#serverless a

[weblozy-india]

Cloud Computing Trends to Watch Out for 2024.

Read our blog at

[nixcraft]

[simple-logic]

#PollTime

What cloud service runs code without servers?

A) Serverless ☁️

B) IaaS 🖥️

C) PaaS 🚀

D) SaaS 📊

Comments your answer below👇

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[fazmid]

repeating the phrase "the cloud is just someone else's computer" to myself as I complete my mandatory work training lest I get sucked in by the marketing terms

[josegremarquez]

Vercel: Tu escaparate al mundo para aplicaciones web

¿Qué es Vercel y por qué deberías usarlo? Vercel es una plataforma de desarrollo y despliegue que ha revolucionado la forma en que los desarrolladores comparten sus aplicaciones web. Pensada para ofrecer una experiencia de desarrollo fluida y un despliegue instantáneo, Vercel se ha convertido en una herramienta indispensable para muchos desarrolladores frontend. Como bien has mencionado, Vercel…

[connectinfo1999]

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What is Serverless Computing?

Serverless computing is a cloud computing model where the cloud provider manages the infrastructure and automatically provisions resources as needed to execute code. This means that developers don’t have to worry about managing servers, scaling, or infrastructure maintenance. Instead, they can focus on writing code and building applications. Serverless computing is often used for building event-driven applications or microservices, where functions are triggered by events and execute specific tasks.

How Serverless Computing Works

In serverless computing, applications are broken down into small, independent functions that are triggered by specific events. These functions are stateless, meaning they don’t retain information between executions. When an event occurs, the cloud provider automatically provisions the necessary resources and executes the function. Once the function is complete, the resources are de-provisioned, making serverless computing highly scalable and cost-efficient.

Serverless Computing Architecture

The architecture of serverless computing typically involves four components: the client, the API Gateway, the compute service, and the data store. The client sends requests to the API Gateway, which acts as a front-end to the compute service. The compute service executes the functions in response to events and may interact with the data store to retrieve or store data. The API Gateway then returns the results to the client.

Benefits of Serverless Computing

Serverless computing offers several benefits over traditional server-based computing, including:

Reduced costs: Serverless computing allows organizations to pay only for the resources they use, rather than paying for dedicated servers or infrastructure.

Improved scalability: Serverless computing can automatically scale up or down depending on demand, making it highly scalable and efficient.

Reduced maintenance: Since the cloud provider manages the infrastructure, organizations don’t need to worry about maintaining servers or infrastructure.

Faster time to market: Serverless computing allows developers to focus on writing code and building applications, reducing the time to market new products and services.

Drawbacks of Serverless Computing

While serverless computing has several benefits, it also has some drawbacks, including:

Limited control: Since the cloud provider manages the infrastructure, developers have limited control over the environment and resources.

Cold start times: When a function is executed for the first time, it may take longer to start up, leading to slower response times.

Vendor lock-in: Organizations may be tied to a specific cloud provider, making it difficult to switch providers or migrate to a different environment.

Some facts about serverless computing

Serverless computing is often referred to as Functions-as-a-Service (FaaS) because it allows developers to write and deploy individual functions rather than entire applications.

Serverless computing is often used in microservices architectures, where applications are broken down into smaller, independent components that can be developed, deployed, and scaled independently.

Serverless computing can result in significant cost savings for organizations because they only pay for the resources they use. This can be especially beneficial for applications with unpredictable traffic patterns or occasional bursts of computing power.

One of the biggest drawbacks of serverless computing is the “cold start” problem, where a function may take several seconds to start up if it hasn’t been used recently. However, this problem can be mitigated through various optimization techniques.

Serverless computing is often used in event-driven architectures, where functions are triggered by specific events such as user interactions, changes to a database, or changes to a file system. This can make it easier to build highly scalable and efficient applications.

Now, let’s explore some other serverless computing frameworks that can be used in addition to Google Cloud Functions.

AWS Lambda: AWS Lambda is a serverless compute service from Amazon Web Services (AWS). It allows developers to run code in response to events without worrying about managing servers or infrastructure.

Microsoft Azure Functions: Microsoft Azure Functions is a serverless compute service from Microsoft Azure. It allows developers to run code in response to events and supports a wide range of programming languages.

IBM Cloud Functions: IBM Cloud Functions is a serverless compute service from IBM Cloud. It allows developers to run code in response to events and supports a wide range of programming languages.

OpenFaaS: OpenFaaS is an open-source serverless framework that allows developers to run functions on any cloud or on-premises infrastructure.

