What are the most reliable cloud infrastructure practices?

The decision to use Public, Private or Hybrid Cloud will mostly be decided by the business and not by the technical models. I know this sucks, but thats what it is :) However the good part is that there are some standard practices which make the cloud infra reliable. 1. Defining thresholds and limits. This sounds very logical thing to do however this also is the most effective step that a lot of folks miss. 2. Design for disaster hopping that it never happens 3. Use distributed zones as much as possible 4. Use the vendor provided services instead of building your own inhouse solutions ( specially for Dbase ) 5. Make use of scaling as much as you can

Design for failure is the key, their must be a time where the infrastructure is down, not accessible, for some duration of time. You name it cloud provider, they must have experience down time. It can happen to a single VM, service or can be an Availability Zone or can be larger area like a region. Design for failure when network down, how system can still be accessible. Design for failure when a single AZ impacted, how system still can accessible from other Availability Zone with High Availability leveraging Auto Scaling Group crossing different AZ. On DB level, to enable Multi AZ Database. Design for failure when a Region, how our DNS routing can fail over to other region and the other region can have same copy from the impacted Region

In my opinion, you should -be capable of being multi-cloud with clear directives -have proper security committees for both security and architectural review of the cloud workload - design for resilience - have automation and the right IaC techniques - have proper governance and guardrails in place.

The right cloud model must also consider the cloud adoption framework (aka landing zone)practice. In my experience on the field with different customers, governance is not considered as a priority in the model definition and latter is addressed in the middle of the cloud adoption in a reactive approach. This common pattern rely on extra operational costs as well as security and administrative breaches that are harder to remediate when the cloud is already supporting critical business workloads. So instead of relying on this common pattern include the governance/cloud adoption framework/landing zone definition since the beginning.

The most reliable cloud infrastructure is the one which meets the unique requirements of your specific use-case the best (not your org). Each workload has its own unique requirements related to security, compliance, latency, services, perpetually, cost, auto-scaling, etc... More important that selecting one cloud or SaaS vendor over another is designing a multi/hybrid-cloud reference architecture/strategy which "future-proofs" your business by providing you with the flexibility to mix & match clouds on a per use-case basis - all while maintaining the existing org-wide security, compliance, resilience, and network frameworks. Build this strategy pre-deployment, not post, and you'll save yourself a ton of time, money, and downtime.

"Design for failure so nothing will fail" is a guiding principle for creating reliable cloud environments. While it's true that cloud providers like AWS offer robust reliability with multiple availability zones in a region, each hosting numerous data centers, there's a geographical limitation to consider. For mission-critical workloads, it's prudent to adopt a multi-region approach. This ensures that even if an entire geographical area faces issues, your application remains unaffected. Alternatively, at the very least, having a disaster recovery plan in another region is essential to maintain uninterrupted service.

I really like this point and as previously highlighted 3 points, would further add these: Implement regular backup strategies for critical data and configurations. Test the backup and restoration processes periodically to ensure they work as expected. Develop and regularly test a disaster recovery plan. This plan should outline the steps to recover from major outages or disasters, including data restoration and system reconfiguration. Practice chaos engineering by intentionally injecting failures into your system to identify weaknesses and points of failure. This helps you build more resilient systems.

As simple as not putting your eggs in one basket. By implementing multiple CDN infrastructure, you could reduce a single point of failure, and enhance your site/apps availability simultaneously. Minimizing the impact of disruptions. When one CDN fails, others will be ready to takeover and ensure your users has a seamless user experience while accessing your content.

Regardless of how well you setup your infrastructure, you must always account for emergencies! In cloud terms we call this "Design for failure". "Design for failure" means having backup services running alongside the primary ones or having an automated recovery plan that replicates the architecture with minimal downtime. Design for failure ensures that in the event of an emergency, attack, unexpected outtage of a service or alternatively unexpected demand for a service, your system is able to remain online with minimal or no interruption to service provision.

This is one of the Architecture principles that as an Architect we should always design the DR plan. This will make cloud infrastructure more resilient.

