AWS Community Builder

I woke up today with fantastic news: AWS Community Builder has been renewed for the second time.

The AWS Community Builders program offers technical resources, education, and networking opportunities to AWS technical enthusiasts and emerging thought leaders passionate about sharing knowledge and connecting with the technical community.

Interested AWS builders should apply to the program to build relationships with AWS product teams, AWS Heroes, and the AWS community.

You can check the program here.



VPC endpoints

A VPC endpoint enables private connections between your VPC and supported AWS services without requiring an internet gateway, NAT device, VPN connection, or Direct Connect connection. Instances in your VPC do not require public IP addresses to communicate with resources in the service. Traffic between your VPC and the other service does not leave the AWS network.

Endpoints are virtual devices. They are horizontally scaled, redundant, and highly available VPC components. They permit communication between instances in your VPC and services without imposing availability risks or bandwidth constraints on your network traffic.

Types of VPC endpoints


Specify a gateway endpoint as a route target in your route table. A gateway endpoint is meant for traffic destined to Amazon S3, or Amazon DynamoDB and remains inside the AWS network.

instance A in the public subnet communicates with Amazon S3 via an internet gateway. Instance A has a route to local destinations in the VPC. Instance B communicates with an Amazon S3 bucket and an Amazon DynamoDB table using unique gateway endpoints. The diagram shows an example of a private route table. The private route table directs your Amazon S3 and DynamoDB requests through each gateway endpoint using routes. The route table uses a prefix list to target the specific Region for each service.


With an interface VPC endpoint (interface endpoint), you can privately connect your VPC to services as if they were in your VPC. When the interface endpoint is created, traffic is directed to the new endpoint without changes to any route tables in your VPC.

For example, a Region is shown with Systems Manager outside of the example VPC. The example VPC has a public and private subnet with an Amazon Elastic Compute Cloud (Amazon EC2) instance in each. Systems Manager traffic sent to is sent to an elastic network interface in the private subnet.

Gateway VPC endpoints and interface VPC endpoints help you access services over the AWS backbone.

gateway VPC endpoint (gateway endpoint) is a gateway that you specify as a target for a route in your route table for traffic destined for a supported AWS service. The following AWS services are supported: Amazon S3 and Amazon DynamoDB.

An interface VPC endpoint (interface endpoint) is an elastic network interface with a private IP address from the IP address range of your subnet. The network interface serves as an entry point for traffic destined to a supported service. AWS PrivateLink powers interface endpoints and it avoids exposing traffic to the public internet.




Monolithic and microservice architectures

To learn the differences between monolithic and microservice architectures, and how to architect for microservices,


Traditional monolithic infrastructures revolve around chains of tightly integrated servers, each with a specific purpose. When one of those components or layers goes down, the disruption to the system can be fatal. This configuration also impedes scaling. If you add or remove servers at one layer, you must also connect every server on each connecting layer.

With loose coupling, you use managed solutions as intermediaries between layers of your system. Failures and scaling of a component are automatically handled by the intermediary. Two primary solutions for decoupling your components are load balancers and message queues.


Microservices are an architectural and organizational approach to software development. Using a microservices approach, you design software as a collection of small services. Each service is deployed independently and communicates over well-defined APIs. This speeds up your deployment cycles, fosters innovation, and improves both maintainability and scalability of your applications.


The component services in a microservices architecture are isolated from one another and communicate through an API. Because of this, you can develop, update, deploy, operate, and scale a service without affecting the other services. These services can be owned by small autonomous teams, allowing for an agile approach.


You design each service for a set of capabilities that focuses on solving a specific problem. Teams can write each service in the programming languages best suited to that service. They can also host their services on different compute resources.

In this example, a monolithic forum application is refactored to use a microservices architecture: a user service, a topic service, and a message service. The /users service team runs the user service on AWS Lambda. The /topics service team runs the topics service on Amazon Elastic Compute Cloud (Amazon EC2). The /messages service team runs the messages service on containers. The microservices application is distributed across two Availability Zones and manages traffic with an Application Load Balancer.

