The role and responsibilities of a site reliability engineer (SRE) may vary depending on the size of the organization, and as such, so do site reliability engineer tools. For the most part, a site reliability engineer is focused on multiple tasks and projects at one time, so for most SREs, the various tools they use reflect their eve-evolving responsibilities. A typical SRE is busy automating, cleaning up code, upgrading servers, and continually monitoring dashboards for performance, etc., so they are going to see more tools in that toolbelt. For that reason, the tools and platforms that an SRE uses can vary greatly from organization to organization, especially in 2022.
For example, in smaller organizations or startups, personnel tend to be more limited, so a site reliability engineer may need to be well-versed in multiple tools, such as Golang, Terraform, Docker, CircleCI, and Puppet, just to name a few. In larger organizations, a site reliability engineer may be more focused or siloed into specific responsibilities, therefore, their toolset may be more limited. And in some cases, an SRE may just be focused or tasked with working in Jenkins day in and day out. It just depends on the situation. Let us look at some of the most common and popular site reliability engineer tools. This is obviously not a comprehensive list, but gives you a general idea of the breadth of knowledge and experience an SRE may need to utilize.
Site reliability engineers will need to have experience with various programming languages, but more importantly, need to know how to use those languages to automate any and all tasks. Let us look at some of the most common programming languages an SRE group will encounter, like Python, Golang, and Ruby.
Python is one of the most common and popular programming languages out there. It is a general-purpose language, meaning that it has a wide-range of uses, such as the backbone of websites or web applications, automating tasks, or even testing. In fact, it is used by companies like Netflix, Venmo, and Dropbox, just to name a few. Python is easy to learn, so it is good for someone just starting out, but versatile and extensive for Python experts as well. Best of all, it is open-source and has a large support community behind it.
Golang, or Go, is an open-source programming language created by Google in 2009 that is used to create software programs. Go, compared to other languages, is easy to learn, especially if you already know C or Java, and can also scale well. It also extremely fast since it is a compiled language, meaning that the code written is converted automatically into machine code immediately. Golang is also the power behind other services that SREs use, like Docker, Terraform, and Kubernetes. Compared to Python, Go is not as descriptive, so in some instances, programmers may need to write more lines of code to carry out a specific function compared to using Python.
Containerization and microservices have quickly become a crucial technology for allowing organizations to more quickly develop and release applications, as well as scaling them across different environments. Platforms like Docker, Kubernetes, and Nomad are some of the leading solutions for supporting modern applications in the ever-growing cloud native environments.
Docker is a popular open-source containerization platform that allows users to package application source code and dependency packages in a single container, or Docker container. Docker, as well as other containerization solutions, makes it possible to package and run applications in a variety of environments, without having to consider factors like operating system or other specific system configurations. Because of this flexibility, applications become more portable and can run anywhere without worrying about outside factors. Additionally, containerization technology lends itself to CI/CD, allowing developers to continuously update code and deploy applications quicker and more efficiently.
Kubernetes is an open-source container orchestration system used to assist in deploying, scaling, and managing containerized applications. Environments can be complex, consisting of multiple platforms or multiple cloud environments. Kubernetes is used to manage all of this for you. While this may seem remarkably familiar to Docker, Kubernetes is not a direct competitor to Docker, as Kubernetes can be used in addition with the Docker platform. However, Docker does have their own orchestration solution, called Docker Swarm. Kubernetes is used to manage many containers at the same time, helping to upgrade applications without interrupting service to users as well as monitor the overall health of applications. Kubernetes can also assist with load balancing, helping to ensure applications perform at scale, as well as providing support for authentication and security at the infrastructure level.
Nomad is another container orchestration platform. The key difference between Nomad and Kubernetes is that Nomad is designed for the Unix operations system. On the other hand, Kubernetes is designed for Linux container-based applications. Compared to Kubernetes, Nomad is much simpler, in terms of the number of services it relies on. Kubernetes relies on variety of other services to provide functionality. Nomad does not require or rely on any external services. Due to this, Kubernetes can be much more resource intensive, in terms of setup and configuration. Companies that are known to use or have used Nomad include Cloudflare, Pandora, Roblox, and many others.
Configuration management tools allow a site reliability engineer to manage, track, control, and most importantly, automate various tasks, such as software upgrades and patches, security, user management, and much more. These tools also help SREs to automate these various tasks at scale. Let us look at some of the most common configuration tools, like Terraform, Ansible, and Chef.
