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codeonedigest · 2 years ago

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AWS Lambda Compute Service Tutorial for Amazon Cloud Developers

Full Video Link - https://youtube.com/shorts/QmQOWR_aiNI Hi, a new #video #tutorial on #aws #lambda #awslambda is published on #codeonedigest #youtube channel. @java @awscloud @AWSCloudIndia @YouTube #youtube @codeonedigest #codeonedigest #aws #amaz

AWS Lambda is a serverless compute service that runs your code in response to events and automatically manages the underlying compute resources for you. These events may include changes in state such as a user placing an item in a shopping cart on an ecommerce website. AWS Lambda automatically runs code in response to multiple events, such as HTTP requests via Amazon API Gateway, modifications…

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govindhtech · 3 days ago

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Build A Smarter Security Chatbot With Amazon Bedrock Agents

Use an Amazon Security Lake and Amazon Bedrock chatbot for incident investigation. This post shows how to set up a security chatbot that uses an Amazon Bedrock agent to combine pre-existing playbooks into a serverless backend and GUI to investigate or respond to security incidents. The chatbot presents uniquely created Amazon Bedrock agents to solve security vulnerabilities with natural language input. The solution uses a single graphical user interface (GUI) to directly communicate with the Amazon Bedrock agent to build and run SQL queries or advise internal incident response playbooks for security problems.

User queries are sent via React UI.

Note: This approach does not integrate authentication into React UI. Include authentication capabilities that meet your company's security standards. AWS Amplify UI and Amazon Cognito can add authentication.

Amazon API Gateway REST APIs employ Invoke Agent AWS Lambda to handle user queries.

User queries trigger Lambda function calls to Amazon Bedrock agent.

Amazon Bedrock (using Claude 3 Sonnet from Anthropic) selects between querying Security Lake using Amazon Athena or gathering playbook data after processing the inquiry.

Ask about the playbook knowledge base:

The Amazon Bedrock agent queries the playbooks knowledge base and delivers relevant results.

For Security Lake data enquiries:

The Amazon Bedrock agent takes Security Lake table schemas from the schema knowledge base to produce SQL queries.

When the Amazon Bedrock agent calls the SQL query action from the action group, the SQL query is sent.

Action groups call the Execute SQL on Athena Lambda function to conduct queries on Athena and transmit results to the Amazon Bedrock agent.

After extracting action group or knowledge base findings:

The Amazon Bedrock agent uses the collected data to create and return the final answer to the Invoke Agent Lambda function.

The Lambda function uses an API Gateway WebSocket API to return the response to the client.

API Gateway responds to React UI via WebSocket.

The chat interface displays the agent's reaction.

Requirements

Prior to executing the example solution, complete the following requirements:

Select an administrator account to manage Security Lake configuration for each member account in AWS Organisations. Configure Security Lake with necessary logs: Amazon Route53, Security Hub, CloudTrail, and VPC Flow Logs.

Connect subscriber AWS account to source Security Lake AWS account for subscriber queries.

Approve the subscriber's AWS account resource sharing request in AWS RAM.

Create a database link in AWS Lake Formation in the subscriber AWS account and grant access to the Security Lake Athena tables.

Provide access to Anthropic's Claude v3 model for Amazon Bedrock in the AWS subscriber account where you'll build the solution. Using a model before activating it in your AWS account will result in an error.

When requirements are satisfied, the sample solution design provides these resources:

Amazon S3 powers Amazon CloudFront.

Chatbot UI static website hosted on Amazon S3.

Lambda functions can be invoked using API gateways.

An Amazon Bedrock agent is invoked via a Lambda function.

A knowledge base-equipped Amazon Bedrock agent.

Amazon Bedrock agents' Athena SQL query action group.

Amazon Bedrock has example Athena table schemas for Security Lake. Sample table schemas improve SQL query generation for table fields in Security Lake, even if the Amazon Bedrock agent retrieves data from the Athena database.

A knowledge base on Amazon Bedrock to examine pre-existing incident response playbooks. The Amazon Bedrock agent might propose investigation or reaction based on playbooks allowed by your company.

Cost

Before installing the sample solution and reading this tutorial, understand the AWS service costs. The cost of Amazon Bedrock and Athena to query Security Lake depends on the amount of data.

Security Lake cost depends on AWS log and event data consumption. Security Lake charges separately for other AWS services. Amazon S3, AWS Glue, EventBridge, Lambda, SQS, and SNS include price details.

Amazon Bedrock on-demand pricing depends on input and output tokens and the large language model (LLM). A model learns to understand user input and instructions using tokens, which are a few characters. Amazon Bedrock pricing has additional details.

The SQL queries Amazon Bedrock creates are launched by Athena. Athena's cost depends on how much Security Lake data is scanned for that query. See Athena pricing for details.

Clear up

Clean up if you launched the security chatbot example solution using the Launch Stack button in the console with the CloudFormation template security_genai_chatbot_cfn:

Choose the Security GenAI Chatbot stack in CloudFormation for the account and region where the solution was installed.

Choose “Delete the stack”.

If you deployed the solution using AWS CDK, run cdk destruct –all.

Conclusion

The sample solution illustrates how task-oriented Amazon Bedrock agents and natural language input may increase security and speed up inquiry and analysis. A prototype solution using an Amazon Bedrock agent-driven user interface. This approach may be expanded to incorporate additional task-oriented agents with models, knowledge bases, and instructions. Increased use of AI-powered agents can help your AWS security team perform better across several domains.

The chatbot's backend views data normalised into the Open Cybersecurity Schema Framework (OCSF) by Security Lake.

#securitychatbot #AmazonBedrockagents #graphicaluserinterface #Bedrockagent #chatbot #chatbotsecurity #Technology #TechNews #technologynews #news #govindhtech

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hexaa12321 · 19 days ago

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Serverless Computing: Simplifying Backend Development

Absolutely! Here's a brand new 700-word blog on the topic: "Serverless Computing: Simplifying Backend Development" — written in a clear, simple tone without any bold formatting, and including mentions of Hexadecimal Software and Hexahome Blogs.