What is a container?

A container is a self-contained environment that includes the all the components needed to run an application. This includes the runtime engine, your application code, dependencies such as libraries, and configuration information. You containers will deploy the same way on any server running Docker which gives your application portability, repeatability and scalability.

We build microservice infrastructures with containers. Although running Virtual Machines (VMs) in the cloud gives you a dynamic, elastic environment, you can simplify your developers’ processes. Containers provide a standard way to package your application’s code, configurations, and dependencies into a single object. 

Containers share an operating system installed on the server and run as resource-isolated processes, ensuring quick, reliable, and consistent deployments, regardless of the environment.

Containers and microservices

Containers are an ideal choice for microservice architectures because they are scalable, portable, and continuously deployable.

Earlier in this module, you learned how microservice architectures decompose traditional, monolithic architectures into independent components that run as services and communicate using lightweight APIs. With these microservice environments, you can iterate quickly, with increased resilience, efficiency, and overall agility. 

You can build each microservice on a container. Because each microservice is a separate component, it can tolerate failure better. If a container fails, it can be shut down and a new one can be started quickly for that particular service. If a certain service has a lot of traffic, you can scale out the containers for that microservice. This eliminates the need to deploy additional servers to support the entire application. Microservices and containers are also great for continuous deployment. You can update individual services without impacting any of the other components of your application.


A bare metal server runs a standalone operating system (OS) with one or many applications by using libraries. Costs remain constant, whether the server is running at 0 percent usage or 100 percent usage. To scale, you must buy and configure additional servers. It is also difficult to build applications that work on multiple servers since the OS on those servers would have to be the same. You also need to synchronize the application library versions.

With virtual machines, you isolate applications and their libraries with their own full OS. The downside of VMs is that the virtualization layer is “heavy.” Each VM has its own OS. This requires more host CPU and RAM, reducing efficiency and performance. Having an individual OS for each VM also means more patching, more updates, and more space on the physical host.

With a containerization platform, containers share a machine’s OS system kernel and the underlying OS file system is exposed. Sharing a machine’s OS system kernel allows shared libraries but can permit individual libraries as needed. This makes containers highly portable. You can also start and stop containers faster than VMs. Containers are lightweight, efficient, and fast.

Unlike a VM, containers can run on any Linux system, with appropriate kernel feature support and the Docker daemon. This makes them portable. Your laptop, your VM, your Amazon EC2 instance, and your bare metal server are all potential hosts. 

The lack of a hypervisor requirement also results in almost no noticeable performance overhead. The processes are communicating directly to the kernel and are largely unaware of their container silo. Most containers boot in only a couple of seconds. 


When running containers on AWS, you have multiple options. 

Running containers on top of an EC2 instance is common practice and uses elements of VM deployments and containerization. This diagram shows the underlying server infrastructure—a physical server, the hypervisor, and two virtual guest operating systems. One of these operating systems runs Docker, and the other runs a separate application. The virtual guest OS with Docker installed can build and run containers. Though possible, this type of deployment can only scale to the size of the EC2 instance used. You also have to actively manage the networking, access, and maintenance of your containers. 

Using an orchestration tool is a scalable solution for running containers on AWS. An orchestration tool uses a pool of compute resources, which can include hundreds of EC2 instances to host containers. The orchestration tool launches and shuts down containers as demand on your application changes. It manages connectivity to and from your containers. It also helps manage container deployments and updates. 

Running containers on AWS

Deploying your managed container solutions on AWS involves selecting and configuring some components.

Amazon Elastic Container Registry (ECR)

Amazon Elastic Container Registry (Amazon ECR) is a managed Docker container registry. You push your container images to Amazon ECR and can then pull those images to launch containers. With Amazon ECR, you can compress, encrypt, and control access to your container images. You also manage versioning and and image tags. An Amazon ECR private registry is provided to each AWS account. You can create one or more repositories in your registry and store images in them. 

