouts and rollbacks, scale up and scale down, etc., are now automated. Resource limits and conditions can be specified. Further, taints and tolerations optimize deployment at runtime.

Technologies such as Istio integrate with Kubernetes to further streamline and automate complex operational tasks such as discovery, traffic management, monitoring and service rollout.

Traditionally, DevOps was the “glue” that bound application development and IT infrastructure. Using Kubernetes, an enterprise now can use declarative API actions to have complete control over the application’s development infrastructure. So, is Kubernetes the “new infrastructure glue,” and if yes, does that make DevOps redundant?

Not quite.

## Evolution of DevOps

DevOps is no longer just about continuous integration and continuous delivery (CI/CD). Kubernetes-based cloud-native application deployments offer tremendous opportunities for the role of DevOps to evolve and expand. The opportunity is to evolve from simply “the people who keep the lights on” to architects, enabling strategic business outcomes.

To a casual observer, it may appear that operational tasks are minimized by the Kubernetes-led automation in the deployment pipeline, and during the deployment and operations processes. A deeper look unveils why that’s not so. While applications can be flexibly deployed using a Kubernetes configuration, understanding replicas, scale, taints and tolerations are not top of mind for many developers.

“Good” configurations require a balance of key vectors such as faster deployment time, optimal resource usage, greater reliability and quick failure resolution, which are the catalysts for the DevOps evolution.

In addition, the role of DevOps will also expand to include complex cross-functional collaboration with teams such as ones tasked with security to help provide better security in Kubernetes environments.

## DevOps’ Transition to DevSecOps

Security cannot be a silo within a Kubernetes environment. In fact, more emphasis these days is being placed on DevOps and security. Security practices are becoming more of a part of the software development life cycle. DevSecOps breaks the traditional silo between the Security and DevOps teams. In a Kubernetes environment, DevSecOps will now certify configurations, ensure security and enable compliance ahead of operational deployment. In other words, “Certify the factory instead of every component built by the factory.”

For instance, this may include vulnerability assessment of images as soon as they are built, ensuring only attested images are deployed, automated checks of deployment manifests—i.e. infrastructure-as-code (IaC) templates against known bad configuration as soon as code is checked in—all well before a container image is deployed

Enterprises must address the following five use cases to enable comprehensive security for cloud-native applications running in Kubernetes environments:

1.  **Rich Discovery and Risk-Based Classification**: This is the ability to discover all services and help prioritize and classify to enable organizations to be more risk-aware. This is critical as there are a high number of resources, many of which are ephemeral.

2.  **Protect Against Configuration Drift and Open Source Software Vulnerabilities**: This is the ability to detect all vulnerabilities in components of the container ecosystem including the container images, registries and the K8s control pane itself. This is also about the ability to manage the security posture of K8s control plane and the running containers clusters.

3.  **Minimize Attack Surface and Prevent Escalations**: This is the ability to perform application or service-based segmentation in an environment based on resource usage. This creates a security zone at a container level, permissions for which are based on learned behavior.

4.  **Extend Security Operations Center (SOC) to Cloud-Native Applications**: This is the ability to drive the detection and remediation of cloud-native threats.

5.  **Access Governance and Compliance**: This is the ability to manage identity and access for all users and application components to create and manage a model of least privilege

Besides the above use cases, the system allows for constant monitoring and fast feedback. This enables the promise of DevSecOps to deliver secure code faster.

## In Summary

Kubernetes brings significant agility, automation and optimization to the DevOps environment. It will be a catalyst for DevOps to break existing silos and evolve as a strategic function enabling business outcomes.

![](/images/Why_DevOps_and_Kubernetes_Are\_-a_Perfect_Match.png)


Containers Containers Containers

Will DevOps survive in a Kubernetes world? 




Docker helps developers build lightweight and portable software containers that simplify application development, testing, and deployment.

