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Below you'll find a list of all posts that have been tagged as "SRE"
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AIOps and the Future of SRE 2022: How Modernized DevOps Automation Services Lead The Way for Site Reliability

Right from its early days Site Reliability Engineering has been inseparable from DevOps automation services for automating IT operations tasks like production system management, change management, incident response, and even emergency response. Still, even the most experienced SRE teams have issues, particularly with the massive amounts of data generated by hybrid cloud and cloud-native technologies. This problem extends itself to DevOps performance because the challenge is to increase the stability, dependability, and availability of SRE models in real-time across different systems. This means that if the SRE-ship is sinking, the DevOps is coming along too. Unless there is something about DevOps that can change the waters altogether. SRE teams are looking toward more intelligent IT operations to assist them to solve the issues mentioned above. A possible candidate for this purpose can be AIOps. AI-based specialized DevOps can aid SRE with intelligent incident management and resolution. AI and machine learning (ML) have emerged to allow teams to focus on high-value work and innovation by reducing the manual work associated with the demanding SRE function. AIOps automates IT operations activities such as event correlation, anomaly detection, and causality determination by combining big data and machine learning. So it would be interesting to look at the possibility of AIOps and SRE coming together for a better DevOps performance. A Quick AIOps Overview Though the advances in AIOps constitute a separate discussion of their own. We, too, have talked about the role of AI in modern DevOps machinery. But for the sake of our existing discussion, we will focus on three crucial aspects of AIOps. Increased Service Levels: AIOps can improve service levels with the help of predictive insights and comprehensive orchestration. Teams can enhance the user experience by reducing the time spent evaluating and resolving issues. Boost In Operational Efficiency: Because manual activities are removed, procedures are optimized, and cooperation across the SDLC cycle is improved, operational efficiency gets a major push in AI-based DevOps Improved Scalability and Agility: By using AIOps to set up automation and visualization, you may gain insights into how to increase the scalability of your software and your SDLC team. It will also improve the agility and speed of your DevOps initiatives as a result. So how do these benefits work in favor of SRE Modernization? Automation is the most valuable aspect of AIOps. SRE can provide continuous and comprehensive service because of automation. It shortens the lifetime by reducing the number of stages in processes. Therefore, it is the automation part where SRE and AIOps can find their common grounds and help the DevOps save time and focus on more critical responsibilities. The Need for AIOps for SRE According to SRE, IT teams should always keep a check on IT outages, and crises are proactively resolved before they have an impact on the user. Even the most experienced SRE teams have issues; teams are accountable for dynamic and complex applications, often across multiple cloud environments. While executing these activities in real-time, SRE confronts obstacles such as lack of visibility and technological fragmentation. This is where AIOps fits into the puzzle. AIOps make proactive monitoring and issue management possible. If AIOps tools can warn SREs of developing concerns before they become actual incidents, AIOps can assist SREs in getting ahead of issues before they become real incidents. That benefits both SREs and end-users. There is also a case that AIOps may assist SREs in getting more done with less technical staff. You can keep the same levels of availability and performance with fewer human engineers on hand if you can utilize AI to automate some elements of monitoring and problem response. Understanding the Working of AIOps and SRE Many SRE teams have already begun using AI skills to find and analyze trends in data, remove noise, and derive valuable insights from current and historical data. As AIOps moves into the area of SRE, it has made issue management and resolution faster and more automated. SRE teams can now devote their attention to strategic projects and focus on delivering high value to consumers. Analyze Datasets Topology Analytics is used by AIOps to collect and correlate information. In general, underlying causes are difficult to locate. AIOps automatically detects and resolves the fundamental causes of problems. In comparison to this technique, manual identifying and correcting is inefficient. Delivery Chain Visibility The supply chain is visible, so teams can see what they’re doing and what they need to accomplish. AIOps depicts two aspects of an organization. The user experience is the first. SRE can improve the end-user experience by leveraging AIOps’ automation and predictive analytics. The network and application performance is the second factor to consider. Network and application performance is improved by eliminating manual chores, boosting cooperation, and automating processes. Categorized and Minimized Noises The goal of SRE is to increase user engagement with the app. The typical monitoring method is inefficient and prone to false alarms. Machine learning is used by AIOps to detect and prioritize alarms. AIOps auto-fixes issues in some circumstances. As a result, SRE teams may concentrate on tackling just the most significant issues. Conclusion: The SRE benefits from AIOps because it integrates autonomous diagnostics and metric-driven continuous improvement for development and operations throughout the SDLC. AIOps boost service levels and enhance teams’ efficiency, scalability, and agility. Continuous improvement builds confidence in SRE members. Adopting SRE and AIOps together allows organizations to achieve their goals smoothly. As a result, there are more chances and time to focus on excellent people and innovative projects that provide more value to users.