Amazon Elastic Container Service (ECS)

Amazon Elastic Container Service (Amazon ECS) is a highly scalable, high-performance container management service that supports Docker containers. Amazon ECS manages the scaling, maintenance, and connectivity for your containerized applications. 

With Amazon ECS, you create ECS services, which launch ECS tasks. Amazon ECS tasks can use one or more container images. Amazon ECS services scale your running task count to meet demand on your application.

You create an Amazon ECS cluster with dedicated infrastructure for your application. You can run your tasks and services on a serverless infrastructure managed by AWS Fargate. If you prefer more control over your infrastructure, manage your tasks and services on a cluster of EC2 instances. Your cluster can scale EC2 hosting capacity by adding or removing EC2 instances from your cluster. 

Amazon EKS 

Kubernetes is an open-source software that you can use to deploy and manage containerized applications at scale. Kubernetes manages clusters of Amazon EC2 compute instances and runs containers on those instances with processes for deployment, maintenance, and scaling. With Kubernetes, you can run any type of containerized applications using the same tool set on premises and in the cloud.

Amazon Elastic Kubernetes Service (Amazon EKS) is a certified conformant, managed Kubernetes service. Amazon EKS helps you provide highly available and secure clusters and automates key tasks such as patching, node provisioning, and updates.

  • Run applications at scale – Define complex containerized applications and run them at scale across a cluster of servers.
  • Seamlessly move applications – Move containerized applications from local development to production deployments on the cloud.
  • Run anywhere – Run highly available and scalable Kubernetes clusters.

Amazon EKS is a managed service that you can use to run Kubernetes on AWS without having to install and operate your own Kubernetes clusters. With Amazon EKS, AWS manages highly available services and upgrades for you. Amazon EKS runs three Kubernetes managers across three Availability Zones. It detects and replaces unhealthy managers and provides automated version upgrades and patching for the managers. Amazon EKS is also integrated with many AWS services to provide scalability and security for your applications.

Amazon EKS runs the latest version of the open-source Kubernetes software, so you can use all of the existing plugins and tooling from the Kubernetes community. Applications running on Amazon EKS are fully compatible with applications running on any standard Kubernetes environment, whether running in on-premises data centers or on public clouds.

Kubernetes architecture

The basic components of Kubernetes architecture are user interfaces, control plane, and data plane. Web user interfaces, such as dashboards or the command-line tool, kubectl, allow you to deploy, manage, and troubleshoot containerized applications and cluster resources. 

The control plane manages object states, responds to changes, and maintains a record of all objects. The data plane provides capacity such as CPU, memory, network, storage, and includes the worker node running in  containers in a pod.

AWS Fargate serverless cluster hosting

AWS Fargate is a technology for Amazon ECS and Amazon EKS that you can use to run containers without having to manage servers or clusters. With Fargate, you no longer have to provision, configure, and scale clusters of VMs to run containers. This removes the need to choose server types, decide when to scale your clusters, or optimize cluster packing. 

DubOPS Event

DubOps is a unique event that brings together DevOps, IT operations, and software development experts to share their knowledge and insights with the community. This event provides a platform for attendees to learn about the latest trends and best practices in the industry, as well as network with peers and thought leaders.

Registration for the Dubops event is now open, and we encourage anyone interested in attending to sign up early, as space is limited. Don’t miss this chance to expand your knowledge, connect with peers, and stay ahead of the curve in the ever-changing world of DevOps and IT operations.

Date: May 11th, 2023
Time: 18:00 – 21:00
Location: Zabeel House, Dubai, UAE
Registration link:
We look forward to seeing you there!



Oracle 23c Is out

Oracle Database 23c Free Version Now Available to Developers.

