#spring boot microservices mongodb example

[codeonedigest]

Spring Boot Microservice Project with MongoDB Step by Step Tutorial for Beginners with Java Code Example

Full Video Link: https://youtu.be/1HnturOhPhs Hi, a new #video on step by step #tutorial for #springboot #microservices with #mongodb is published on #codeonedigest #youtube channel. Quick guide for spring boot microservices with mongodb. #Springboot #

In this video, we will learn, how to download, install mongodb, how to integrate MongoDB with a Spring Boot Microservice Application and perform different CRUD operations (Create, Read, Update, and Delete operations) on the Customer entity. Spring Boot is built on the top of the spring and contains all the features of spring. And is becoming a favorite of developers these days because it’s a…

[codingbrushup]

7 Advantages of Joining a Full Stack Developer Coding Brushup

In today’s dynamic tech industry, staying updated with the latest tools, frameworks, and best practices is not optional—it’s essential. For professionals aiming to solidify their expertise or refresh their knowledge, a coding brushup for Java full stack developer roles can be the perfect stepping stone. Whether you're returning to development after a break or preparing for a job interview, a full stack developer coding brushup bootcamp offers structured, high-impact training to help you reach your goals faster.

Below, we explore the top 7 advantages of joining such a bootcamp, especially if you're targeting a career as a Java full stack developer.

1. Focused Review of Core Concepts

A coding brushup for Java full stack developer roles focuses on reinforcing essential front-end and back-end concepts in a streamlined way. Instead of sifting through hundreds of tutorials or outdated resources, you’ll get structured learning that covers:

Java programming fundamentals

Spring and Spring Boot frameworks

RESTful APIs

Front-end technologies like HTML, CSS, JavaScript, React or Angular

Database operations with MySQL or MongoDB

This focused review ensures that you don’t just remember syntax, but also understand how to structure scalable, efficient code across the entire stack—front end to back end.

2. Bridging Skill Gaps Quickly

Even experienced developers can develop knowledge gaps due to changing technologies. A full stack developer course designed as a brushup bootcamp can bridge these gaps in weeks, not months.

Java evolves regularly, and frameworks like Spring Boot are consistently updated. Attending a coding brushup for Java full stack developers ensures you're up to date with the latest industry standards and practices.

Plus, the bootcamp model ensures that you’re learning by doing, reinforcing both theoretical and practical skills in real time.

3. Preparation for Job Interviews and Assessments

Hiring processes in tech are rigorous. Most companies looking for a Java full stack developer will test your technical aptitude through:

Coding challenges

Technical interviews

System design tests

A full stack developer coding brushup bootcamp typically includes mock interviews, live coding sessions, and problem-solving exercises tailored to real-world job assessments. You’ll gain the confidence and experience needed to crack interviews at top companies.

4. Hands-On Project Experience

Theory without practice is incomplete—especially in full stack development. The best full stack developer course bootcamps emphasize building hands-on projects that showcase your capabilities. You might build:

A CRUD application using Spring Boot and React

An e-commerce site with user authentication

REST APIs with integrated front-end components

These practical projects not only reinforce your learning but also become strong additions to your professional portfolio—an essential asset when applying for Java full stack developer roles.

5. Expert Mentorship and Peer Learning

Bootcamps are not just about what you learn, but also who you learn from. Most full stack developer bootcamp programs are taught by experienced professionals with years in the industry. Their guidance ensures that you're not just reading documentation but understanding how to apply it in real-world business scenarios.

In addition, you’ll be part of a cohort of like-minded peers. This community-driven learning environment fosters collaboration, idea exchange, and peer-to-peer feedback—critical for personal and professional growth in software development.

6. Updated Curriculum Based on Industry Trends

Unlike static college curriculums or outdated YouTube playlists, a coding brushup for Java full stack developer roles is regularly updated to reflect real industry demands. You’ll get hands-on experience with tools and frameworks currently used by top employers.

For example:

Working with Spring Boot for microservices

Integrating frontend frameworks like React with Java backends

Using Git, Docker, and CI/CD pipelines

An updated curriculum ensures that when you complete the full stack developer course, your skills are relevant and market-ready.

7. Boosted Confidence and Career Clarity

Sometimes, the biggest obstacle is not lack of knowledge but lack of confidence. A coding brushup for Java full stack developer roles can help reignite your passion for coding, clear doubts, and provide clarity on your career direction.

Whether you’re preparing for a switch, returning to development after a break, or aiming for a promotion, a brushup bootcamp equips you with the confidence and clarity to move forward decisively.

Additionally, many bootcamps offer career services like:

Resume reviews

LinkedIn optimization

Job placement assistance

This complete package ensures that your transition from learning to earning is as smooth as possible.

Final Thoughts

A full stack developer coding brushup bootcamp is more than a crash course—it's a career investment. For aspiring or working professionals looking to refresh their Java skills or upskill for the latest technologies, it offers the perfect blend of theoretical depth, hands-on practice, and career guidance.

With a targeted coding brushup for Java full stack developers, you can fast-track your learning, build an impressive project portfolio, and confidently pursue your next opportunity in the ever-growing tech industry.

Whether you're aiming to enroll in a full stack developer course or simply want to keep your skills sharp, consider a coding brushup bootcamp as your next smart move.

Are you ready to reboot your developer journey? Explore coding brushup programs tailored for Java full stack developers and make the leap today.

[sathcreation]

Full Stack Web Development Coaching at Gritty Tech

Master Full Stack Development with Gritty Tech

If you're looking to build a high-demand career in web development, Gritty Tech's Full Stack Web Development Coaching is the ultimate solution. Designed for beginners, intermediates, and even experienced coders wanting to upskill, our program offers intensive, hands-on training. You will master both front-end and back-end development, preparing you to create complete web applications from scratch For More…

At Gritty Tech, we believe in practical learning. That means you'll not only absorb theory but also work on real-world projects, collaborate in teams, and build a strong portfolio that impresses employers.

Why Choose Gritty Tech for Full Stack Coaching?

Gritty Tech stands out because of our commitment to excellence, personalized mentorship, and career-oriented approach. Here's why you should choose us:

Expert Instructors: Our trainers are seasoned professionals from leading tech companies.

Project-Based Learning: You build real applications, not just toy examples.

Career Support: Resume workshops, interview preparation, and networking events.

Flexible Learning: Evening, weekend, and self-paced options are available.

Community: Join a vibrant community of developers and alumni.

What is Full Stack Web Development?

Full Stack Web Development refers to the creation of both the front-end (client-side) and back-end (server-side) portions of a web application. A full stack developer handles everything from designing user interfaces to managing servers and databases.

Front-End Development

Front-end development focuses on what users see and interact with. It involves technologies like:

HTML5 for structuring web content.

CSS3 for designing responsive and visually appealing layouts.

JavaScript for adding interactivity.

Frameworks like React, Angular, and Vue.js for building scalable web applications.

Back-End Development

Back-end development deals with the server-side, databases, and application logic. Key technologies include:

Node.js, Python (Django/Flask), Ruby on Rails, or Java (Spring Boot) for server-side programming.

Databases like MySQL, MongoDB, and PostgreSQL to store and retrieve data.

RESTful APIs and GraphQL for communication between client and server.

Full Stack Tools and DevOps

Version Control: Git and GitHub.

Deployment: AWS, Heroku, Netlify.

Containers: Docker.

CI/CD Pipelines: Jenkins, GitLab CI.

Gritty Tech Full Stack Coaching Curriculum

Our curriculum is carefully crafted to cover everything a full stack developer needs to know:

1. Introduction to Web Development

Understanding the internet and how web applications work.

Setting up your development environment.

