The world is still getting used to operating within the cloud. Moving to the cloud is challenging for many organizations. So why do we see a rise in the adoption of multi cloud strategies? In this blog, we will explore why this trend is worth considering for your organization, as well as look at the challenges that it brings.
‍
What is Multi-cloud ?
Multi-cloud strategies come into play when organizations blend private and public cloud providers like Azure, AWS, and Google in their IT solutions. In the past, the focus was on whether to move to the cloud and which one to choose.Â
However, the shift is now towards leveraging solutions from multiple cloud vendors. As cloud adoption matures, core functionalities among major players become similar, yet each vendor provides unique services with variations in delivery capabilities.Â
Considerations include the time to spin up a Kubernetes cluster, low-latency network availability, storage costs at different performance tiers, and compatibility of IAM services. Multi-cloud solutions provide flexibility in selecting desired services, but it comes with its complexities.Â
Here are five key concerns to address before opting for the multi-cloud model:
Cost-Saving Awareness: Ensure the business comprehends potential cost-saving aspects in navigating multi-cloud complexity.
Clarity and Reliability: Obtain the necessary tooling to maintain clarity and reliability within the multi-cloud environment.
Exploration of Environments: Start exploring multiple cloud environments to understand both similarities and differences in the context of multi-cloud complexity.
Evaluation for Savings: Always evaluate areas with the potential for significant savings within the multi-cloud framework.
Automation Emphasis: Continuously work on automating processes to manage the increasing complexity inherent in multi-cloud environments.
Let's check some examples to illustrate these differences and shed light on the intricacies of multi-cloud complexity.
Examining current cost factors, Simform provides insights into serverless costs across major cloud service providers - AWS, Azure, and GCP. Serverless functions incur charges based on code execution time. In a hypothetical scenario where a serverless function with 0.5 GB of RAM executes in a second, running 3 million times per month, the cost breakdown is as follows:
AWS Lambda: The total monthly cost is approximately $18.74.
Azure Function: Costs slightly less at $18 for the same function.
Google Cloud Functions: Priced at around $25.15, making it about 40% more expensive than the other two.
It's crucial to note the extreme volatility in cloud computing costs, with fluctuations anticipated in the near future. However, this analysis underscores the potential for significant cost savings through the strategic use of multi-cloud strategies in navigating the complexities of serverless computing.
Kubernetes Clusters
In the realm of Kubernetes clusters, the time required to spin up services is a crucial factor influencing decision-making, particularly in troubleshooting or conducting iterative Proof of Concepts (POCs). Let's examine this variable across three major service providers:
Google Kubernetes Engine (GKE): Remarkably faster at 5 minutes, making it twice as fast as some counterparts.
This discrepancy in deployment times emphasizes the practical significance of such time differentials. Now, let's explore what it means to implement a multi-cloud strategy and delve into the high-level overview of a multi-cloud system architecture, as depicted in the accompanying diagram.
‍
As illustrated, extending your on-premise Active Directory (AD) to Azure AD enables the authentication and authorization of a Kubernetes cluster running in the Google Cloud. On the backend, logs from Google Kubernetes Engine (GKE) and Azure are forwarded to Splunk, with a similar process for on-premise workloads forwarded to Splunk Enterprise in an AWS environment.
Cloud architecture is a dynamic and evolving process, with the migration of services and solutions adapting to changing market needs. While implementing multi-cloud solutions may seem daunting, it offers long-term benefits, significantly saving organizations resources. The ability to easily redeploy to alternate locations becomes feasible, provided there is flexible tooling and knowledge of diverse environments, highlighting the importance of understanding and navigating multi-cloud complexity.
Potential Gains of Implementation
Data Privacy and Protection
Privacy and data protection laws like GDPR in the EU can present challenges during organizational migrations. Referring to the earlier diagram example, where various cloud services interact within a multi-cloud framework.
Workloads with sensitive data may require storage within the Azure compute environment in a European data center.
Utilizing Azure AD simplifies Identity and Access Management (IAM) processes, streamlining operations in Google Cloud and Kubernetes environments, potentially situated in North America.
Multi-cloud solutions offer customization of data management to meet the diverse needs of multiple regions.
Multi-cloud solutions facilitate the migration of individual workloads at a pace aligned with organizational capability, comfort, and strategic targets.
Global Service Diversification allows organizations to diversify and provide services on a global scale, tailoring solutions to meet the specific requirements of various markets.
Hence, multi-cloud solutions emerge as a strategic enabler, not only ensuring compliance with data protection laws but also providing the flexibility needed for secure and efficient global operations.
Reduced Vendor Lock-In Risk
Many stakeholders rely solely on services from a single cloud provider.
Integration within a provider's ecosystem can lead to difficulty and high costs in exiting or integrating with other providers.
Multi-cloud implementations serve to diminish the risk of vendor lock-in and enhance operational flexibility.