The new Oracle Database 23c Free – Developer Release is a free version of the trusted Oracle Database used by businesses of all sizes around the globe. Obtaining the only converged database that works with any data model and any task type is as easy as downloading it from the internet with no user account or license click-through requirements.

If you’re looking for a free database to use for developing data-driven applications, look no further than Oracle Database 23c Free – Developer Release. Users can upgrade to other Oracle Database products at any moment because of its backwards compatibility with Oracle Database Enterprise Edition and Oracle Database cloud services.

Documentation here





Infrastructure as code (IaC)

You can simplify the deployment of your AWS resources using an infrastructure as code approach. With and IaC solution, you create a template that describes all the resources that you want (like Amazon EC2 instances or Amazon RDS DB instances), and IaC solution takes care of provisioning and configuring those resources for you.

The benefits of infrastructure as code 

Gain the benefits of repeatability and reusability while building your environments. Build the same complex environments with one template, or a combination of templates.

For instance, a template can be designed so that different AMIs are used in the development or the production environments.

In this scenario, the template has been updated to add new security groups to the instance stacks. With one change to the templates, both environments can have the new security group resource added.


The template describes the resources to be created

Essentially, CloudFormation is an API wrapper. When you create an EC2 instance in the AWS Management Console wizard, you initiate an API call to the Amazon EC2 service. The information you enter through the wizard is passed on as parameters. 

CloudFormation manages the dependencies and relationships.

Author your CloudFormation template with any code editor, check it into a version-control system such as GitHub or CodeCommit, and review files before deploying. 


All resources in a stack are defined by the stack’s CloudFormation template. Stacks are a collection of AWS resources managed as a single unit. Stacks allow the creation and deletion of resources as a unit.

Change management in stacks

Change sets

Change sets allow you to preview how proposed changes to a stack might impact your running resources. For example, whether your changes will delete or replace any critical resources. AWS CloudFormation makes the changes to your stack only when you decide to execute the change set. You can create and manage change sets using the CloudFormation console, AWS CLI, or CloudFormation API.

Infrastructure tools

When building on AWS you can use different tools to help automate the deployment of infrastructure and manage those resources once deployed.

Tools for deployment

When choosing infrastructure deployment tools, you need to find a balance between convenience and control. Some tools give you complete control and have you choose every component and configuration. Though you can customize your deployment to fit your business needs, this requires greater expertise and more resources to manage and maintain. Other tools are designed for convenience and include preconfigured infrastructure templates for common solutions. Though these tools are easier to use and require less maintenance, you do not always have the ability to customize your infrastructure components. 

AWS Elastic Beanstalk

The goal of Elastic Beanstalk is to help developers deploy and maintain scalable web applications and services in the cloud without having to worry about the underlying infrastructure. Elastic Beanstalk configures each EC2 instance in your environment with the components necessary to run applications for the selected platform. With Elastic Beanstalk you can provision infrastructure to support common application designs, such as web applications and worker services.

AWS Solutions Library

AWS Solutions Library helps you solve common problems and build faster using the AWS platform. Solutions are vetted by AWS architects and are designed to be operationally effective, reliable, secure, and cost efficient.

AWS Cloud Development Kit (AWS CDK)

AWS CDK is a software development framework that defines your cloud application resources using a declarative model and familiar programming languages. AWS CDK includes a library of customizable constructs, which are building blocks consisting of one or more resources and include common configurations. You can use AWS CDK to generate CloudFormation templates and deploy your infrastructure along with your application runtime assets.

Automating infrastructure management with AWS Systems Manager

AWS Systems Manager makes it easier to bridge your existing infrastructure with AWS.
 Systems Manager helps you automatically collect software inventory, apply operating system (OS) patches, create system images, and configure Windows and Linux OSs. These capabilities help you:

  • Define and track system configurations
  • Prevent drift
  • Maintain software compliance of your Amazon EC2 and on-premises configurations 

With AWS Systems Manager, you can:

  • Centralize operational data from multiple AWS services and automate tasks across your AWS resources.
  • Create logical groups of resources such as applications, different layers of an application stack, or development and production environments.
  • Select a resource group and view its recent API activity, resource configuration changes, related notifications, operational alerts, software inventory, and patch compliance status.
  • Take action on each resource group depending on your operational needs.

