The "End of Life" (EOL) page for Software provides information on the release dates, support periods, and security status of different Software versions. It lists the latest supported version, the end dates for older versions, and provides links to further resources. This page is useful for understanding the support lifecycle of Software releases and ensuring that you are using a version that receives updates and security patches.
Ref: https://endoflife.date/kotlin
Could not prepare statement [Table “XXXX” not found (this database is empty); SQL statement
Solution:
Add bellow configuration in test application.ymlspring:test:database:replace: none
---
Code:
testImplementation("org.springframework.boot:spring-boot-testcontainers")
testImplementation("org.testcontainers:junit-jupiter")
testImplementation("org.testcontainers:mariadb")
Test containers:
References:
test container examples here
Now a days, it's very difficult remember the vm passwords while connecting in the office network. So, Connect easily using sshpass.
For installation for mac/Linux:
Mac:
brew install hudochenkov/sshpass/sshpass
Linux:
yum install sshpass
Example of usage:
Ex:
sshpass -p test123 ssh root@192.168.1.1
Reafference:
https://stackoverflow.com/questions/32255660/how-to-install-sshpass-on-mac
The Single Root I/O Virtualization (SR-IOV) specification is a standard for a type of PCI device assignment that can share a single device with multiple pods.
SR-IOV enables you to segment a compliant network device, recognized on the host node as a physical function (PF), into multiple virtual functions (VFs), and make them available for direct IO to the POD.
Network Interface Cards (NICs) with SR-IOV capabilities are managed through physical functions (PFs) and virtual functions (VFs). A PF is used by the host and usually represents a single NIC port. VF configurations are applied through the PF. With SR-IOV CNI each VF can be treated as a separate network interface, assigned to a container, and configured with it's own MAC, VLAN, IP and more.
SR-IOV CNI plugin works with SR-IOV device plugin for VF allocation in Kubernetes. A metaplugin such as Multus gets the allocated VF's deviceID(PCI address) and is responsible for invoking the SR-IOV CNI plugin with that deviceID.
The end result will be similar to the in the picture except for the SRIOV-CNI and the DPDK userspace.
Reference:
https://github.com/ramanujadasu/sriov-cni
https://dramasamy.medium.com/high-performance-containerized-applications-in-kubernetes-f494cef3f8e8
Kubernetes is an open-source orchestration engine for automating deployments, scaling, managing, and providing the infrastructure to host containerized applications. At the infrastructure level, a Kubernetes cluster is comprised of a set of physical or virtual machines, each acting in a specific role.
Master components are responsible for managing the Kubernetes cluster. They manage the life cycle of pods, the base unit of a deployment within a Kubernetes cluster. Master servers run the following components:
kube-apiserver – the main component, exposing APIs for the other master components.
etcd – distributed key/value store which Kubernetes uses for persistent storage of all cluster information.
kube-scheduler – uses information in the pod spec to decide on which node to run a pod.
kube-controller-manager – responsible for node management (detecting if a node fails), pod replication, and endpoint creation.
cloud-controller-manager – daemon acting like an abstraction layer between the APIs and the different cloud providers’ tools (storage volumes, load balancers etc.)
Node components are worker machines in Kubernetes and are managed by the Master. A node may be a virtual machine (VM) or physical machine, and Kubernetes runs equally well on both types of systems. Each node contains the necessary components to run pods:
kubelet – watches the API server for pods on that node and makes sure they are running
cAdvisor – collects metrics about pods running on that particular node
kube-proxy – watches the API server for pods/services changes in order to maintain the network up to date
container runtime – responsible for managing container images and running containers on that node
Reference:
https://www.suse.com/c/rancher_blog/understanding-the-kubernetes-node/#:~:text=kubelet%20%E2%80%93%20watches%20the%20API%20server,the%20network%20up%20to%20date
MacBook process to add new VPN entry:
cd /opt/cisco/anyconnect/profile
sudo cp clientprofile_old.xml clientprofile_new.xml
sudo vi clientprofile_new.xml
Update hostname and hostaddress
Ex:
<ServerList>
<HostEntry>
<HostName>NEW</HostName>
<HostAddress>127.0.0.1</HostAddress>
</HostEntry>
</ServerList>
Few mac tools for easy connect Virtual Machines:
https://mobaxterm.mobatek.net/
https://apps.apple.com/us/app/zen-term-lite-ssh-client/id1422475219?mt=12
Reference:
https://documentation.meraki.com/MX/AnyConnect_on_the_MX_Appliance/Client_deployment
DevOps is about cultural change and providing a way for development teams and operations teams to work together collaboratively. GitOps gives you tools and a framework to take DevOps practices, like collaboration, CI/CD, and version control, and apply them to infrastructure automation and application deployment.
