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tutorials dojo

/Tag: tutorials dojo

Amazon Aurora Machine Learning

2023-01-30T13:31:55+00:00

Amazon Aurora Machine Learning is a proprietary technology of Amazon that enables a native SQL user to integrate Machine Learning-based predictions to an application without knowing or understanding any machine learning algorithms. Machine learning heavily relies on datasets for it to work. You can say that data is the oil that keeps the engine of machine learning running. There is a massive amount of data generated every day. To give you an idea, according to this article, “By 2020, it’s estimated that for every person on earth, 1.7 MB of data will be created every second.”  Almost 2 MB of [...]

Amazon Aurora Machine Learning2023-01-30T13:31:55+00:00

Logging Using awslogs Log Driver in Amazon ECS

2021-05-04T09:25:50+00:00

Monitoring and logging can be as important as developing and deploying applications. Imagine managing an enterprise-level distributed application that runs on hundreds of containers. You must place your containers cleverly on instances to achieve a certain level of resilience and performance. On top of that, you would want to have visibility into CPU and memory usage so you’ll have an idea which task/tasks are resource-hungry at a given time. You may also want to check the disk space of your instance and see if you still have enough storage for your application. Fortunately, monitoring distributed applications hosted in AWS has [...]

Logging Using awslogs Log Driver in Amazon ECS2021-05-04T09:25:50+00:00

AWS Glue

2021-09-26T03:34:56+00:00

Bookmarks Use Cases Concepts Populating the AWS Glue Data Catalog Authoring Jobs Glue DataBrew Monitoring Security Pricing Validate Your Knowledge A fully managed service to extract, transform, and load (ETL) your data for analytics. Discover and search across different AWS data sets without moving your data. AWS Glue consists of: Central metadata repository ETL engine Flexible scheduler Use Cases Run queries against an Amazon S3 data lake You can use AWS Glue to make your data available for analytics without moving your data. Analyze the log data in [...]

AWS Glue2021-09-26T03:34:56+00:00

Managing Amazon GuardDuty Security Findings Across Multiple Accounts

2023-02-03T10:16:00+00:00

In our previous article, we discussed how GuardDuty can help organizations monitor their workloads and  AWS accounts from malicious activities and how to monitor findings with Amazon CloudWatch Events. Imagine that your organization has multiple AWS accounts for different workloads, teams, and projects. With every account, you need to monitor GuardDuty findings individually. It will be quite difficult for your security team to monitor these findings with their constant switching between AWS accounts.  Amazon GuardDuty supports the consolidation of these findings to one AWS account. For example, your organization has 10 AWS accounts. All you have to do is to [...]

Managing Amazon GuardDuty Security Findings Across Multiple Accounts2023-02-03T10:16:00+00:00

Monitoring GuardDuty Findings with Amazon CloudWatch Events

2023-02-03T10:14:18+00:00

Large scale cyber attacks are now becoming normal in this age of interconnectivity. As we rely more and more on cloud technologies, companies are looking to tap into digital innovations to improve their businesses. Cyber attacks are costing companies millions of dollars of downtime not to mention the possibility of lawsuits whenever an attack occurs. It is imperative that security teams have the means to prevent, detect, and take actions to ensure that the security of their workloads in AWS are airtight. Amazon GuardDuty was released during the 2017 re:Invent conference. Amazon GuardDuty is an agentless threat detection service that [...]

Monitoring GuardDuty Findings with Amazon CloudWatch Events2023-02-03T10:14:18+00:00

Aurora Serverless Tutorial Part 2

2021-05-03T13:22:18+00:00

In the first part of this tutorial, we gave a walkthrough on Aurora Serverless and its use case. You can read the article here. For this tutorial, we will do some hands-on training and create an Aurora Serverless database. Creating an Aurora Serverless Database: 1. Open the AWS console and go to RDS. Click the button “Create database”. 2. Choose Amazon Aurora. You can either choose MySQL or PostgreSQL compatibility. In this tutorial, we will use MySQL compatibility. As of this writing, there are two versions of MySQL that Aurora serverless supports. Under the Database Features, select serverless. 3. Under [...]

Aurora Serverless Tutorial Part 22021-05-03T13:22:18+00:00

Aurora Serverless Tutorial – Part 1

2021-05-03T13:22:11+00:00

What is Aurora Serverless?  Before we get into it, let us briefly define Aurora and serverless first. Aurora is a fully managed, closed source relational database that is compatible with MySQL and PostgreSQL. According to Amazon, it is five times faster than the standard MySQL and three times faster than PostgreSQL. It uses a distributed architecture that provides fault tolerance and high availability.  Serverless is a technique in the cloud that follows the ‘pay-per-use’ model. As opposed to its name, serverless does not mean not using ‘servers’. There is no magic in it. It still uses a physical server that [...]

Aurora Serverless Tutorial – Part 12021-05-03T13:22:11+00:00

Google BigQuery vs BigTable

2021-03-09T07:38:51+00:00

BigQuery BigTable BigQuery is Google Cloud's fully managed, petabyte-scale, and cost-effective analytics data warehouse that lets you run analytics over vast amounts of data in near real-time. You can use bq command-line tool or Google Cloud Console to interact with BigTable. You can access BigQuery by using the Cloud Console, by using the bq command-line tool, or by making calls to the BigQuery REST API using a variety of client libraries such as Java, .NET, or Python. A dataset is contained within a specific project. Datasets are top-level containers that are used to organize and control access to your tables [...]

Google BigQuery vs BigTable2021-03-09T07:38:51+00:00

Google Cloud Functions vs App Engine vs Cloud Run vs GKE

2021-03-09T07:38:33+00:00

Serverless compute platforms like Cloud Functions, App Engine, and Cloud Run lets you build, develop, and deploy applications while simplifying the developer experience by eliminating all infrastructure management. On the other hand, Google Kubernetes Engine (GKE) runs Certified Kubernetes that helps you facilitate the orchestration of containers via declarative configuration and automation. Both Google serverless platforms and GKE allows you to scale your application based on your infrastructure requirement. Here’s a table to help you identify when to use these specific services. Cloud Functions App Engine Cloud Functions is a fully managed, serverless platform for creating stand-alone functions that respond [...]

Google Cloud Functions vs App Engine vs Cloud Run vs GKE2021-03-09T07:38:33+00:00

Google Cloud Storage vs Persistent Disks vs Local SSD vs Cloud Filestore

2021-03-09T23:46:32+00:00

Google Cloud Storage Persistent Disks Local SSD Cloud Filestore Cloud Storage is a service for storing your objects in Google Cloud. An object is an immutable piece of data consisting of a file of any format. You store objects in containers called buckets. You specify a location for storing your object data when you create a bucket. You can either select region, dual-region, and multi-region as location. Objects stored in a multi-region or dual-region are geo-redundant. Cloud Storage offers different storage classes for various storage requirements: Standard, Nearline, Coldline, and Archive. GCS offers unlimited storage with no minimum object size. [...]

Google Cloud Storage vs Persistent Disks vs Local SSD vs Cloud Filestore2021-03-09T23:46:32+00:00

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