Practical Site Reliability Engineering: Automate the process of designing, developing, and delivering highly reliable apps and services with SRE

Software applications are increasingly complicated yet sophisticated. Highly integrated systems are the new norm these days. Enterprise-grade applications ought to be seamlessly integrated with several third-party software components running in distributed and disparate systems. Increasingly, software applications are made out of a number of interactive, transformative, and disruptive services in an ad hoc manner on an as-needed basis. Multi-channel, multimedia, multi-modal, multi-device, and multi-tenant applications are becoming pervasive and persuasive. There are also enterprise, cloud, mobile, Internet of Things (IoT), blockchain, cognitive, and embedded applications hosted in virtual and containerized environments. Then, there are industry-specific and vertical applications (energy, retail, government, telecommunication, supply chain, utility, healthcare, banking, and insurance, automobiles, avionics, and robotics) being designed and delivered via cloud infrastructures.

There are software packages, homegrown software, turnkey solutions, scientific, and technical computing services, and customizable and configurable software applications to meet distinct business requirements. In short, there are operational, transactional, and analytical applications running on private, public, and hybrid clouds. With the exponential growth of connected devices, smart sensors, and actuators, fog gateways, smartphones, microcontrollers, and single board computers (SBCs), the software enabled data analytics and proximate moves to edge devices to accomplish real-time data capture, processing, decision-making, and action.

We are destined to move towards real-time analytics and applications. Thus, it is clear that software is purposefully penetrative, participative, and productive. Largely, it is quite a software-intensive world.

Similar to the quickly growing software engineering field, hardware engineering is also on the fast track. These days, there are clusters, grids, and clouds of IT infrastructures. There are powerful appliances, cloud-in-a-box options, hyper-converged infrastructures, and commodity servers for hosting IT platforms and business applications. The physical machines are touted as bare metal servers. The virtual versions of the physical machines are the virtual machines and containers. We are heading toward the era of hardware infrastructure programming. That is, closed, inflexible, and difficult to manage and maintain bare-metal servers are being partitioned into a number of virtual machines and containers that are highly flexible, open, easily manageable, and replaceable, not to mention quickly provisionable, independently deployable, and horizontally scalable. The infrastructure partitioning and provisioning gets sped up with scores of automated tools to enable the rapid delivery of software applications. The rewarding aspects of continuous integration, deployment, and delivery are being facilitated through a combination of containers, microservices, configuration management solutions, DevOps tools, and Continuous Integration (CI) platforms.

Worldwide institutions, individuals, and innovators are keenly embracing cloud technology with all its clarity and confidence. With the faster maturity and stability of cloud environments, there is a distinct growth in building and delivering cloud-native applications, and there are viable articulations and approaches to readily make cloud native software. Traditional and legacy software applications are being meticulously modernized and moved to cloud environments to reap the originally envisaged benefits of the cloud idea. Cloud software engineering is one hot area, drawing the attention of many software engineers across the globe. There are public, private, and hybrid clouds. Recently, we have heard more about edge/fog clouds. Still, there are traditional IT environments that are being considered in the hybrid world.

There are development teams all over the world working in multiple time zones. Due to the diversity and multiplicity of IT systems and business applications, distributed applications are being touted as the way forward. That is, the various components of any software application are being distributed across multiple locations for enabling redundancy enabled high availability. Fault-tolerance, less latency, independent software development, and no vendor lock-in are being given as the reason for the realm of distributed applications. Accordingly, software programming models are being adroitly tweaked so that they deliver optimal performance in the era of distributed and decentralized applications. Multiple development teams working in multiple time zones across the globe have become the new norm in this hybrid world of on-shore and off-shore development.

With the big-data era upon us, we need the most usable and uniquely distributed computing paradigm through the dynamic pool of commoditized servers and inexpensive computers. With the exponential growth of connected devices, the days of device clouds are not too far away. That is, distributed and decentralized devices are bound to be clubbed together in large numbers to form ad hoc and application-specific cloud environments for data capture, ingestion, pre-processing, and analytics. Thus, there is no doubt that the future belongs to distributed computing. The fully matured and stabilized centralized computing is unsustainable due to the need for web-scale applications. Also, the next-generation internet is the internet of digitized things, connected devices, and microservices.