Introduction to Git and GitHub.

2. Front-End Development Mastery

HTML & Semantic HTML: Best practices for accessibility.

CSS & Responsive Design: Media queries, Flexbox, Grid.

JavaScript Fundamentals: Variables, functions, objects, and DOM manipulation.

Modern JavaScript (ES6+): Arrow functions, promises, async/await.

Front-End Frameworks: Deep dive into React.js.

3. Back-End Development Essentials

Node.js & Express.js: Setting up a server, building APIs.

Database Management: CRUD operations with MongoDB.

Authentication & Authorization: JWT, OAuth.

API Integration: Consuming third-party APIs.

4. Advanced Topics

Microservices Architecture: Basics of building distributed systems.

GraphQL: Modern alternative to REST APIs.

Web Security: Preventing common vulnerabilities (XSS, CSRF, SQL Injection).

Performance Optimization: Caching, lazy loading, code splitting.

5. DevOps and Deployment

CI/CD Fundamentals: Automating deployments.

Cloud Services: Hosting apps on AWS, DigitalOcean.

Monitoring & Maintenance: Tools like New Relic and Datadog.

6. Soft Skills and Career Coaching

Resume writing for developers.

Building an impressive LinkedIn profile.

Preparing for technical interviews.

Negotiating job offers.

Real-World Projects You'll Build

At Gritty Tech, you won't just learn; you'll build. Here are some example projects:

E-commerce Website: A full stack shopping platform.

Social Media App: Create a mini version of Instagram.

Task Manager API: Backend API to handle user tasks with authentication.

Real-Time Chat Application: WebSocket-based chat system.

Each project is reviewed by mentors, and feedback is provided to ensure continuous improvement.

Personalized Mentorship and Live Sessions

Our coaching includes one-on-one mentorship to guide you through challenges. Weekly live sessions provide deeper dives into complex topics and allow real-time Q&A. Mentors assist with debugging, architectural decisions, and performance improvements.

Tools and Technologies You Will Master

Languages: HTML, CSS, JavaScript, Python, SQL.

Front-End Libraries/Frameworks: React, Bootstrap, TailwindCSS.

Back-End Technologies: Node.js, Express.js, MongoDB.

Version Control: Git, GitHub.

Deployment: Heroku, AWS, Vercel.

Other Tools: Postman, Figma (for UI design basics).

Student Success Stories

Thousands of students have successfully transitioned into tech roles through Gritty Tech. Some notable success stories:

Amit, from a sales job to Front-End Developer at a tech startup within 6 months.

Priya, a stay-at-home mom, built a portfolio and landed a full stack developer role.

Rahul, a mechanical engineer, became a software engineer at a Fortune 500 company.

Who Should Join This Coaching Program?

This coaching is ideal for:

Beginners with no coding experience.

Working professionals looking to switch careers.

Students wanting to learn industry-relevant skills.

Entrepreneurs building their tech startups.

If you are motivated to learn, dedicated to practice, and open to feedback, Gritty Tech is the right place for you.

Career Support at Gritty Tech

At Gritty Tech, our relationship doesn’t end when you finish the course. We help you land your first job through:

Mock interviews.

Technical assessments.

Building an impressive project portfolio.

Alumni referrals and job placement assistance.

Certifications

After completing the program, you will receive a Full Stack Web Developer Certification from Gritty Tech. This certification is highly respected in the tech industry and will boost your resume significantly.

Flexible Payment Plans

Gritty Tech offers affordable payment plans to make education accessible to everyone. Options include:

Monthly Installments.

Pay After Placement (Income Share Agreement).

Early Bird Discounts.

How to Enroll

Enrolling is easy! Visit Gritty Tech Website and sign up for the Full Stack Web Development Coaching program. Our admissions team will guide you through the next steps.

Frequently Asked Questions (FAQ)

How long does the Full Stack Web Development Coaching at Gritty Tech take?

The program typically spans 6 to 9 months depending on your chosen pace (full-time or part-time).

Do I need any prerequisites?

No prior coding experience is required. We start from the basics and gradually move to advanced topics.

What job roles can I apply for after completing the program?

You can apply for roles like:

Front-End Developer

Back-End Developer

Full Stack Developer

Web Application Developer

Software Engineer

Is there any placement guarantee?

While we don't offer "guaranteed placement," our career services team works tirelessly to help you land a job by providing job referrals, mock interviews, and resume building sessions.

Can I learn at my own pace?

Absolutely. We offer both live cohort-based batches and self-paced learning tracks.

Ready to kickstart your tech career? Join Gritty Tech's Full Stack Web Development Coaching today and transform your future. Visit grittytech.com to learn more and enroll!

[freshparadisepaper]

Software Engineer Resume Examples That Land 6-Figure Jobs

Introduction: Why Your Resume Is Your First Line of Code

When it comes to landing a 6-figure software engineering job, your resume isn’t just a document—it’s your personal algorithm for opportunity.

Recruiters spend an average of 6–8 seconds on an initial resume scan, meaning you have less time than a function call to make an impression. Whether you're a backend expert, front-end developer, or full-stack wizard, structuring your resume strategically can mean the difference between “Interview scheduled” and “Application rejected.”

This guide is packed with real-world engineering resume examples and data-backed strategies to help you craft a resume that breaks through the noise—and lands you the role (and salary) you deserve.

What Makes a Software Engineer Resume Worth 6 Figures?

Before diving into examples, let's outline the key ingredients that top-tier employers look for in high-paying engineering candidates:

Clear technical specialization (e.g., front-end, DevOps, cloud)

Strong project outcomes tied to business value

Demonstrated leadership or ownership

Modern, ATS-friendly formatting

Tailored content for the job role

According to LinkedIn’s 2024 Emerging Jobs Report, software engineers with cloud, AI/ML, and DevOps experience are the most in-demand, with average salaries exceeding $120,000 annually in the U.S.

Structuring the Perfect Software Engineer Resume

Here’s a proven framework used in many successful engineering resume examples that landed six-figure jobs:

1. Header and Contact Information

Keep it clean and professional. Include:

Full name

Email (professional)

GitHub/Portfolio/LinkedIn URL

Phone number

2. Professional Summary (3–4 Lines)

Use this space to summarize your experience, key technologies, and what makes you stand out.

Example: "Full-stack software engineer with 7+ years of experience building scalable web applications using React, Node.js, and AWS. Passionate about clean code, continuous delivery, and solving real-world business problems."

3. Technical Skills (Grouped by Category)

Format matters here—grouping helps recruiters scan quickly.

Languages: JavaScript, Python, Java

Frameworks: React, Django, Spring Boot

Tools/Platforms: Git, Docker, AWS, Kubernetes, Jenkins

Databases: MySQL, MongoDB, PostgreSQL

4. Experience (Show Impact, Not Just Tasks)

Use action verbs + quantifiable results + technologies used.

Example:

Designed and implemented a microservices architecture using Spring Boot and Docker, improving system uptime by 35%.

Migrated legacy systems to AWS, cutting infrastructure costs by 25%.

Led a team of 4 engineers to launch a mobile banking app that acquired 100,000+ users in 6 months.

5. Education

List your degree(s), university name, and graduation date. If you're a recent grad, include relevant coursework.

6. Projects (Optional but Powerful)

Projects are crucial for junior engineers or those transitioning into tech. Highlight the challenge, your role, the tech stack, and outcomes.

Real-World Engineering Resume Examples (For Inspiration)

Example 1: Backend Software Engineer Resume (Mid-Level)

Summary: Backend developer with 5+ years of experience in building RESTful APIs using Python and Django. Focused on scalable architecture and robust database design.