Serverless Computing: Simplifying Backend Development

The world of software development is constantly evolving. One of the most exciting shifts in recent years is the rise of serverless computing. Despite the name, serverless computing still involves servers — but the key difference is that developers no longer need to manage them.

With serverless computing, developers can focus purely on writing code, while the cloud provider automatically handles server management, scaling, and maintenance. This approach not only reduces operational complexity but also improves efficiency, cost savings, and time to market.

What is Serverless Computing?

Serverless computing is a cloud computing model where the cloud provider runs the server and manages the infrastructure. Developers simply write functions that respond to events — like a file being uploaded or a user submitting a form — and the provider takes care of executing the function, scaling it based on demand, and handling all server-related tasks.

Unlike traditional cloud models where developers must set up virtual machines, install software, and manage scaling, serverless removes those responsibilities entirely.

How It Works

Serverless platforms use what are called functions-as-a-service (FaaS). Developers upload small pieces of code (functions) to the cloud platform, and each function is triggered by a specific event. These events could come from HTTP requests, database changes, file uploads, or scheduled timers.

The platform then automatically runs the code in a stateless container, scales the application based on the number of requests, and shuts down the container when it's no longer needed. You only pay for the time the function is running, which can significantly reduce costs.

Popular serverless platforms include AWS Lambda, Google Cloud Functions, Azure Functions, and Firebase Cloud Functions.

Benefits of Serverless Computing

Reduced infrastructure management Developers don’t have to manage or maintain servers. Everything related to infrastructure is handled by the cloud provider.

Automatic scaling Serverless platforms automatically scale the application depending on the demand, whether it's a few requests or thousands.

Cost efficiency Since you only pay for the time your code runs, serverless can be more affordable than always-on servers, especially for applications with variable traffic.

Faster development Serverless enables quicker development and deployment since the focus is on writing code and not on managing environments.

High availability Most serverless platforms ensure high availability and reliability without the need for additional configuration.

Use Cases of Serverless Computing

Serverless is suitable for many types of applications:

Web applications: Serverless functions can power APIs and backend logic for web apps.

IoT backends: Data from devices can be processed in real-time using serverless functions.

Chatbots: Event-driven logic for responding to messages can be handled with serverless platforms.

Real-time file processing: Automatically trigger functions when files are uploaded to storage, like resizing images or analyzing documents.

Scheduled tasks: Functions can be set to run at specific times for operations like backups or report generation.

Challenges of Serverless Computing

Like any technology, serverless computing comes with its own set of challenges:

Cold starts: When a function hasn’t been used for a while, it may take time to start again, causing a delay.

Limited execution time: Functions often have time limits, which may not suit long-running tasks.

Vendor lock-in: Each cloud provider has its own way of doing things, making it hard to move applications from one provider to another.

Debugging and monitoring: Tracking errors or performance in distributed functions can be more complex.

Despite these challenges, many teams find that the benefits of serverless outweigh the limitations, especially for event-driven applications and microservices.

About Hexadecimal Software

Hexadecimal Software is a leading software development company specializing in cloud-native solutions, DevOps, and modern backend systems. Our experts help businesses embrace serverless computing to build efficient, scalable, and low-maintenance applications. Whether you’re developing a new application or modernizing an existing one, we can guide you through your cloud journey. Learn more at https://www.hexadecimalsoftware.com

Explore More on Hexahome Blogs

To discover more about cloud computing, DevOps, and modern development practices, visit our blog platform at https://www.blogs.hexahome.in. Our articles are written in a simple, easy-to-understand style to help professionals stay updated with the latest tech trends.

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chloedecker0 · 19 days ago

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Top Function as a Service (FaaS) Vendors of 2025

Businesses encounter obstacles in implementing effective and scalable development processes. Traditional techniques frequently fail to meet the growing expectations for speed, scalability, and innovation. That's where Function as a Service comes in.

FaaS is more than another addition to the technological stack; it marks a paradigm shift in how applications are created and delivered. It provides a serverless computing approach that abstracts infrastructure issues, freeing organizations to focus on innovation and core product development. As a result, FaaS has received widespread interest and acceptance in multiple industries, including BFSI, IT & Telecom, Public Sector, Healthcare, and others.

So, what makes FaaS so appealing to corporate leaders? Its value offer is based on the capacity to accelerate time-to-market and improve development outcomes. FaaS allows companies to prioritize delivering new goods and services to consumers by reducing server maintenance, allowing for flexible scalability, cost optimization, and automatic high availability.

In this blog, we'll explore the meaning of Function as a Service (FaaS) and explain how it works. We will showcase the best function as a service (FaaS) software that enables businesses to reduce time-to-market and streamline development processes.

Download the sample report of Market Share: https://qksgroup.com/download-sample-form/market-share-function-as-a-service-2023-worldwide-5169

What is Function-as-a-Service (FaaS)?

Function-as-a-Service (FaaS), is a cloud computing service that enables developers to create, execute, and manage discrete units of code as individual functions, without the need to oversee the underlying infrastructure. This approach enables developers to focus solely on writing code for their application's specific functions, abstracting away the complexities of infrastructure management associated with  developing and deploying microservices applications. With FaaS, developers can write and update small, modular pieces of code, which are designed to respond to specific events or triggers. FaaS is commonly used for building microservices, real-time data processing, and automating workflows. It decreases much of the infrastructure management complexity, making it easier for developers to focus on writing code and delivering functionality. FaaS can power the backend for mobile applications, handling user authentication, data synchronization, and push notifications, among other functions.

How Does Function-as-a-Service (FaaS) Work?

FaaS provides programmers with a framework for responding to events via web apps without managing servers.PaaS infrastructure frequently requires server tasks to continue in the background at all times. In contrast, FaaS infrastructure is often invoiced on demand by the service provider, using an event-based execution methodology.

FaaS functions should be formed to bring out a task in response to an input. Limit the scope of your code, keeping it concise and lightweight, so that functions load and run rapidly. FaaS adds value at the function separation level. If you have fewer functions, you will pay additional costs while maintaining the benefit of function separation. The efficiency and scalability of a function may be enhanced by utilizing fewer libraries. Features, microservices, and long-running services will be used to create comprehensive apps.

