What is Scalability in Cloud Computing

What is Scalability in Cloud Computing

Site reliability engineering (SRE) is fast becoming an essential aspect of modern IT operations, particularly in highly scaled, big data environments. As businesses and industries shift to the digital and embrace new IT infrastructures and technologies to remain operational and competitive, the need for a new approach for IT teams to find and manage the balance between launching new systems and features and ensuring these are intuitive, reliable, and friendly for end users has intensified as well.

Interest in and around site reliability engineering has surged over the last few years. According to a recent finding by LinkedIn, site reliability engineer is listed as among the 25 fastest growing professions within the last five years. But what exactly is site reliability engineering? And how does it impact a digital enterprise’s ability to satisfy completely or even exceed their Service Level Objectives (SLOs) and reach their business goals, even in large-scale environments? Though there is no such thing as perfect technology, having the right processes in place may make a world of difference. Continue reading to learn more about site reliability engineering and how to implement best practices to ensure all your systems run at maximum efficiency and reliability.

What is Site Reliability Engineering?

Site reliability engineering looks and treats IT operations from a software engineering perspective. The mission is to constantly monitor IT systems, tools, and features, primarily their availability, latency, performance, and capacity.

Site reliability engineers rely on software to manage systems, pinpoint problems, and automate various operation tasks. SRE obtains the tasks that have been historically assigned to and performed manually by the operations teams and hands them over to site reliability engineers. The SREs then take the tasks and leverage automation and standardization to address problems and further improve the reliability of the entire production system.

SREs are now seen as a critical part in the creation and management of scalable and highly reliable software systems. With SREs, IT teams and system admins can govern and operate much larger systems via code. This practice allows them to scale and sustain thousands or hundreds of thousands of machines. 

What Does a Site Reliability Engineer Do?

An SRE is responsible for maximizing a computer system’s reliability and efficiency. SREs understand what all people who interface with a computer system expect from that system and work to meet those expectations at scale. As such, SREs serve as the glue between software engineering and IT operations. SREs often describe their job in terms of creatively filling in the gaps to make people happy, from developers to end-users to members of the management team. You know that your SREs are doing a good job when you can take it for granted that all your systems are running at maximum efficiency and reliability. 

Site reliability engineers usually work in tandem with both IT operations and software development teams. SRE teams help IT operations drive deeper reliability into their production systems. On top of that, SR teams likely help IT, support and development teams reduce time spent on support tickets and escalations, thus allowing them to focus, develop, and roll out new and improved features and services.

Enterprises task site reliability engineers to proactively create and implement software and services designed to boost IT operations and support. This can range from monitoring capabilities to sending notifications when there are changes in the code during production. SRE teams usually work on homegrown tools from scratch as this allows them to efficiently deal with issues in software delivery or incident management.

SRE teams can also be deployed to work on support escalation. However, as systems mature, they become reliable. This then results in fewer critical events in production, which translates to fewer support escalations. Site reliability engineers gather up so much knowledge in both software engineering and IT operations that they become great support teams themselves, helping organizations route issues to the right people.

Because they touch on many aspects of software development and IT, site reliability engineers also take part in the documentation of tribal knowledge. SRE teams also perform post-documentation work such as constant upkeep and runbooks to keep the quality and integrity of knowledge updated and intact.

Site reliability engineers often take on-call responsibilities. Given their exposure to various areas of engineering and IT, SRE teams constantly collaborate to enhance system reliability and optimize on-call processes.

SRE Best Practices in Big Data Environments

There is no perfect SRE strategy. Any site reliability framework requires constant refinement to make sure operational needs are met. The following SRE principles and best practices will help big data organizations execute and tailor their SRE strategy based on their requirements.

  • Construct SLOs SLOs form the bedrock of your SRE strategy. It is the foundation on which other essential aspects such as budgets, schedules, and priorities are based on and built upon. To help create SLOs, experts recommend defining them like an end user. To do just that, you need to genuinely ask how good your services should be? This helps you set a threshold for acceptable performance and reliability, which any point beyond will prompt users to open support tickets. In big data environments, defining your SLOs translates directly into the amount of investment you need to make in SRE.
  • Monitoring and Measuring SRE teams constantly monitor their applications/systems for performance issues and service availability, especially in large-scale environments. All is good when everything is behaving as expected. But when an issue is important enough to affect a user, that issue must be dealt with immediately.For such reliability concerns, the best way to deal with it is to treat these issues as bugs. That means entering these issues into the bug tracking system and applying immediate action when it surfaces before it impacts the user experience.
  • Efficient Capacity Planning Enterprises need to look ahead when it comes to planning their capacity, especially in today’s complex on-premises and cloud environments. They need to take into account the capacity requirements to address increased organic growth (more product adoptions) and inorganic growth (surges in demand driven by feature launches, marketing campaigns, etc.). Failure to forecast and plan for adequate capacity can result in outages. For example, massive user events such as  Black Friday or Cyber Monday require more capacity than usual. Sites and apps that don’t have the capacity to handle volumes of visitors during these events will likely crash.
  • Look Out for System Changes In many instances, the majority of outages are due to changes made to a live system. This can be a reconfiguration for a new binary push. It’s important to realize that even the slightest change can lead to a big impact. Thus, it’s prudent that SRE teams analyze any change and the potential risk it entails. Any change to the management should be supervised. Prior to making the change, SRE teams need to take into account the long-term effects of the change, not just how it can affect the system now. If the change results in unexpected behavior, site reliability engineers must immediately roll back the system to its previous configurations and diagnose after to cut down Mean Time to Recovery (MTTR). Conducting loading testing and accurate provisioning is key to efficient capacity planning. Overprovisioning can result in underutilized resources going to waste, thus increasing your expenses.
  • Automation, Automation, Automation Toil is the type of production service task that’s usually repetitive, and scales linearly as the service evolves. Toil is manual, yet automatable. Especially in today’s complex, big data environments, SRE teams must automate their toil responses, such as testing every backup and other manual and repetitive processes. By developing an automated solution to manage toil, engineers can reduce their manual workload and focus on innovating.
  • Blameless, Constructive Postmortems Postmortems are crucial to SREs as it provides engineers with written documentation of an incident and other important details such as impact, actions performed for mitigation and resolutions, root causes, and recommended follow-up actions. For postmortems to be completely blameless, it must include matters pertaining to the incident, its processes, actions, and recommendations. It should not mention or indict specific individuals or teams as well as inappropriate behavior. This approach prevents a culture of finger-pointing and laying the blame on people. Instead, it encourages engineers to identify flaws and focus on improving their systems and processes.