Experience:

Developed a REST API using Django and PostgreSQL, powering a SaaS platform with 10k+ daily users.

Implemented CI/CD pipelines with Jenkins and Docker, reducing deployment errors by 40%.

Skills: Python, Django, PostgreSQL, Git, Docker, Jenkins, AWS

Why It Works: It’s direct, results-focused, and highlights technical depth aligned with backend engineering roles.

Example 2: Front-End Engineer Resume (Senior Level)

Summary: Senior front-end developer with 8 years of experience crafting responsive and accessible web interfaces. Strong advocate of performance optimization and user-centered design.

Experience:

Led UI redevelopment of an e-commerce platform using React, increasing conversion rate by 22%.

Integrated Lighthouse audits to enhance Core Web Vitals, resulting in 90+ scores across all pages.

Skills: JavaScript, React, Redux, HTML5, CSS3, Webpack, Jest

Why It Works: Focuses on user experience, performance metrics, and modern front-end tools—exactly what senior roles demand.

Example 3: DevOps Engineer Resume (6-Figure Role)

Summary: AWS-certified DevOps engineer with 6 years of experience automating infrastructure and improving deployment pipelines for high-traffic platforms.

Experience:

Automated infrastructure provisioning using Terraform and Ansible, reducing setup time by 70%.

Optimized Kubernetes deployment workflows, enabling blue-green deployments across services.

Skills: AWS, Docker, Kubernetes, Terraform, CI/CD, GitHub Actions

Why It Works: It highlights automation, scalability, and cloud—all high-value skills for 6-figure DevOps roles.

ATS-Proofing Your Resume: Best Practices

Applicant Tracking Systems are a major hurdle—especially in tech. Here’s how to beat them:

Use standard headings like “Experience” or “Skills”

Avoid tables, columns, or excessive graphics

Use keywords from the job description naturally

Save your resume as a PDF unless instructed otherwise

Many successful candidates borrow formatting cues from high-performing engineering resume examples available on reputable sites like GitHub, Resume.io, and Zety.

Common Mistakes That Can Cost You the Job

Avoid these pitfalls if you’re targeting 6-figure roles:

Listing outdated or irrelevant tech (e.g., Flash, VBScript)

Using vague responsibilities like “worked on the website”

Failing to show impact or metrics

Forgetting to link your GitHub or portfolio

Submitting the same resume to every job

Each job should have a slightly tailored resume. The effort pays off.

Bonus Tips: Add a Competitive Edge

Certifications: AWS, Google Cloud, Kubernetes, or relevant coding bootcamps

Contributions to open source projects on GitHub

Personal projects with real-world use cases

Blog or technical writing that demonstrates thought leadership

Conclusion: Turn Your Resume Into a Career-Launching Tool

Crafting a winning software engineer resume isn’t just about listing skills—it’s about telling a compelling story of how you create value, solve problems, and ship scalable solutions.

The best engineering resume examples strike a perfect balance between clarity, credibility, and customization. Whether you're a bootcamp grad or a seasoned engineer, investing time into your resume is one of the highest ROI career moves you can make.

👉 Visit our website for professionally designed templates, expert tips, and more examples to help you land your dream role—faster.

[learning-code-ficusoft]

A Guide to Creating APIs for Web Applications

APIs (Application Programming Interfaces) are the backbone of modern web applications, enabling communication between frontend and backend systems, third-party services, and databases. In this guide, we’ll explore how to create APIs, best practices, and tools to use.

1. Understanding APIs in Web Applications

An API allows different software applications to communicate using defined rules. Web APIs specifically enable interaction between a client (frontend) and a server (backend) using protocols like REST, GraphQL, or gRPC.

Types of APIs

RESTful APIs — Uses HTTP methods (GET, POST, PUT, DELETE) to perform operations on resources.

GraphQL APIs — Allows clients to request only the data they need, reducing over-fetching.

gRPC APIs — Uses protocol buffers for high-performance communication, suitable for microservices.

2. Setting Up a REST API: Step-by-Step

Step 1: Choose a Framework

Node.js (Express.js) — Lightweight and popular for JavaScript applications.

Python (Flask/Django) — Flask is simple, while Django provides built-in features.

Java (Spring Boot) — Enterprise-level framework for Java-based APIs.

Step 2: Create a Basic API

Here’s an example of a simple REST API using Express.js (Node.js):javascriptconst express = require('express'); const app = express(); app.use(express.json());let users = [{ id: 1, name: "John Doe" }];app.get('/users', (req, res) => { res.json(users); });app.post('/users', (req, res) => { const user = { id: users.length + 1, name: req.body.name }; users.push(user); res.status(201).json(user); });app.listen(3000, () => console.log('API running on port 3000'));

Step 3: Connect to a Database

APIs often need a database to store and retrieve data. Popular databases include:

SQL Databases (PostgreSQL, MySQL) — Structured data storage.

NoSQL Databases (MongoDB, Firebase) — Unstructured or flexible data storage.

Example of integrating MongoDB using Mongoose in Node.js:javascriptconst mongoose = require('mongoose'); mongoose.connect('mongodb://localhost:27017/mydb', { useNewUrlParser: true, useUnifiedTopology: true });const UserSchema = new mongoose.Schema({ name: String }); const User = mongoose.model('User', UserSchema);app.post('/users', async (req, res) => { const user = new User({ name: req.body.name }); await user.save(); res.status(201).json(user); });

3. Best Practices for API Development

🔹 Use Proper HTTP Methods:

GET – Retrieve data

POST – Create new data

PUT/PATCH – Update existing data

DELETE – Remove data

🔹 Implement Authentication & Authorization

Use JWT (JSON Web Token) or OAuth for securing APIs.

Example of JWT authentication in Express.js:

javascript

const jwt = require('jsonwebtoken'); const token = jwt.sign({ userId: 1 }, 'secretKey', { expiresIn: '1h' });

🔹 Handle Errors Gracefully

Return appropriate status codes (400 for bad requests, 404 for not found, 500 for server errors).

Example:

javascript

app.use((err, req, res, next) => { res.status(500).json({ error: err.message }); });

🔹 Use API Documentation Tools

Swagger or Postman to document and test APIs.

4. Deploying Your API

Once your API is built, deploy it using:

Cloud Platforms: AWS (Lambda, EC2), Google Cloud, Azure.

Serverless Functions: AWS Lambda, Vercel, Firebase Functions.

Containerization: Deploy APIs using Docker and Kubernetes.

Example: Deploying with DockerdockerfileFROM node:14 WORKDIR /app COPY package.json ./ RUN npm install COPY . . CMD ["node", "server.js"] EXPOSE 3000

5. API Testing and Monitoring

Use Postman or Insomnia for testing API requests.

Monitor API Performance with tools like Prometheus, New Relic, or Datadog.

Final Thoughts

Creating APIs for web applications involves careful planning, development, and deployment. Following best practices ensures security, scalability, and efficiency.

WEBSITE: https://www.ficusoft.in/python-training-in-chennai/

[itbeatsbookmarks]

(Via: Hacker News)

Today’s developers are expected to develop resilient and scalable distributed systems. Systems that are easy to patch in the face of security concerns and easy to do low-risk incremental upgrades. Systems that benefit from software reuse and innovation of the open source model. Achieving all of this for different languages, using a variety of application frameworks with embedded libraries is not possible.

Recently I’ve blogged about “Multi-Runtime Microservices Architecture” where I have explored the needs of distributed systems such as lifecycle management, advanced networking, resource binding, state abstraction and how these abstractions have been changing over the years. I also spoke about “The Evolution of Distributed Systems on Kubernetes” covering how Kubernetes Operators and the sidecar model are acting as the primary innovation mechanisms for delivering the same distributed system primitives.