There are a bunch of digitization and edge technologies bringing forth a number of business innovations and improvisations. As enterprises are embracing these technologies, the ensuring era is being touted as the digital transformation and intelligence era. This section helps in telling you about all that needs to be changed through the absorption of these pioneering and path-breaking technologies and tools. 

The field of information and communication technology (ICT) is rapidly growing with the arrival of scores of pioneering technologies, and this trend is expediently and elegantly automating multiple business tasks. Then, the maturity and stability of orchestration technologies and tools is bound to club together multiple automated jobs and automate the aggregated ones. We will now discuss the latest trends and transitions happening in the ICT space.

Due to the heterogeneity and multiplicity of software technologies such as programming languages, development models, data formats, and protocols, software development and operational complexities are growing continuously. There are several breakthrough mechanisms to develop and run enterprise-grade software in an agile and adroit fashion. There came a number of complexity mitigation and rapid development techniques for producing production-grade software in a swift and smart manner. The leverage of "divide and conquer" and "the separation of crosscutting concerns" techniques is being consistently experimented with and developers are being encouraged to develop risk-free and futuristic software services. The potential concepts of abstraction, encapsulation, virtualization, and other compartmentalization methods are being invoked to reduce the software production pain. In addition, there are performance engineering and enhancement aspects that are getting the utmost consideration from software architects. Thus, software development processes, best practices, design patterns, evaluation metrics, key guidelines, integrated platforms, enabling frameworks, simplifying templates, and programming models are gaining immense significance in this software-defined world.

Thus, there are several breakthrough technologies for digital innovations, disruptions, and transformations. Primarily, the IoT paradigm generates a lot of multi-structured digital data and the famous artificial intelligence (AI) technologies, such as machine and deep learning, enables the extrication of actionable insights out of the digital data. Transitioning raw digital data into information, knowledge, and wisdom is the key differentiator for implementing digitally transformed and intelligent societies. Cloud IT is being positioned as the best-in-class IT environment for enabling and expediting the digital transformation. 

With digitization and edge technologies, our everyday items become digitized to join in with mainstream computing. That is, we will be encountering trillions of digitized entities and elements in the years ahead. With the faster stability and maturity of the IoT, cyber physical systems (CPS), ambient intelligence (AmI), and pervasive computing technologies and tools, we are being bombarded with innumerable connected devices, instruments, machines, drones, robots, utilities, consumer electronics, wares, equipment, and appliances. Now, with the unprecedented interest and investment in AI (machine and deep learning, computer vision, and natural language processing), algorithms and approaches, and IoT device data (collaborations, coordination, correlation, and corroboration) are meticulously captured, cleansed, and crunched to extricate actionable insights/digital intelligence in time. There are several promising, potential, and proven digital technologies emerging and evolving quickly in synchronization, with a variety of data mining, processing, and analytics. These innovations and disruptions eventually lead to digital transformation. Thus, digitization and edge technologies in association with digital intelligence algorithms and tools lead to the realization and sustenance of digitally transformed environments (smarter hotels, homes, hospitals, and so on). We can easily anticipate and articulate digitally transformed countries, counties, and cities in the years to come with pioneering and groundbreaking digital technologies and tools.  

The cloud era is setting in and settling steadily. The aiding processes, platforms, policies, procedures, practices, and patterns are being framed and firmed up by IT professionals and professors, to tend toward the cloud. The following sections give the necessary details for our esteemed readers.  

