01. AWS Well-Architected Framework
The five pillars of the AWS Well-Architected Framework
The principles are ubiquitous, you can find them in the documentations of GCP and Azure. Moreover, you can apply them to any clouds, hyprid coulds or on-premise environments.
- GCP: https://cloud.google.com/architecture/framework
- Azure: https://docs.microsoft.com/zh-tw/azure/architecture/framework/
| Name | Description |
|---|---|
| Operational Excellence (卓越營運) | The ability to support development and run workloads effectively, gain insight into their operations, and to continuously improve supporting processes and procedures to deliver business value. |
| Security (安全) | The security pillar encompasses the ability to protect data, systems, and assets to take advantage of cloud technologies to improve your security. |
| Reliability (可靠性) | The reliability pillar encompasses the ability of a workload to perform its intended function correctly and consistently when it’s expected to. This includes the ability to operate and test the workload through its total lifecycle. This paper provides in-depth, best practice guidance for implementing reliable workloads on AWS. |
| Performance Efficiency (效能效率) | The ability to use computing resources efficiently to meet system requirements, and to maintain that efficiency as demand changes and technologies evolve. |
| Cost Optimization (成本最佳化) | The ability to run systems to deliver business value at the lowest price point. |
Definition
- component:
- code, configuration, AWS Resources
- workload:
- identify a set of components that together deliver business value
- Architecture:
- being how components work together in a workload. How components communicate and interact is often the focus of architecture diagrams.
- When architecting workloads, you make trade-offs between pillars based on your business context.
1. Operational Excellence (卓越營運)
Design Principles
- Perform operations as code
- In the cloud, you can apply the same engineering discipline that you use for application code to your entire environment. You can define your entire workload (applications, infrastructure) as code and update it with code. You can implement your operations procedures as code and automate their execu- tion by triggering them in response to events. By performing operations as code, you limit human error and enable consistent responses to events.
- Make frequent, small, reversible changes
- Refine operations procedures frequently
- Anticipate failure
- Learn from all operational failure
Whitepaper
2. Security (安全)
Design Principles
- Implement a strong identity foundation:
- Implement the principle of least privilege and enforce separation of duties with appropriate authorization for each interaction with your AWS resources. Centralize identity management, and aim to eliminate reliance on long-term static credentials.
- Enable traceability:
- Monitor, alert, and audit actions and changes to your environment in real time. Integrate log and metric collection with systems to automatically investigate and take action.
- Apply security at all layers:
- Apply a defense in depth approach with multiple security controls. Apply to all layers (for example, edge of network, VPC, load balancing, every instance and compute service, operating system, application, and code).
- Automate security best practices:
- Automated software-based security mechanisms improve your ability to securely scale more rapidly and cost-effectively. Create secure architectures, including the implementation of controls that are defined and managed as code in version-controlled templates
- Protect data in transit and at rest:
- Classify your data into sensitivity levels and use mechanisms, such as encryption, tokenization, and access control where appropriate.
- Keep people away from data:
- Use mechanisms and tools to reduce or eliminate the need for direct access or manual processing of data. This reduces the risk of mishandling or modification and human error when handling sensitive data.
- Prepare fore securiy events:
- Prepare for an incident by having incident management and investigation policy and processes that align to your organizational requirements. Run incident response simulations and use tools with automation to increase your speed for detection, investigation, and recovery.
Definition
-
Security
- To operate your workload securely, you must apply overarching best practices to every area of security.
- In AWS, segregating different workloads by account, based on their function and compliance or data sensitivity requirements, is a recommended approach.
-
Identity and Access Management
- How to:
- Identity and access management are key parts of an information security program, ensuring that only authenticated (signed in) and authorized (has permissions) users and components are able to access your resources, and only in a manner that you intend. </lo>
- For example, you should define principals (that is, accounts, users, roles, and services that can perform actions in your account), build out policies aligned with these principals, and implement strong credential management. These privilege-management elements form the core of authentication and authorization. </ol>
- Identity
- Human Identity
- Machine Identity
- Credentials must not be shared between any user or system. User access should be granted using a least-privilege approach with best practices including password re- quirements and MFA enforced. Programmatic access including API calls to AWS ser- vices should be performed using temporary and limited-privilege credentials such as those issued by the AWS Security Token Service.
- How to:
-
Detection
- You can use detective controls to identify a potential security threat or incident.