Terraform is an open-source software from HashiCorp that is considered an IaC, or Infrastructure-as-code solution. Terraform, along with Ansible, which we will talk about more next, are two of the most used tools for a site reliability engineer and DevOps teams. Terraform is used to provision, manage, and orchestrate infrastructure, no matter if that infrastructure is on-premises, in the cloud, or a combination of both, as in a hybrid environment. Using a solution like Terraform is more efficient than trying to provision and manage infrastructure, especially with multiple providers. In the past, this process would have taken an entire team of individuals. Now, developers and SREs can provision infrastructure on demand. Having a platform that can manage all of this in one place is also beneficial for consistency and collaboration.
Ansible, like Terraform, is an open-source configuration management tool. They do share a lot of similarities, and in some cases are used as complementary solutions, but there are some key differences between the two solutions. For example, Ansible’s playbook instructions are based on YAML, but is written in Python language, which provides for extensibility as well as handling a wide-range of roles and scripts. Terraform uses its own configuration language, called HCL.
If we dig deeper between the two, Ansible is more focused on mutability, which is a concept that developers are familiar with. Mutability revolves around the idea that something, in this case a resource, can be changed. To change a resource, you can modify it (mutable), or re-create completely (immutable). Ansible focuses mutability, or trying to change a resource’s state rather than destroy it, which is better for more traditional IT environments. On the other hand, Terraform is focused on immutability, which may be better for cloud, or hybrid environments.
Chef is another open-source configuration management tool that is more like Ansible or Puppet, another tool that is commonly used by SREs and DevOps teams. Chef supports multiple platforms, like Windows, Ubuntu, Solaris, Linux, FreeBSD, and more. It also can integrate with cloud-based providers, like Amazon, Google Cloud Platform, Azure, and others. However, unlike Ansible, it is based off the Ruby programming language, which makes it an easy choice for developers and teams that are comfortable with working in this language. Like the other tools we have discussed, the goal of any of these tools is to remove as much manual work as possible. Environments can become complex and even harder to manage daily, which is why a tool like Chef can be a blessing to SREs and DevOps teams.
Monitoring & Analytics
Lastly, a site reliability engineer needs the ability to monitor their applications and complete IT stack to ensure continuous functionality, performance, and availability. These monitoring and analyticcs tools need to also be able to send immediate alerts if any applications go down or these performance metrics fails to meet the predefined thresholds. SREs have a variety of monitoring solutions and tools available to them to ensure SLA (Service Level Agreements) and SLO (Service Level Objectives) are always within adequate range. Let us look at popular tools and solutions like Prometheus, Grafana, Kibana, and Dotcom-Monitor.
Like many of the tools on this list, Prometheus is another open-source software used by site reliability engineers. It is one of the most popular tools with SREs as it works well with Kubernetes and has an extensive set of features and plugins it supports. Prometheus is used to monitor and collect metrics about your infrastructure and applications and outputs that data in the form of dashboards and visualizations. One of the major differences between Prometheus and other monitoring tools is that Prometheus uses its own datastore to collect data on the metrics it can monitor. Other tools rely on a separate database to pull monitoring data and metrics; however, Prometheus can integrate with an extensive list of other databases and third-party solutions.
Grafana is an open-source analytics and monitoring tools used by SREs to visualize data and metrics at-a-glance. Grafana can also be configured with various alerts, so the correct teams or individuals can be notified immediately when issues occur. Dashboard panels can be configured with the metrics that are most important. Datas sources supported by Grafana include Prometheus, MySQL, Elasticsearch, SQL, AWS (Amazon Web Services), and many more. These dashboards can also be easily shared with other team members by creating and sending via link or even a quick snapshot. Lastly, Grafana supports a lot of the tools that SREs and their teams use daily via plugins, such as Splunk, MongoDB, Jira, Cloudflare, and many others.
Kibana is another dashboard visualization software that is popular among SREs. Kibana is a front-end application that is free to use, however, it is proprietary to Elasticsearch, and works in conjunction with the Elastic Stack (previously ELK Stack). Kibana has a plethora of features and visualization types, such as heat maps, pie charts, time series charts, etc. This data can also be viewed through geographical maps. Like other tools, these visualizations can be shared securely with team members, customers, stakeholders, etc. Kibana supports many other tools, third-party integrations, and has a strong user community for technical issues and support needs.
Dotcom-Monitor is a comprehensive monitoring platform used by organizations to monitor everything from websites, web applications, and web services to full end-to-end visibility into IT infrastructure. The platform provides site reliability engineers with the features they need to set up and customize their specific monitoring requirements. Teams can run various on-demand SLA and performance reports, as well as view real-time dashboards to ensure ongoing performance of their entire stack. Dotcom-Monitor also integrates with third-party communication platforms and alerting tools that DevOps teams are utilizing, such as Azure, Slack, PagerDuty, VictorOps, and many more.
See how Dotcom-Monitor compares to other monitoring platforms in the market, like Uptrends, Site24x7, Datadog, and others.