The cloud applications, platforms, and infrastructures are gaining immense popularity these days. Cloud applications are of two primary types:

The current and conventional applications that are hosted and running on various IT environments are being meticulously modernized and migrated to standardized and multifaceted cloud environments to reap all the originally expressed benefits of cloud paradigm. Besides enabling business-critical, legacy, and monolithic applications to be cloud-ready, there are endeavors for designing, developing, debugging, deploying, and delivering enterprise-class applications in cloud environments, harvesting all of the unique characteristics of cloud infrastructure and platforms. These applications natively absorb the various characteristics of cloud infrastructures and act adaptively. There is microservices architecture (MSA) for designing next-generation enterprise-class applications. MSA is being deftly leveraged to enable massive applications to be partitioned into a collection of decoupled, easily manageable, and fine-grained microservices.

With the decisive adoption of cloud technologies and tools, every component of enterprise IT is being readied to be delivered as a service. The cloud idea has really and rewardingly brought in a stream of innovations, disruptions, and transformations for the IT industry. The days of IT as a Service (ITaaS) will soon become a reality, due to a stream of noteworthy advancements and accomplishments in the cloud space. 

Marc Andreessen famously penned the article Why software is eating the world several years ago. Today, we widely hear, read, and even sometimes experience buzzwords such as software-defined, compute, storage, and networking. Software is everywhere and gets embedded in everything. Software has, unquestionably, been the principal business automation and acceleration enabler. Nowadays, on its memorable and mesmerizing journey, software is penetrating into every tangible thing (physical, mechanical, and electrical) in our everyday environments to transform them into connected entities, digitized things, smart objects, and sentient materials. For example, every advanced car today has been sagaciously stuffed with millions of lines of code to be elegantly adaptive in its operations, outputs, and offerings.

Precisely speaking, the ensuing era sets the stage for having knowledge-filled, situation-aware, event-driven, service-oriented, cloud-hosted, process-optimized, and people-centric applications. These applications need to exhibit a few extra capabilities. That is, the next-generation software systems innately have to be reliable, rewarding, and reactive ones. Also, we need to arrive at competent processes, platforms, patterns, procedures, and practices for creating and sustaining high-quality systems. There are widely available non-functional requirements (NFRs), quality of service (QoS), and quality of experience (QoE) attributes, such as availability, scalability, modifiability, sustainability, security, portability, and simplicity. The challenge for every IT professional lies in producing software that unambiguously and intrinsically guarantees all the NFRs.

Agile application design: We have come across a number of agile software development methodologies. We read about extreme and pair programming, scrum, and so on. However, for the agile design of enterprise-grade applications, the stability of MSA is to activate and accelerate the application design. 

Accelerated software programming: As we all know, enterprise-scale and customer-facing software applications are being developed speedily nowadays, with the faster maturity of potential agile programming methods, processes, platforms, and frameworks. There are other initiatives and inventions enabling speedier software development. There are component-based software assemblies, and service-oriented software engineering is steadily growing. There are scores of state-of-the-art tools consistently assisting component and service-based application-building phenomena. On the other hand, the software engineering aspect gets simplified and streamlined through the configuration, customization, and composition-centric application generation methods. 

Automated software deployment through DevOps: There are multiple reasons for software programs to be running well in the developer's machine but not so well in other environments, including production environments. There are different editions, versions, and releases of software packages, platforms, programming languages, and frameworks. Coming to the running software is suites across different environments. There is a big disconnect between developers and operation teams due to constant friction between development and operating environments. 

Further on, with agile programming techniques and tips, software applications get constructed quickly, but their integration, testing, building, delivery, and deployment aspects are not automated. Therefore, concepts such as DevOps, NoOps, and AIOps have gained immense prominence and dominance to bring in several automation enabling IT administrators. That is, these new arrivals have facilitated a seamless and spontaneous synchronization between software design, development, debugging, deployment, delivery and decommissioning processes, and people. The emergence of configuration management tools and cloud orchestration platforms enables IT infrastructure programming. That is, the term Infrastructure as Code (IaC) is facilitating the DevOps concept. That is, faster provisioning of infrastructure resources through configuration files, and the deployment of software on those infrastructure modules, is the core and central aspect of the flourishing concept of DevOps. 