- You can also use internal auditing, an examination of controls related to information systems, to en- sure that practices meet policies and requirements and that you have set the correct automated alerting notifications based on defined conditions.
-
Infrastructure Protection
- Infrastructure protection encompasses control methodologies, such as defense in depth, necessary to meet best practices and organizational or regulatory obligations.
- For example: VPC
-
Data Protection
- In AWS, the following practices facilitate protection of data:
- As an AWS customer you mainta in full control over your data.
- AWS makes it easier for you to encrypt your data and manage keys,including regular key rotation, which can be easily automated by AWS or maintained by you.
- Detailed logging that contains important content, such as file access and changes, is available.
- AWS has designed storage systems for exceptional resiliency. For example, Amazon S3 Standard, S3 Standard–IA, S3 One Zone-IA, and Amazon Glacier are all designed to provide 99.999999999% durability of objects over a given year. This durability level corresponds to an average annual expected loss of 0.000000001% of objects.
- Versioning, which can be part of a larger data life cycle managementprocess, can protect against accidental overwrites, deletes, and similar harm.
- AWS never initiates the movement of data between Regions. Content placed in a Region will remain in that Region unless you explicitly enable a feature or leverage a service that provides that functionality.
- Q. How do you classify your data?
- Q. How do you protect your data at rest?
- Q. How do you protect your data in transit?
- In AWS, the following practices facilitate protection of data:
-
Incident Response
- Preparation is critical to timely and effective investigation, response to, and recovery from security incidents to help minimize disruption to your organization.
- In AWS, the following practices facilitate effective incident response:
- Detailed logging is available that contains important content, such as file access and changes.
- Event scan be automatically processed and trigger tools that automate responses through the use of AWS APIs.
- You can pre-provision tool in ganda “clean room” using AWS CloudFormation. This allows you to carry out forensics in a safe, isolated environment.
Whitepaper
3. Reliability (可靠性)
- The Reliability pillar includes encompasses the ability of a workload to perform its intended function correctly and consistently when it’s expected to. this includes the ability to operate and test the workload through its total lifecycle.
Design Principles
- 1.Automatically recover from failure
- By monitoring a workload for key performance indicators (KPIs), you can trigger automation when a threshold is breached. These KPIs should be a measure of business value, not of the technical aspects of the operation of the service. This allows for automatic notification and tracking of failures, and for automated recovery processes that work around or repair the failure. With more sophisticated automation, it’s possible to anticipate and remediate failures before they occur.
- 2.Test recovery procedures
- In an on-premises environment, testing is often conducted to prove that the workload works in a particular scenario. Testing is not typically used to validate recovery strategies. In the cloud, you can test how your work- load fails, and you can validate your recovery procedures. You can use automation to simulate different failures or to recreate scenarios that led to failures before. This approach exposes failure pathways that you can test and fix before a real failure scenario occurs, thus reducing risk.
- 3.Scale horizontally to increase aggregate workload availability
- Replaceonelarge resource with multiple small resources to reduce the impact of a single failure on the overall workload. Distribute requests across multiple, smaller resources to en- sure that they don’t share a common point of failure.
- 4.Stop guessing capacity
- A common cause of failure in on-premises workloads is re- source saturation, when the demands placed on a workload exceed the capacity of that workload (this is often the objective of denial of service attacks). In the cloud, you can monitor demand and workload utilization, and automate the addition or removal of resources to maintain the optimal level to satisfy demand without over- or under-provisioning. There are still limits, but some quotas can be controlled and others can be managed (see Manage Service Quotas and Constraints).
- 5.Manage change in automation
- Changes to your infrastructure should be made using automation. The changes that need to be managed include changes to the automation, which then can be tracked and reviewed.
Definition
- Foundations
- Foundational requirements are those whose scope extends beyond a single workload or project. Before architecting any system, foundational requirements that influence reliability should be in place. For example, you must have sufficient network bandwidth to your data center.
- Workload Architecture
- A reliable workload starts with upfront design decisions for both software and infrastructure. Your architecture choices will impact your workload behavior across all five Well-Architected pillars. For reliability, there are specific patterns you must follow.
- Change Management
- Changes to your workload or its environment must be anticipated and accommodated to achieve reliable operation of the workload. Changes include those imposed on your workload, such as spikes in demand, as well as those from within, such as feature deployments and security patches.
