Site reliability engineering is a process that relies on software tools to automate and streamline IT infrastructure tasks like incident response, system management, change management, and application monitoring. Enterprise IT and business leaders typically prioritize cost control when evaluating cloud adoption strategies and look to implement observability frameworks for greater reliability.
That’s where cloud managed services come in — MSPs can temper business agility with financial awareness for a cost-aware engineering culture. A key takeaway is that cost as a metric doesn’t necessarily need to impede site reliability and business agility. With the right guidance, businesses can develop and implement a cost-conscious cloud monitoring strategy that supports resilience and promotes innovation.
What is SRE?
SRE creates a bridge between the development and operations teams for reliable and scalable services and software systems.
The value of SRE far outweighs the toil and cost of implementing it. The practice covers a range of operations, including reliability and capacity planning for optimized cloud cost management. Businesses can use SLIs (service-level indicators) and SLOs (service-level objectives) to track the reliability of cloud storage, automatically scaling resource utilization based on demand.
Capacity planning and performance tuning allow businesses to ensure a smooth customer experience during periods of peak demand. Automated disaster recovery, backup and traffic routing improve system reliability and resilience at optimal costs while preventing potential losses due to preventable downtime or runtime failures.
Key principles to ensure effective SRE implementation
SRE is not an exact science, and it largely depends on the people, tools, and processes in place. According to Dynatrace, only 20% of organizations can claim to have a mature SRE practice. As such, there are a few key principles that SRE teams need to follow, either in-house or in collaboration with an external cloud managed service provider.
1. Application monitoring and blameless postmortems
Cloud monitoring involves constant surveillance of applications to ensure optimal performance and swift remediation of potential issues. This could involve infrastructure monitoring, network monitoring, and end-user behavior monitoring. Constantly observing the applications can help in identifying patterns and quickly pinpointing any anomalies or failures.
Blameless postmortems are a cultural aspect of SRE where failures are treated as opportunities for learning and improvement rather than for assigning blame. When an incident occurs, SRE teams carry out a blameless postmortem, analyzing the sequence of events, the root cause, and the impact, without attributing the fault to any individual or team. This approach encourages transparency and learning from mistakes, leading to system and process improvements that prevent recurrence and cost savings in the long run.
2. Eliminating toil through gradual change implementation
Toil refers to manual and repetitive tasks that are devoid of enduring value. SRE aims to eliminate such tasks as they contribute to inefficiency and burnout. Gradual change implementation introduces small changes regularly, which are easier to manage and less likely to cause significant issues compared to large-scale changes. This approach also allows for continuous improvement and adaptation to new requirements or circumstances. Gradual implementation of change reduces the probability of irreversible errors that can adversely affect company finances and reputation.
3. Reliability improvement via automation
SRE teams typically seek to automate any process that is repetitive, predictable, and well-defined. This can include activities such as server provisioning, software deployments, testing, and incident responses. Automation helps in reducing human errors, improving efficiency, and freeing up time and resources for SREs to focus on high-value tasks that can't be automated. Additionally, it also aids in scaling operations as the infrastructure grows, leading to greater control over cloud costs.
4. Allocating an error budget
An error budget is a novel concept in SRE where the acceptable level of unreliability for a service is quantified. It is defined as the inverse of the service's availability target. For example, if the target availability of a service is 99.9% (known as "three nines"), then the error budget—the allowable downtime—is 0.1%.
The error budget provides a balance between the need for velocity and the need for reliability. If a service is consuming its error budget too quickly, it's an indication for the team to focus more on reliability. On the other hand, if a service constantly runs under its error budget, it could be a sign that the team could move faster or take more risks.
5. Pre-establishing metrics to track reliability and test resolution
SRE promotes the use of metrics in the form of Service Level Indicators (SLIs) and Service Level Objectives (SLOs) to measure and manage system reliability. SLOs are targets for the level of service, based on SLIs, that you aim to provide to users. According to a survey by The DevOps Institute, approximately 50% of respondents continually refine SLOs while 30% publish them to their customers to set expectations.