GitOps Free Training(LinuxFoundation):
https://trainingportal.linuxfoundation.org/learn/course/introduction-to-gitops-lfs169/course-introduction/course-information
Reference:
https://www.redhat.com/en/topics/devops/what-is-gitops#:~:text=DevOps%20is%20about%20cultural%20change,infrastructure%20automation%20and%20application%20deployment.
Skopeo is a tool for moving container images between different types of container storages. It allows you to copy container images between container registries like docker.io, quay.io, and your internal container registry or different types of storage on your local system.
Below are the steps to push or pull images from artifactory using skopeo instead of docker. Skopeo is just a cli and does not require any service/privilege. No change is needed on the docker or docker-desktop settings also.
Pre-Steps: Install skopeo
brew instal skopeo
Setup proxies if any issue with environment:
export http_proxy=<hostname>:<port>
export https_proxy=<hostname>:<port>
export no_proxy="io,com,org"
Login:
skopeo login --tls-verify=false -u USERNAME <repo-url>
Inspecting a repository
skopeo inspect --config docker://quay.io/podman/stable | json_pp
Copying images
Skopeo can copy container images between various storage mechanisms:
skopeo copy docker://<imagename:latest> docker://<imagename:latest>
ex: skopeo copy docker://registry.access.redhat.com/ubi8-init docker://reg.company.com/ubi-init
skopeo copy docker://registry.fedoraproject.org/fedora:latest containers-storage:fedora
If any restrictions repo: skopeo copy --override-arch=amd64 --override-os=linux --dest-tls-verify=false docker-daemon:<imagename:latest> docker://<imagename:latest>
Deleting images from a registry:
skopeo delete docker://localhost:5000/<imagename:latest>
Reference:
https://www.redhat.com/en/blog/skopeo-10-released#:~:text=Skopeo%20is%20a%20tool%20for,storage%20on%20your%20local%20system
A note on Python threads
If you start uWSGI without threads, the Python GIL will not be enabled, so threads generated by your application will never run. You may not like that choice, but remember that uWSGI is a language-independent server, so most of its choices are for maintaining it “agnostic”. But do not worry, there are basically no choices made by the uWSGI developers that cannot be changed with an option.
If you want to maintain Python threads support without starting multiple threads for your application, just add the --enable-threads option (or enable-threads = true in ini style).
[uwsgi] # ------------- # Settings: # key = value # Comments >> # # ------------- strict uid = root gid = root # socket = [addr:port] http-socket = 0.0.0.0:9034 wsgi-file = app.py callable = TEST_SERVICE # master = [master process (true of false)] master = true # processes = [number of processes] processes = 5 py-autoreload = 0 buffer-size = 32768 need-app = true attach-daemon = celery -A app.CELERY worker --loglevel=INFO --concurrency=1
Above properties detail information available below url:
Reference:
https://uwsgi-docs.readthedocs.io/en/latest/WSGIquickstart.html
List can be sorted using Java 8 Lambda Expressions, moving right past syntactic sugar and into real and powerful functional semantics. The implementation of all of these examples and code snippets can be found over on gitHub: https://github.com/ramanujadasu/tutorials/tree/master/core-java-modules/core-java-lambdas
List<Human> humans = Lists.newArrayList( new Human("Sarah", 10), new Human("Jack", 12) ); Basic Sort Without Lambdas: Collections.sort(humans, new Comparator<Human>() { @Override public int compare(Human h1, Human h2) { return h1.getName().compareTo(h2.getName()); } }); Basic Sort With Lambda Support: humans.sort( (Human h1, Human h2) -> h1.getName().compareTo(h2.getName())); Basic Sorting With No Type Definitions: humans.sort((h1, h2) -> h1.getName().compareTo(h2.getName())); Sort Using Reference to Static Method: public static int compareByNameThenAge(Human lhs, Human rhs) { if (lhs.name.equals(rhs.name)) { return Integer.compare(lhs.age, rhs.age); } else { return lhs.name.compareTo(rhs.name); } } humans.sort(Human::compareByNameThenAge); Sort Extracted Comparators: Collections.sort( humans, Comparator.comparing(Human::getName)); Reverse Sort: Comparator<Human> comparator = (h1, h2) -> h1.getName().compareTo(h2.getName()); humans.sort(comparator.reversed()); Sort With Multiple Conditions: List<Human> humans = Lists.newArrayList( new Human("Sarah", 12), new Human("Sarah", 10), new Human("Zack", 12) ); humans.sort((lhs, rhs) -> { if (lhs.getName().equals(rhs.getName())) { return Integer.compare(lhs.getAge(), rhs.getAge()); } else { return lhs.getName().compareTo(rhs.getName()); } }); Sort With Multiple Conditions -Composition: humans.sort( Comparator.comparing(Human::getName).thenComparing(Human::getAge) ); Sorting a List With Stream.sorted(): List<String> letters = Lists.newArrayList("B", "A", "C"); List<String> sortedLetters = letters.stream().sorted().collect(Collectors.toList()); == List<Human> humans = Lists.newArrayList(new Human("Sarah", 10), new Human("Jack", 12)); Comparator<Human> nameComparator = (h1, h2) -> h1.getName().compareTo(h2.getName()); List<Human> sortedHumans = humans.stream().sorted(nameComparator).collect(Collectors.toList()); Or List<Human> sortedHumans = humans.stream() .sorted(Comparator.comparing(Human::getName)) .collect(Collectors.toList()); Sorting a List in Reverse With Stream.sorted(): List<String> letters = Lists.newArrayList("B", "A", "C"); List<String> reverseSortedLetters = letters.stream() .sorted(Comparator.reverseOrder()) .collect(Collectors.toList()); == List<Human> humans = Lists.newArrayList(new Human("Sarah", 10), new Human("Jack", 12)); Comparator<Human> reverseNameComparator = (h1, h2) -> h2.getName().compareTo(h1.getName()); List<Human> reverseSortedHumans = humans.stream().sorted(reverseNameComparator) .collect(Collectors.toList()); Or List<Human> reverseSortedHumans = humans.stream() .sorted(Comparator.comparing(Human::getName, Comparator.reverseOrder())) .collect(Collectors.toList()); Null Values: List<Human> humans = Lists.newArrayList(null, new Human("Jack", 12)); humans.sort((h1, h2) -> h1.getName().compareTo(h2.getName())); == List<Human> humans = Lists.newArrayList(null, new Human("Jack", 12), null); humans.sort((h1, h2) -> { if (h1 == null) { return h2 == null ? 0 : 1; } else if (h2 == null) { return -1; } return h1.getName().compareTo(h2.getName()); }); Or humans.sort(Comparator.nullsLast(Comparator.comparing(Human::getName))); Or humans.sort(Comparator.nullsFirst(Comparator.comparing(Human::getName)));
Marker interface has no method. Java has built-in marker interface like Serializable, Cloneable & Event Listener etc that are understand by JVM.
We can create our own marker interface, but it has nothing to do with JVM, we can add some checks with instanceOf.
Create the empty interface interface Marker{ } Write a class and implements the interface class A implements Marker { //do some task } Main class to check the marker interface instanceof class Main { public static void main(String[] args) { A ob = new A(){ if (ob instanceof A) { // do some task } } }
public class Test {
public static int test(int i) { try { if (i == 0) throw new Exception(); return 0; } catch (Exception e) { return 1; } finally { return 2; } } public static void main(String[] args) { System.out.println(test(0)); System.out.println(test(1)); } }
Output:22Found few good tutorials and capture the profile building and data-structure concepts examples.
Profile creation tips and related sites:
https://github.com/ramanujadasu/golden-profile-tips/tree/main/profilecreationtips
Data structure concepts and example git repos:
https://github.com/ramanujadasu/golden-profile-tips/tree/main/datastructures
Visual view for DataStructures:
Java 9 Features:
Solution:
Reference: https://www.interviewbit.com/mongodb-interview-questions/
Question: Write program: get the employee salary > 10000 rupees in the provided list
Solution:
packagecom.test;
importjava.util.*;
importjava.util.stream.Collectors;
publicclassTestEmployee {
publicstaticvoidmain(String... args) {
List<Employee> empList= newArrayList<>();
empList.add(newEmployee("test1", 1235));
empList.add(newEmployee("test2", 12353));
empList.add(newEmployee("test3", 12352));
empList.add(newEmployee("test4", 12345));
empList.add(newEmployee("test5", 1235));
List<String> resEmpList= empList.stream().filter(e-> e.getSalary() > 10000).map(e-> e.getName())
.collect(Collectors.toList());
resEmpList.stream().forEach(System.out::println);
}
}
classEmployee {
privateString name;
privateInteger salary;
publicString getName() {
return name;
}
publicvoidsetName(String name) {
this.name= name;
}
publicInteger getSalary() {
return salary;
}
publicvoidsetSalary(Integer salary) {
this.salary= salary;
}
publicEmployee(String name, Integer salary) {
this.name= name;
this.salary= salary;
}
}
Question: What is docker?
Docker is a very popular and powerful open-source containerization platform that is used for building, deploying, and running applications. Docker allows you to decouple the application/software from the underlying infrastructure.
In order to get the status of all the containers, we run the below command:
docker ps -a
docker save command and the syntax is:
docker save -o <exported_name>.tar <container-name>
docker load command and the syntax is
docker load -i <export_image_name>.tar
There are three docker components, they are - Docker Client, Docker Host, and Docker Registry.
Reference: https://www.interviewbit.com/docker-interview-questions/
Question: What is Thread life Cycle?
Solution:
Reference: https://www.baeldung.com/java-thread-lifecycle
Question: What is Hibernate Lifecycle?
Solution:
Reference: https://www.geeksforgeeks.org/hibernate-lifecycle/
AWS S3 CURD Operations including spring boot actuator features
README file mentioned to run procedure
GITURL: https://github.com/ramanujadasu/aws-curd-apis
GIT SSH link:
git@github.com:ramanujadasu/aws-curd-apis.git
Spring Boot AWS Cloud Support
https://spring.io/projects/spring-cloud-aws#overview
Samples:
Scaling an on-premise infrastructure is hard. You need to plan for peak capacity, wait for equipment to arrive, configure the hardware and software, and hope you get everything right the first time. But deploying your application in the cloud can address these headaches.
Vertical scaling means that you scale by adding more power (CPU, RAM) to an existing machine. AWS provides instances up to 488 GB of RAM or 128 virtual cores.
Horizontal scaling essentially involves adding machines in the pool of existing resources. When users grow up to 1000 or more, vertical scaling can’t handle requests and horizontal scaling is required. Horizontal scalability can be achieved with the help of clustering, distributed file system, and load balancing.
Example for horizontal scaling:
{{- if ne <value_check> "\"false\"" -}}
{{- if <value_check }}
apiVersion: autoscaling/v2beta1
kind: HorizontalPodAutoscaler
metadata:
name: xxxx
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: xxxx
minReplicas: 1 <replica_count>
maxReplicas: 10 <max_replicas>
metrics:
- type: Resource
resource:
name: cpu
targetAverageUtilization: 90
- type: Resource
resource:
name: memory
targetAverageUtilization: 90
{{- end }}
{{- end }}
Example for vertical scalling:
apiVersion: v1
kind: Pod
metadata:
name: xxx-demo
namespace: xxx-example
spec:
containers:
- name: xxx
image: vish/stress
resources:
limits:
memory: "2Gi"
cpu: "2"
requests:
memory: "1.5Gi"
cpu: "1.5"
args:
- -cpus
- "2"
Reference:
https://devblog.axway.com/apis/helm-and-kubernetes-adoption/
https://github.com/ramanujadasu/apigw-helm-charts
https://dzone.com/articles/vertical-scaling-and-horizontal-scaling-in-aws
https://kubernetes.io/docs/tasks/configure-pod-container/assign-cpu-resource/
AWS Code optimization techniques:
https://www.whizlabs.com/blog/aws-cost-optimization-best-practices/