This is the prime reason why the concept of DevOps has started flourishing these days. This is quite a new idea that's gaining a lot of momentum within enterprise and cloud IT teams. Companies embrace this new cultural change with the leverage of multiple toolsets for Continuous Integration (CI), Continuous Delivery (CD), and Continuous Deployment (CD). Precisely speaking, besides producing enterprise-grade software applications and platforms, realizing and sustaining virtualized/containerized infrastructures with the assistance of automated tools to ensure continuous and guaranteed delivery of software-enabled and IT-assisted business capabilities to mankind is the need of the hour.

The following are some challenges you may come across:

The idea is to clearly illustrate the serious differences between agile programming, DevOps, and the SRE movement. There are several crucial challenges ahead, as we have mentioned. And the role and responsibility of the SRE technologies, tools, and tips are going to be strategic and significant toward making IT reliable, robust, and rewarding.

We know that the subject of software reliability is a crucial one for the continued success of software engineering in the ensuing digital era. However, it is not easy thing to do. Because of the rising complexity of software suites, ensuring high reliability turns out to be a tough and time-consuming affair. Experts, evangelists, and exponents have come out with a few interesting and inspiring ideas for accomplishing reliable software systems. Primarily, there are two principal approaches; these are as follows:

Here are the other aspects being considered for producing reliable software packages:

Let's discuss these in detail.

Kubernetes for container orchestration

A MSA requires the creating and clubbing together of several fine-grained and easily manageable services that are lightweight, independently deployable, horizontally scalable, extremely portable, and so on. Containers provides an ideal hosting and run time environment for the accelerated building, packaging, shipping, deployment, and delivery of microservices. Other benefits include workload isolation and automated life-cycle management. With a greater number of containers (microservices and their instances) being stuffed into every physical machine, the operational and management complexities of containerized cloud environments are on the higher side. Also, the number of multi-container applications is increasing quickly. Thus, we need a standardized orchestration platform along with container cluster management capability. Kubernetes is the popular container cluster manager, and it consists of several architectural components, including pods, labels, replication controllers, and services. Let's take a look at them:

• As mentioned elsewhere, there are several important ingredients in the Kubernetes architecture. Pods are the most visible, viable, and ephemeral units that comprise one or more tightly coupled containers. That means containers within a pod sail and sink together. There is no possibility of monitoring, measuring, and managing individual containers within a pod. In other words, pods are the base unit of operation for Kubernetes. Kubernetes does not operate at the level of containers. There can be multiple pods in a single server node and data sharing easily happens in between pods. Kubernetes automatically provision and allocate pods for various services. Each pod has its own IP address and shares the localhost and volumes. Based on the faults and failures, additional pods can be quickly provisioned and scheduled to ensure the continuity of services. Similarly, under heightened loads, Kubernetes adds additional resources in the form of pods to ensure system and service performance.  Depending on the traffic, resources can be added and removed to fulfil the goal of elasticity.

• Labels are typically the metadata that is attached to objects, including pods.
• Replication controllers, as articulated previously, have the capability to create new pods leveraging a pod template. That is, as per the configuration, Kubernetes is able to run the sufficient number of pods at any point in time. Replication controllers accomplish this unique demand by continuously polling the container cluster. If there is any pod going down, this controller software immediately jumps into action to incorporate an additional pod to ensure that the specified number of pods with a given set of labels are running within the container cluster.
• Services is another capability that embedded into Kubernetes architecture. This functionality and facility offers a low-overhead way to route all kinds of service requests to a set of pods to accomplish the requests. Labels is the way forward for selecting the most appropriate pods. Services provide methods to externalize legacy components, such as databases, with a cluster. They also provide stable endpoints as clusters shrink and grow and become configured and reconfigured across new nodes within the cluster manager. Their job is to remove the pain of keeping track of application components that exist within a cluster instance.