Site Reliability Engineer vs. DevOps Engineer vs. Software Engineer

Site reliability engineers are development-focused IT professionals who work on developing and implementing solutions that solve reliability, availability, and scale problems. On the other hand, DevOps engineers are ops-focused workers who solve development pipeline problems.  While there is a divide between the two professions, both sets of engineers cross the gap regularly,  delivering their expertise and opinions to the other side and vice versa.

Site reliability engineers keep their services running and available to users, DevOps cover the product life cycle from end to end with the goal of making all processes continuous based on Agile technologies. Delivering continuity across the product life cycle is key to speeding time to market and implementing rapid changes.

While the roles of site reliability engineer and software engineer overlap to a certain extent, there are major differences between the two professions. Software engineers design and write software solutions. In most cases, software engineers factor in cost of deployment as well as application update and maintenance to their designs.

An SRE is not a developer who knows a thing or two about operations, or an operations person who codes. It’s an entirely new and separate discipline on your development team. The SRE brings expertise in deployment, configuration management, monitoring, and metrics. SREs focus on improving application performance, freeing up developers to focus on feature improvements and IT operations to focus on managing infrastructure. When SREs are actively engaged, developers and IT operations have the latitude to do what they do best.

What is The SRE Framework?

The Site Reliability Engineering Framework is built on the following principles.

  • Codified best practices. This pertains to the ability to carry out what works well in production to code. Using the said code will result in services being “production ready” by design.
  • Reusable solutions. Common techniques that are easily shared and implemented, allowing for effective mitigation of scalability and reliability issues.
  • Common production platform with a common control surface. Identical sets of interfaces to production facilities for easy operational management, logging, and configuration for every service.
  • Easier automation and smarter systems. Superior automation and data aggregation provide engineers and developers a complete picture of their systems, applications, including all relevant information. No more manual data collection and analysis from different sources.

SRE creates various framework modules that serve as implementation guides for the solutions designed for a particular production area. An SRE framework essentially directs engineers on how to implement software components as well as a canonical way to integrate these components.

SRE frameworks provide engineers and developers multiple benefits in terms of efficiency and consistency. For one, they free developers from having to find,  piece together, and configure individual components in an ad hoc service-specific manner.

These frameworks deliver a single solution for production concerns that’s reusable across various services. Framework users execute their production and other processes using common implementation rules and minimal configuration differences.

Pepperdata for SREs

By providing optimization of and observability into massively-scaled data systems, Pepperdata is an ideal partner for SREs

Consider the example of memory utilization in a complex, big data system. Maybe an SRE discovers more memory needs to be allocated to running applications to avoid garbage collection. Or, in the case of multi-tenant environments, maybe too much memory was allocated, causing queueing and other problems between tenants. With Pepperdata, an SRE would have full observability into how to properly allocate memory, plus optimization capabilities to reduce overall memory usage and thus improve efficiency and performance.

Another example for Spark big data applications is tuning to reduce or eliminate data skew. Data skew causes certain application elements to work longer than they should, while other compute resources sit idly, underutilized. Spark is highly sensitive to data skew, and for a highly distributed and paralyzed application, it can be very damaging. Pepperdata tracks this Spark data skew and makes effective recommendations to correct it, enabling SREs to meet their SLOs.

In today’s massively scaled computer systems, SREs must rely on automation to effectively support the sheer volume and variety of applications under their purview. Pepperdata provides automatic optimization that simplifies the job of an SRE, in the cloud or on-prem.

Utilizing machine learning (ML), Pepperdata Capacity Optimizer analyzes and automatically optimizes CPU, memory, and I/O resource usage, increasing capacity and enabling SREs to run many more applications without consuming additional resources. 

Once a computer system is optimally tuned, an SRE may eventually say, “All our applications are running without failures, and we’re meeting SLAs consistently.” For that, SREs need the right observability tools to help them determine their memory utilization, data skew, and other issues that might arise.