On both occasions, the main takeaway is the prediction that the progression of software application architectures on Kubernetes moves towards the sidecar model managed by operators. Sidecars and operators could become a mainstream software distribution and consumption model and in some cases even replace software libraries and frameworks as we are used to.

The sidecar model allows the composition of applications written in different languages to deliver joint value, faster and without the runtime coupling. Let’s see a few concrete examples of sidecars and operators, and then we will explore how this new software composition paradigm could impact us.

Out-of-Process Smarts on the Rise

In Kubernetes, a sidecar is one of the core design patterns achieved easily by organizing multiple containers in a single Pod. The Pod construct ensures that the containers are always placed on the same node and can cooperate by interacting over networking, file system or other IPC methods. And operators allow the automation, management and integration of the sidecars with the rest of the platform. The sidecars represent a language-agnostic, scalable data plane offering distributed primitives to custom applications. And the operators represent their centralized management and control plane.

Let’s look at a few popular manifestations of the sidecar model.

Envoy

Service Meshes such as Istio, Consul, and others are using transparent service proxies such as Envoy for delivering enhanced networking capabilities for distributed systems. Envoy can improve security, it enables advanced traffic management, improves resilience, adds deep monitoring and tracing features. Not only that, it understands more and more Layer 7 protocols such as Redis, MongoDB, MySQL and most recently Kafka. It also added response caching capabilities and even WebAssembly support that will enable all kinds of custom plugins. Envoy is an example of how a transparent service proxy adds advanced networking capabilities to a distributed system without including them into the runtime of the distributed application components.

Skupper

In addition to the typical service mesh, there are also projects, such as Skupper, that ship application networking capabilities through an external agent. Skupper solves multicluster Kubernetes communication challenges through a Layer 7 virtual network and offers advanced routing and connectivity capabilities. But rather than embedding Skupper into the business service runtime, it runs an instance per Kubernetes namespace which acts as a shared sidecar.

Cloudstate

Cloudstate is another example of the sidecar model, but this time for providing stateful abstractions for the serverless development model. It offers stateful primitives over GRPC for EventSourcing, CQRS, Pub/Sub, Key/Value stores and other use cases. Again, it an example of sidecars and operators in action but this time for the serverless programming model.

Dapr

Dapr is a relatively young project started by Microsoft, and it is also using the sidecar model for providing developer-focused distributed system primitives. Dapr offers abstractions for state management, service invocation and fault handling, resource bindings, pub/sub, distributed tracing and others. Even though there is some overlap in the capabilities provided by Dapr and Service Mesh, both are very different in nature. Envoy with Istio is injected and runs transparently from the service and represents an operational tool. Dapr, on the other hand, has to be called explicitly from the application runtime over HTTP or gRPC and it is an explicit sidecar targeted for developers. It is a library for distributed primitives that is distributed and consumed as a sidecar, a model that may become very attractive for developers consuming distributed capabilities.

Camel K

Apache Camel is a mature integration library that rediscovers itself on Kubernetes. Its subproject Camel K uses heavily the operator model to improve the developer experience and integrate deeply with the Kubernetes platform. While Camel K does not rely on a sidecar, through its CLI and operator it is able to reuse the same application container and execute any local code modification in a remote Kubernetes cluster in less than a second. This is another example of developer-targeted software consumption through the operator model.

More to Come

And these are only some of the pioneer projects exploring various approaches through sidecars and operators. There is more work being done to reduce the networking overhead introduced by container-based distributed architectures such as the data plane development kit (DPDK), which is a userspace application that bypasses the layers of the Linux kernel networking stack and access directly to the network hardware. There is work in the Kubernetes project to create sidecar containers with more granular lifecycle guarantees. There are new Java projects based on GraalVM implementation such as Quarkus that reduce the resource consumption and application startup time which makes more workloads attractive for sidecars. All of these innovations will make the side-car model more attractive and enable the creation of even more such projects.

Sidecars providing distributed systems primitives

I’d not be surprised to see projects coming up around more specific use cases such as stateful orchestration of long-running processes such as Business Process Model and Notation (BPMN) engines in sidecars. Job schedulers in sidecars. Stateless integration engines i.e. Enterprise Integration Patterns implementations in sidecars. Data abstractions and data federation engines in sidecars. OAuth2/OpenID proxy in sidecars. Scalable database connection pools for serverless workloads in sidecars. Application networks as sidecars, etc. But why would software vendors and developers switch to this model? Let’s see a few of the benefits it provides.

Runtimes with Control Planes over Libraries

If you are a software vendor today, probably you have already considered offering your software to potential users as an API or a SaaS-based solution. This is the fastest software consumption model and a no-brainer to offer, when possible. Depending on the nature of the software you may be also distributing your software as a library or a runtime framework. Maybe it is time to consider if it can be offered as a container with an operator too. This mechanism of distributing software and the resulting architecture has some very unique benefits that the library mechanism cannot offer.

Supporting Polyglot Consumers

By offering libraries to be consumable through open protocols and standards, you open them up for all programming languages. A library that runs as a sidecar and consumable over HTTP, using a text format such as JSON does not require any specific client runtime library. Even when gRPC and Protobuf are used for low-latency and high-performance interactions, it is still easier to generate such clients than including third party custom libraries in the application runtime and implement certain interfaces.

Application Architecture Agnostic

The explicit sidecar architecture (as opposed to the transparent one) is a way of software capability consumption as a separate runtime behind a developer-focused API. It is an orthogonal feature that can be added to any application whether that is monolithic, microservices, functions-based, actor-based or anything in between. It can sit next to a monolith in a less dynamic environment, or next to every microservice in a dynamic cloud-based environment. It is trivial to create sidecars on Kubernetes, and doable on many other software orchestration platforms too.

Tolerant to Release Impedance Mismatch

Business logic is always custom and developed in house. Distributed system primitives are well-known commodity features, and consumed off-the-shelf as either platform features or runtime libraries. You might be consuming software for state abstractions, messaging clients, networking resiliency and monitoring libraries, etc. from third-party open source projects or companies. And these third party entities have their release cycles, critical fixes, CVE patches that impact your software release cycles too. When third party libraries are consumed as a separate runtime (sidecar), the upgrade process is simpler as it is behind an API and it is not coupled with your application runtime. The release impedance mismatch between your team and the consumed 3rd party libraries vendors becomes easier to manage.

Control Plane Included Mentality

When a feature is consumed as a library, it is included in your application runtime and it becomes your responsibility to understand how it works, how to configure, monitor, tune and upgrade. That is because the language runtimes (such as the JVM) and the runtime frameworks (such as Spring Boot or application servers) dictate how a third-party library can be included, configured, monitored and upgraded. When a software capability is consumed as a separate runtime (such as a sidecar or standalone container) it comes with its own control plane in the form of a Kubernetes operator.

That has a lot of benefits as the control plane understands the software it manages (the operand) and comes with all the necessary management intelligence that otherwise would be distributed as documentation and best practices. What’s more, operators also integrate deeply with Kubernetes and offer a unique blend of platform integration and operand management intelligence out-of-the-box. Operators are created by the same developers who are creating the operands, they understand the internals of the containerized features and know how to operate the best. Operators are executables SREs in containers, and the number of operators and their capabilities are increasing steadily with more operators and marketplaces coming up.

Software Distribution and Consumption in the Future

Software Distributed as Sidecars with Control Planes

Let’s say you are a software provider of a Java framework. You may distribute it as an archive or a Maven artifact. Maybe you have gone a step further and you distribute a container image. In either case, in today’s cloud-native world, that is not good enough. The users still have to know how to patch and upgrade a running application with zero downtime. They have to know what to backup and restore its state. They have to know how to configure their monitoring and alerting thresholds. They have to know how to detect and recover from complex failures. They have to know how to tune an application based on the current load profile.