Apache OpenWhisk: Apache OpenWhisk is an open-source serverless platform that allows developers to run functions in response to events. It supports a wide range of programming languages and can be deployed on any cloud or on-premises infrastructure.

Kubeless: Kubeless is a Kubernetes-native serverless framework that allows developers to run functions on Kubernetes clusters. It supports a wide range of programming languages and can be deployed on any Kubernetes cluster.

IronFunctions: IronFunctions is an open-source serverless platform that allows developers to run functions on any cloud or on-premises infrastructure. It supports a wide range of programming languages and can be deployed on any container orchestrator.

These serverless computing frameworks offer developers a range of options for building and deploying serverless applications. Each framework has its own strengths and weaknesses, so developers should choose the one that best fits their needs.

Real-time examples

Coca-Cola: Coca-Cola uses serverless computing to power its Freestyle soda machines, which allow customers to mix and match different soda flavors. The machines use AWS Lambda functions to process customer requests and make recommendations based on their preferences.

iRobot: iRobot uses serverless computing to power its Roomba robot vacuums, which use computer vision and machine learning to navigate homes and clean floors. The Roomba vacuums use AWS Lambda functions to process data from their sensors and decide where to go next.

Capital One: Capital One uses serverless computing to power its mobile banking app, which allows customers to manage their accounts, transfer money, and pay bills. The app uses AWS Lambda functions to process requests and deliver real-time information to users.

Fender: Fender uses serverless computing to power its Fender Play platform, which provides online guitar lessons to users around the world. The platform uses AWS Lambda functions to process user data and generate personalized lesson plans.

Netflix: Netflix uses serverless computing to power its video encoding and transcoding workflows, which are used to prepare video content for streaming on various devices. The workflows use AWS Lambda functions to process video files and convert them into the appropriate format for each device.

Conclusion

Serverless computing is a powerful and efficient solution for building and deploying applications. It offers several benefits, including reduced costs, improved scalability, reduced maintenance, and faster time to market. However, it also has some drawbacks, including limited control, cold start times, and vendor lock-in. Despite these drawbacks, serverless computing will likely become an increasingly popular solution for building event-driven applications and microservices.

Read more

[vayamsblog]

In this article, we break down what is serverless computing or architecture. We also touch upon its benefits and why it is a game-changer for developers. Whether you are building web applications, APIs, or microservices, understanding serverless architecture can be a huge game-changer for you.

[cruxcreations]

Serverless Architecture

A cloud-themed image shows developers coding on laptops in an open, server-free environment. Cloud icons and digital pipelines represent serverless deployment. The title hovers in the cloud visuals, and CruxCreations appears on a virtual server graphic.

[capitalnumbers]

Serverless Architecture for Scalable, Cost-Effective Web Apps

Serverless architecture helps businesses build web apps faster, cheaper, and without worrying about server maintenance. Cloud providers like AWS and Google Cloud take care of all the backend work, so developers can focus on writing code.

In this setup, apps scale automatically based on demand, and companies only pay for the actual usage, not idle time. This means less cost, better security, and quicker updates.

Popular tools include AWS Lambda, API Gateway, and Google Cloud Functions. These tools support tasks like running code, storing data, or building APIs - all without managing servers.

Use cases include mobile and web backends, real-time data processing, and scheduled jobs. Best practices include keeping code small, monitoring performance, and securing environments.

Overall, serverless makes building apps easier and more efficient. It’s ideal for growing businesses that want to stay fast, flexible, and budget-friendly.

[digitaleduskill]

Cost Optimization Strategies in Public Cloud

Businesses around the globe have embraced public cloud computing to gain flexibility, scalability, and faster innovation. While the cloud offers tremendous advantages, many organizations face an unexpected challenge: spiraling costs. Without careful planning, cloud expenses can quickly outpace expectations. That’s why cost optimization has become a critical component of cloud strategy.

Cost optimization doesn’t mean cutting essential services or sacrificing performance. It means using the right tools, best practices, and strategic planning to make the most of every dollar spent on the cloud. In this article, we explore proven strategies to reduce unnecessary spending while maintaining high availability and performance in a public cloud environment.

1. Right-Sizing Resources

Many businesses overprovision their cloud resources, thinking it's safer to allocate more computing power than needed. However, this leads to wasted spending. Right-sizing involves analyzing usage patterns and scaling down resources to match actual needs.