Download the sample report of Market Forecast: https://qksgroup.com/download-sample-form/market-forecast-function-as-a-service-2024-2028-worldwide-4685

Top Function-as-a-Service (FaaS) Vendors

Amazon

Amazon announced AWS Lambda in 2014. Since then, it has developed into one of their most valuable offerings. It serves as a framework for Alexa skill development and provides easy access to many of AWS's monitoring tools. Lambda natively supports Java, Go, PowerShell, Node.js, C#, Python, and Ruby code.

Alibaba Functions

Alibaba provides a robust platform for serverless computing. You may deploy and run your code using Alibaba Functions without managing infrastructure or servers. To run your code, computational resources are deployed flexibly and reliably. Dispersed clusters exist in a variety of locations. As a result, if one zone becomes unavailable, Alibaba Function Compute will immediately switch to another instance. Using distributed clusters allows any user from anywhere to execute your code faster. It increases productivity.

Microsoft

Microsoft and Azure compete with Microsoft Azure Functions. It is the biggest FaaS provider for designing and delivering event-driven applications. It is part of the Azure ecosystem and supports several programming languages, including C#, JavaScript, F#, Python, Java, PowerShell, and TypeScript.

Azure Functions provides a more complex programming style built around triggers and bindings. An HTTP-triggered function may read a document from Azure Cosmos DB and deliver a queue message using declarative configuration. The platform supports multiple triggers, including online APIs, scheduled tasks, and services such as Azure Storage, Azure Event Hubs, Twilio for SMS, and SendGrid for email.

Vercel

Vercel Functions offers a FaaS platform optimized for static frontends and serverless functions. It hosts webpages and online apps that install rapidly and expand themselves.

The platform stands out for its straightforward and user-friendly design. When running Node.js, Vercel manages dependencies using a single JSON. Developers may also change the runtime version, memory, and execution parameters. Vercel's dashboard provides monitoring logs for tracking functions and requests.

Key Technologies Powering FaaS and Their Strategic Importance

According to QKS Group and insights from the reports “Market Share: Function as a Service, 2023, Worldwide” and “Market Forecast: Function as a Service, 2024-2028, Worldwide”, organizations around the world are increasingly using Function as a Service (FaaS) platforms to streamline their IT operations, reduce infrastructure costs, and improve overall business agility. Businesses that outsource computational work to cloud service providers can focus on their core capabilities, increase profitability, gain a competitive advantage, and reduce time to market for new apps and services.

Using FaaS platforms necessitates sharing sensitive data with third-party cloud providers, including confidential company information and consumer data. As stated in Market Share: Function as a Service, 2023, Worldwide, this raises worries about data privacy and security, as a breach at the service provider's end might result in the disclosure or theft of crucial data. In an era of escalating cyber threats and severe data security rules, enterprises must recognize and mitigate the risks of using FaaS platforms. Implementing strong security measures and performing frequent risk assessments may assist in guaranteeing that the advantages of FaaS are realized without sacrificing data integrity and confidentiality.

Vendors use terms like serverless computing, microservices, and Function as a Service (FaaS) to describe similar underlying technologies. FaaS solutions simplify infrastructure management, enabling rapid application development, deployment, and scalability. Serverless computing and microservices brake systems into small, independent tasks that can be executed on demand, resulting in greater flexibility and efficiency in application development.

Conclusion

Function as a Service (FaaS) is helping businesses build and run applications more efficiently without worrying about server management. It allows companies to scale as needed, reduce costs, and focus on creating better products and services. As more sectors use FaaS, knowing how it works and selecting the right provider will be critical to keeping ahead in a rapidly altering digital landscape.

Related Reports –

https://qksgroup.com/market-research/market-forecast-function-as-a-service-2024-2028-western-europe-4684

https://qksgroup.com/market-research/market-share-function-as-a-service-2023-western-europe-5168

https://qksgroup.com/market-research/market-forecast-function-as-a-service-2024-2028-usa-4683

https://qksgroup.com/market-research/market-share-function-as-a-service-2023-usa-5167

https://qksgroup.com/market-research/market-forecast-function-as-a-service-2024-2028-middle-east-and-africa-4682

https://qksgroup.com/market-research/market-share-function-as-a-service-2023-middle-east-and-africa-5166

https://qksgroup.com/market-research/market-forecast-function-as-a-service-2024-2028-china-4679

https://qksgroup.com/market-research/market-share-function-as-a-service-2023-china-5163

https://qksgroup.com/market-research/market-forecast-function-as-a-service-2024-2028-asia-excluding-japan-and-china-4676

https://qksgroup.com/market-research/market-share-function-as-a-service-2023-asia-excluding-japan-and-china-5160

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sphinxshreya · 25 days ago

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The Future of Cloud: Best Serverless Development Company Trends

Introduction

Cloud computing is evolving, and one of the most innovative advancements is serverless technology. A Serverless development company eliminates the need for businesses to manage servers, allowing them to focus on building scalable and cost-effective applications. As more organizations adopt serverless computing, it's essential to understand the trends and benefits of working with a serverless provider.

From automating infrastructure management to reducing operational costs, serverless development is revolutionizing how businesses operate in the cloud. This blog explores the role of serverless development, key trends, and how companies can benefit from partnering with a serverless provider.

Why Choose a Serverless Development Company?

A Serverless development company provides cloud-based solutions that handle backend infrastructure automatically. Instead of provisioning and maintaining servers, businesses only pay for what they use. This reduces costs, enhances scalability, and improves efficiency.

Companies across industries are leveraging serverless technology to deploy cloud applications quickly. Whether it's handling high-traffic websites, processing large-scale data, or integrating AI-driven solutions, serverless computing offers unmatched flexibility and reliability.

Latest Trends in Serverless Computing

The adoption of serverless technology is on the rise, with various trends shaping the industry. Some key developments include:

Multi-cloud serverless computing for better flexibility and redundancy.

Enhanced security frameworks to protect cloud-based applications.

Integration of AI and machine learning to automate workflows.

Low-code and no-code development enabling faster application deployment.

These trends indicate that a Serverless development company is not just about reducing costs but also about optimizing business operations for the future.

Top 10 SaaS Development Companies Driving Serverless Adoption

The SaaS industry is a significant player in the adoption of serverless computing. Many SaaS providers are integrating serverless architecture to enhance their platforms.

Here are the Top 10 SaaS Development Companies leading the way in serverless innovation:

Amazon Web Services (AWS Lambda)

Microsoft Azure Functions

Google Cloud Functions

IBM Cloud Functions

Netlify

Cloudflare Workers

Vercel

Firebase Cloud Functions

Twilio Functions

StackPath

These companies are paving the way for serverless solutions that enable businesses to scale efficiently without traditional server management.

Best SaaS Examples in 2025 Showcasing Serverless Success

Many successful SaaS applications leverage serverless technology to provide seamless experiences. Some of the Best SaaS Examples in 2025 using serverless include:

Slack for real-time messaging with scalable cloud infrastructure.

Shopify for handling e-commerce transactions efficiently.

Zoom for seamless video conferencing and collaboration.

Dropbox for secure and scalable cloud storage solutions.

Stripe for processing payments with high reliability.

These SaaS companies use serverless technology to optimize performance and enhance customer experiences.

Guide to SaaS Software Development with Serverless Technology

A Guide to SaaS Software Development with serverless technology involves several crucial steps:

Choose the right cloud provider – AWS, Azure, or Google Cloud.

Leverage managed services – Databases, authentication, and API gateways.

Optimize event-driven architecture – Serverless functions triggered by events.

Implement security best practices – Encryption, IAM policies, and monitoring.

Monitor and scale efficiently – Using automated scaling mechanisms.

These steps help businesses build robust SaaS applications with minimal infrastructure management.

Custom Software Development Company and Serverless Integration

A custom software development company can integrate serverless technology into tailored software solutions. Whether it's developing enterprise applications, e-commerce platforms, or AI-driven solutions, serverless computing enables companies to deploy scalable applications without worrying about server management.

By partnering with a custom software provider specializing in serverless, businesses can streamline development cycles, reduce costs, and improve system reliability.

How Cloud-Based Apps Benefit from Serverless Architecture

The shift towards cloud-based apps has accelerated the adoption of serverless computing. Serverless architecture allows cloud applications to:

Scale automatically based on demand.

Reduce operational costs with pay-as-you-go pricing.

Enhance security with managed cloud services.

Improve application performance with faster response times.

As more companies move towards cloud-native applications, serverless technology will continue to be a game-changer in modern app development.

Conclusion

The Serverless development company landscape is growing, enabling businesses to build scalable, cost-efficient applications with minimal infrastructure management. As serverless trends continue to evolve, partnering with the right development company can help businesses stay ahead in the competitive cloud computing industry.

Whether you're developing SaaS applications, enterprise solutions, or AI-driven platforms, serverless technology provides a flexible and efficient approach to modern software development. Embrace the future of cloud computing with serverless solutions and transform the way your business operates.

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hawkstack · 25 days ago

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🚀 Integrating ROSA Applications with AWS Services (CS221)

As cloud-native applications evolve, seamless integration between orchestration platforms like Red Hat OpenShift Service on AWS (ROSA) and core AWS services is becoming a vital architectural requirement. Whether you're running microservices, data pipelines, or containerized legacy apps, combining ROSA’s Kubernetes capabilities with AWS’s ecosystem opens the door to powerful synergies.

In this blog, we’ll explore key strategies, patterns, and tools for integrating ROSA applications with essential AWS services — as taught in the CS221 course.

🧩 Why Integrate ROSA with AWS Services?

ROSA provides a fully managed OpenShift experience, but its true potential is unlocked when integrated with AWS-native tools. Benefits include:

Enhanced scalability using Amazon S3, RDS, and DynamoDB

Improved security and identity management through IAM and Secrets Manager

Streamlined monitoring and observability with CloudWatch and X-Ray

Event-driven architectures via EventBridge and SNS/SQS

Cost optimization by offloading non-containerized workloads

🔌 Common Integration Patterns

Here are some popular integration patterns used in ROSA deployments:

1. Storage Integration:

Amazon S3 for storing static content, logs, and artifacts.

Use the AWS SDK or S3 buckets mounted using CSI drivers in ROSA pods.

2. Database Services:

Connect applications to Amazon RDS or Amazon DynamoDB for persistent storage.

Manage DB credentials securely using AWS Secrets Manager injected into pods via Kubernetes secrets.

3. IAM Roles for Service Accounts (IRSA):

Securely grant AWS permissions to OpenShift workloads.

Set up IRSA so pods can assume IAM roles without storing credentials in the container.

4. Messaging and Eventing:

Integrate with Amazon SNS/SQS for asynchronous messaging.

Use EventBridge to trigger workflows from container events (e.g., pod scaling, job completion).

5. Monitoring & Logging:

Forward logs to CloudWatch Logs using Fluent Bit/Fluentd.

Collect metrics with Prometheus Operator and send alerts to Amazon CloudWatch Alarms.

6. API Gateway & Load Balancers:

Expose ROSA services using AWS Application Load Balancer (ALB).

Enhance APIs with Amazon API Gateway for throttling, authentication, and rate limiting.

📚 Real-World Use Case

Scenario: A financial app running on ROSA needs to store transaction logs in Amazon S3 and trigger fraud detection workflows via Lambda.

Solution:

Application pushes logs to S3 using the AWS SDK.

S3 triggers an EventBridge rule that invokes a Lambda function.

The function performs real-time analysis and writes alerts to an SNS topic.

This serverless integration offloads processing from ROSA while maintaining tight security and performance.

✅ Best Practices

Use IRSA for least-privilege access to AWS services.

Automate integration testing with CI/CD pipelines.

Monitor both ROSA and AWS services using unified dashboards.

Encrypt data in transit and at rest using AWS KMS + OpenShift secrets.

🧠 Conclusion

ROSA + AWS is a powerful combination that enables enterprises to run secure, scalable, and cloud-native applications. With the insights from CS221, you’ll be equipped to design robust architectures that capitalize on the strengths of both platforms. Whether it’s storage, compute, messaging, or monitoring — AWS integrations will supercharge your ROSA applications.

For more details visit - https://training.hawkstack.com/integrating-rosa-applications-with-aws-services-cs221/

#hawkstack #hawkstack technologies #kubernetes #redhat #ansible #automation #openshift

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dzinesoniya · 1 month ago

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Introduction to Serverless Computing for Web Development

If you’ve ever built a website, you know how much time goes into managing servers. What if you could skip that part and focus purely on creating great designs and features? That’s the idea behind serverless computing. Let’s talk about what it is, why it matters, and how it can make life easier for developers—whether you’re working solo or with a team like a website designing company in India.

So, What’s Serverless?

The name sounds confusing, right? “Serverless” doesn’t mean there are no servers. It just means someone else (like Amazon Web Services or Google Cloud) handles them for you. Imagine ordering food delivery instead of cooking—you get the meal without worrying about the kitchen. Similarly, you write code, upload it, and the cloud provider manages the rest. No server crashes to fix, no updates to install.

How It Works

Serverless runs on triggers. Your code activates only when needed—like when a user clicks a button or uploads a file. Once the task finishes, everything quiets down. You’re billed only for the time your code runs, not for idle servers. For example, if your client’s online store gets a surge during festivals, the system scales up automatically. No manual tweaks required.

Why Try Serverless?

Save Money: Traditional servers charge you even when nobody’s using your site. With serverless, costs drop because you pay per action. This is perfect for small teams or businesses watching their budgets.

Less Hassle: Forget server setup. Just write code and push it live.

Auto-Scaling: Your site handles traffic spikes smoothly, whether 10 users or 10,000 show up.

Focus on Creativity: Spend time designing interfaces or improving user experience instead of fixing backend issues.

When to Use It

Serverless shines for tasks like:

Building APIs that adapt to user demand.

Processing data in real time (e.g., resizing images after upload).

Running automated jobs, like sending order confirmations or updating inventory.

But It’s Not Perfect

Serverless isn’t ideal for everything. Tasks that run for hours (like rendering videos) might cost more here. Debugging can also get tricky since your code runs in scattered pieces. Still, for most websites—especially those with unpredictable traffic—it’s a solid choice.

How to Get Started

Choose a Platform: AWS Lambda and Google Cloud Functions are popular picks.

Test with Simple Tasks: Move a small feature, like a newsletter signup, to serverless first.

Use Helper Tools: Frameworks like Serverless Framework cut down deployment steps.

Why Businesses Love It

For clients, serverless means faster launches and fewer upfront costs. Imagine building an app that scales during sales events without paying for idle servers the rest of the year. This efficiency is why even a website designing company in India might lean toward serverless for client projects.

Wrapping Up

Serverless computing is changing how we build websites. By handing off server management, developers can focus on what users actually see and experience. Whether you’re coding alone or collaborating with a team, trying serverless could mean fewer headaches and more time for creative work.

Next time you start a project, ask yourself: Could skipping servers make this easier? The answer might just save you time and money.

#website development company in india #web design company india #website designing company in india #best web development agencies india #digital marketing agency india #online reputation management companies in india

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codebriefly · 2 months ago

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New Post has been published on https://codebriefly.com/how-to-handle-bounce-and-complaint-notifications-in-aws-ses/

How to handle Bounce and Complaint Notifications in AWS SES with SNS, SQS, and Lambda

In this article, we will discuss “how to handle complaints and bounce in AWS SES using SNS, SQS, and Lambda”. Amazon Simple Email Service (SES) is a powerful tool for sending emails, but handling bounce and complaint notifications is crucial to maintaining a good sender reputation. AWS SES provides mechanisms to capture these notifications via Amazon Simple Notification Service (SNS), Amazon Simple Queue Service (SQS), and AWS Lambda.

This article will guide you through setting up this pipeline and provide Python code to process bounce and complaint notifications and add affected recipients to the AWS SES suppression list.

Table of Contents

Toggle

Architecture Overview

Step 1: Configure AWS SES to Send Notifications

Step 2: Subscribe SQS Queue to SNS Topic

Step 3: Create a Lambda Function to Process Notifications

Python Code for AWS Lambda

Step 4: Deploy the Lambda Function

Step 5: Test the Pipeline

Conclusion

Architecture Overview

SES Sends Emails: AWS SES is used to send emails.

SES Triggers SNS: SES forwards bounce and complaint notifications to an SNS topic.

SNS Delivers to SQS: SNS publishes these messages to an SQS queue.

Lambda Processes Messages: A Lambda function reads messages from SQS, identifies bounced and complained addresses, and adds them to the SES suppression list.

Step 1: Configure AWS SES to Send Notifications

Go to the AWS SES console.

Navigate to Email Identities and select the verified email/domain.

Under the Feedback Forwarding section, set up SNS notifications for Bounces and Complaints.

Create an SNS topic and subscribe an SQS queue to it.

Step 2: Subscribe SQS Queue to SNS Topic

Create an SQS queue.

In the SNS topic settings, subscribe the SQS queue.

Modify the SQS queue’s access policy to allow SNS to send messages.

Step 3: Create a Lambda Function to Process Notifications

The Lambda function reads bounce and complaint notifications from SQS and adds affected email addresses to the AWS SES suppression list.

Python Code for AWS Lambda

import json import boto3 sqs = boto3.client('sqs') sesv2 = boto3.client('sesv2') # Replace with your SQS queue URL SQS_QUEUE_URL = "https://sqs.us-east-1.amazonaws.com/YOUR_ACCOUNT_ID/YOUR_QUEUE_NAME" def lambda_handler(event, context): messages = receive_sqs_messages() for message in messages: process_message(message) delete_sqs_message(message['ReceiptHandle']) return 'statusCode': 200, 'body': 'Processed messages successfully' def receive_sqs_messages(): response = sqs.receive_message( QueueUrl=SQS_QUEUE_URL, MaxNumberOfMessages=10, WaitTimeSeconds=5 ) return response.get("Messages", []) def process_message(message): body = json.loads(message['Body']) notification = json.loads(body['Message']) if 'bounce' in notification: bounced_addresses = [rec['emailAddress'] for rec in notification['bounce']['bouncedRecipients']] add_to_suppression_list(bounced_addresses) if 'complaint' in notification: complained_addresses = [rec['emailAddress'] for rec in notification['complaint']['complainedRecipients']] add_to_suppression_list(complained_addresses) def add_to_suppression_list(email_addresses): for email in email_addresses: sesv2.put_suppressed_destination( EmailAddress=email, Reason='BOUNCE' # Use 'COMPLAINT' for complaint types ) print(f"Added email to SES suppression list") def delete_sqs_message(receipt_handle): sqs.delete_message( QueueUrl=SQS_QUEUE_URL, ReceiptHandle=receipt_handle )

Step 4: Deploy the Lambda Function

Go to the AWS Lambda console.

Create a new Lambda function.

Attach the necessary IAM permissions:

Read from SQS

Write to SES suppression list

Deploy the function and configure it to trigger from the SQS queue.

Step 5: Test the Pipeline

Send a test email using SES to an invalid address.

Check the SQS queue for incoming messages.

Verify that the email address is added to the SES suppression list.

Conclusion

In this article, we are discussing “How to handle Bounce and Complaint Notifications in AWS SES with SNS, SQS, and Lambda”. This setup ensures that bounce and complaint notifications are handled efficiently, preventing future emails to problematic addresses and maintaining a good sender reputation. By leveraging AWS Lambda, SQS, and SNS, you can automate the process and improve email deliverability.

Keep learning and stay safe 🙂

You may like:

How to Setup AWS Pinpoint (Part 1)

How to Setup AWS Pinpoint SMS Two Way Communication (Part 2)?

Basic Understanding on AWS Lambda

#AWS Lambda #AWS SES #AWS SNS #AWS SQS #AWS

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technorucs · 2 months ago

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Workflow Automation: A Technical Guide to Streamlining Business Processes

In an era where digital transformation is crucial for business success, workflow automation has emerged as a key strategy to enhance efficiency, eliminate manual errors, and optimize processes. This guide provides an in-depth technical understanding of automating workflows, explores the architecture of automation tools like Power Automate workflow, and highlights the benefits of workflow automation from a technical perspective.

What is Workflow Automation?

Workflow automation is the process of using software to define, execute, and manage business processes automatically. These processes consist of a sequence of tasks, rules, and conditions that dictate how data flows across systems. The goal is to reduce human intervention, improve speed, and ensure process consistency.

Automation can be applied to various workflows, including:

Document Management – Automating approvals, storage, and retrieval.

Customer Relationship Management (CRM) – Auto-updating customer data, triggering notifications, and assigning tasks.

IT Operations – Automating system monitoring, log analysis, and incident responses.

Financial Processes – Invoice processing, payment reconciliations, and fraud detection.

Key Components of Workflow Automation

A typical workflow automation system consists of:

Trigger Events – Initiate automation based on user actions (e.g., form submission, email receipt) or system changes (e.g., new database entry).

Condition Logic – Defines rules using conditional statements (IF-THEN-ELSE) to determine workflow execution.

Actions and Tasks – The automated steps executed (e.g., sending emails, updating records, triggering API calls).

Integrations – Connections with third-party applications and APIs for data exchange.

Logging and Monitoring – Capturing logs for debugging, performance monitoring, and compliance tracking.

Technical Benefits of Workflow Automation

1. API-Driven Workflows

Modern automation tools rely on RESTful APIs to integrate with external applications. For example, Microsoft Power Automate workflow uses connectors to interact with services like SharePoint, Salesforce, and SAP.

2. Event-Driven Architecture

Automation platforms support event-driven models, allowing workflows to respond to real-time changes. Technologies like AWS Lambda, Azure Logic Apps, and Kafka enable scalable automation based on event triggers.

3. RPA and AI Integration

Robotic Process Automation (RPA) enhances traditional automation by using AI-powered bots to handle tasks like document scanning, data extraction, and decision-making. AI-based automation tools leverage:

Optical Character Recognition (OCR) for processing scanned documents.

Natural Language Processing (NLP) for sentiment analysis in customer feedback.

Machine Learning (ML) for predictive analytics in workflow decision-making.

4. Security and Compliance Considerations

When implementing automating workflows, businesses must ensure:

Role-Based Access Control (RBAC) – Ensures only authorized users can modify automation rules.

Audit Trails – Logs all workflow activities for compliance and troubleshooting.

Data Encryption – Protects sensitive information during automation.

5. Serverless Automation

Serverless computing platforms like AWS Step Functions and Azure Logic Apps enable serverless workflow execution, reducing infrastructure costs while improving scalability.

How to Implement Workflow Automation?

Step 1: Process Identification

Identify repetitive and rule-based processes suitable for automation. Use process mining tools like Celonis or UIPath Process Mining to analyze workflows.

Step 2: Selecting the Right Automation Platform

Choose a tool based on business requirements:

Microsoft Power Automate workflow – Best for enterprises using Microsoft 365.

Zapier – Ideal for no-code integrations between cloud apps.

UiPath, Blue Prism – Suitable for RPA-based automation.

Step 3: Workflow Design & Configuration

Define triggers (e.g., email receipt, API call).

Configure actions (e.g., database updates, message notifications).

Set conditions (e.g., decision logic, approval steps).

Step 4: Integration with Enterprise Systems

Use APIs, Webhooks, and middleware (e.g., Mulesoft, Apache Kafka) to connect automated workflows with CRM, ERP, and HRMS systems.

Step 5: Testing & Deployment

Unit Testing – Validate each step of the workflow.

Integration Testing – Ensure proper data exchange across systems.

Performance Testing – Assess automation speed and efficiency.

Step 6: Monitoring and Optimization

Utilize monitoring tools like Splunk, ELK Stack, or Azure Monitor to analyze workflow performance and optimize automation rules.

Future of Workflow Automation

Hyperautomation – The combination of RPA, AI, and ML for end-to-end business process automation.

Blockchain for Workflow Security – Smart contracts ensuring transparent and tamper-proof workflows.

Edge Computing in Automation – Bringing automation closer to IoT devices for real-time decision-making.

Conclusion

Workflow automation is revolutionizing business operations by enabling intelligent, data-driven decision-making. Leveraging automating workflows through tools like Power Automate workflow, businesses can achieve greater efficiency, accuracy, and scalability. The benefits of workflow automation extend beyond cost savings, impacting compliance, security, and business agility.

Investing in the right automation technology will ensure a future-proof and competitive business environment. Start implementing workflow automation today to drive innovation and efficiency!

#workflow automation software #Power Automate workflow #benefits of workflow automation #microsoft

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danielweasly · 2 months ago

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Serverless Computing: Building & Deploying Applications without Infrastructure Management

Serverless computing is revolutionizing how developers build and deploy applications by eliminating the need for traditional infrastructure management. In a serverless environment, developers can focus solely on writing code while cloud providers handle the provisioning, scaling, and management of servers. This approach reduces operational overhead, improves agility, and allows developers to only pay for the computing resources they use, making it an efficient and cost-effective solution. Serverless computing services, such as AWS Lambda, Google Cloud Functions, and Azure Functions, automatically scale based on traffic, ensuring optimal performance without manual intervention.

This model is especially beneficial for microservices architectures, where different components of an application are deployed independently. Developers can build and deploy individual functions without worrying about managing the underlying servers, allowing for faster iteration and development cycles. Furthermore, serverless computing supports event-driven programming, making it an ideal choice for applications that respond to specific triggers, such as HTTP requests, database changes, or file uploads. This paradigm is quickly gaining traction across industries as it offers a flexible and scalable approach to application development.

Click here to know more about Serverless Computing: Building & Deploying Applications without Infrastructure Management https://www.intelegain.com/serverless-computing-building-deploying-applications-without-infrastructure-management/

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learning-code-ficusoft · 3 months ago

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Serverless DevOps: How Lambda and Cloud Functions Fit In

Introduction to Serverless DevOps: What It Is and Why It Matters

1. What Is Serverless DevOps?

Serverless DevOps is a modern approach to software development and operations that leverages serverless computing for automating CI/CD pipelines, infrastructure management, and deployments — without provisioning or maintaining servers.

Key Features of Serverless DevOps

✅ No Server Management: Developers focus on writing code while cloud providers handle scaling and infrastructure. ✅ Event-Driven Automation: Functions (e.g., AWS Lambda, Google Cloud Functions) are triggered by events like code commits or API requests. ✅ Cost-Efficient: Pay only for execution time, reducing costs compared to always-on infrastructure. ✅ Scalability: Auto-scales based on demand, ensuring high availability. ✅ Faster Development & Deployment: CI/CD pipelines can be entirely serverless, improving deployment speed.

2. Why Does Serverless Matter for DevOps?

Traditional DevOps practices require managing infrastructure for CI/CD, monitoring, and deployments. Serverless DevOps eliminates this complexity, making DevOps workflows:

🔹 More Agile → Deploy new features quickly without worrying about infrastructure. 🔹 More Reliable → Auto-scaling and built-in fault tolerance ensure high availability. 🔹 More Cost-Effective → No need to run VMs or containers 24/7. 🔹 More Efficient → Automate workflows using functions instead of dedicated servers.

3. How Serverless DevOps Works

A typical Serverless DevOps workflow consists of:

1️⃣ Code Commit → Developer pushes code to a repository (GitHub, CodeCommit, Bitbucket). 2️⃣ Trigger Build Process → AWS Lambda or Cloud Functions start the CI/CD process. 3️⃣ Code Testing & Packaging → AWS Code Build or Cloud Build compiles and tests code. 4️⃣ Deployment → Code is deployed to a serverless platform (AWS Lambda, Cloud Functions, or Fargate). 5️⃣ Monitoring & Logging → Serverless monitoring tools track performance and errors.

4. Serverless Tools for DevOps

5. Conclusion

Serverless DevOps accelerates software delivery, reduces costs, and improves scalability by automating deployments without managing servers.

Whether using AWS Lambda or Google Cloud Functions, integrating serverless into DevOps workflows enables faster, more efficient development cycles.

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

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awsaicourse12 · 3 months ago

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AWS Data Analytics Training | AWS Data Engineering Training in Bangalore

What’s the Most Efficient Way to Ingest Real-Time Data Using AWS?

AWS provides a suite of services designed to handle high-velocity, real-time data ingestion efficiently. In this article, we explore the best approaches and services AWS offers to build a scalable, real-time data ingestion pipeline.

Understanding Real-Time Data Ingestion

Real-time data ingestion involves capturing, processing, and storing data as it is generated, with minimal latency. This is essential for applications like fraud detection, IoT monitoring, live analytics, and real-time dashboards. AWS Data Engineering Course

Key Challenges in Real-Time Data Ingestion

Scalability – Handling large volumes of streaming data without performance degradation.

Latency – Ensuring minimal delay in data processing and ingestion.

Data Durability – Preventing data loss and ensuring reliability.

Cost Optimization – Managing costs while maintaining high throughput.

Security – Protecting data in transit and at rest.

AWS Services for Real-Time Data Ingestion

1. Amazon Kinesis

Kinesis Data Streams (KDS): A highly scalable service for ingesting real-time streaming data from various sources.

Kinesis Data Firehose: A fully managed service that delivers streaming data to destinations like S3, Redshift, or OpenSearch Service.

Kinesis Data Analytics: A service for processing and analyzing streaming data using SQL.

Use Case: Ideal for processing logs, telemetry data, clickstreams, and IoT data.

2. AWS Managed Kafka (Amazon MSK)

Amazon MSK provides a fully managed Apache Kafka service, allowing seamless data streaming and ingestion at scale.

Use Case: Suitable for applications requiring low-latency event streaming, message brokering, and high availability.

3. AWS IoT Core

For IoT applications, AWS IoT Core enables secure and scalable real-time ingestion of data from connected devices.

Use Case: Best for real-time telemetry, device status monitoring, and sensor data streaming.

4. Amazon S3 with Event Notifications

Amazon S3 can be used as a real-time ingestion target when paired with event notifications, triggering AWS Lambda, SNS, or SQS to process newly added data.

Use Case: Ideal for ingesting and processing batch data with near real-time updates.

5. AWS Lambda for Event-Driven Processing

AWS Lambda can process incoming data in real-time by responding to events from Kinesis, S3, DynamoDB Streams, and more. AWS Data Engineer certification

Use Case: Best for serverless event processing without managing infrastructure.

6. Amazon DynamoDB Streams

DynamoDB Streams captures real-time changes to a DynamoDB table and can integrate with AWS Lambda for further processing.

Use Case: Effective for real-time notifications, analytics, and microservices.

Building an Efficient AWS Real-Time Data Ingestion Pipeline

Step 1: Identify Data Sources and Requirements

Determine the data sources (IoT devices, logs, web applications, etc.).

Define latency requirements (milliseconds, seconds, or near real-time?).

Understand data volume and processing needs.

Step 2: Choose the Right AWS Service

For high-throughput, scalable ingestion → Amazon Kinesis or MSK.

For IoT data ingestion → AWS IoT Core.

For event-driven processing → Lambda with DynamoDB Streams or S3 Events.

Step 3: Implement Real-Time Processing and Transformation

Use Kinesis Data Analytics or AWS Lambda to filter, transform, and analyze data.

Store processed data in Amazon S3, Redshift, or OpenSearch Service for further analysis.

Step 4: Optimize for Performance and Cost

Enable auto-scaling in Kinesis or MSK to handle traffic spikes.

Use Kinesis Firehose to buffer and batch data before storing it in S3, reducing costs.

Implement data compression and partitioning strategies in storage. AWS Data Engineering online training

Step 5: Secure and Monitor the Pipeline

Use AWS Identity and Access Management (IAM) for fine-grained access control.

Monitor ingestion performance with Amazon CloudWatch and AWS X-Ray.

Best Practices for AWS Real-Time Data Ingestion

Choose the Right Service: Select an AWS service that aligns with your data velocity and business needs.

Use Serverless Architectures: Reduce operational overhead with Lambda and managed services like Kinesis Firehose.

Enable Auto-Scaling: Ensure scalability by using Kinesis auto-scaling and Kafka partitioning.

Minimize Costs: Optimize data batching, compression, and retention policies.

Ensure Security and Compliance: Implement encryption, access controls, and AWS security best practices. AWS Data Engineer online course

Conclusion

AWS provides a comprehensive set of services to efficiently ingest real-time data for various use cases, from IoT applications to big data analytics. By leveraging Amazon Kinesis, AWS IoT Core, MSK, Lambda, and DynamoDB Streams, businesses can build scalable, low-latency, and cost-effective data pipelines. The key to success is choosing the right services, optimizing performance, and ensuring security to handle real-time data ingestion effectively.

Would you like more details on a specific AWS service or implementation example? Let me know!

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hexaa12321 · 19 days ago

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Serverless Computing: Simplifying Backend Development

Absolutely! Here's a brand new 700-word blog on the topic: "Serverless Computing: Simplifying Backend Development" — written in a clear, simple tone without any bold formatting, and including mentions of Hexadecimal Software and Hexahome Blogs.

Serverless Computing: Simplifying Backend Development

The world of software development is constantly evolving. One of the most exciting shifts in recent years is the rise of serverless computing. Despite the name, serverless computing still involves servers — but the key difference is that developers no longer need to manage them.

With serverless computing, developers can focus purely on writing code, while the cloud provider automatically handles server management, scaling, and maintenance. This approach not only reduces operational complexity but also improves efficiency, cost savings, and time to market.

What is Serverless Computing?

Serverless computing is a cloud computing model where the cloud provider runs the server and manages the infrastructure. Developers simply write functions that respond to events — like a file being uploaded or a user submitting a form — and the provider takes care of executing the function, scaling it based on demand, and handling all server-related tasks.

Unlike traditional cloud models where developers must set up virtual machines, install software, and manage scaling, serverless removes those responsibilities entirely.

How It Works

Serverless platforms use what are called functions-as-a-service (FaaS). Developers upload small pieces of code (functions) to the cloud platform, and each function is triggered by a specific event. These events could come from HTTP requests, database changes, file uploads, or scheduled timers.

The platform then automatically runs the code in a stateless container, scales the application based on the number of requests, and shuts down the container when it's no longer needed. You only pay for the time the function is running, which can significantly reduce costs.

Popular serverless platforms include AWS Lambda, Google Cloud Functions, Azure Functions, and Firebase Cloud Functions.

Benefits of Serverless Computing

Reduced infrastructure management Developers don’t have to manage or maintain servers. Everything related to infrastructure is handled by the cloud provider.

Automatic scaling Serverless platforms automatically scale the application depending on the demand, whether it's a few requests or thousands.

Cost efficiency Since you only pay for the time your code runs, serverless can be more affordable than always-on servers, especially for applications with variable traffic.

Faster development Serverless enables quicker development and deployment since the focus is on writing code and not on managing environments.

High availability Most serverless platforms ensure high availability and reliability without the need for additional configuration.

About Hexadecimal Software

Hexadecimal Software is a leading software development company specializing in cloud-native solutions, DevOps, and modern backend systems. Our experts help businesses embrace serverless computing to build efficient, scalable, and low-maintenance applications. Whether you’re developing a new application or modernizing an existing one, we can guide you through your cloud journey. Learn more at https://www.hexadecimalsoftware.com

Explore More on Hexahome Blogs

To discover more about cloud computing, DevOps, and modern development practices, visit our blog platform at https://www.blogs.hexahome.in. Our articles are written in a simple, easy-to-understand style to help professionals stay updated with the latest tech trends.

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