In our previous blog How to build a Serverless Workflow with AWS Step Functions? (Part 1), we have discussed AWS Step functions, its features, benefits, use cases, etc. In this blog, we will discuss a business scenario to configure and create a serverless workflow to handle the issue resolution statuses raised by each of the customers and follow a systematic process for the same.
Let’s say a company has a department of customer service that handles all the service requests raised by the customers. It’s getting difficult to handle the record of each issue raised by each of the customers…
AWS Step Functions is a serverless orchestration service that lets you easily coordinate multiple Lambda functions into flexible workflows that are easy to debug and easy to change. In this blog, we have discussed AWS Step functions, its features, benefits, use cases, etc.
You can refer our blog How to build a Serverless Workflow with AWS Step Functions? (Part 2) to understand and built a Serverless Workflow with AWS Step Functions
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Did you know AWS (Amazon Web Services) is the predominant player in the global cloud business with 33% of the market share followed by Microsoft, Google, Alibaba and IBM with 18%, 9%, 6% and 5% respectively? (Source of data — Statista Research Group)
Modern applications such as those running on microservices architectures generate large volumes of data in the form of metrics, logs, and events. Amazon CloudWatch enables you to collect, access, and correlate this data on a single platform from across all your AWS resources, applications, and services that run on AWS.
Amazon CloudWatch enables you to set alarms and automate actions based on either predefined threshold. You can also perform metric math on your data to derive operational and utilization insights. You can also use CloudWatch Events for serverless to trigger workflows with services like AWS Lambda, Amazon SNS.
Whether you’re considering a cloud migration or have already made the switch to AWS, you’ll want to know how to manage your digital environment. With Amazon CloudWatch, AWS makes monitoring simple. CloudWatch is the foundational basis for management of your AWS infrastructure. It provides a strong capture and storage mechanism for metrics and logs.
While the management tools for viewing and analysis are basic, by augmenting CloudWatch with 3rd party tools, you can easily create a comprehensive monitoring and management platform for your infrastructure.
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Docker is a technology that provides the tools for you to build, run, test, and deploy distributed applications that are based on Linux containers. Docker provides the ability to package and run an application in a loosely isolated environment called a container. The isolation and security allow you to run many containers simultaneously on a given host. Containers are lightweight and contain everything needed to run the application, so you do not need to rely on what is currently installed on the host. …
The fast rise in interest and use of container-based solutions has necessitated the development of industry standards for container technology and the packaging of software code. Docker is currently one of the most well-known and widely utilised container engines on the market. Docker was launched in 2013 by a company called Dotcloud, Inc which was later renamed as Docker, Inc. It is written in the Go language.
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Data scientists, machine learning engineers, and practitioners must devote significant time and resources to developing, testing, updating, and optimising Docker images for deep learning. Instead of concentrating on developing and enhancing models, practitioners are forced to divert valuable resources to unrelated tasks. Installing packages, resolving compatibility concerns, performance optimization, and integrating and testing with Amazon Sagemaker, Amazon EC2, Amazon ECS, and Amazon EKS are examples of these tasks. AWS DL Containers provide deep learning Docker environments that are fully tested and optimised and require no installation, configuration, or maintenance. …
There are chances where the employees / users either intentionally or unintentionally make changes or delete the AWS resources. These scenarios cannot be traced or brought into our notice unless we have a proper monitoring and alerting mechanism to take action immediately to avoid any business interruptions.
Proactive monitoring is one of the key items in maintaining a Secure infrastructure.
To catch such activities, we can make use of the AWS services such as CloudTrail, CloudWatch and SNS topic with subscribers to actively monitor the activities happening in the AWS account, log them and notify the subscribers when such an…
Someone logged into your AWS Console and forced the shutdown of an EC2 instance, and you need to discover who did it as it was a critical instance for production, but you have no records. Here AWS CloudTrail comes to your rescue! In your AWS infrastructure, you can use AWS CloudTrail for logging, continuously monitoring, and retaining account activity related to all day to day operations.
In this blog, we will explore AWS CloudTrail benefits, features, use cases, pricing and customer stories. …