How can DevOps engineers keep cloud projects cost-effective?

As a devops Engineer we have to understand that devops is not a technology but a methodology which logo represents as infinite. Which means it's a continuous process. Few steps I'm mentioning below. 1st - Keep Monitoring resources usage and Cost - need to monitor how much CPU utilization is there are we paying or using higher Ram and resources which can be done through lower resources. We can also add billing alarm and we can set budget. 2nd - We should use auto scaling 3rd If we know our requirements we should go with reserved instances and saving plans. 4th optimize storage class use 5th We should use right region 6th Regular review of services which we are using 7th Educate team member about the same Last Continuous Improvement

Enforce the golden principle of the least access policy as a least-cost policy, emphasising cost as a primary consideration from the outset, involving all stakeholders—Dev, QA, DevOps, Leads, Manager—in decision-making and implementation processes. In one line you have to be frugal

Basically we need to follow the common theory - “use the right tool at the right place”. People tends to use the “latest” services from the cloud providers (CSP) without knowing the efficiency and effectiveness. Another practice many people missing is the use of immutable infrastructure designs. Eg: we can spin up Kubernetes or OpenShift clusters in minutes for the development and testing, but still people keep the clustered running after office hours and on weekends in idle state! There are several such scenarios where the DevOps and cloud-Ops can save the cloud infrastructure costs!

Understanding cloud pricing is vital for effective resource and cost management. Pay-as-You-Go: Flexible but watch for overspending. Ideal for dynamic workloads with strict budget control. Reserved Instances: Cost savings for long-term commitments but limits flexibility. Spot Instances: Lower costs for non-urgent tasks but may be terminated suddenly. On-Demand: Reliable but costly, suited for immediate resource needs. Monitoring and Optimization: Implement cost monitoring, alerts, rightsizing, and cloud provider tools for efficient cost management. Understanding and selecting the right cloud pricing model is essential for efficient resource management while staying within budget.

Smart Spending: Opt for pay-as-you-go for flexibility, but track usage to avoid overspending. Strategic Commitments: Consider reserved instances for discounts, balancing cost and flexibility. Cost-Effective Flexibility: Leverage spot instances for cost savings, understanding the risk of sudden termination. Reliable Investment: Choose on-demand for predictability and reliability, especially for critical workloads, and utilize monitoring tools like AWS Cost Explorer or Azure Cost Management for cost management insights.

Cloud governance, crucial for DevOps, defines rules aligning with business goals. It enforces security, compliance, and automation, maintaining consistency and transparency in the cloud. It encompasses policies on resource tagging, naming conventions, provisioning, backup, encryption, auditing, and reporting, using tools like CloudFormation, Terraform, or Azure DevOps. DevOps engineers rely on it to ensure efficient, controlled, and secure cloud operations.

Your cloud governance model should deliver value to its users and stakeholders. For instance, if you employ resource tagging, tailor your cost reporting to cater to engineers, managers, and executives, as each group has distinct requirements. I've observed many tagging policies that are inflexible, preventing groups from adding custom cost tags tailored to their specific needs. If your cost reporting tool lacks such adaptability, ensure you provide at least a half-dozen generic cost tags that teams can leverage.

Begin by pinpointing costs per project or application. Opt for strategies like project or subscription isolation, network segmentation, resource tagging, and Kubernetes namespaces to achieve clear cost attribution. Once established, employ monitoring tools and set budget alerts to preempt cost overruns. Promote standardized deployments to ensure consistency and predictability. Integrate cost estimation into your DevOps pipeline, allowing teams to anticipate expenses prior to deployment. Robust governance not only manages costs but also fosters efficiency and transparency throughout cloud operations.

1. Define Policies: Set rules for resource tagging, naming, provisioning, backup, encryption, auditing, and reporting. 2. Automate Enforcement: Use tools like CloudFormation or Terraform to automate policy enforcement, reducing errors. 3. Ensure Compliance: Regularly audit your cloud environment to ensure adherence to policies. 4. Educate Teams: Train teams on the importance of following governance policies. 5. Adapt and Evolve: Continuously update policies to meet changing business needs and regulations.

Cloud governance involves rule-setting for your cloud environment, addressing security, compliance, access, quality, and costs. Align policies with business goals and DevOps practices. Employ tools and frameworks for policy automation and enforcement, enhancing consistency, accountability, and transparency in cloud projects.

Monitoring and optimizing cloud resources is vital for cost-efficiency and performance. Use tools like CloudWatch, Azure Monitor, or Google Cloud Monitoring to track utilization, errors, and availability. Automate with CloudFormation, Terraform, or Azure DevOps for provisioning and scaling. Consider cost allocation tags, rightsizing instances, and security monitoring for comprehensive management.