These metrics are crucial to prioritize system resiliency while making architectural decisions. SLIs provide a benchmark to automate build testing while SLOs help detect issues through the implementation of quality gates. Having pre-established metrics allows teams to measure the impact of their actions and changes on system reliability. Additionally, these metrics are crucial in incident response scenarios to determine the severity of the incident and to measure the effectiveness of the resolution steps.
How to manage cloud expenses with SRE?
Naturally enough, cloud costs are not an issue that concerns the typical engineer. Therefore, it’s important to first locate where cloud costs factor into the context of site reliability engineering.
At a very basic level, SRE influences cloud cost management in four major aspects:
- Balancing reliability and development speed: By enforcing error budgets, SRE teams strike a balance between the speed of rolling out new developments (which can increase potential errors but is beneficial for business growth) and system reliability (which is essential for user satisfaction and cost efficiency).
- Resource optimization: SRE ensures that systems are not over-provisioned (which could lead to unnecessary costs) or under-provisioned (which could affect performance and reliability) through efficient resource usage and capacity planning.
- Automation and cost reduction: Automation reduces the need for manual interventions, which can be time-consuming and expensive. Automated systems are generally more consistent and less prone to error leading to cost savings in the long run.
- Incident management: Quick incident response and effective disaster recovery strategies can minimize downtime and thus reduce the potential revenue loss associated with system outages.
Implementation guidelines to align SRE with cloud costs
While site reliability engineering reduces toil and streamlines business operations and delivery speed, it’s still a significant shift from existing company culture and operational procedures. Cloud managed service providers need to first break down the implementation strategy and build a business case. Shared below are key strategies to align the SRE implementation process with cost-consciousness.
|Optimize resource utilization||Make use of autoscaling and serverless technologies to match your resource usage with demand and avoid over-provisioning.|
|Automation||Automation Automate wherever possible; from infrastructure provisioning to application deployment and system management tasks.|
|Monitoring and alerting||Implement monitoring and alerting systems to identify and respond to potential issues before they become serious problems. These can help you spot inefficiencies and areas where costs can be cut.|
|Optimize data transfer||Build out and optimize your data architecture to reduce costs incurred by unnecessary data transfers across cloud environments.|
|Right sizing||Continuously review and adjust your cloud resources based on the actual usage. Regularly right sizing your instances ensures you’re not paying for more resources than you actually need, leading to significant savings.|
|Adopt SRE principles||Build a culture that understands and supports SRE principles. This includes accepting that failure is normal and should be planned for, emphasizing automation, and basing decisions on data and observation.|
|Build a culture of shared responsibility||Encourage your teams, including everyone from developers to operations staff to managers, to share responsibility for system reliability and cost management.|
|Continuous learning||Create a culture of continuous learning and improvement based on postmortems and blameless retrospectives. The ultimate goal of learning from failures is to continuously improve the existing systems and processes.|
|Cost management practices||Implement general cost management practices such as regular cost reviews, setting cost budgets and alerts, and using tools for cost optimization.|
|Prioritize cost as a key metric||Include cost as one of the key metrics for your SRE team. This encourages the team to consider cost in their decision-making and fosters a mindset of cost optimization.|
|Business alignment||By aligning your SRE strategies with your business goals the SRE team will be able to make better decisions about trade-offs between reliability, performance, and cost.|
Real-time insights into the actual cost of resources across all instances, combined with automation and data-driven decision making will allow you to make sound cost-tuning decisions and avoid cloud waste. The goals of SRE and cloud cost management are inherently tied in – with a focus on applications and services that are resilient, reliable, scalable, and agile. Prioritizing cost as a metric in SRE implementation is therefore a natural transition that can add value to the entire discipline. Cloud managed service providers help businesses bridge this gap between DevOps and cloud cost management to develop a site reliability engineering approach that uses cost-consciousness to complement business agility in the long run.