Waylon  Bruen

Waylon Bruen


Deploy Your Application or Microservice on Kubernetes

Migrating containerized workloads to Kubernetes? See which Kubernetes resources work best, and how you can get multiple replicas of your application running simply, and quickly.

At the end of this Tech Talk, you will be able to deploy your application or microservice as a Kubernetes Deployment.

#kubernetes #microservices 

What is GEEK

Buddha Community

Deploy Your Application or Microservice on Kubernetes
Christa  Stehr

Christa Stehr


50+ Useful Kubernetes Tools for 2020 - Part 2


Last year, we provided a list of Kubernetes tools that proved so popular we have decided to curate another list of some useful additions for working with the platform—among which are many tools that we personally use here at Caylent. Check out the original tools list here in case you missed it.

According to a recent survey done by Stackrox, the dominance Kubernetes enjoys in the market continues to be reinforced, with 86% of respondents using it for container orchestration.

(State of Kubernetes and Container Security, 2020)

And as you can see below, more and more companies are jumping into containerization for their apps. If you’re among them, here are some tools to aid you going forward as Kubernetes continues its rapid growth.

(State of Kubernetes and Container Security, 2020)

#blog #tools #amazon elastic kubernetes service #application security #aws kms #botkube #caylent #cli #container monitoring #container orchestration tools #container security #containers #continuous delivery #continuous deployment #continuous integration #contour #developers #development #developments #draft #eksctl #firewall #gcp #github #harbor #helm #helm charts #helm-2to3 #helm-aws-secret-plugin #helm-docs #helm-operator-get-started #helm-secrets #iam #json #k-rail #k3s #k3sup #k8s #keel.sh #keycloak #kiali #kiam #klum #knative #krew #ksniff #kube #kube-prod-runtime #kube-ps1 #kube-scan #kube-state-metrics #kube2iam #kubeapps #kubebuilder #kubeconfig #kubectl #kubectl-aws-secrets #kubefwd #kubernetes #kubernetes command line tool #kubernetes configuration #kubernetes deployment #kubernetes in development #kubernetes in production #kubernetes ingress #kubernetes interfaces #kubernetes monitoring #kubernetes networking #kubernetes observability #kubernetes plugins #kubernetes secrets #kubernetes security #kubernetes security best practices #kubernetes security vendors #kubernetes service discovery #kubernetic #kubesec #kubeterminal #kubeval #kudo #kuma #microsoft azure key vault #mozilla sops #octant #octarine #open source #palo alto kubernetes security #permission-manager #pgp #rafay #rakess #rancher #rook #secrets operations #serverless function #service mesh #shell-operator #snyk #snyk container #sonobuoy #strongdm #tcpdump #tenkai #testing #tigera #tilt #vert.x #wireshark #yaml

Autumn  Blick

Autumn Blick


Microservices in Practice: Deployment Shouldn't Be an Afterthought

Microservice architecture is one of the most popular software architecture styles that enables the rapid, frequent, and reliable delivery of large, complex applications. There are numerous learning materials on the benefits of microservices, design, and implementations. However, there are very few resources that discuss how to write your code to cloud-native platforms like Kubernetes in a way that just works. In this article, I am going to use the same microservice E-Commerce sample used in the Rethinking Programming: Automated Observability article and discuss Ballerina’s built-in Kubernetes support to extend it to run in Kubernetes platforms.

The sample code covers the implementation of an e-commerce backend that simulates the microservices required to implement searching for goods, adding them to a shopping cart, doing payments, and shipping.

E-Commerce Backend Microservices Architecture

E-Commerce Backend Microservices Architecture

Code to Kubernetes

Docker helps to package the application with its dependencies while Kubernetes helps to automate deployment and scaling and to manage containerized applications. Kubernetes defines a set of unique building blocks that collectively provide mechanisms to deploy, maintain, and scale applications.

On the other hand, the developer has to write code in a certain way to work well in a given execution environment. The microservices have to be designed, architected, and implemented in a way that performs well in a platform like Kubernetes. Otherwise, the application code will not be well-fitting to the Kubernetes building blocks. In other words, deployment should not be an afterthought, we should design and write our code to run in Kubernetes.

Let’s look at potential Kubernetes deployment architecture for the above e-commerce application.

Kubernetes Deployment Architecture for E-commerce Backend Microservices

Kubernetes Deployment Architecture for E-commerce Backend Microservices

One of the main challenges that developers are facing is the lack of tools and programing language abstraction support to design and implement the microservices to work well in Kubernetes. As a solution to this problem, Ballerina has introduced a set of cloud-native abstractions and tools to write microservices that just work in platforms like Kubernetes.

Let’s look at how we can use Ballerina’s Kubernetes abstraction to extend the e-commerce microservices to run in Kubernetes.