The fast proliferation of application and data containers in producing composite services is facilitated through the leveraging of Kubernetes, and it fastening the era of containerization. Both traditional and modern IT environments are embracing this compartmentalization technology to surmount some of the crucial challenges and concerns of the virtualization technology.

API Gateways and management suite: This is another platform for bringing in reliable client and service interactions. The various features and functionalities of API tools include the following:

• It acts as a router. It is the only entry point to our collection of microservices. This way, microservices are not needed to be public anymore but are behind an internal network. An API Gateway is responsible for making requests against a service or another one (service discovery).
• It acts as a data aggregator. API Gateway fetches data from several services and aggregates it to return a single rich response. Depending on the API consumer, data representation may change according to the needs, and here is where backend for frontend (BFF) comes into play.
• It is a protocol abstraction layer. The API Gateway can be exposed as a REST API or a GraphQL or whatever, no matter what protocol or technology is being used internally to communicate with the microservices.

• Error management is centralized. When a service is not available, is getting too slow, and so on, the API Gateway can provide data from the cache, default responses or make smart decisions to avoid bottlenecks or fatal errors propagation. This keeps the circuit closed (circuit breaker) and makes the system more resilient and reliable.
• The granularity of APIs provided by microservices is often different than what a client needs. Microservices typically provide fine-grained APIs, which means that clients need to interact with multiple services. The API Gateway can combine these multiple fine-grained services into a single combined API that clients can use, thereby simplifying the client application and improving performance. 
• Network performance is different for different types of clients. The API Gateway can define device-specific APIs that reduce the number of calls required to be made over slower WAN or mobile networks. The API Gateway being a server-side application makes it more efficient to make multiple calls to backend services over LAN.
• The number of service instances and their locations (host and port) changes dynamically. The API Gateway can incorporate these backend changes without requiring frontend client applications by determining backend service locations. 
• Different clients may need different levels of security. For example, external applications may need a higher level of security to access the same APIs that internal applications may access without the additional security layer.

Service mesh solutions for microservice resiliency: Distributed computing is the way forward for running web-scale applications and big-data analytics. By the horizontal scalability and individual life cycle of management of various application modules (microservices) of customer-facing applications, the aspect of distributed deployment of IT resources (highly programmable and configurable bare metal servers, virtual machines, and containers) is being insisted. That is, the goal of the centralized management of distributed deployment of IT resources and applications has to be fulfilled. Such kinds of monitoring, measurement, and management is required for ensuring proactive, preemptive, and prompt failure anticipation and correction of all sorts of participating and contributing constituents. In other words, accomplishing the resiliency target is given much importance with the era of distributed computing. Policy establishment and enforcement is a proven way for bringing in a few specific automations. There are programming language-specific frameworks to add additional code and configuration into application code for implementing highly available and fault-tolerant applications.

It is therefore paramount to have a programming-agnostic resiliency and fault-tolerance framework in the microservices world. Service mesh is the appropriate way forward for creating and sustaining resilient microservices. Istio, an industry-strength open source framework, provides an easy way to create this service mesh. The following diagram conveys the difference between the traditional ESB tool-based and service-oriented application integration and the lightweight and elastic microservices-based application interactions:

A service mesh is a software solution for establishing a mesh out of all kinds of participating and contributing services. This mesh software enables the setting up and sustaining of inter-service communication. The service mesh is a kind of infrastructure solution. Consider the following:

• A given microservice does not directly communicate with the other microservices.
• Instead, all service-to-service communications take place on a service mesh software solution, which is a kind of sidecar proxy. Sidecar is a famous software integration pattern.
• Service mesh provides the built-in support for some of the critical network functions such as microservice resiliency and discovery.

That is, the core and common network services are being identified, abstracted, and delivered through the service mesh solution. This enables service developers to focus on business capabilities alone. That is, business-specific features are with services, whereas all the horizontal (technical, network communication, security, enrichment, intermediation, routing, and filtering) services are being implemented in the service mesh software. For instance, today, the circuit-breaking pattern is being implemented and inscribed in the service code. Now, this pattern is being accomplished through a service mesh solution.