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Site Reliability Engineering (SRE) 101 with DevOps vs SRE

Consider the scenario belowAn Independent Software Provider (ISV) developed a financial application for a global investment firm that serves global conglomerates, leading central banks, asset managers, broking firms, and governmental bodies. The development strategy for the application encompassed a thought through DevOps plan with cutting-edge agile tools. This has ensured zero downtime deployment at maximum productivity. The app now handles financial transactions in real-time at an enormous scale, while safeguarding sensitive customer data and facilitating uninterrupted workflow. One unfortunate day, the application crashed, and this investment firm suffered a severe backlash (monetarily and morally) from its customers.Here is the backstory – application’s workflow exchange had crossed its transactional threshold limit, and lack of responsive remedial action crippled the infrastructure. The intelligent automation brought forth by DevOps was confined mainly to the development and deployment environment. The IT operations, thus, remained susceptible to challenges.Decoupling DevOps and RunOps – The Genesis of Site Reliability Engineering (SRE)A decade or two ago, companies operated with a legacy IT mindset. IT operations consisted mostly of administrative jobs without automation. This was the time when the code writing, application testing, and deploying was done manually. Somewhere around 2008-2010, automation started getting prominence. Now Dev and Ops worked concurrently towards continuous integration and continuous deployment – backed by the agile software movement. The production team was mainly in charge of the runtime environment. However, they lacked skillsets to manage IT operations, which resulted in application instability, as depicted in the scenario above.Thus, DevOps and RunOps were decoupled, paving the way for SRE – a preventive technique to infuse stability in the IT operations.“Site Reliability Engineering is the practice and a cultural shift towards creating a robust IT operation process that would instill stability, high performance, and scalability to the production environment.”Software-First Approach: Brain Stem of SRE“SRE is what happens when you ask a software engineer to design an operations team,” Benjamin Treynor Sloss, Google. This means an SRE function is run by IT operational specialists who code. These specialist engineers implement a software-first approach to automate IT operations and preempt failures. They apply cutting edge software practices to integrated Dev and Ops on a single platform, and execute test codes across the continuous environment. Therefore, they carry advanced software skills, including DNS Configuration, remediating server, network, and infrastructure problems, and fixing application glitches.The software approach codifies every aspect of IT operations to build resiliency within infrastructure and applications. Thus, changes are managed via version control tools and checked for issues leveraging test frameworks, while following the principle of observability.The Principle of Error BudgetSRE engineers verify the code quality of changes in the application by asking the development team to produce evidence via automated test results. SRE managers can fix Service Level Objectives (SLOs) to gauge the performance of changes in the application. They should set a threshold for permissible minimum application downtime, also known as Error Budget. If a downtime during any changes in the application is within the scale of the Error Budget, then SRE teams can approve it. If not, then the changes should be rolled back for improvements to fall within the Error Budget formula.Error Budgets tend to bring balance between SRE and application development by mitigating risks. An Error Budget is unaffected until the system availability will fall within the SLO. The Error Budget can always be adjusted by managing the SLOs or enhancing the IT operability. The ultimate goal remains application reliability and scalability.Calculating Error BudgetA simple formula to calculate Error Budget is (System Availability Percentage) minus (SLO Benchmark Percentage). Please refer to the System Availability Calculator below.Illustration.Suppose the system availability is 95%. And, your SLO threshold is 80%.Error Budget: 95%-80%= 15%AvailabilitySLA/SLO TargetError BudgetError Budget per Month (30 days)Error Budget per Quarter (90 days)95%80%15%108 hours324 hoursError Budget/month: 108 hours. (At 