Order Management Microservice

The order management microservice named OrderMgt is the simplest microservices because it provides a set of functionality for billing, shipping, and admins but it is not dependant on any other microservices to complete the tasks. Let’s see how we can extend the OrderMgt microservice to support running in Kubernetes.


@kubernetes:HPA {
   minReplicas: 1,
   maxReplicas: 4,
   cpuPercentage: 75,
   name: "ordermgt-hpa"
@kubernetes:Service {
   name: "ordermgt-svc"
@kubernetes:Deployment {
   name: "ordermgt",
   image: "index.docker.io/$env{DOCKER_USERNAME}/ecommerce-ordermgt:1.0",
   username: "$env{DOCKER_USERNAME}",
   password: "$env{DOCKER_PASSWORD}",
   push: true,
   livenessProbe: true,
   readinessProbe: true,
   prometheus: true
service OrderMgt on new http:Listener(8081) {

Listing 1: OrderMgt Microservice

In the code snippet above, I have added three Kubernetes annotations on top of the OrderMgt service code block. I have set some properties in @kubernetes:Deployment to extend the code to run in Kubernetes.

  • _  image        : Name, registry and tag of the Docker image_
  • _  username     : Username for Docker registry_
  • _  password     : Password for Docker registry_
  • _  push         : Enable pushing Docker image to the registry_
  • _  livenessProbe. : Enable livenessProbe for the health check_
  • _  readinessProbe : Enable readinessProbe for the health check_
  • _  prometheus   : Enabled Prometheus for observability _

#microservice architecture #microservice #kubernates #ballerina #programing language #deploying microservices #deploying to kubernetes

Einar  Hintz

Einar Hintz


Testing Microservices Applications

The shift towards microservices and modular applications makes testing more important and more challenging at the same time. You have to make sure that the microservices running in containers perform well and as intended, but you can no longer rely on conventional testing strategies to get the job done.

This is where new testing approaches are needed. Testing your microservices applications require the right approach, a suitable set of tools, and immense attention to details. This article will guide you through the process of testing your microservices and talk about the challenges you will have to overcome along the way. Let’s get started, shall we?

A Brave New World

Traditionally, testing a monolith application meant configuring a test environment and setting up all of the application components in a way that matched the production environment. It took time to set up the testing environment, and there were a lot of complexities around the process.

Testing also requires the application to run in full. It is not possible to test monolith apps on a per-component basis, mainly because there is usually a base code that ties everything together, and the app is designed to run as a complete app to work properly.

Microservices running in containers offer one particular advantage: universal compatibility. You don’t have to match the testing environment with the deployment architecture exactly, and you can get away with testing individual components rather than the full app in some situations.

Of course, you will have to embrace the new cloud-native approach across the pipeline. Rather than creating critical dependencies between microservices, you need to treat each one as a semi-independent module.

The only monolith or centralized portion of the application is the database, but this too is an easy challenge to overcome. As long as you have a persistent database running on your test environment, you can perform tests at any time.

Keep in mind that there are additional things to focus on when testing microservices.

  • Microservices rely on network communications to talk to each other, so network reliability and requirements must be part of the testing.
  • Automation and infrastructure elements are now added as codes, and you have to make sure that they also run properly when microservices are pushed through the pipeline
  • While containerization is universal, you still have to pay attention to specific dependencies and create a testing strategy that allows for those dependencies to be included

Test containers are the method of choice for many developers. Unlike monolith apps, which lets you use stubs and mocks for testing, microservices need to be tested in test containers. Many CI/CD pipelines actually integrate production microservices as part of the testing process.

Contract Testing as an Approach

As mentioned before, there are many ways to test microservices effectively, but the one approach that developers now use reliably is contract testing. Loosely coupled microservices can be tested in an effective and efficient way using contract testing, mainly because this testing approach focuses on contracts; in other words, it focuses on how components or microservices communicate with each other.

Syntax and semantics construct how components communicate with each other. By defining syntax and semantics in a standardized way and testing microservices based on their ability to generate the right message formats and meet behavioral expectations, you can rest assured knowing that the microservices will behave as intended when deployed.

#testing #software testing #test automation #microservice architecture #microservice #test #software test automation #microservice best practices #microservice deployment #microservice components

Maud  Rosenbaum

Maud Rosenbaum


Microservice and Serverless With Micronaut + GraalVM

Micronaut® framework is creating a buzz around cloud-native (microservice, serverless ) application development due to its enriched features and optimizations based out of modern Polyglot JVM — GraalVMoptimizers.