The service mesh software works across multiple languages. That is, services can be coded using any programming and script languages. Also, there are several text and binary data transmission protocols. Microservices, to talk to other microservices, have to interact with the service mesh for initiating service communication. This service-to-service mesh communication can happen over all the standard protocols, such as HTTP1.x/2.x, gRPC, and so on. We can write microservices using any technology, and they still work with the service mesh. The following diagram illustrates the contributions of the service mesh in making microservices resilient:

 

Finally, when resilient services get composed, we can produce reliable applications. Thus, the resiliency of all participating microservices leads to applications that are highly dependable.

Reactive systems fully comply with the reactive manifesto (resilient, responsive, elastic, and message-driven), which was contemplated and released by a group of IT product vendors. A variety of architectural design and decision principles are being formulated and firmed up for building most modernized and cognitive systems that are innately capable of fulfilling todays complicated yet sophisticated requirements. Messages are the most optimal unit of information exchange for reactive systems to function and facilitate. These messages create a kind of temporal boundary between application components. Messages enable application components to be decoupled in time (this allows for concurrency) and in space (this allows for distribution and mobility). This decoupling capability facilitates the much-needed isolation among various application services. Such a decoupling ultimately ensures the much-needed resiliency and elasticity, which are the most sought-after needs for producing reliable systems. 

Resilience is about the capability of responsiveness even under failure and is an inherent functional property of the system. Resilience is beyond fault-tolerance, which is all about graceful degradation. It is all about fully recovering from any failure. It is empowering systems to self-diagnose and self-heal. This property requires component isolation and containment of failures to avoid failures spreading to neighboring components. If errors and failure are allowed to cascade into other components, then the whole system is bound to fail.

So, the key to designing, developing, and deploying resilient and self-healing systems is to allow any type of failure to be proactively found and contained, encoded as messages, and sent to supervisor components. These can be monitored, measured, and managed from a safe distance. Here, being message-driven is the greatest enabler. Moving away from tightly coupled systems to loosely and lightly coupled systems is the way forward. With less dependency, the affected component can be singled out, and the spread of errors can be nipped in the bud.

Elasticity is about the capability of responsiveness under a load. Systems can be used by many users suddenly, or a lot of data can be pumped by hundreds of thousands of sensors and devices into the system. To tackle this unplanned rush of users and data, systems have to automatically scale up or out by adding additional resources (bare metal servers, virtual machines, and containers). The cloud environments are innately enabled to be auto-scaling based on varying resource needs. This capability makes systems to use their expensive resources in an optimized manner. When resource utilization goes up, the capital and operational costs of systems comes down sharply.

Systems need to be adaptive enough to perform auto-scaling, replication of state, and behavior, load-balancing, fail-over, and upgrades without any manual intervention, instruction, and interpretation. In short, designing, developing, and deploying reactive systems through messaging is the need of the hour.

Serverless computing allows for the building and running of applications and services without thinking about server machines, storage appliances, and arrays and networking solutions. Serverless applications don't require developers to provision, scale, and manage any IT resources to handle serverless applications. It is possible to build a serverless application for nearly any type of applications or backend services. The scalability aspect of serverless applications is being taken care of by cloud service and resource providers. Any spike in load is being closely monitored and acted upon quickly. The developer doesn't need to worry about the infrastructure portions. That is, developers just focus on the business logic and the IT capability being delegated to the cloud teams. This hugely reduced overhead empowers designers and developers to reclaim the time and energy wasted on the IT infrastructure plumping part. Developers typically can focus on other important requirements, such as resiliency and reliability.

The surging popularity of containers comes in handy when automating the relevant aspects to have scores of serverless applications. That is, a function is developed and deployed quickly without worrying about the provisioning, scheduling, configuration, monitoring, and management. Therefore, the new buzzword, FaaS, is gaining a lot of momentum these days. We are moving toward NoOps. That is, most of the cloud operations get automated through a host of technology solutions and tools, and this transition comes in handy for institutions, individuals, and innovators to deploy and deliver their software applications quickly.