Another way to cut and optimize cloud costs is to collect and process only relevant logs that are possible to analyze or are relevant from an audit perspective. This way, you can reduce the storage costs and focus on the essential data only. Cloud auditing can help identify unused or inefficient resources and take corrective actions to optimize cloud spending. Also, create automated scripts that can detect errors or anomalies in resource utilization and react quickly to minimize cloud bills.

Monitoring and optimizing your cloud resources is like keeping an eye on your car's fuel gauge and getting the best mileage. In the cloud, it means regularly checking how your apps and data are using resources like servers and storage. By doing this, you can spot problems early, like if something is using too much power (or money), and fix it. You can also make sure you're not paying for things you don't need. It's like tuning up your car for better performance and saving on gas – monitoring and optimizing in the cloud helps your business run smoother and saves you money.

This is a very wide topic and often overlooked in lot of cloud migration. Right tagging, right tools installed should be used for monitoring resources. A proper governance model should be established to talk on this. Each department in any organisation should have a set budget enforced via budgets in each cloud provider and appropriate cost center owner should be made aware of the usage pattern every week. Each department should be made responsible and should be made answerable to their own spending. CxO's should be aware of their cloud usage and spending to enforce the importance of the Cloud Hosting Cost

1. Monitor with Tools: Utilize CloudWatch, Azure Monitor, or Google Cloud Monitoring to track resource utilization, performance, availability, and errors. 2. Analyze Metrics: Use metrics to identify areas for optimization and improvement. 3. Automate Provisioning: Employ tools like CloudFormation, Terraform, or Azure DevOps to automate resource provisioning, configuration, and management. 4. Scale Efficiently: Set up auto-scaling to adjust resources based on demand, ensuring optimal performance without unnecessary spending. 5. Identify Waste: Regularly review usage patterns to identify and eliminate waste, inefficiencies, and bottlenecks.

Benefits of Serverless architecture are: Pay only for resources used, reducing cloud computing costs. Auto-scaling based on demand, no server provisioning or management. Focus on core business logic, not infrastructure. However, Serverless architecture is not suitable for every scenario. Some drawbacks are: Limited control over performance, security, and reliability. Potential vendor lock-in due to varying cloud provider offerings. Higher latency due to function initialization(Warmup time).

Not every serverless offering can scale down to zero. While you may argue that your application is busy and runs round the clock, ask yourself: does it need to be operational 24/7 in development or testing? If you only run your dev/test environment for 5 days a week, 10 hours a day, that's a potential savings of 511 hours a month.

Embracing serverless architecture has been transformative for me in the cloud space. This approach removes the need for server management, allowing you to focus solely on your code. The immediate advantage is a cost-effective system; you only foot the bill for the actual compute and resources utilized. I've had success using AWS Lambda, Azure Functions, and Google Cloud Functions, deploying functions that react to specific events or triggers. Moreover, with services like AWS Fargate, Azure Container Instances, or Google Cloud Run, it's possible to run containers without getting into the weeds of server or cluster management.

Be aware of potential cold start latency in serverless functions, especially if they're not used frequently. Optimize code, use provisioned concurrency, or choose services that minimize cold start times. Leverage event-driven architecture to trigger functions in response to events, such as HTTP requests, database changes, or file uploads. This reduces idle compute time and costs.

Whenever possible, use serverless computing and managed services. These services often offer cost optimization features like auto-scaling and automatic resource provisioning, reducing the need for manual management.

Using cloud-native tools such as the Cost Advisor/Explorer offered by cloud providers is a good first resource. However, the use of automation is key to schedule instances, and/or stop instances when they are not in use. Likewise, automation can be used to identify rightsizing oportunities and act on them.

Leveraging cloud-native tools and services can significantly enhance the efficiency, security, and scalability of your cloud projects. By effectively leveraging these cloud-native tools and services, you can streamline your DevOps workflows, accelerate software delivery, and enhance the security and performance of your cloud-based applications and infrastructure. Prioritize the integration of best practices and automation to foster a culture of continuous improvement and innovation within your organization.

Embracing cloud-native tools has transformed my cloud projects. These tools, built to maximize cloud benefits like elasticity, have enhanced my productivity and security. I've utilized AWS CloudFormation and Azure DevOps to automate cloud tasks. Additionally, tools like AWS CodeDeploy have optimized my CI/CD pipelines. Their streamlined nature has accelerated my DevOps processes, ensuring efficient executions.

Adopting cloud-native tools was a strategic move, not merely a technological shift. At some point we decided to limit our manual deployments cycles, adopting a cloud-agnostic 'Everything-as-Code' ethos, fortified by a 'cross cloud Landing Zone deployment' for fast, secure launches. We leveraged tools/services like GitHub Actions, Jenkins/Azure DevOps, and ArgoCD, k8s, etc to automate the E2E CI/CD pipeline. This approach yielded us 40% uptick in deployment speed.. But we learned a lesson! - it is not just about speed! it's about how we become better. Yes, we had complexities and delays initially with this approach, but they served as stepping stones, compelling us to continuously refine our game-plan and ascend to new heights.