- Q: How do you monitor workload resources?
- Q: How do you design your workload to adapt to changes in demand?
- Q: How do you implement change?
- Failure Management
- In any system of reasonable complexity, it is expected that failures will occur. Reliability requires that your workload be aware of failures as they occur and take action to avoid impact on availability. Workloads must be able to both withstand failures and automatically repair issues.
- Q: How do you back up data?
- Back up data, applications, and configuration to meet your requirements for recovery time objectives (RTO) and recovery point objectives (RPO).
- RPO (Recovery Time Objective):
- A metric that helps to calculate how quickly you need to recover your IT infrastructure and services following a disaster in order to maintain business continuity.
- PTO (Recovery Point Objective):
- A measurement of the maximum tolerable amount of data to lose.
- Q: How do you design your workload to withstand component failures?
- Q: How do you test reliability?
- Workloads with a requirement for high availability and low mean time to recovery (MTTR) must be architected for resiliency.
- Q: How do you plan for disaster recovery (DR)?
Whitepaper
4. Performance Efficiency (效能效率)
Design Principles
- Democratize advanced technologies
- Make advanced technology implementation easier for your team by delegating complex tasks to your cloud vendor. Rather than asking your IT team to learn about hosting and running a new technology, consider consuming the technology as a service. For example, NoSQL databases, media transcoding, and machine learning are all technologies that require specialized ex- pertise. In the cloud, these technologies become services that your team can consume, allowing your team to focus on product development rather than resource provisioning and management.
- Go global in minutes
- Deploying your workload in multiple AWS Regions around the world allows you to provide lower latency and a better experience for your customers at minimal cost.
- Use serverless architectures
- Serverless architectures remove the need for you to run and maintain physical servers for traditional compute activities. For example, serverless storage services can act as static websites (removing the need for web servers) and event services can host code. This removes the operational burden of managing physical servers, and can lower transactional costs because managed services operate at cloud scale.
- Experiment more often
- With virtual and automatable resources, you can quickly carry out comparative testing using different types of instances, storage, or config urations.
- Consider mechanical sympathy
- Understand how cloud services are consumed and always use the technology approach that aligns best with your workload goals. For example, consider data access patterns when you select database or storage approaches.
Definition
- Selection
- The optimal solution for a particular workload varies, and solutions often combine multiple approaches. Well-architected workloads use multiple solutions and enable different features to improve performance.
- Compute:
- Selecting compute resources that meet your requirements, performance needs, and provide great efficiency of cost and effort will enable you to accomplish more with the same number of resources. When evaluating compute options, be aware of your requirements for workload performance and cost requirements and use this to make informed decisions.
- Types:
- Instances:
- are virtualized servers, allowing you to change their capabilities with a button or an API call. Because resource decisions in the cloud aren’t fixed, you can experiment with different server types. At AWS, these virtual server instances come in different families and sizes, and they offer a wide variety of capabilities, including solid-state drives (SSDs) and graphics processing units (GPUs).
- Containers:
- are amethod of operating system virtualization that allow you to run an application and its dependencies in resource-isolated processes. AWS Fargate is serverless compute for containers or Amazon EC2 can be used if you need control over the installation, configuration, and management of your compute environment. You can also choose from multiple container orchestration platforms: Amazon Elastic Container Service (ECS) or Amazon Elastic Kubernetes Service (EKS).
- Functions:
- abstract the execution environment from the code you want to execute. For example, AWS Lambda allows you to execute code without running an instance.
- Instances:
- Storage
- Object Storage:
- provides a scalable, durable platform to make data accessible from any internet location for user-generated content, active archive, serverless computing, Big Data storage or backup and recovery. Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance. Amazon S3 is designed for 99.999999999% (11 9’s) of durability, and stores data for millions of applications for companies all around the world.
- Block Storage:
- provides highly available, consistent, low-latency block storage for each virtual host and is analogous to direct-attached storage (DAS) or a Storage Area Network (SAN). Amazon Elastic Block Store (Amazon EBS) is designed for workloads that require persistent storage accessible by EC2 instances that helps you tune applications with the right storage capacity, performance and cost.
- File Storage:
- provides access to a shared file system across multiple systems. File storage solutions like Amazon Elastic File System (EFS) are ideal for use cases, such as large content repositories, development environments, media stores, or user home directories. Amazon FSx makes it easy and cost effective to launch and run popular file systems so you can leverage the rich feature sets and fast performance of widely used open source and commercially-licensed file systems.