You can open AWS Systems Manager from the Amazon EC2 console. Select the instances you want to manage, and define the management tasks you want to perform. Systems Manager is available at no cost to manage your Amazon EC2 and on-premises resources.

Benefits of Systems Manager

Shortens the time to detect problems

View operational data for groups of resources, so you can quickly identify any issues that might impact applications that use those resources. 

Automates tasks to increase efficiency

Automate operational tasks to help make your teams more efficient.

Improves visibility and control

Understand and control the state of your resource groups. 

Manages hybrid environments

Manage servers running on AWS and in your on-premises data center through a single interface.

Maintains security and compliance

Maintain security and compliance by scanning your instances against your patch, configuration, and custom policies.



AWS Auto Scaling 

AWS Auto Scaling lets you build scaling plans that automate how groups of different resources respond to changes in demand. You can optimize availability, costs, or a balance of both. AWS Auto Scaling automatically creates all of the scaling policies and sets targets for you, based on your needs.

Auto scaling

AWS Auto Scaling monitors your applications and automatically adjusts capacity to maintain steady, predictable performance at the lowest possible cost. Using AWS Auto Scaling, you can set up application scaling for multiple resources across multiple services in minutes. 

The service provides a simple, powerful user interface that lets you build scaling plans for resources including Amazon EC2 instances and Spot Fleets, and other compute and database services that will be addressed later in the course. 

AWS Auto Scaling makes scaling simple with recommendations that let you optimize performance, costs, or balance between them.

Amazon EC2 Auto Scaling

With Amazon EC2 Auto Scaling, you can build scaling plans that automate how groups of different EC2 resources respond to changes in demand. You can optimize availability, costs, or a balance of both.

If you specify scaling policies, then Amazon EC2 Auto Scaling can launch or terminate instances as demand on your application increases or decreases. Amazon EC2 Auto Scaling integrates with ELB so you can attach one or more load balancers to an existing Amazon EC2 Auto Scaling group. After you attach the load balancer, it automatically registers the instances in the group and distributes incoming traffic across the instances.

Amazon EC2 Auto Scaling components

Launch templateAmazon EC2 Auto Scaling groupAuto scaling policy
What resources do you need?Where and how many do you need?When and for how long do you need them?
Instance type
Security groups
VPC and subnets
Load balancer
Minimum instances
Maximum instances
Desired capacity (optional)
Predictive auto scaling
Scale-out policy
Scale-in policy

Launch template

A launch template is an instance configuration template that a group uses to launch EC2 instances. Included are the instance type, EBS volume, ID of the AMI, a key pair, security groups, and the other parameters that you use to launch EC2 instances.

Launch templates are the preferred method to configure your group in AWS because they provide:

  • A consistent experience
  • Simple permissions
  • Governance and best practices
  • Increased productivity

Optimize cost with EC2 Auto Scaling

Amazon EC2 Auto Scaling supports multiple purchasing options within the same group. You can launch and automatically scale a fleet of On-Demand Instances and Spot Instances within a single Auto Scaling group. In addition to receiving discounts for using Spot Instances, you can use Reserved Instances or a Savings Plan to receive discounted rates of the regular On-Demand Instance pricing. All of these factors combined help you to optimize your cost savings for EC2 instances, while making sure that you obtain the desired scale and performance for your application.

Using Amazon EC2 Fleet, you can define a combination of EC2 instance types to make up the desired capacity of your group. This is defined as a percentage of each type of purchasing option. Amazon EC2 Auto Scaling will maintain the desired cost optimization as your group scales in or out. Groups made up of mixed fleets still support the same lifecycle hooks, instance health checks, and scheduled scaling as a single-fleet group.