Multi-cloud solutions enable the seamless migration of workloads across environments when necessary.
Streamlining APIs for cross-cloud communication is essential.
Running Proof of Concepts (POCs) for custom architectures ensures compatibility and mitigates challenges.
Availability of cloud services is often tied to the geographical location of the provider's infrastructure.
Despite similar services, variations in data centers and networking accessibility can impact crucial factors like edge computing and latency.
Larger organizations require global access for an enhanced client experience.
Forced regional access may hinder the seamless operation of services.
Multi-cloud solutions facilitate the scaling of applications to run within different public clouds based on their region and availability.
Investigation of regional data centers significantly benefits workloads of streaming services, enhancing the overall customer experience.
Challenges and Their Mitigations
Multi-cloud solutions, while beneficial, can be complex to implement, requiring careful consideration and planning.Â
Adequate manpower and in-house knowledge are essential to fully leverage the available features of multi-cloud environments.
The challenge lies in tracking multiple rapidly evolving environments, necessitating proactive monitoring and adaptability.
Supporting architectural decisions must be constantly adjusted to align with the evolving nature of environments.
Deployment across multiple cloud environments may require software with a single codebase, streamlining infrastructure deployment.
Managing hardware and services across several clouds can result in complex cost management, demanding continuous attention.
Staying on top of security and reliability practices is critical to ensuring the integrity of multi-cloud systems.
More environments necessitate increased testing, policy and identity management, redundancy, adding to the overall management overhead.
SREs and DevOps professionals play a crucial role in constantly managing and observing services to maintain appropriate incident response times.
In the near future, an increasing number of organizations are expected to adopt multi-cloud strategies.While acknowledging the challenges, embracing multi-cloud strategies early on positions organizations for success in the cloud-native future, offering enhanced flexibility, scalability, and efficiency. We trust that you have found value in exploring the intricacies of multi-cloud environments in this blog.
Squadcast is an incident management tool that’s purpose-built for SRE. Get rid of unwanted alerts, receive relevant notifications and integrate with popular ChatOps tools. Work in collaboration using virtual incident war rooms and use automation to eliminate toil.
What you should do now
Schedule a demo with Squadcast to learn about the platform, answer your questions, and evaluate if Squadcast is the right fit for you.
Curious about how Squadcast can assist you in implementing SRE best practices? Discover the platform's capabilities through our Interactive Demo.
The world is still getting used to operating within the cloud. Moving to the cloud is challenging for many organizations. So why do we see a rise in the adoption of multi cloud strategies? In this blog, we will explore why this trend is worth considering for your organization, as well as look at the challenges that it brings.
‍
What is Multi-cloud ?
Multi-cloud strategies come into play when organizations blend private and public cloud providers like Azure, AWS, and Google in their IT solutions. In the past, the focus was on whether to move to the cloud and which one to choose.Â
However, the shift is now towards leveraging solutions from multiple cloud vendors. As cloud adoption matures, core functionalities among major players become similar, yet each vendor provides unique services with variations in delivery capabilities.Â
Considerations include the time to spin up a Kubernetes cluster, low-latency network availability, storage costs at different performance tiers, and compatibility of IAM services. Multi-cloud solutions provide flexibility in selecting desired services, but it comes with its complexities.Â
Here are five key concerns to address before opting for the multi-cloud model:
Cost-Saving Awareness: Ensure the business comprehends potential cost-saving aspects in navigating multi-cloud complexity.
Clarity and Reliability: Obtain the necessary tooling to maintain clarity and reliability within the multi-cloud environment.
Exploration of Environments: Start exploring multiple cloud environments to understand both similarities and differences in the context of multi-cloud complexity.
Evaluation for Savings: Always evaluate areas with the potential for significant savings within the multi-cloud framework.
Automation Emphasis: Continuously work on automating processes to manage the increasing complexity inherent in multi-cloud environments.
Let's check some examples to illustrate these differences and shed light on the intricacies of multi-cloud complexity.
Examining current cost factors, Simform provides insights into serverless costs across major cloud service providers - AWS, Azure, and GCP. Serverless functions incur charges based on code execution time. In a hypothetical scenario where a serverless function with 0.5 GB of RAM executes in a second, running 3 million times per month, the cost breakdown is as follows:
AWS Lambda: The total monthly cost is approximately $18.74.
Azure Function: Costs slightly less at $18 for the same function.
Google Cloud Functions: Priced at around $25.15, making it about 40% more expensive than the other two.
It's crucial to note the extreme volatility in cloud computing costs, with fluctuations anticipated in the near future. However, this analysis underscores the potential for significant cost savings through the strategic use of multi-cloud strategies in navigating the complexities of serverless computing.