You can:

Use monitoring tools to analyze CPU and memory utilization

Adjust virtual machine sizes to suit workloads

Switch to serverless computing when possible, paying only for what you use

This strategy ensures optimal performance at the lowest cost.

2. Take Advantage of Reserved Instances

Most public cloud providers, including AWS, Azure, and Google Cloud, offer Reserved Instances (RIs) at discounted prices for long-term commitments. If your workload is predictable and long-term, reserving instances for one or three years can save up to 70% compared to on-demand pricing.

This is ideal for production environments, baseline services, and other non-variable workloads.

3. Auto-Scaling Based on Demand

Auto-scaling helps match computing resources with current demand. During off-peak hours, cloud services automatically scale down to reduce costs. When traffic spikes, resources scale up to maintain performance.

Implementing auto-scaling not only improves cost efficiency but also ensures reliability and customer satisfaction.

4. Delete Unused or Orphaned Resources

Cloud environments often accumulate unused resources—volumes, snapshots, IP addresses, or idle virtual machines. These resources continue to incur charges even when not in use.

Make it a regular practice to:

Audit and remove orphaned resources

Clean up unattached storage volumes

Delete old snapshots and unused databases

Cloud management tools can automate these audits, helping keep your environment lean and cost-effective.

5. Use Cost Monitoring and Alerting Tools

Every major public cloud provider offers native cost management tools:

AWS Cost Explorer

Azure Cost Management + Billing

Google Cloud Billing Reports

These tools help track spending in real time, break down costs by service, and identify usage trends. You can also set budgets and receive alerts when spending approaches limits, helping prevent surprise bills.

6. Implement Tagging for Cost Allocation

Properly tagging resources makes it easier to identify who is spending what within your organization. With tagging, you can allocate costs by:

Project

Department

Client

Environment (e.g., dev, test, prod)

This visibility empowers teams to take ownership of their cloud spending and look for optimization opportunities.

7. Move to Serverless and Managed Services

In many cases, serverless and managed services provide a more cost-efficient alternative to traditional infrastructure.

Consider using:

Azure Functions or AWS Lambda for event-driven applications

Cloud SQL or Azure SQL Database for managed relational databases

Firebase or App Engine for mobile and web backends

These services eliminate the need for server provisioning and maintenance while offering a pay-as-you-go pricing model.

8. Choose the Right Storage Class

Public cloud providers offer different storage classes based on access frequency:

Hot storage for frequently accessed data

Cool or infrequent access storage for less-used files

Archive storage for long-term, rarely accessed data

Storing data in the appropriate class ensures you don’t pay premium prices for data you seldom access.

9. Leverage Spot and Preemptible Instances

Spot instances (AWS) or preemptible VMs (Google Cloud) offer up to 90% savings compared to on-demand pricing. These instances are ideal for:

Batch processing

Testing environments

Fault-tolerant applications

Since these instances can be interrupted, they’re not suitable for every workload, but when used correctly, they can slash costs significantly.

10. Train Your Teams

Cost optimization isn’t just a technical task—it’s a cultural one. When developers, DevOps, and IT teams understand how cloud billing works, they make smarter decisions.

Regular training and workshops can:

Increase awareness of cost-effective architectures

Encourage the use of automation tools

Promote shared responsibility for cloud cost management

Final Thoughts

Public cloud computing offers unmatched agility and scalability, but without deliberate cost control, organizations can face financial inefficiencies. By right-sizing, leveraging automation, utilizing reserved instances, and fostering a cost-aware culture, companies can enjoy the full benefits of the cloud without overspending.

Cloud optimization is a continuous journey—not a one-time fix. Regular reviews and proactive planning will keep your cloud costs aligned with your business goals.

[simple-logic]

#Scrabble Scrabble Word of the Day 🎲

Uncover the tech jargon! 🖥️💡

Comments your answer below👇

💻 Explore insights on the latest in #technology on our Blog Page 👉 https://simplelogic-it.com/blogs/

🚀 Ready for your next career move? Check out our #careers page for exciting opportunities 👉 https://simplelogic-it.com/careers/

[asadmukhtarr]

"Building Microservices" by Sam Newman is a definitive guide to designing, developing, and deploying microservices-based architectures. The book provides a deep understanding of the principles, patterns, and practices required to build scalable, maintainable, and resilient microservices. Below is a user-friendly, step-by-step breakdown of the key outcomes and takeaways from the book, designed to help readers understand and apply microservices effectively.

[futuristicbugpvtltd]

Serverless Computing: Streamlining Web Application Deployment