AWS Cloud Practitioner

History of Computing Infrastructure
1. The Past
  1. Companies host their own data centers, which means they must pay operation costs and provision for their worst-case scenario, leading to over-provisioning
2. The Present
  1. Infrastructure is provided as a service (IaaS) by cloud providers like AWS, GCP, or Azure
    1. Pay as you go
    2. Scale as necessary
    3. New IT Resources on Demand
    4. Benefit from Economies of Scale
    5. Result: Deploy globally quickly and focus on what differentiates your application
Cloud Economics: Business Value
1. Cost Benefits
  1. Compare cost of traditional IT setup to AWS
    1. Identify end-to-end costs
      1. Typically 20-40% less
  2. Best Practices
    1. Ensure releavnt shareholders are present
    2. Use realistic estimates for usage
    3. Assign cost / value to business value factors like agility, risk, automation
  3. anti-practices
    1. Apples to apples comparison. AWS Is more than just discounts
    2. Forget operational costs like power, administration, rent, software, hardware
  4. Lower costs with AWS
    1. Consumption model: only pay for what you need
    2. Average payback time of 6 months
    3. AWS Flywheel
  5. Migration
    1. Return on Investment
      1. Customers want to retire hardware that is fully deprecated.
      2. Cost ( and effort ) of migration requires analysis
      3. Cost savings / (sunk costs + migration costs ) = ROI
    2. Cloud Readiness
      1. Human factor
        Team lacks the skills and experience to transform
        May oppose cloud development for logical or illogical reasons
      2. Application factor
        Dependency and Tension
        Identify easy and difficult applications
    3. Process typically takes about a month
2. Staff Productivity
  1. Less tactical ( undifferentiated ) more strategic (undifferentiated work)
  2. Staff Productivity functions
    1. Facilities
      1. Disaster recovery, planning, power, cooling reduced / eliminated
    2. Security
      1. Security tool administration, set up new devices reduced
    3. Network
      1. Network maintenance, hardware, infrastructure eliminated or reduced
    4. Server
      1. Reduce patching, arranging hardware planning, repairing, purchasing, etc
    5. Storage
      1. System updates, installation reduced or eliminated
    6. Application
      1. Test code, execution, environment improved
3. Operational Resilience
  1. important factors are up-time and security
  2. Cornerstones
    1. Operations
      1. causes for failure: human errors, configuration errors, commonplace accidents
      2. how AWS helps: leverages automation, monitors access, end-to-end servuce management
    2. Security
      1. Causes for failure : malware, network, poor authentication
      2. How AWS Helps: Shared security model, built in DDOS protection, AWS IAM
    3. Software
      1. Causes for failure: Resources exhaustion, logic errors, bad monitoring, failed updates
      2. How AWS helps: quick rollouts, auto CI, smaller deployments, collects resources
    4. Infrastructure
      1. causes for failure: hardware failure, natural disaster, power outage
      2. How AWS helps: run applications over multiple AZs, multiple power sources
4. Business Agility
  1. Delivering more value in less time
  2. Measure using key performance indicators (KPI)
    1. ex. new applications launched per year, features per release, etc.
  3. Innovate by failing fast while reducing risk and cost
AWS Tools
1. Compute
  1. Elastic Cloud Compute (EC2)
    1. Elastic for auto-scaling
    2. Multiple Instance-types
  2. Elastic Auto-scaling
    1. Monitors instance health
    2. Replaces broken instances
    3. Balance across AZ
    4. Dynamic and predictive Scaling
  3. EC2 Auto-Scaling
    1. Types: Application load balancer, network load balancer, classic load balancer
    2. Distributes application traffic across EC2 Instances
  4. AWS Lambda
    1. Serverless Computing
  5. Container-Service
    1. Scalable Container management
2. Storage
  1. Elastic Block Storage (EBS)
    1. Network-attached service like a hard drive
    2. Independent of EC2, can be attached to an instance in same AZ
      1. One EBS volume to one ec2 instance, one instance can have many EBS
  2. Simple Storage Service (S3)
    1. Stores data as objects in buckets
    2. Common use cases: backup + storage, media hosting, software delivery, application hosting
    3. Cheaper based on infrequency of access
3. Database
  1. DynamoDB
    1. No SQL
  2. RDS / Aurora
    1. Relational Database. Auroa: Postgres
  3. Elasticache
    1. Caching System
  4. Host DB on EC2
    1. Option to host DB on compute instance
      1. Pros: More control. Cons: less automation
4. Network
  1. Virtual Private Cloud (VPC)
    1. Gives users full control over application network
      1. Utilize subnets, which are ranges of IPs
  2. Security Groups
    1. Controls access to instances. Instances can be added to subsets of security groups
  3. Network Access Control Lists (NACL)
    1. Control Access to subnets
  4. Route 53
    1. Routes end users to internet application
5. Security
  1. Identity and Access Management (IAM)
    1. Fine-grained access control
      1. Access Analysis and MFA
      2. Integration with company directories
  2. Shared Responsibility Model
    1. AWS Responsible for infrastructure, user responsible for application
6. Management
  1. Management Console (GUI)
  2. CLI
  3. SDKs
Well-Architected Infrastructure
1. Security
  1. Encompasses infrastructure, data, incidence protection
  2. Best Practices
    1. Implement security at all levels
    2. Enable traceability for all important actions
    3. Principle of least privilege - Give people only as much privilege as they need
    4. Focus on security your system - Shared Responsibility model
2. Reliability
  1. Ability to recover from failure and meet demand
  2. Best Practices
    1. Test recovery procedures
    2. Automatically Recover
      1. ex. use auto-scale to remove broken instances
    3. Scale horizontally, Scale automatically
      1. use auto-scale to create more instances instead of better instances.