Automation and orchestration when done well frees up man power and helps to ensure that 'boring' and repetitive tasks are dealt with efficiently. On the business end, it frees up your experts to finish more urgent tasks instead of wasting time and effort to continuously manually monitor the architecture. Additionally, proper automation and orchestration enables one to build a reliable, resilient and secure system.

I prefer to revolutionarily to imply LIamaIndex on automation and orchestration . Like query engine , agents and chat engine .

Cloud in my opinion is more of a model than a destination, at the end of the day it's still a infrastructure in a datacenter the difference is the processes and the way resources are consumed. Often times IT organizations find themselves going to the "cloud" not necessarily by choice but because the different business areas want to consume services at the click of a button. Organizations should strive to provide the same ease of consumption processes as the public cloud on-prem through automation and orchestration. While I'm not against the public cloud, I believe not all applications are suited for it but what if you can have the best of both worlds? a public cloud feel in your private cloud with the ability to move back and forth...

Incorporate "Monitoring" for swift response, and "Automation" for error reduction and resource optimization. What I meant by the above statement is: 1. Monitoring, utilizing Real User Monitoring, will enable you to promptly detect traffic spikes or anomalies, enabling swift responses. 2. Implementing Multi-CDN Infrastructure will enhance redundancy and resilience, thus preventing single points of failure. 3. Utilize AI based technology (Machine Learning) to automate and orchestrate traffic to the best-performing CDN (Implement Multi CDN infrastructure first) based on latency and availability. Therefore ensuring consistent performance standards.

Automation is the backbone of the Cloud. Automate infrastructure creation using IaC like Terraform. Create reusable modules which can be used to quickly create and replicate the environment. Automate operational tasks

Protecting and securing cloud infrastructure is of paramount importance due to the exponential growth in cloud adoption. A proven concept used in cybersecurity is Defense in Depth where multiple layers of security defenses are placed at all levels of IT systems, applications and networks. Applying this concept to cloud security is no exception. The first layer is perimeter defense through firewalls and DDoS protection as well as protection from internal attack vectors. The second layer is host protection through protection from viruses and malware as well as OS security patches. Another layer is data protection through encryption in transit and at rest. Security policies, procedures and training should be weaved into the layers of defense.

Security is not negotiable! Depending on the regulatory and compliance customer requirements, security guardrails are needed. The cloud architects are trained to design and implement zero trust security concepts where all the solution components are well implemented: identity and access management, endpoint security, network management, infrastructure, apps and data as well as all the security policies.

Securing and protecting your cloud infrastructure is critical to maintaining the integrity and confidentiality of your data, as well as ensuring the reliability of your services. - Enforce MFA to add an additional layer of security - Use encryption for data transmitted between servers and for data stored in databases or on storage devices. - Implement a robust key management system to secure keys used for encryption and decryption. - Segment your network to restrict lateral movement in case of a security breach. Use virtual networks, firewalls, and security groups to control traffic. - Enable logging for all relevant activities. - Perform regular audits of your cloud infrastructure and ensure compliance with security best practices.

Think zero trust whenever security is involved. For cloud, here're some ways: Follow security best practices to protect your infrastructure from vulnerabilities and attacks. Regularly update and patch software, implement strong access controls, and monitor for security incidents. Develop an incident response plan to effectively address and resolve incidents. Define roles and responsibilities, establish communication channels, and conduct post-incident reviews for continuous improvement. Conduct regular testing of your disaster recovery and business continuity plans. This ensures that your team is well-prepared to handle unexpected events.

I agree - During my Master's program, I learned that a robust cloud security foundation hinges on encryption protocols, multi-factor authentication, and regular security audits. Implementing real-time threat detection and response mechanisms adds an extra layer of defense, ensuring our cloud infrastructures remain resilient and secure & protect organizations against threats.

Optimizing cloud infrastructure is an ongoing journey, essential for maximizing performance and value. Key approaches include: Metrics & Analytics: Utilize tools like AWS CloudWatch to monitor performance, usage, and costs, making data-driven decisions. User Feedback: Implement feedback mechanisms to align services with user expectations and needs. Benchmarking: Compare your practices with industry standards and competitors using tools like RightScale for insights and improvement areas. Efficiency Tools: Employ solutions like AWS Trusted Advisor to identify and rectify inefficiencies and reduce waste. Innovation & Experimentation: Encourage a culture of innovation, using platforms like AWS Lambda to explore new solutions.