In all of these and similar scenarios, intelligent control planes in the form of Kubernetes operators are the answer. An operator encapsulates platform and domain knowledge of an application in a declaratively configured component to manage the workload.

Sidecars and operators could become a mainstream software distribution and consumption model and in some cases even replace software libraries and frameworks as we are used to.

Let’s assume that you are providing a software library that is included in the consumer applications as a dependency. Maybe it is the client-side library of the backend framework described above. If it is in Java, for example, you may have certified it to run it on a JEE server, provided Spring Boot Starters, Builders, Factories, and other implementations that are all hidden behind a clean Java interface. You may have even backported it to .Net too.

With Kubernetes operators and sidecars all of that is hidden from the consumer. The factory classes are replaced by the operator, and the only configuration interface is a YAML file for the custom resource. The operator is then responsible for configuring the software and the platform so that users can consume it as an explicit sidecar, or a transparent proxy. In all cases, your application is available for consumption over remote API and fully integrated with the platform features and even other dependent operators. Let’s see how that happens.

Software Consumed over Remote APIs Rather than Embedded Libraries

One way to think about sidecars is similar to the composition over inheritance principle in OOP, but in a polyglot context. It is a different way of organizing the application responsibilities by composing capabilities from different processes rather than including them into a single application runtime as dependencies. When you consume software as a library, you instantiate a class, call its methods by passing some value objects. When you consume it as an out-of-process capability, you access a local process. In this model, methods are replaced with APIs, in-process methods invocation with HTTP or gRPC invocations, and value objects with something like CloudEvents. This is a change from application servers to Kubernetes as the distributed runtime. A change from language-specific interfaces, to remote APIs. From in-memory calls to HTTP, from value objects to CloudEvents, etc.

This requires software providers to distribute containers and controllers to operate them. To create IDEs that are capable of building and debugging multiple runtime services locally. CLIs for quickly deploying code changes into Kubernetes and configuring the control planes. Compilers that can decide what to compile in a custom application runtime, what capabilities to consume from a sidecar and what from the orchestration platform.

Software consumers and providers ecosystem

In the longer term, this will lead to the consolidation of standardized APIs that are used for the consumption of common primitives in sidecars. Rather than language-specific standards and APIs we will have polyglot APIs. For example, rather than Java Database Connectivity (JDBC) API, caching API for Java (JCache), Java Persistence API (JPA), we will have polyglot APIs over HTTP using something like CloudEvents. Sidecar centric APIs for messaging, caching, reliable networking, cron jobs and timer scheduling, resource bindings (connectors to other APIs, protocols), idempotency, SAGAs, etc. And all of these capabilities will be delivered with the management layer included in the form of operators and even wrapped with self-service UIs. The operators are key enablers here as they will make this even more distributed architecture easy to manage and self-operate on Kubernetes. The management interface of the operator is defined by the CustomResourceDefinition and represents another public-facing API that remains application-specific.

This is a big shift in mentality to a different way of distributing and consuming software, driven by the speed of delivery and operability. It is a shift from a single runtime to multi runtime application architectures. It is a shift similar to what the hardware industry had to go through from single-core to multicore platforms when Moore’s law ended. It is a shift that is slowly happening by building all the elements of the puzzle: we have uniformly adopted and standardized containers, we have a de facto standard for orchestration through Kubernetes, possibly improved sidecars coming soon, rapid operators adoption, CloudEvents as a widely agreed standard, light runtimes such as Quarkus, etc. With the foundation in place, applications, productivity tools, practices, standardized APIs, and ecosystem will come too.

This post was originally published at ​The New Stack here.

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What’s After the MEAN Stack?

Introduction

We reach for software stacks to simplify the endless sea of choices. The MEAN stack is one such simplification that worked very well in its time. Though the MEAN stack was great for the last generation, we need more; in particular, more scalability. The components of the MEAN stack haven’t aged well, and our appetites for cloud-native infrastructure require a more mature approach. We need an updated, cloud-native stack that can boundlessly scale as much as our users expect to deliver superior experiences.

 Stacks

When we look at software, we can easily get overwhelmed by the complexity of architectures or the variety of choices. Should I base my system on Python?  Or is Go a better choice? Should I use the same tools as last time? Or should I experiment with the latest hipster toolchain? These questions and more stymie both seasoned and newbie developers and architects.

 Some patterns emerged early on that help developers quickly provision a web property to get started with known-good tools. One way to do this is to gather technologies that work well together in “stacks.” A “stack” is not a prescriptive validation metric, but rather a guideline for choosing and integrating components of a web property. The stack often identifies the OS, the database, the web server, and the server-side programming language.

 In the earliest days, the famous stacks were the “LAMP-stack” and the “Microsoft-stack”. The LAMP stack represents Linux, Apache, MySQL, and PHP or Python. LAMP is an acronym of these product names. All the components of the LAMP stack are open source (though some of the technologies have commercial versions), so one can use them completely for free. The only direct cost to the developer is the time to build the experiment.

 The “Microsoft stack” includes Windows Server, SQL Server, IIS (Internet Information Services), and ASP (90s) or ASP.NET (2000s+). All these products are tested and sold together.

 Stacks such as these help us get started quickly. They liberate us from decision fatigue, so we can focus instead on the dreams of our start-up, or the business problems before us, or the delivery needs of internal and external stakeholders. We choose a stack, such as LAMP or the Microsoft stack, to save time.

 In each of these two example legacy stacks, we’re producing web properties. So no matter what programming language we choose, the end result of a browser’s web request is HTML, JavaScript, and CSS delivered to the browser. HTML provides the content, CSS makes it pretty, and in the early days, JavaScript was the quick form-validation experience. On the server, we use the programming language to combine HTML templates with business data to produce rendered HTML delivered to the browser.

 We can think of this much like mail merge: take a Word document with replaceable fields like first and last name, add an excel file with columns for each field, and the engine produces a file for each row in the sheet.

 As browsers evolved and JavaScript engines were tuned, JavaScript became powerful enough to make real-time, thick-client interfaces in the browser. Early examples of this kind of web application are Facebook and Google Maps.

 These immersive experiences don’t require navigating to a fresh page on every button click. Instead, we could dynamically update the app as other users created content, or when the user clicks buttons in the browser. With these new capabilities, a new stack was born: the MEAN stack.

 What is the MEAN Stack?

The MEAN stack was the first stack to acknowledge the browser-based thick client. Applications built on the MEAN stack primarily have user experience elements built in JavaScript and running continuously in the browser. We can navigate the experiences by opening and closing items, or by swiping or drilling into things. The old full-page refresh is gone.

 The MEAN stack includes MongoDB, Express.js, Angular.js, and Node.js. MEAN is the acronym of these products. The back-end application uses MongoDB to store its data as binary-encoded JavaScript Object Notation (JSON) documents. Node.js is the JavaScript runtime environment, allowing you to do backend, as well as frontend, programming in JavaScript. Express.js is the back-end web application framework running on top of Node.js. And Angular.js is the front-end web application framework, running your JavaScript code in the user’s browser. This allows your application UI to be fully dynamic.

 Unlike previous stacks, both the programming language and operating system aren’t specified, and for the first time, both the server framework and browser-based client framework are specified.