- Q. How do you select your storage solution?
- The optimal storage solution for a system varies based on the kind of access method (block, file, or object), patterns of access (random or sequential), required throughput, frequency of access (online, offline, archival), frequency of update (WORM, dynamic), and availability and durability constraints. Well-architected systems use multiple storage solutions and enable different features to improve performance and use resources efficiently.
- Object Storage:
- Database
- The cloud offers purpose-built database services that address different problems pre- sented by your workload. You can choose from many purpose-built database engines including relational, key-value, document, in-memory, graph, time series, and ledger databases. By picking the best database to solve a specific problem (or a group of problems), you can break away from restrictive one-size-fits-all monolithic databases and focus on building applications to meet the performance needs of your customers.
- Network
- Since the network is between all workload components, it can have great impacts, both positive and negative, on workload performance and behavior. There are also workloads that are heavily dependent on network performance such as High Perfor- mance Computing (HPC) where deep network understanding is important to increase cluster performance. You must determine the workload requirements for bandwidth, latency, jitter, and throughput.
- On AWS, networking is virtualized and is available in a number of different types and configurations. This makes it easier to match your networking methods with your needs. AWS offers product features (for example, Enhanced Networking, Amazon EBS-optimized instances, Amazon S3 transfer acceleration, and dynamic Amazon CloudFront) to optimize network traffic. AWS also offers networking features (for ex- ample, Amazon Route 53 latency routing, Amazon VPC endpoints, AWS Direct Con- nect, and AWS Global Accelerator) to reduce network distance or jitter.
- Review
- Cloud technologies are rapidly evolving and you must ensure that workload components are using the latest technologies and approaches to continually improve performance. You must continually evaluate and consider changes to your workload components to ensure you are meeting its performance and cost objectives. New technologies, such as machine learning and artificial intelligence (AI), can allow you to re-imagine customer experiences and innovate across all of your business workloads.
- Monitoring
- After you implement your workload, you must monitor its performance so that you can remediate any issues before they impact your customers. Monitoring metrics should be used to raise alarms when thresholds are breached.
- Tradeoffs
- When you architect solutions, think about tradeoffs to ensure an optimal approach. Depending on your situation, you could trade consistency, durability, and space for time or latency, to deliver higher performance.
White paper
Cost Optimization (成本最佳化)
The Cost Optimization pillar includes the ability to run systems to deliver business value at the lowest price point.
Design Principles
- Implement Cloud Financial Management
- Adopt a consumption model
- Measure overall efficiency
- Stop spending money on undifferentiated heavy lifting
- Analyze and attribute expenditure
Definition
- Practice Cloud Financial Management
- e.g., use Cost Explorer, and optionally Amazon Athena and Amazon Quick- Sight with the Cost and Usage Report (CUR), to provide cost and usage awareness throughout your organization. AWS Budgets provides proactive notifications for cost and usage.
- Expenditure and usage awareness
- In AWS, you create an account structure with AWS Organizations or AWS Control Tower, which provides separation and assists in allocation of your costs and usage. You can also use resource tagging to apply business and organization information to your usage and cost. Use AWS Cost Explorer for visibility into your cost and usage, or create customized dashboards and analytics with Amazon Athena and Amazon Quick- Sight. Controlling your cost and usage is done by notifications through AWS Budgets, and controls using AWS Identity and Access Management (IAM), and Service Quotas.
- Cost-effective resources
- By factoring in cost during service selection, and using tools such as Cost Explorer and AWS Trusted Advisor to regularly review your AWS usage, you can actively monitor your utilization and adjust your deployments accordingly.
- Manage demand and supply resources
- In AWS, you can automatically provision resources to match the workload demand. Auto Scaling using demand or time-based approaches allow you to add and remove resources as needed. If you can anticipate changes in demand, you can save more money and ensure your resources match your workload needs. You can use Amazon API Gateway to implement throttling, or Amazon SQS to implementing a queue in your workload. These will both allow you to modify the demand on your workload components.
- Optimize over time
- As AWS releases new services and features, it’s a best practice to review your existing architectural decisions to ensure they continue to be the most cost effective. As your requirements change, be aggressive in decommissioning resources, entire services, and systems that you no longer require.