3. Cost Optimization
  1. Pillars
    1. Match supply with demand
      1. leverage auto-scaling and elasticity
    2. Increase expenditure awareness
    3. Optimize over time
      1. use reserved instances over on-demand
  2. Best Practices
    1. Pay only for what you use
    2. Measure and attribute expenditure
4. Operational Excellence
  1. Pillars
    1. Manage and automate changes
    2. Respond to events
    3. Define Standards
5. Performance Efficiency
  1. Pillars
    1. Select customizable solutions
    2. Review to continually innovate
      1. Monitor Performance
      2. Automate using CloudWatch
    3. Monitor AWS Services
    4. Consider trade-offs
  2. Best Pratices
    1. Democratize advanced technologies
      1. Consider consuming as a service instead of learning a skill
    2. Experiment and use the best tool for the job
Customer Strategies
1. Migration Strategies
  1. Rehost
    1. Recreate on-premises setup on AWS
    2. Lift and Shift
  2. Replatform
    1. Lift, Tinker, and Shift
    2. Retain core architecture, but make targeted AWS optimizations. ex migrate db to RDS
  3. Refactor
    1. Modernize by re-imagining how the application is architected and developed. ex monolith to services
  4. Retire
    1. Shutting off non-useful components
  5. Retain / Revisit
    1. Keeping certain applications on-premise, only migrate what you need
  6. Repurchase
    1. Moving workflows to software as a service
2. Customer facing discussion stages
  1. Discovery
    1. Understand the customer's challenges
    2. Preparation
      1. Research customer's industry. Understand trends , competitors, recent news, etc.
      2. Research customer's business, understanding business mode, mission statements, products, leadership, and customer's relationship with AWS
    3. Practices
      1. Encourage detailed conversation with open-ended questions
      2. 5 Whys. Dive deeper to discover the real desired outcome
      3. Whiteboarding. Keep track of the conversation and illustrate workflows
  2. Presenting the Solution
    1. Present findings and propose AWS solution
    2. Preparations
      1. Collraborate, Illustrate, Iterate
      2. Vary solutions by different factors
    3. Pratices
      1. Revise, gain buy-in from customer, propose PoC
      2. Bring supplies, maintain eye contact, draw clearly, stand aside
  3. Handling Objections
    1. Goals
      1. Connect - empathize. Make them feel heard and validated
      2. Condense - identify the core concern
      3. Continue - Take steps towards resolution
    2. Practices
      1. Data-driven approach
      2. Use case studies
      3. Have confidence in your response
    3. Common Object Responses
      1. Security
        Top Priority, validated against third party frameworks
      2. Cost or Cost savings
        Reduced total cost of ownership
        Optimized and predictable
      3. Scalability and Response
        Create Guardrails around security, availability, resilience, compliance
        Amazon Watch Tower
    4. Customer Meeting Practices
      1. Keys to consistent results
        prepare - understand industry, terminology
        Anticipate, differentiate, stay on message
      2. Anti-practices
        Promises- don't use guaranteed, definitely, never
        Use acronyms or jargon - spell it out
        Focus on technology - focus on the customer
        Focus on the short-term: focus on long-term
  4. Delivering a PoC
    1. PoC and Purpose
      1. a PoC is a small-scale practical version of the proposed solution that runs the customer's application
      2. Purpose is to help customer evaluate solution and compare to existing environment
        Don't just demonstrate technology, cater to their busienss
    2. Build a PoC
      1. Take the feedback from the solution proposal
      2. Collect networking and security, application code, databases, data, etc.
    3. Utilize AWS online resources
Cloud Financial Management
1. Measurement and Accountability
  1. Help customers understand their spending
  2. Measuring and monitoring tools
    1. Generate automated reporting and recommendations
      1. Reports should have cost and usage data, optimization, recommendations
    2. Options
      1. Build a custom dashboard
      2. APN tool
      3. AWS Cost Explorer
2. Cost Optimization
  1. Right-sizing Instances
    1. Identify instances that can be downsized
      1. Reserved Instances
        up to 75% savings
        Use for stuff that needs to run for most of the time
        Convertible to other instance types
      2. Spot Instances
        Spare EC2 capacity, can be reclaimed at 2 minute notice
        Use for fault-tolerant, flexible, stateless workloads
        ex. big data, CI/ CD, high performance computing
    2. utilize CloudWatch metrics
3. Cloud Financial Operations
  1. Establish a Cloud Center of excellence
    1. goals: align incentives, automate report, set up KPI
    2. Cost Management Questions
      1. How much of our workloads are steady state? Can we make them reserved instances, etc.
    3. Establish clear metrics and targets
4. Migration Portfolio Assessment
  1. Use to validate business plan, plan migration, and estimate cost of migration
  2. Business case
    1. Discovery
      1. Evaluate total cost of ownership or cost savings
      2. Estimate comparisons between on-premises and AWS
      3. Estimate migration costs
    2. Directional sense without getting too deep
    3. Streamlines, automates, and scales financial analysis
  3. MPA Data Import using Configuration Management Database extract
  4. MPA Cost Comparison

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	Erstellt von Jason Chan vor fast 4 Jahre