On the cost front, users have to pay for the used capacity. Through the automated and dynamic provisioning of resources, the resource utilization goes up significantly. Also, the cost efficiency is fully realized and passed on to the cloud users and subscribers. 

Precisely speaking, serverless computing is another and additional abstraction toward automated computing and analytics. 

An SRE is responsible for ensuring the systems availability, performance-monitoring, and incident response of the cloud IT platforms and services. SREs must make sure that all software applications entering production environments fully comply with a set of important requirements, such as diagrams, network topology illustrations, service dependency details, monitoring and logging plans, backups, and so on. A software application may fully comply with all of the functional requirements, but there are other sources for disruption and interruption. There may be hardware degradation, networking problems, high usage of resources, or slow responses from applications, and services could happen at any time. SREs always need to be extremely sensitive and responsive. The SREs effectiveness may be measured as a function of mean time to recover (MTTR) and mean time to failure (MTTF). In other words, the availability of system functions in the midst of failures and faults has to be guaranteed. Similarly, when the system load varies sharply, the system has to have the inherent potential to do scale up and out.

Software developers typically develop the business functionality of the application and do the necessary unit tests for the functionality they created from scratch or composed out of different, distributed, and decentralized services. But they don't always focus on creating and incorporating the code for achieving scalability, availability, reliability, and so on. System administrators, on the other hand, do everything to design, build, and maintain an organization's IT infrastructure (computing, storage, networking, and security). System administrators do try to achieve these QoS attributes through infrastructure sizing and by provisioning additional infrastructural modules (bare metal (BM) servers, virtual machines (VM) servers, and containers) to authoritatively tackle any sudden rush of users and bigger payloads. As described previously, the central goal of DevOps is to build a healthy and working relationship between the operations and the development teams. Any gaps and other friction between developers and operators ought to be identified and eliminated at the earliest by SREs so as to run any application on any machine or cluster without many twists and tweaks. The most critical challenges are how to ensure NFRs/QoS attributes.

SREs solve a very basic yet important problem that administrators and DevOps professionals do not. The infrastructures resiliency and elasticity to safeguard application scalability and reliability has to be ensured. The business continuity and productivity through minute monitoring of business applications and IT services along with other delights for customers, has to be guaranteed.  The meeting of the identified NFRs through infrastructure optimization alone is neither viable nor sustainable. NFRs have to be rather realized by skillfully etching in all the relevant code snippets and segments in the application source code itself. In short, the source code for any application has to be made aware of and is capable of easily absorbing the capacity and capability of the underlying infrastructure. That is, we are destined toward the era of infrastructure-aware applications, and, on the other side, we are heading toward application-aware infrastructures.

This is where SREs pitch in. These specially empowered professionals, with all the education, experience, and expertise, are to assist both developers and system administrators to develop, deploy, and deliver highly reliable software systems via software-defined cloud environments. SREs spend half of their time with developers and the other half with operation team to ensure much-needed reliability. SREs set clear and mathematically modeled service-level agreements (SLAs) that set thresholds for the stability and reliability of software applications.

SREs have many skills:

Furthermore, SREs learn and position themselves to be a single point of contact (SPOC) in the following areas:

In the case of SREs, ensuring the stability and the highest uptime of software applications are the top priorities. However, they should have the ability to take the responsibility and code their own way out of hazards, hurdles, and hitches. They cannot add to the to-do lists of the development teams. SREs are typically software engineers with a passion for system, network, storage, and security administration. They have to have the unique strength of development and operations, and they are highly comfortable with a bevy of script languages, automation tools, and other software solutions to speedily automate the various aspects of IT operations, monitoring, and management, especially application performance management, IT infrastructure orchestration, automation, and optimization. Though automation is the key competency of SREs, SREs ought to educate themselves and gain experience to gain expertise in the following technologies and tools: