Cloud Computing for Managers with AWS Cloud

Explore how AWS S3 stores data on the internet, enabling unlimited, pay-as-you-go cloud storage accessible from anywhere while decoupling data from compute and enabling serverless processing with tools like Athena.

Explore how to structure data in s3 with buckets and folders, including unique bucket names, regional placement, cross-region replication, and object storage costs, featuring practical bucket demos.

Create an S3 bucket, add a Sales folder, upload a file, generate a presigned URL for access, and practice deleting objects to finish the S3 demo.

Compress data to cut storage costs, using Parquet or ORC before uploading to S3. Encrypt with 128/256 keys via AWS managed or CMEK, and safeguard keys.

Demonstrates uploading to an S3 bucket, enabling and using versioning to recover deleted or overwritten files, and considers versioning costs and lifecycle options.

Explore AWS Outposts for hybrid cloud, enabling S3 bucket management on premises in your data center to meet regulatory needs and reduce latency, with AWS handling software and patches.

Learn to cut S3 costs by using storage classes like Standard, Standard-IA, Glacier, and Glacier Instant Retrieval, and automate transitions with lifecycle policies for archives and backups.

Compare json, parquet, and orc storage formats to understand schema, compression, and predicate pushdown, and learn how csv's lack of schema affects data handling.

Enforce cloud storage discipline with organization-wide controls and regular audits to track S3 data and costs, and apply lifecycle policies that move aged data to cheaper storage or archive.

Learn why cloud storage is popular and how to set up aws s3 buckets with versioning, encryption, and lifecycle policies to reduce costs.

Explore how serverless enables quick cloud adoption with AWS, using Athena, Glue, EventBridge, Lambda, DynamoDB, and Redshift serverless for big data processing.

Explore how serverless processing on AWS eliminates server provisioning. Scale automatically to petabytes of data, and pay only for data processed or run time.

Explore how Athena supports standard sql, including select and create table as select, with joins, window functions, inserts, and S3 demos, while data remains read-only.

Leverage Athena partitioning to reduce data scanned and query costs by filtering on year and month, with data stored in column=value folders and partition columns not in the data.

Harness AWS Glue, a serverless ETL service for extracting, transforming, and loading data in S3. Build and maintain the Glue catalog with crawlers, shared with Athena and other tools.

Utilize the Glue data catalog as a repository for data schemas, using a crawler to parse data and enable access to S3 data from Athena, Redshift, EMR, and AWS Lambda.

Amazon Simple Notification Service enables pub-sub messaging with publishers and subscribers via a named topic. It supports email, sms, and lambda integrations with a serverless, secure, durable, pay-as-you-go model.

Explore how Amazon SQS organizes messages into queues, with producers adding messages and consumers retrieving and deleting them. Understand message retention from four days up to fourteen days.

Amazon EventBridge is a serverless AWS service that uses event buses, sources, rules, and targets to route json events, with S3 and Lambda examples and schema inference and code bindings.

Discover DynamoDB, a real-time NoSQL document database with Json objects and a primary key, delivering subsecond latency and simple operations to create tables, put items, get items, and update items.

Explore how DynamoDB stores data as items in tables, with varying fields per item, unlike fixed relational columns, and queries like French cuisine or online orders.

Explore how to create a DynamoDB table, insert and delete items, and manage data in AWS DynamoDB, including partition key and eventual consistency.

Explore how Amazon Redshift serves as a fully managed cloud data warehouse that handles petabyte-scale data, supports Postgres SQL and stored procedures, and enables migration from Oracle and SQL Server.

Explore how Redshift Spectrum extends Redshift into a serverless data warehouse that scales on S3 with data scanned pricing and on-demand provisioning.

The SCT, a free AWS service, converts in-house data warehouse schemas to Redshift, translating table and stored procedure definitions from sources like Oracle and SQL Server, and reports conversion statistics.

Learn Redshift serverless, paying only for storage and compute when queries run, with auto-scaling RPUs, zero-cost idle periods, and snapshot-based migration.

Move your in-house Hadoop and Spark workloads to the cloud with AWS EMR, spin up on-demand clusters, and pay only for use while running jobs on S3.

Learn to set up emr serverless, create an s3 and glue access role, deploy a spark word-count job, monitor status from pending to success, and clean up resources.

Learn how AWS step functions orchestrate serverless workflows to run lambda functions, manage data on S3 and EMR clusters, and send notifications via SNS and SQS, cost-effectively, with JSON parameterization.

Set up an event-driven processing pipeline by configuring S3 to publish events to AWS EventBridge and trigger a Lambda function, then monitor via CloudWatch logs.

Discover how serverless computing powers data processing with AWS tools such as Athena, Glue, EventBridge, Lambda, DynamoDB, Redshift, and EMR.

Understand authentication and authorization on AWS, and how identity determines access to an S3 bucket. See how groups and roles like developers and testers manage permissions with multifactor authentication.

Define AWS roles as bundles of permissions, attach policies to them, and associate roles with services like Redshift and S3 to enable secure cross-service access.

Create an AWS account to begin using the cloud; the account holds resources. Define IAM policies at the account level to govern access for users, groups, and roles.

Create an identity-based IAM policy with a JSON form, grant S3 read, write, and list permissions, and attach the policy to a Lambda role with proper trust relationships.

Demonstrate creating a resource-based bucket policy in S3 to enforce encryption, deny put object when the encryption key is missing, and apply an inline policy with policy examples.

Master security by understanding the shared responsibility model and configuring access with AWS IAM—managing users, groups, roles, and identity-level and resource-level policies, and applying organizational units via the IAM console.

Explore Google's site reliability engineering principles: reliability, monitoring, automation, and scalability, and their relevance to cloud management with AWS.

Discover how AWS CloudWatch monitors resource usage, collects logs, and analyzes metrics to trigger alarms, while AWS CloudTrail captures management and data events, guiding site reliability engineering practices.

Identify key service level indicators to monitor cloud services, such as availability above 99%, downtime, and metrics like jobs running, bytes scanned per query, event counts, and S3 bucket activity.

Balance cost and revenue risk by distinguishing availability from durability, note S3's 99.999% durability, set minimum availability levels, and design proactive alerts that require concrete corrective actions.

Analyze and debug distributed applications with AWS X-Ray to troubleshoot errors and slow performance, using a step-by-step view of requests and checkpoints to identify root causes in development and production.

Learn to configure meaningful alerts using uptime checks and AWS simple notification service to send email, sms, or push notifications, and route events through EventBridge to minimize alert fatigue.

Learn to monitor symptoms, not causes, with automated logging and alerts for disk space and system down events, focusing on latency, traffic, errors, and saturation to reduce alert fatigue.

Explore monitoring essentials by using logs, metrics, log-based metrics, dashboards, notification channels, and cloudwatch alarms; apply four golden signals: latency, traffic, errors, and saturation.

Learn how cloud computing began with renting virtual machines and how Amazon EC2 offers elastic compute cloud with on-demand, reserved, and spot instances, per-second billing, and scalable, secure access.

Discover how AWS machine learning tools scale without heavy infrastructure. Use Rekognition for image and video analysis, Transcribe and Polly for speech tasks, Translate for language, and Lex for chatbots.

Explore containerized applications, a virtual environment that bundles all dependencies so an app runs anywhere, offering portability, independence, easy maintenance, parallelization, and scalable cloud deployment.

Explore Kubernetes, an open source platform for managing containers. See how Amazon Elastic Kubernetes Service, a fully managed solution, enables master and worker nodes, load balancing, auto scaling, and monitoring.

Explore AWS Cloud Shell, a free, always-available virtual machine in the AWS console with Linux, 1 GB storage, and pre-installed AWS CLI for managing AWS and S3, including a versioning demo.

Configure cloud native desktops with AWS workspaces to provide employees a consistent, secure remote desktop across devices, with active directory, always-on or auto-stop options, and pay-as-you-go compute and storage.

Master infrastructure as code with Terraform to deploy and maintain AWS resources like virtual machines, redshift clusters, S3 storage buckets, Glue jobs, and event flow topics.

Wrap up the course by reinforcing serverless AWS skills—Athena, Lambda, S3, EventBridge, SNS, DynamoDB, IAM—empowering managers to guide cloud design and cost savings.