Connect to AKS cluster nodes

sometimes you need to access AKS worker node to troubelshoot, but how to do that with AKS

Run the below command

kubectl get nodes

Output will give an idea about the worker nodes you have

Run a container image on the node by issuing the kubectl debug command in order to establish a connection to it. The following command begins the process of connecting to a privileged container that has been started on your node.

kubectl debug node/<node-name-you-wish-to-connect> -it



AWS Load Balancing

A load balancer distributes incoming application traffic across multiple targets, such as EC2 instances, in multiple Availability Zones to increase the availability of your application. A load balancer works with listeners. You can have more than one listener per load balancer. 

A listener checks for connection requests from clients, using the protocol and port that you configure. The load balancer forwards requests to one or more target groups, based on the rules that you define.

Each rule specifies a target group, condition, and priority. The traffic is forwarded to that group when the condition is met. You define a default rule for each listener. You can add rules that specify different target groups based on the content of the request. Each target group routes requests to one or more registered targets, for example EC2 instances, using the specified protocol and port number. You can register a target with multiple target groups.

Elastic Load Balancing

AWS Elastic Load Balancing (ELB) is one of the most widely used AWS services. It has been adopted by organizations of all sizes, in all geographies, and across every industry. ELBs automatically distribute traffic across multiple targets, provide high availability, incorporate security features, and perform health checks.

ELB features

ELB load balancers are the only load balancers available on AWS that natively connect users to your EC2 instances, container deployments, and AWS Lambda functions. Some key feature sets include the following:

  • High availability – ELB automatically distributes your traffic across multiple targets in a single Availability Zone or multiple Availability Zones. Examples of targets include EC2 instances, containers, and IP addresses.
  • Layer 4 or Layer 7 HTTP and HTTPS load balancing – You can load balance your HTTP or HTTPS applications for Layer 7-specific features. Alternatively, you can use strict Layer 4 load balancing for applications that rely purely on the TCP.
  • Security features – Use Amazon VPC to create and manage security groups associated with load balancers to provide additional networking and security options. You can also create an internal (non-internet-facing) load balancer.
  • Health checks – ELB load balancers can detect unhealthy targets, stop sending traffic to them, and spread the load across the remaining healthy targets.
  • Monitoring operations – To monitor the performance of your applications in real time, ELB integrates with CloudWatch metrics and provides request tracing.

Types of load balancers

Application Load Balancer

This load balancer functions at the application layer, the seventh layer of the Open Systems Interconnection (OSI) model. Application Load Balancers support the following: Content-based routing, applications that run in containers, and open standard protocols (WebSocket and HTTP/2). This type of balancer is ideal for advanced load balancing of HTTP and HTTPS traffic. 

Network Load Balancer

This load balancer is designed to handle tens of millions of requests per second while maintaining high throughput at ultra low-latency. Network Load Balancer operates at the connection level (Layer 4), routing connections to targets based on IP protocol data. Targets include EC2 instances, containers, and IP addresses. It is ideal for balancing TCP traffic.

Gateway Load Balancer

This load balancer makes it easy to deploy, scale, and manage your third-party virtual appliances. It provides one gateway for distributing traffic across multiple virtual appliances, and scales them up, or down, based on demand. This distribution reduces potential points of failure in your network and increases availability. Gateway Load Balancer transparently passes all Layer 3 traffic through third-party virtual appliances. It is invisible to the source and destination.

Classic Load Balancer

ELB common features

FeaturesApplication Load BalancerNetwork  Load BalancerGateway  Load Balancer
Health checks
CloudWatch metrics
Secure Sockets Layer (SSL) offloading
Connection draining
Preserve source IP address
Static IP address**
Lambda functions as a target
Fixed-response actions