 In the MEAN stack, MongoDB is the data store. MongoDB is a NoSQL database, making a stark departure from the SQL-based systems in previous stacks. With a document database, there are no joins, no schema, no ACID compliance, and no transactions. What document databases offer is the ability to store data as JSON, which easily serializes from the business objects already used in the application. We no longer have to dissect the JSON objects into third normal form to persist the data, nor collect and rehydrate the objects from disparate tables to reproduce the view.

 The MEAN stack webserver is Node.js, a thin wrapper around Chrome’s V8 JavaScript engine that adds TCP sockets and file I/O. Unlike previous generations’ web servers, Node.js was designed in the age of multi-core processors and millions of requests. As a result, Node.js is asynchronous to a fault, easily handling intense, I/O-bound workloads. The programming API is a simple wrapper around a TCP socket.

 In the MEAN stack, JavaScript is the name of the game. Express.js is the server-side framework offering an MVC-like experience in JavaScript. Angular (now known as Angular.js or Angular 1) allows for simple data binding to HTML snippets. With JavaScript both on the server and on the client, there is less context switching when building features. Though the specific features of Express.js’s and Angular.js’s frameworks are quite different, one can be productive in each with little cross-training, and there are some ways to share code between the systems.

 The MEAN stack rallied a web generation of start-ups and hobbyists. Since all the products are free and open-source, one can get started for only the cost of one’s time. Since everything is based in JavaScript, there are fewer concepts to learn before one is productive. When the MEAN stack was introduced, these thick-client browser apps were fresh and new, and the back-end system was fast enough, for new applications, that database durability and database performance seemed less of a concern.

 The Fall of the MEAN Stack

The MEAN stack was good for its time, but a lot has happened since. Here’s an overly brief history of the fall of the MEAN stack, one component at a time.

 Mongo got a real bad rap for data durability. In one Mongo meme, it was suggested that Mongo might implement the PLEASE keyword to improve the likelihood that data would be persisted correctly and durably. (A quick squint, and you can imagine the XKCD comic about “sudo make me a sandwich.”) Mongo also lacks native SQL support, making data retrieval slower and less efficient.

 Express is aging, but is still the defacto standard for Node web apps and apis. Much of the modern frameworks — both MVC-based and Sinatra-inspired — still build on top of Express. Express could do well to move from callbacks to promises, and better handle async and await, but sadly, Express 5 alpha hasn’t moved in more than a year.

 Angular.js (1.x) was rewritten from scratch as Angular (2+). Arguably, the two products are so dissimilar that they should have been named differently. In the confusion as the Angular reboot was taking shape, there was a very unfortunate presentation at an Angular conference.

 The talk was meant to be funny, but it was not taken that way. It showed headstones for many of the core Angular.js concepts, and sought to highlight how the presenters were designing a much easier system in the new Angular.

 Sadly, this message landed really wrong. Much like the community backlash to Visual Basic’s plans they termed Visual Fred, the community was outraged. The core tenets they trusted every day for building highly interactive and profitable apps were getting thrown away, and the new system wouldn’t be ready for a long time. Much of the community moved on to React, and now Angular is struggling to stay relevant. Arguably, Angular’s failure here was the biggest factor in React’s success — much more so than any React initiative or feature.

 Nowadays many languages’ frameworks have caught up to the lean, multi-core experience pioneered in Node and Express. ASP.NET Core brings a similarly light-weight experience, and was built on top of libuv, the OS-agnostic socket framework, the same way Node was. Flask has brought light-weight web apps to Python. Ruby on Rails is one way to get started quickly. Spring Boot brought similar microservices concepts to Java. These back-end frameworks aren’t JavaScript, so there is more context switching, but their performance is no longer a barrier, and strongly-typed languages are becoming more in vogue.

 As a further deterioration of the MEAN stack, there are now frameworks named “mean,” including mean.io and meanjs.org and others. These products seek to capitalize on the popularity of the “mean” term. Sometimes it offers more options on the original MEAN products, sometimes scaffolding around getting started faster, sometimes merely looking to cash in on the SEO value of the term.

 With MEAN losing its edge, many other stacks and methodologies have emerged.

 The JAM Stack

The JAM stack is the next evolution of the MEAN stack. The JAM stack includes JavaScript, APIs, and Markup. In this stack, the back-end isn’t specified – neither the webserver, the back-end language, or the database.

 In the JAM stack we use JavaScript to build a thick client in the browser, it calls APIs, and mashes the data with Markup — likely the same HTML templates we would build in the MEAN stack. The JavaScript frameworks have evolved as well. The new top contenders are React, Vue.js, and Angular, with additional players from Svelte, Auralia, Ember, Meteor, and many others.

 The frameworks have mostly standardized on common concepts like virtual dom, 1-way data binding, and web components. Each framework then combines these concepts with the opinions and styles of the author.

 The JAM stack focuses exclusively on the thick-client browser environment, merely giving a nod to the APIs, as if magic happens behind there. This has given rise to backend-as-a-service products like Firebase, and API innovations beyond REST including gRPC and GraphQL. But, just as legacy stacks ignored the browser thick-client, the JAM stack marginalizes the backend, to our detriment.

 Maturing Application Architecture

As the web and the cloud have matured, as system architects, we have also matured in our thoughts of how to design web properties.

 As technology has progressed, we’ve gotten much better at building highly scalable systems. Microservices offer a much different application model where simple pieces are arranged into a mesh. Containers offer ephemeral hardware that’s easy to spin up and replace, leading to utility computing.

 As consumers and business users of systems, we almost take for granted that a system will be always on and infinitely scalable. We don’t even consider the complexity of geo-replication of data or latency of trans-continental communication. If we need to wait more than a second or two, we move onto the next product or the next task.

 With these maturing tastes, we now take for granted that an application can handle near infinite load without degradation to users, and that features can be upgraded and replaced without downtime. Imagine the absurdity if Google Maps went down every day at 10 pm so they could upgrade the system, or if Facebook went down if a million people or more posted at the same time.

 We now take for granted that our applications can scale, and the naive LAMP and MEAN stacks are no longer relevant.

 Characteristics of the Modern Stack

What does the modern stack look like?  What are the elements of a modern system?  I propose a modern system is cloud-native, utility-billed, infinite-scale, low-latency, user-relevant using machine learning, stores and processes disparate data types and sources, and delivers personalized results to each user. Let’s dig into these concepts.

 A modern system allows boundless scale. As a business user, I can’t handle if my system gets slow when we add more users. If the site goes viral, it needs to continue serving requests, and if the site is seasonally slow, we need to turn down the spend to match revenue. Utility billing and cloud-native scale offers this opportunity. Mounds of hardware are available for us to scale into immediately upon request. If we design stateless, distributed systems, additional load doesn’t produce latency issues.

 A modern system processes disparate data types and sources. Our systems produce logs of unstructured system behavior and failures. Events from sensors and user activity flood in as huge amounts of time-series events. Users produce transactions by placing orders or requesting services. And the product catalog or news feed is a library of documents that must be rendered completely and quickly. As users and stakeholders consume the system’s features, they don’t want or need to know how this data is stored or processed. They need only see that it’s available, searchable, and consumable.

 A modern system produces relevant information. In the world of big data, and even bigger compute capacity, it’s our task to give users relevant information from all sources. Machine learning models can identify trends in data, suggesting related activities or purchases, delivering relevant, real-time results to users. Just as easily, these models can detect outlier activities that suggest fraud. As we gain trust in the insights gained from these real-time analytics, we can empower the machines to make decisions that deliver real business value to our organization.

 MemSQL is the Modern Stack’s Database

Whether you choose to build your web properties in Java or C#, in Python or Go, in Ruby or JavaScript, you need a data store that can elastically and boundlessly scale with your application. One that solves the problems that Mongo ran into – that scales effortlessly, and that meets ACID guarantees for data durability.