For GraalVM ** optimizers go thought Part1 of this series GraalVM — Byte Code to Bit Code.**

Why Micronaut® and what makes it the next level stuff as a framework for Cloud-Native development :

  • Natively Cloud Native
  • Micronaut®’s cloud support is built right in, including support for common discovery services, distributed tracing tools, cloud runtimes and leading vendors ( AWS, AZURE, GCP).
  • Ready for Serverless Development
  • Micronaut® low overhead compile-time DI and AOP make it perfect for writing functions for serverless environments like AWS Lambda, Azure Functions etc.
  • Fast Start Time — Low Memory Consumption
  • Reflection-based IoC framework load and cache reflection data for every single field, method, and constructor in your code. Whereas with Micronaut®, your application startup time and memory consumption are not bound to the size of your codebase. Micronaut® build around GraalVM. Micronaut features a dependency injection and aspect-oriented programming runtime that uses no reflection. This makes it easier for Micronaut applications to run on GraalVM.
  • Micronaut apps start in a tenth of millisecond with GraalVM!
  • Built with Non-Blocking Http Server on Netty
  • With a smooth learning curve, Micronaut’s HTTP server makes it as easy as possible to expose APIs that can be consumed by HTTP clients.
  • Design for Building Resilient Microservices
  • Distributed environments require planning for failure. Micronaut’s built-in support for retry, circuit breaker, and fallbacks help you plan.
  • Faster Data Layer Configuration
  • Micronaut provides sensible defaults that automatically configure your favorite data access toolkit and APIs to make it easy to write your own integrations. Supports like Caching, SQL, NoSQL, and different DB vendor products are readily available.
  • Fast and Easy Testing
  • Easily spin up servers and clients in your unit tests, and run them instantaneously with mostly auto-generated test stuff for main source code.
  • Reloading (or “hot-loading”)
  • Out of box excellent support of hot reloading, restart, and reinitialization with build-in JVM agent support rather than relying on classloader reloading or proprietary JVM agents like JRebel etc. It is an important feature to make the development cycle efficient and fast.
  • Refreshable feature
  • @Refreshable is another interesting scope offered by Micronaut. You can refresh the state of a bean by calling the HTTP endpoint /refresh or by publishing RefreshEvent to the application context.

How to Get Started Along Microservice With Micronaut

Create an app using the Micronaut Command Line Interface.

Installing Micronaut® manually comes with a super-rich & intuitive CLI that we will be using for the rest of the project lifecycle ( its power-pack CLI features add to developers productivity). We will be doing 3case studies with Micronaut® to compare and benchmark its potential relative to today’s Cloud-Native de-facto framework — SpringBoot.

_Case A : _ Micronaut ® _ app on GraalVM optimised JIT_

_Case B : _ Micronaut ® _ app on GraalVM “Native-Image”_

Case C : SpringBoot on openJDK HotSpotVM JIT — conventional way

Let’s get to the suspense straight-in with below depiction of different benchmarking results :

Benchmarking Micronaut

Micronaut application benchmarking

#kubernetes #serverless #microservice architecture #microservice #aws lambda #cloud native applications #microservice best practices #cloud application #serverless adoption #azure function

Maud  Rosenbaum

Maud Rosenbaum


Kubernetes in the Cloud: Strategies for Effective Multi Cloud Implementations

Kubernetes is a highly popular container orchestration platform. Multi cloud is a strategy that leverages cloud resources from multiple vendors. Multi cloud strategies have become popular because they help prevent vendor lock-in and enable you to leverage a wide variety of cloud resources. However, multi cloud ecosystems are notoriously difficult to configure and maintain.

This article explains how you can leverage Kubernetes to reduce multi cloud complexities and improve stability, scalability, and velocity.

Kubernetes: Your Multi Cloud Strategy

Maintaining standardized application deployments becomes more challenging as your number of applications and the technologies they are based on increase. As environments, operating systems, and dependencies differ, management and operations require more effort and extensive documentation.

In the past, teams tried to get around these difficulties by creating isolated projects in the data center. Each project, including its configurations and requirements were managed independently. This required accurately predicting performance and the number of users before deployment and taking down applications to update operating systems or applications. There were many chances for error.

Kubernetes can provide an alternative to the old method, enabling teams to deploy applications independent of the environment in containers. This eliminates the need to create resource partitions and enables teams to operate infrastructure as a unified whole.

In particular, Kubernetes makes it easier to deploy a multi cloud strategy since it enables you to abstract away service differences. With Kubernetes deployments you can work from a consistent platform and optimize services and applications according to your business needs.

The Compelling Attributes of Multi Cloud Kubernetes

Multi cloud Kubernetes can provide multiple benefits beyond a single cloud deployment. Below are some of the most notable advantages.


In addition to the built-in scalability, fault tolerance, and auto-healing features of Kubernetes, multi cloud deployments can provide service redundancy. For example, you can mirror applications or split microservices across vendors. This reduces the risk of a vendor-related outage and enables you to create failovers.

#kubernetes #multicloud-strategy #kubernetes-cluster #kubernetes-top-story #kubernetes-cluster-install #kubernetes-explained #kubernetes-infrastructure #cloud