5% downtime, per day downtime hours is 1.2 hours. Therefore for 15% it is 1.2*3 = 3.6. So for 30 days it will be 30*3.6 = 108 hours)Error Budget/quarter: 108*3 = 324 hours.Quick Trivia – Breaking monolithic applications lets us derive SLOs at a granular level.Cultural Shift: A Right Step towards Reliability and ScalabilityPopular SRE engagement models such as Kitchen Sink, a.k.a. “Everything SRE” – a dedicated SRE team, Infrastructure – a backend managed services or Embedded – tagging SRE engineer with developer/s, require additional hiring. These models tend to build dedicated teams that lead to a ‘Silo’ SRE environment. The problem with the Silo environment is that it promotes a hands-off approach, which results in a lack of standardization and co-ordination between teams. So, a sensible approach is shelving off a project-oriented mindset and allowing SRE to grow organically within the whole organization. It starts by apprising the teams of customer principles and instilling a data-driven method for ensuring application reliability and scalability.Organizations must identify a change agent who would create and promote a culture of maximum system availability. He / She can champion this change by practicing the principle of observability, where monitoring is a subset. Observability essentially requires engineering teams to be vigilant of common and complex problems hindering the attendance of reliability and scalability in the application. See the principles of observability below.The principle of observability follows a cyclical approach, which ensures maximum application uptime.Step Zero – Unlocking Potential of Pyramid of ObservabilityStep zero is making employees aware of end-to-end product detail – technical and functional. Until an operational specialist knows what to observe, the subsequent steps in the pyramid of observability remain futile.Also, remember that this culture shift isn’t achievable overnight – it will be successful when practiced sincerely over a few months.DevOps vs. SREPeople often confuse SRE with DevOps. DevOps and SRE are complementary practices to drive quality in the software development process and maintain application stability.Let’s analyze four key the fundamental difference between DevOps and SRE.ParameterDevOpsSREMonitoring vs. RemediationDevOps typically deals with the pre-failure situation. It ensures conditions that do not lead to system downtime.SRE deals with the post-failure situation. It needs to have a postmortem for root cause analysis. The main aim is to ensure maximum uptime and weed out failures for long term reliability.Role in Software Development Life Cycle (SDCL)DevOps is primarily concerned with the efficient development and effective delivery of software products. It must ensure Zero Down Time Deployment (ZDD). It also requires to identify blind spots within infrastructure and application.SRE is managing IT operations efficiently once the application is deployed. It must ensure maximum application uptime and stability within the production environment.Speed and Cost of Incremental ChangeDevOps is all about rolling out new updates/features, faster release cycle, quicker deployment and continuous integration, and continuous development. The cost of achieving all this isn’t of significance.SRE is all about instilling resilience and robustness in the new updates/features. However, it expects small changes at frequent intervals. This gives a larger room to measure those changes and adopt corrective measures in case of a possible failure. The bottom line is efficient testing and remediation to bring down the cost of failure.Key MeasurementsDevOps’ measurement plan revolves around CI/CD. It tends to measure process improvements and workflow productivity to maintain a quality feedback loop.SRE regulates IT operations with some specific parameters like Service Level Indicators (SLIs) and Service Level Objectives (SLOs).Conclusion – SRE Teams as Value CenterA software product is expected to deliver uninterrupted services. The ideal and optimal condition is maximum uptime with 24/7 service availability. This requires unmatched reliability and ultra-scalability.Therefore, the right mindset will be to treat SRE teams as a value center, which carries a combination of customer-facing skills and sharp technical acumen. Lastly, for SRE to be successful, it is necessary to create SLI driven SLOs, augment capabilities around cloud infrastructure, a smooth inter-team co-ordination, and thrust Automation and AI within IT operations.

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