What is Docker? The spark for the container revolution

Docker is a software platform for building applications based on containers—small and lightweight execution environments that make shared use of the operating system kernel but otherwise run in isolation from one another. While containers have been used in Linux and Unix systems for some time, Docker, an open source project launched in 2013, helped popularize the technology by making it easier than ever for developers to package their software to “build once and run anywhere.”

A brief history of Docker

Founded as DotCloud in 2008 by Solomon Hykes in Paris, what we now know as Docker started out as a platform as a service (PaaS) before pivoting in 2013 to focus on democratizing the underlying software containers its platform was running on.

Hykes first demoed Docker at PyCon in March 2013, where he explained that Docker was created because developers kept asking for the underlying technology powering the DotCloud platform. “We did always think it would be cool to be able to say, ‘Yes, here is our low-level piece. Now you can do Linux containers with us and go do whatever you want, go build your platform.’ So that’s what we are doing.”

And so Docker was born, with the open source project quickly picking up traction with developers and attracting the attention of high-profile technology providers like Microsoft, IBM, and Red Hat, as well as venture capitalists willing to pump millions of dollars into the innovative startup. The container revolution had begun.

What are containers?

As Hykes described it in his PyCon talk, containers are “self-contained units of software you can deliver from a server over there to a server over there, from your laptop to EC2 to a bare-metal giant server, and it will run in the same way because it is isolated at the process level and has its own file system.”

By simplifying this process, Docker quickly became close to a de facto industry standard for containers. Docker let developers deploy, replicate, move, and back up a workload in one streamlined way, using a set of reusable images to make workloads more portable and flexible than previous methods allowed.

In the virtual machine (VM) world, this could be done by keeping applications separate while running on the same hardware, but in that world each VM requires its own operating system, meaning they are typically large, slow to start up, difficult to move around, and cumbersome to maintain and upgrade. Where containers marked a defined shift from the VM era was by isolating execution environments while sharing the underlying OS kernel, providing a lightweight and speedy option for developers.

Docker

How the virtualization and container infrastructure stacks stack up. 

Docker: the component parts

Docker took off with software developers because it found a novel way to package the tools required to build and launch a container in a more streamlined and simplified way than was previously possible. Broken down into its component parts, Docker comprises Dockerfile, container images, the Docker run utility, Docker Hub, Docker Engine, Docker Compose, and Docker Desktop.

Dockerfile. Each Docker container starts with a Dockerfile. This text file provides a set of instructions to build a Docker image, including the operating system, languages, environmental variables, file locations, network ports, and any other components it needs to run.

Docker image. Similar to a snapshot in the VM world, a Docker image is a portable, read-only, executable file containing the instructions for creating a container and the specifications for which software components the container will run and how.

Docker run utility. Docker’s run utility is the command that launches a container. Each container is an instance of an image, and multiple instances of the same image can be run simultaneously.

Docker Hub. Docker Hub is a repository where container images can be stored, shared, and managed. Think of it as Docker’s own version of GitHub, but specifically for containers.

Docker Engine. Docker Engine is the core of Docker. It is the underlying client-server technology that creates and runs the containers. The Docker Engine includes a long-running daemon process called dockerd for managing containers, APIs that allow programs to communicate with the Docker daemon, and a command-line interface.

Docker Compose. Docker Compose is a command-line tool that uses YAML files to define and run multicontainer Docker applications. It allows you to create, start, stop, and rebuild all the services from your configuration and view the status and log output of all running services.

Docker Desktop. All of these component parts are wrapped in Docker’s Desktop application, providing a user-friendly way to build and share containerized applications and microservices.

Docker advantages

Docker containers provide a way to build applications that are easier to assemble, maintain, and move around than previous methods allowed. That provides several advantages to software developers.

Docker containers are minimalistic and enable portability. Docker lets applications and their environments be kept clean and minimal by isolating them, which allows for more granular control and greater portability.