Ways to reduce cloud computing costs in Azure: Use Azure Advisor for personalized resource optimization recommendations. Monitor spending with Azure Cost Management, set budgets, alerts, and cost control policies. Save up to 72% with Azure Reserved Instances. Reuse on-premises licenses with Azure Hybrid Benefit for up to 40% savings. Utilize Azure Spot VMs for discounted prices on interruptible workloads.

Cloud strategy, like any strategy (e.g. business, operational), should be flexible and open to change. More than expecting some one to come up with changes, the strategy should be regularly reviewed on a cadence basis, for example quarterly. The cloud strategy should be created by a multi-disciplinary team, not only cloud architects, but also FinOps engineers, management, and others. Having the buy-in from high-level management is a type of incentize i've seen to work well for adoption.

Remember, your cloud strategy isn't set in stone; it's a living plan that needs regular attention. Stay nimble by consistently reviewing and adjusting your strategy to match the evolving needs of your business and customers. Keep a close eye on performance, costs, risks, and opportunities. Tools like AWS Cost Explorer, Azure Cost Management, or Google Cloud Billing help you analyze and forecast spending. Leverage tools like AWS Trusted Advisor, Azure Advisor, or Google Cloud Recommendations to uncover best practices and improvements. By routinely reviewing and fine-tuning your cloud strategy, you'll keep your cloud projects aligned with your business goals and values.

On thing I have seen in my experience is cloud strategy depends on whether or not you want a vendor lock in. If you don't care which cloud vendor you prefer, then with skilled employees you may be able to work through it. In terms of cost, the more you move to cloud the more you pay. Cloud native tools gives an indication of savings however these need to be budgeted at the planning phase.

Think of your cloud strategy as a GPS for your business in the digital landscape. Regular reviews and adjustments are like recalibrating your route to avoid traffic and take shortcuts. Cloud costs, risks, and opportunities are dynamic, just like road conditions. Tools like Cost Explorer and Trusted Advisor are your traffic updates, helping you make informed decisions. Keep your cloud journey efficient and cost-effective by staying flexible and adapting to the ever-changing digital terrain.

Regularly reviewing and adjusting your cloud strategy is vital for staying aligned with business goals. Consider a financial institution using the cloud. They analyze quarterly reports, noticing increased mobile app usage. They adjust their cloud strategy, emphasizing mobile app optimization. This agility ensures efficient resource allocation and enhanced customer experience.

Something I often see forgotten is to shutdown/delete unused resources... Many dev projects are just left to sit there. Likewise, there are many workloads that can benefit from being shutdown during some hours (e.g. at nigh) and/or during the weekends. Regularly checking for resources that are not accessed is just as useful for costs as it is for security.

In any project, cost-effectiveness depends on both the efficiency and effectiveness of the solution. The lack of efficiency leads to resource wastage, while the lack of effectiveness necessitates rework. In any case, having a detailed understanding of the project's scope is essential to design an appropriate cloud architecture that meets requirements for security, performance, etc., and can scale horizontally as demand increases. This pertains to efficiency. On the other hand, concerning effectiveness, it focuses more on the software solution, ensuring it meets expectations in the fewest possible iterations. To achieve this, it is crucial to employ agile methodologies and execute assigned roles effectively.

Cost Alerts and Budgets, Idle Resource Management, Performance Optimization, Resource Sharing, Cost Awareness and Training, Regular Cost Reviews The key to keeping cloud projects cost-effective? Collaboration! DevOps engineers, developers, and stakeholders must work together to achieve better cost control and allocate cloud resources efficiently. By implementing cost-conscious strategies and fostering a culture of optimization. #cloudcomputing #costefficiency #collaboration.

Understand the utilization patterns of your application. This will enable you to make informed decisions about which service to choose without having costs explode. If somethings needs to be running all the time, serverless is probably not the right choice for example.

In my experience, in highly distributed enterprises, I have seen scenarios where certain organizations had been on fence to migrate workloads to Cloud while maintaining a minimal footprint in form of hybrid constructs. Software defined data center technologies were quite matured form obviating the need to quickly move the workloads to public clouds. These business decisions have also been due to regulatory and compliance reasons. As of today, in hindsight these enterprises have dodged the bullet of vendor lock-ins, and elevated expenditures where in-house capabilities can be leverage with considerable saving. Example - leveraging an on-premises Mongo DB VMware cluster can he purposed to derive same competencies and align with use cases.