Chaos testing is a way to test the integrity of a system. Its purpose is to simulate failures that could crash a production system in a controlled environment. This helps to identify failures before they cause unplanned downtime that disrupts the user experience. Unlike standard testing, which tests a system response against a predefined result, chaos testing does not have a predefined result. Rather, the entire purpose of the experiment is to find out new information about the system.

Toil is a term coined by Google which describes the repetitive and tedious tasks associated with running a production service. Toil tends to be manual and devoid of any long-term value. Toil is not just ‘work I do not like to do’. Each time an engineer engages with a production system, it represents time devoted to toil. These types of tasks get worse as your service grows even more extensive. Site Reliability Engineers (SRE) should spend less time on toil.

As systems continue to become more complex, reliability is becoming an increasingly important requirement. Organizations are quickly realizing that making reliability a critical part of their service means that other organizations will be less likely to cut costs on them. As a result of this, the field of service reliability engineering (SRE) has grown rapidly over the past few years.

SLOs or Service Level Objectives are the foundation of Site Reliability Engineering (SRE). To correctly understand SLOs, the first step is to understand Service Level Indicators or SLIs. SLIs are metrics that measure the vitals of the service. These vitals are chosen based on two conditions. First, they are the features that the user is primarily concerned about. Second, they allow the engineering team to get an overview of the system’s health.

By investing in a CI/CD pipeline, it’s entirely possible to automate a large part of the software development life cycle – letting businesses deliver high-quality, high-efficiency outputs with a faster time to market. But there are multiple elements to the CI/CD process, including the all-seeing eye that is continuous validation. So what exactly is continuous validation, and why should software developers bother to engage with it?

Continuous documentation is the process of creating and maintaining code documentation incrementally throughout a project in a way that seamlessly incorporates it into the development workflow. It is a key part of improving reliability within an organization. It’s not just new features that need to be documented – anything useful from bug fixes, to how to get started using the code should be documented. It should also be updated frequently to ensure that it stays relevant.

There is a distinctive gap opening up between the top engineers and the rest. The elite engineers represent the top few percent of engineering teams and are making incredible gains year on year in velocity, reliability, and human compatibility, whilst the bottom 50% are losing ground. The loss has nothing to do with engineering ability.

OKR stands for Objectives and Key Results (OKRs). They are essential frameworks for establishing and monitoring goals and outcomes. They also facilitate discussions regarding the alignment of an employee’s job with the company’s objectives. Many companies such as Google use OKRs to improve engineering team culture and productivity. OKRs require a strong, open, and creative workplace culture to take root. OKRs offer you focus, alignment, commitment, and goal tracking.

No buzzwords were harmed in the making of this post Let’s take one of the most overloaded terms, DevOps, and mix it with the haziest of topics, security. What do you get, apart from confusion? SecDevOps. Or maybe it’s DevSecOps. If you’re not sure what either means, you’re not alone. Even the industry at large can’t decide what they should call it. And so they - we - came up with a new term altogether.

Distributed systems are responsible for many different tasks and processes that need to be monitored and managed. In this article, we will explore what you should monitor in a distributed system, including network communication, resources, and performance.