Docker containers enable composability. Containers make it easier for developers to compose the building blocks of an application into a modular unit with easily interchangeable parts, which can speed up development cycles, feature releases, and bug fixes.

Docker containers ease orchestration and scaling. Because containers are lightweight, developers can launch lots of them for better scaling of services. These clusters of containers do then need to be orchestrated, which is where Kubernetes typically comes in.

Docker drawbacks

Containers solve a great many problems, but they don’t solve all developer ills.

Docker containers are not virtual machines. Unlike virtual machines, containers use controlled portions of the host operating system’s resources, which means elements aren’t as strictly isolated as they would be on a VM.

Docker containers don’t provide bare-metal speed. Containers are significantly more lightweight and closer to the metal than virtual machines, but they do incur some performance overhead. If your workload requires bare-metal speed, a container will get you close but not all the way there.

Docker containers are stateless and immutable. Containers boot and run from an image that describes their contents. That image is immutable by default—once created, it doesn’t change. But a container instance is transient. When it is removed from system memory it’s gone forever. If you want your containers to persist state across sessions, like a virtual machine, you need to design for that persistence.

What is Docker today?

Container usage continues to grow as cloud-native development techniques become the mainstream model for building and running software, but Docker is now only a part of that puzzle.

Docker became mainstream by making it easy to move the code for an application and all of its dependencies from the developer’s laptop to a server. But the rise of containers led to a shift in the way applications are built—from monolithic stacks to networks of microservices. Soon many users needed a way to orchestrate and manage groups of containers at scale.

Born out of Google, the Kubernetes open source project quickly emerged as the best way to do this, superseding Docker’s own attempts to solve this problem with its Swarm orchestrator (RIP). Amidst increasing funding trouble, Docker eventually sold its enterprise business to Mirantis in 2019, which has since absorbed Docker Enterprise into the Mirantis Kubernetes Engine.

The remains of Docker—which includes the original open source Docker Engine container runtime, Docker Hub image repository, and Docker Desktop application—live on under the leadership of company veteran Scott Johnston, who is looking to reorient the business around its core customer base of software developers.


The spark for the container revolution

What is Docker?

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The world of IT can be scary and intimidating,but it doesn't have to be that way. If you have a grain of faith in YOU and can allocate 3-4 hours per day to study, YOU can achieve in 6 months what others are accomplishing in 4 years of College. Our curriculum is inspired from the real life corporate IT world, combined with all the cool new technologies. We primarily focus on Linux, Ansible, AWS and Kubernetes. But we also cover Docker, Git, Terraform, Python to name a few. After the technical level is achieved we guide our students through the interview process, as getting in the right set of mind is crucial to success

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> *Class starts on:*
>
> *DOCKER*

*   Docker enables you to separate your applications from your infrastructure so you can deliver software quickly.

*   With Docker, you can manage your infrastructure in the same ways you manage your applications.

*   By taking advantage of Docker’s methodologies for shipping, testing, and deploying code quickly.

*   Significantly reduce the delay between writing code and running it in production.

*   Docker works with all development tools you use including VS Code, CircleCI and GitHub. Leveraging Docker images to efficiently develop your own unique applications on Windows and Mac. 


25 October 2021



A fundamental difference between Kubernetes and Docker is that Kubernetes is meant to run across a cluster while Docker runs on a single node. Kubernetes is more extensive than Docker Swarm and is meant to coordinate clusters of nodes at scale in production in an efficient manner.


What is Kubernetes vs Docker?



> *Class starts on:*
>
> **kubernetes**

*   Learn everything *Kubernetes* offers for each particular pattern, with tested conclusions.

*   Get detailed, reusable *Kubernetes* patterns for container deployment and orchestration.


06 NOVEMBER 2021

### Amazon Web Services (AWS)

is a secure  and versatile cloud services platform, offering compute power, database storage, content delivery and other functionality to help businesses scale and grow.


04 DECEMBER 2021

Upcoming DevOps Courses  at Kloudvibe


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