Kubernetes Clusters
In the realm of Kubernetes clusters, the time required to spin up services is a crucial factor influencing decision-making, particularly in troubleshooting or conducting iterative Proof of Concepts (POCs). Let's examine this variable across three major service providers:
Google Kubernetes Engine (GKE): Remarkably faster at 5 minutes, making it twice as fast as some counterparts.
This discrepancy in deployment times emphasizes the practical significance of such time differentials. Now, let's explore what it means to implement a multi-cloud strategy and delve into the high-level overview of a multi-cloud system architecture, as depicted in the accompanying diagram.
‍
As illustrated, extending your on-premise Active Directory (AD) to Azure AD enables the authentication and authorization of a Kubernetes cluster running in the Google Cloud. On the backend, logs from Google Kubernetes Engine (GKE) and Azure are forwarded to Splunk, with a similar process for on-premise workloads forwarded to Splunk Enterprise in an AWS environment.
Cloud architecture is a dynamic and evolving process, with the migration of services and solutions adapting to changing market needs. While implementing multi-cloud solutions may seem daunting, it offers long-term benefits, significantly saving organizations resources. The ability to easily redeploy to alternate locations becomes feasible, provided there is flexible tooling and knowledge of diverse environments, highlighting the importance of understanding and navigating multi-cloud complexity.
Potential Gains of Implementation
Data Privacy and Protection
Privacy and data protection laws like GDPR in the EU can present challenges during organizational migrations. Referring to the earlier diagram example, where various cloud services interact within a multi-cloud framework.
Workloads with sensitive data may require storage within the Azure compute environment in a European data center.
Utilizing Azure AD simplifies Identity and Access Management (IAM) processes, streamlining operations in Google Cloud and Kubernetes environments, potentially situated in North America.
Multi-cloud solutions offer customization of data management to meet the diverse needs of multiple regions.
Multi-cloud solutions facilitate the migration of individual workloads at a pace aligned with organizational capability, comfort, and strategic targets.
Global Service Diversification allows organizations to diversify and provide services on a global scale, tailoring solutions to meet the specific requirements of various markets.
Hence, multi-cloud solutions emerge as a strategic enabler, not only ensuring compliance with data protection laws but also providing the flexibility needed for secure and efficient global operations.
Reduced Vendor Lock-In Risk
Many stakeholders rely solely on services from a single cloud provider.
Integration within a provider's ecosystem can lead to difficulty and high costs in exiting or integrating with other providers.
Multi-cloud implementations serve to diminish the risk of vendor lock-in and enhance operational flexibility.
Multi-cloud solutions enable the seamless migration of workloads across environments when necessary.
Streamlining APIs for cross-cloud communication is essential.
Running Proof of Concepts (POCs) for custom architectures ensures compatibility and mitigates challenges.
Availability of cloud services is often tied to the geographical location of the provider's infrastructure.
Despite similar services, variations in data centers and networking accessibility can impact crucial factors like edge computing and latency.
Larger organizations require global access for an enhanced client experience.
Forced regional access may hinder the seamless operation of services.
Multi-cloud solutions facilitate the scaling of applications to run within different public clouds based on their region and availability.
Investigation of regional data centers significantly benefits workloads of streaming services, enhancing the overall customer experience.
Challenges and Their Mitigations
Multi-cloud solutions, while beneficial, can be complex to implement, requiring careful consideration and planning.Â
Adequate manpower and in-house knowledge are essential to fully leverage the available features of multi-cloud environments.
The challenge lies in tracking multiple rapidly evolving environments, necessitating proactive monitoring and adaptability.
Supporting architectural decisions must be constantly adjusted to align with the evolving nature of environments.
Deployment across multiple cloud environments may require software with a single codebase, streamlining infrastructure deployment.
Managing hardware and services across several clouds can result in complex cost management, demanding continuous attention.
Staying on top of security and reliability practices is critical to ensuring the integrity of multi-cloud systems.
More environments necessitate increased testing, policy and identity management, redundancy, adding to the overall management overhead.
SREs and DevOps professionals play a crucial role in constantly managing and observing services to maintain appropriate incident response times.
In the near future, an increasing number of organizations are expected to adopt multi-cloud strategies.While acknowledging the challenges, embracing multi-cloud strategies early on positions organizations for success in the cloud-native future, offering enhanced flexibility, scalability, and efficiency. We trust that you have found value in exploring the intricacies of multi-cloud environments in this blog.
Squadcast is an incident management tool that’s purpose-built for SRE. Get rid of unwanted alerts, receive relevant notifications and integrate with popular ChatOps tools. Work in collaboration using virtual incident war rooms and use automation to eliminate toil.
What you should do now
Schedule a demo with Squadcast to learn about the platform, answer your questions, and evaluate if Squadcast is the right fit for you.
Curious about how Squadcast can assist you in implementing SRE best practices? Discover the platform's capabilities through our Interactive Demo.