Agreed! Its long-term commitment and really a case of user-driven. Here're some ways: Implement auto-scaling to automatically adjust the number of resources based on demand. This ensures that you have the necessary capacity during peak times and can scale down during periods of lower demand. Be mindful of data transfer costs, especially if your application involves a lot of data transfer between regions or outside the cloud provider's network. Optimize data transfer patterns where possible. Such as for storage, there are often egress costs as well! Last but not least, ensure that your team is aware of cost implications and best practices. Provide training on resource optimization and encourage a culture of cost consciousness.

Some of the ways to optimize the cloud infrastructure: (1) Assess the customer needs on a regular basis and adjust the cloud resources accordingly. (2) Use Automation wherever possible. Automation can help in reducing operational costs and the risk of human error. (3) Keep an eye on your utilization levels. This can help in identifying underutilized resources and reduce the cost of spending. (4) Make use of reserved instances if the application architecture permits. Significant savings can be achieved. (5) Take advantage of spot instances that offer significant discounts on unused compute capacity. A word of caution with spot instances is they may not be available continuously and may not be suitable for all workloads.

Regularly assess and optimize your infrastructure for performance and cost efficiency. This involves monitoring resource utilization, scaling appropriately, and identifying areas for improvement to enhance overall effectiveness.

Continuous optimization is essential for maintaining a reliable and efficient cloud infrastructure. This involves: 👉 Monitoring and Performance Analysis: Continuously monitor resource utilization, application performance, and network traffic to identify areas for improvement and potential bottlenecks. 👉 Cost Optimization: Analyze cloud resource usage and identify opportunities to reduce costs by optimizing resource allocation, rightsizing instances, and leveraging cost-saving features. 👉 Capacity Planning: Forecast future resource requirements based on business growth an

You can build modern, scalable applications on AWS to transform your organization, all while optimizing costs. AWS continuously innovates and delivers the latest technologies across every solution area so you can meet high performance needs and scale at a lower cost. The variety of AWS pricing options provide you with the flexibility to design your purchase plan to meet your specific workload needs. AWS offers a suite of management tools to monitor your application cost and identify modernizing and rightsizing opportunities. You can seamlessly scale up and down with AWS to operate more cost effectively in an uncertain economy and better position your organization for long-term success.

Although costly, one of my previous employers had done this superb outcomes and service delivery. Most other providers really avoid this and just use their hardware beyond serviceability dates. Adopt Immutable Infrastructure that is! The practice of immutable infrastructure, where components are replaced rather than updated. This reduces the risk of configuration drift and ensures consistency across your environment. Complement this with regular monitoring and other optimisation techniques. Plus, document all the steps involved and you'll be sure to develop really reliable cloud practices for now and future!

Selecting the right cloud provider becomes a key pillar or factor for devising cloud best practices Aka factors like vendor locking makes it imperative to have a mix Having a mix cloud provider poses compatibility challenges i.e if infrastructure as code is using Bicep(native Azure language) it's not portable on AWS so neutral choice is Terraform Some organizations use fail over across different cloud as alternative to avoid vendor locking but it poses other challenges like knowledge and learning curve. Cloud Best practices should be designed taking into consideration complete Lifecycle of application from design right till aftercare/maintenance and support. Also taking into consideration that speed and reliability is not impacted

The most reliable cloud infrastructure practices include ensuring redundancy and failover mechanisms, implementing strong security measures, regular backups, monitoring and automation, scalability planning, compliance with regulations, optimized resource utilization, robust disaster recovery plans, efficient data management, and regular performance testing. These practices ensure high availability, data protection, efficient operations, and overall reliability in the cloud infrastructure.

Having a resilient design starting from day one will help you avoid lots of issues later on. A resilient design lets you stay confident in knowing that the system can handle most of the common issues that occur. Also note that scaling vertically ensures that your servers are able to handle more robust applications but scaling horizontally helps to increase reliability by relying on multiple decoupled systems instead of one large monolith. Finding the right mix between the two forms of scaling mentioned will save you cost but also ensure that your system remains reliable.