 We also need a database that supports the SQL standard for data retrieval. This brings two benefits: a SQL database “plays well with others,” supporting the vast number of tools out there that interface to SQL, as well as the vast number of developers and sophisticated end users who know SQL code. The decades of work that have gone into honing the efficiency of SQL implementations is also worth tapping into.

 These requirements have called forth a new class of databases, which go by a variety of names; we will use the term NewSQL here. A NewSQL database is distributed, like Mongo, but meets ACID guarantees, providing durability, along with support for SQL. CockroachDB and Google Spanner are examples of NewSQL databases.

 We believe that MemSQL brings the best SQL, distributed, and cloud-native story to the table. At the core of MemSQL is the distributed database. In the database’s control plane is a master node and other aggregator nodes responsible for splitting the query across leaf nodes, and combining the results into deterministic data sets. ACID-compliant transactions ensure each update is durably committed to the data partitions, and available for subsequent requests. In-memory skiplists speed up seeking and querying data, and completely avoid data locks.

 MemSQL Helios delivers the same boundless scale engine as a managed service in the cloud. No longer do you need to provision additional hardware or carve out VMs. Merely drag a slider up or down to ensure the capacity you need is available.

 MemSQL is able to ingest data from Kafka streams, from S3 buckets of data stored in JSON, CSV, and other formats, and deliver the data into place without interrupting real-time analytical queries. Native transforms allow shelling out into any process to transform or augment the data, such as calling into a Spark ML model.

 MemSQL stores relational data, stores document data in JSON columns, provides time-series windowing functions, allows for super-fast in-memory rowstore tables snapshotted to disk and disk-based columnstore data, heavily cached in memory.

 As we craft the modern app stack, include MemSQL as your durable, boundless cloud-native data store of choice.

 Conclusion

Stacks have allowed us to simplify the sea of choices to a few packages known to work well together. The MEAN stack was one such toolchain that allowed developers to focus less on infrastructure choices and more on developing business value.

 Sadly, the MEAN stack hasn’t aged well. We’ve moved on to the JAM stack, but this ignores the back-end completely.

 As our tastes have matured, we assume more from our infrastructure. We need a cloud-native advocate that can boundlessly scale, as our users expect us to deliver superior experiences. Try MemSQL for free today, or contact us for a personalized demo.[Source]-https://www.memsql.com/blog/whats-after-the-mean-stack/

62 Hours Mean Stack Developer Training  includes MongoDB, JavaScript, A62 angularJS Training, MongoDB, Node JS and live Project Development. Demo Mean Stack Training available.

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Fwd: Urgent requirements of below positions.

New Post has been published on https://www.hireindian.in/fwd-urgent-requirements-of-below-positions-10/

Fwd: Urgent requirements of below positions.

We have an opportunity for below positions. Please see the job details below and let me know if you would be interested in this role. If interested, please send me a copy of your updated resume, your contact details, your availability and a good time to connect with you.

    Technical  Architect-eCommerce——>Rochester, New York Technical Lead-Java, J2EE—–>New York, NY Sr. ETL Architect———>Teaneck, NJ Sr. Solution Architect——->Media, PA SQL-Server/SSAS person with Azure——->Ewing, New Jersey Sr. Linux Administrator——>Seattle, WA/ Austin, TX/ Dallas, TX Onsite Workday HCM Functional Consultant——->Sunnyvale, CA

    Job Description

Job title : Technical  Architect-eCommerce

 Location : Rochester, New York

Duration : 1 Year

Mandatory Skills : eCommerce Architect

      Job description :

1.    8+ Years’ experience in Leading and developing prototype eCommerce applications.

2.     Proficient in Designing and implementing eCommerce application development projects.

3.     Research, assess and lead the initiation of new technologies to maximize performance.

4.    Monitor problem solving initiatives and resolve complex issues.

5.     Initiate and implement architecture level quality control reviews.

6.     Collaborate with other architects to update architecture documents and other development processes documents.

7.     Create prototypes and working examples to drive solutions.

  Position: Technical Lead-Java, J2EE

Location: New York, NY

Duration: 1 Year

Work Authorization: USC/GC/H1/L2/ANY

    Job Description: 

Video streaming, video file formatting, java, j2ee, broadcasting domain

Improve the operational systems, processes and policies in support of organizations mission — specifically, support better management reporting, information flow and management, business process planning.

Manage and increase the effectiveness and efficiency of Support Services through improvements to each function as well as coordination and communication between support and business functions.

Play a significant role in long-term planning, including an initiative geared toward operational excellence.

Develop skills to be the SME for each applications under your track

Act as SME to expedite and remediate application's critical issues and escalations

Take the lead to research and investigate the most complex questions or application defects using traces, dumps, debuggers, reviewing application source code, or diagnostic software tools

Review issue backlogs of engineers to provide mentoring and conduct Issue reviews to coach your functional team members

Own, Plan, Conduct trainings as and when you feel the team needs it

Improve the team members on the application skill matrix.

Creation of technical documents for complex issues, known errors and standard operating procedures

Take ownership of queries raised by the team and ensure quicker resolution

Ensure weekly reports are sent across at the EOD Friday

Create Change request and represent team in change control board.

Write and Review Deployment plans. Assist in application release process

Identity incident trends and provide proactive solution to problem tickets

Preform RCA for outages and provide Future avoidance plans/changes

Position: Sr. ETL Architect

Location: Teaneck, NJ

Duration: 10 months+

  Job Description: 

Primary skills – Informatica On premise, Informatica Cloud, Informatica Real Time Integration 

Rich years experienced Information Management & Data Analytics professional with expertise working in projects developing Enterprise wide Data Warehouse / Integration solution, Operational Data store, ETL applications and Business Analytics solutions using Informatica / Other integration tools

Experience in Informatica cloud integrations –  Batch integrations using ICS and REAL time integrations using ICRT

Solid experience in defining & designing the Data & Integration Architecture for BI programs

Proficiency in leading ETL & DI projects involving ETL tools, including INFORMATICA with primary databases as Teradata, Oracle, Azure SQL DW, SQL Server

Understanding and experience in CDC (Change data capture) implementations

Experience in Metadata management, Data Quality / Audit-Balancing / RI frameworks

Implement best practices and frameworks to ensure the solution to fully comply with data quality standards, architectural guidelines & recommendations

Thorough understanding of Software Development Life Cycle (SDLC), exposure to Waterfall & Agile Methodologies;

  Position: Sr. Solution Architect

Location: Media, PA

Duration: Long term

Experience: 13 Years

    Job Description: 

Architect with at least 13yrs of experience who has

Expert level programming skills in Java

Experience with TDD utilizing Mocking and similar concepts

Strong understanding of Microservices architectures

Experience with technologies used for service registry like Zookeeper, Eureka etc

Experience with event-based and message-driven distributed system

Experience with reactive programming (RX, Reactive Streams, Akka etc)

Experience with NoSQL Datastores such as Cassandra and MongoDB

Experience with distributed caching frameworks such as Redis

Experienced with container orchestration platforms such as OpenShift, Amazon EKS, and Google GKE.

Experience with Continuous Integration / Continuous Delivery using modern DevOps tools and workflows such as git, GitHub, Jenkins

Experience with agile development (Scrum, Kanban, etc.) and Test Automation (behaviour, unit, integration testing)

Desirable:

Java Certification

Experience with JMS, Kafka

Experience with Spring boot

Experience with Spring cloud

Experience with Apache Camel

Position: SQL-Server/SSAS person with Azure

Location: Ewing, New Jersey

Duration: 4 months

    Job Description: 

Ability to understand business requirements and convert them into technical specifications

High competency in database / development programming frameworks specifically SQL – Server/SSIS/SSAS and Azure Data Lake

Proficiency in advanced Excel functions (e.g., pivot tables, power pivot, advanced formulas)

Independent, self-starter with strong self-management and communication skills

Job  title : Sr. Linux Administrator

Location: Seattle, WA/ Austin, TX/ Dallas, TX      

Duration: 6 months

Note: mandatory skils – Linux; MySQL DB

Job description :

Job Description: Looking for a Sr. Linux Admin Who Should be self-dependent and will be able to work independently.

Responsibilities will include to develop and build a multi-level application that used a MySQL database.

 Required skills/abilities: – Extensive knowledge troubleshooting Linux, ability to perform health         check on Linux and custom services & tasks.

 Extensive knowledge supporting IIS Web services- Working knowledge of PowerShell scripting – Extensive familiarity with processes involved Service to bring software from development to deployment on high traffic, high availability production systems.

Working familiarity with MySQL Server for troubleshooting.

 Ability to be part of an on-call rotation to provide L2 support – Should be ready for early hour shifts or late-night shift depending on client requirement Additional skills/abilities:

 Working knowledge of CI/CD automation tools such as: Octopus Deploy, Ansible, Jenkins, Puppet – Experience working with developers to streamline access to resources like logging & system health dashboards.

 Azure Application Insights – Deploying infrastructure-as-code with ARM – Azure: vnet and subnetting, Key Vault service, web app, web jobs, functions, IaaS,  autoscaling, Azure AAD, Storage Blobs – Azure CLI scripting

    Position: Onsite Workday HCM Functional Consultant

Location: Sunnyvale, CA

Duration: Contract

Experience: 8-10 Years

Note: FTF mandatory

  Job description:

Functional consultant with good knowledge of HR process and hands-on Workday configuration experience.

Subject Matter Expertise on HR processes, reports and integrations while identifying opportunities for automation and process improvement.

  Thanks, Steve Hunt Talent Acquisition Team – North America Vinsys Information Technology Inc SBA 8(a) Certified, MBE/DBE/EDGE Certified Virginia Department of Minority Business Enterprise(SWAM) 703-594-5490 www.vinsysinfo.com

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Spring Boot GraphQL Mongo DB Project Tutorial with Example for API Devel... Full Video Link        https://youtu.be/JElcKeh9a5A Hello friends, new #video on #springboot #graphql #mongodb #api #microservices #application #tutorial for #developer #programmers with #examples are published on #codeonedigest #youtube channel.  @java #java #aws #awscloud @awscloud @AWSCloudIndia #salesforce #Cloud #CloudComputing @YouTube #youtube #azure #msazure #codeonedigest @codeonedigest   #graphqlspringboot #graphqlspringboottutorial #graphqlspringbootmicroservicesexample #graphqlspringbootexample #graphqlmongodbexample #graphqlmongodbspringboot #springbootmongodb #springbootgraphql #springbootgraphqltutorial #springbootgraphqlexample #springbootgraphqlresolver #springbootgraphqlschema #springbootgraphqlschemamapping #springbootgraphqlmongodb #mongodbtutorialforbeginners #springboottutorial #springbootproject #graphql

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Spring Boot Microservice Project with MongoDB in Docker Container | Tutorial with Java Example

Full Video Link: https://youtu.be/dgGoQuZyszs Hi, a new #video on step by step #tutorial for #springboot #microservices with #mongodb in #docker #container is published on #codeonedigest #youtube channel. Quick guide for spring boot microservices proje

In this video, we will learn, how to pull mongodb image from dockerhub repository, how to run mongodb in docker container, how to connect Spring Boot Microservice Application with the mongodb running in a docker container and testing the GET and POST end-points of the microservices to pull and push customer data. Spring Boot is built on the top of the spring framework and contains all the…

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Spring Boot Microservice Project with MongoDB Step by Step Tutorial for Beginners with Java Code Example

Hi, a new #video on step by step #tutorial for #springboot #microservices with #mongodb is published on #codeonedigest #youtube channel. Quick guide for spring boot microservices with mongodb. #Springboot #mongodb #microservices #springboot

In this video, we will learn, how to download, install mongodb, how to integrate MongoDB with a Spring Boot Microservice Application and perform different CRUD operations (Create, Read, Update, and Delete operations) on the Customer entity. Spring Boot is built on the top of the spring and contains all the features of spring. And is becoming a favorite of developers these days because it’s a…

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What Java skills do you need to boost your developer career in 2019?

Continuing our series of articles, we processed 300 vacancies for Java developers from such websites as AngelList, StackOverflow, LinkedIn, etc. The vacancies were from companies of different sizes and different fields of activity. Here is the outcome — the rating of the skills, which were mentioned the most frequently.

 Key takeaways

Our main conclusion is: the demand for Java developers is big. I mean, really big. If you type ‘Java’ in LinkedIn’s search bar, you will get 370k vacancies. For comparison, there will be 249k job listings for Python and 278k for JavaScript. Hence now’s the perfect time to build a successful Java developer career!

 Here are some other key takeaways from our research about the current and upcoming Java trends.

 Java for web programming

As of our study, most companies prefer building the back-end of their web applications using Spring MVC, while the most widespread front-end frameworks are Angular (95) or React.js (50). Surely, that doesn’t mean that a Java developer must have a perfect knowledge of JavaScript front-end frameworks, but a general understanding of how these technologies work and interact with your Java code will definitely be useful.

 Among those Java back-end frameworks, not mentioned in the chart, Apache Struts (33) was the most popular one. However, I’d recommend learning this framework only if your (future) employer is definitely using it, (for example, to maintain the old applications). The latest version of Struts was released 5 years ago, but the same is not true of Spring, which is constantly trying to keep up with the newest Java updates. Moreover, Spring MVC is only a part of the complex solution, which can take care of many aspects of your application, (such as testing or data access).

 Data processing

Big data is not the most popular use of Java language, but from our research, it seems that it’s going to gain momentum in the nearest future. According to IBM, 90% of all data were created in the past two years, therefore we definitely need powerful and stable solutions to process all this information. I reckon Java is the one. Perhaps, it will even share the Data Science market with Python one day 🙂

 As for now, some employers already want candidates to be familiar with such data-related solutions as Apache Kafka (49), Hadoop (27), Azure (23), and Spark (21). By the way, the term Big Data itself was mentioned 33 times across the vacancies we analyzed, which is quite eloquent.

 JVM Languages

As we were analyzing vacancies for Java devs only, none of the JVM languages was mentioned frequently enough to get to our chart. However, they still were met in some of the job specs, and the most popular one was Scala (33). If you’re not familiar with Scala yet, you might want to learn more about this language in 2019, (especially if you’re working with data).

 Microservices

Java is considered by many seasoned devs the best language for microservices development. So, we weren’t wondered to see the terms Microservices and Spring Boot quite close to the top of our chart of the Java trends. Developers love microservices, too: better microservices support is the main community priority for Jakarta EE in 2019.

 I guess expanding your knowledge about this software development technique is a must in 2019. By the way, you might also want to learn more about service meshes. Although the term Istio (7) was mentioned not so frequently, as was Kubernetes (18), similar orchestration technologies are definitely going to become more popular with the growing popularity of microservice apps.

 Web servers and databases

Finally, if talking about NoSQL databases, here is what employers prefer: Cassandra (41) and MongoDB (33). As for web servers, Tomcat (35) and Apache (35) were the leaders.[Source]-https://cvcompiler.com/blog/what-java-skills-do-you-need-to-boost-your-developer-career-in-2019/

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