Site reliability engineering (SRE) is the practice of ensuring that a software system is available, performant, and scalable. Teams often use various SRE tools that monitor and manage the system to achieve these goals. These tools can monitor the system's performance, track errors and exceptions, automate code deployment, and more.
Some standard SRE tools include monitoring tools like Nagios and Datadog, deployment automation tools like Ansible and Puppet, and logging tools like Splunk and the ELK stack. This article will explore the types of SRE tools and how SRE teams use them in detail.
Summary of key SRE tool concepts
The table below summarizes the concepts related to SRE tools we will explore in this article.
DevOps tools vs. SRE tools
The terms DevOps and SRE are often used interchangeably. However, they are different concepts.
DevOps (a portmanteau of “development” and “operations”) is a software development and delivery approach that emphasizes collaboration between development and operations teams. One key aspect of DevOps is using tools and practices for continuous integration (CI), continuous delivery (CD), and release management.
SRE is a discipline that focuses on ensuring software systems' reliability, performance, and availability. While SRE might not own or maintain the DevOps tools, they often use them to support the platform. This article will focus on tools related to the SRE discipline.
SRE tools and use cases
SRE tools have evolved significantly in recent years to better support the goals of high availability, scalability, and reliability. The following are the areas of growth:
- Development of tools and platforms for monitoring and observability
- Automation of various SRE tasks and processes
- Tools and practices for promoting resilience and reliability
In the following sections, we discuss the different categories of modern SRE tools and use cases.
In the context of SRE, a service catalog is a central repository of information about the systems and services that are managed by an SRE team. Service catalogs can document the various components of a system or service and track the status and availability of these components.
Some of the information an SRE team’s service catalog might contain include:
- A list of systems and services supported by the SRE team and owned by development teams.
- Detailed documentation of the components and dependencies of each system or service
- Performance and availability metrics for each system or service
- Service level agreements (SLAs), service level indicators (SLIs), and service level objectives (SLOs) for each system or service
- Contact information for the team members responsible for managing each system or service
- Escalation plan for incident response
Service catalogs can be created and maintained using various tools and technologies, such as documentation platforms, service level management platforms, and configuration management tools. By using a service catalog, SRE teams can create a comprehensive and accurate record of the systems and services they manage, which can improve the reliability, availability, and performance of these systems and services.
Observability (o11y) tools are essential for SRE because they provide real-time data about the performance and availability of systems. This data is used to identify issues and potential bottlenecks and take proactive measures to prevent outages and improve the system's overall reliability.
Many monitoring tools are available, including Nagios, Icinga, Zabbix, Prometheus, and Datadog. One of the key features of monitoring tools is the ability to collect and analyze metrics from systems and applications. These metrics can include CPU utilization, memory usage, network traffic, disk I/O, and application performance.
In addition to analyzing metrics, many monitoring tools also offer alerting capabilities. This allows SREs to be notified when certain conditions are met. Some monitoring tools also offer trend analysis and visualization capabilities.
Consolidating observability tools into a single view can be challenging, as it involves integrating data from multiple sources and ensuring that the tools work together seamlessly.
Here are a few steps that can help you to consolidate observability tools and create a single view:
- Identify the essential observability tools you are currently using. The first step in consolidating observability tools is to identify the tools you currently use for logging, tracing, metrics collection, and alerting. This will give you an idea of the consolidation project's scope and the tools you will need to integrate. For example, you will need a view with both the Prometheus dashboards and Nagios alerts.
- Decide on a central platform for storing and visualizing data. To create a single view of your observability data, you will need to decide on a central platform that will be used to store and visualize the data from all of your observability tools. This could be a tool like Elastic Stack, which includes Elasticsearch, Logstash, and Kibana. It could be a custom-built platform that takes the form of a web application developed using the MERN (MongoDB, Express.js, React.js and Node.js) stack. You could also integrate tools like Prometheus, Grafana, and Jaeger into your platform.
- Configure your observability tools to send data to the central platform. Once you have decided on a central platform for storing and visualizing your observability data, you will need to configure your observability tools to send data to this platform. This may involve setting up connectors or integrations between your tools and the central platform, or it may involve modifying the configuration of your tools to send data directly to the central platform. For example, using webhooks, you could route an alert from Prometheus alert manager to both Slack and the web application developed in the previous step.
- Create dashboards and visualizations to view your data. Once you have configured your observability tools to send data to the central platform, you can create dashboards and visualizations to view and analyze your data. This will typically involve using the visualization tools provided by the central platform, such as Kibana, to create graphs, charts, and other visualizations that allow you to view your data in a meaningful way.
Log management systems allow engineering teams to collect, store, and analyze log data from their systems. Log data can include error messages, warning messages, and performance metrics.
Log management systems provide a centralized location for storing and accessing log data and can be used to identify trends and patterns in log data, as well as to troubleshoot issues and perform root cause analysis.
There are several benefits to using a log management system:
- Centralized storage: Log management systems provide a centralized location for storing and accessing log data.
- Scalability: Log management systems are designed to handle large volumes of log data and can scale to meet the needs of even the largest organizations.
- Search and analysis: Log management systems often include powerful search and analysis capabilities, allowing SREs to quickly search through and analyze log data.
- Alerting: Many log management systems include alerting capabilities, allowing SREs to set up alerts for when certain conditions are met in log data. For example, SREs may set up an alert for when a particular error message appears in log data or when the number of warning messages exceeds a certain threshold.
- Integrations: Many log management systems can be integrated with other tools, such as monitoring and incident management systems. This allows SREs to get a complete view of the health and performance of their systems and to identify and resolve issues more efficiently.
Some examples of log management systems include Splunk and ELK (Elasticsearch, Logstash, and Kibana).
Infrastructure & configuration management
Configuration management tools allow SRE teams to automate the deployment and management of their systems. These tools enable SREs to define their systems' configuration and automate the application process. This can include installing software, configuring settings, and managing dependencies. Configuration management tools can be used to ensure that systems are consistently configured and compliant with company policies and best practices.
There are several benefits to using configuration management tools:
- Consistency: Configuration management tools allow SRE teams to ensure that systems are consistently configured across their organization. This can help reduce the risk of errors and inconsistencies and make it easier for SREs to manage their systems.
- Automation: Configuration management tools allow SRE teams to automate deploying and managing their systems. This can save time, reduce the risk of errors, and allow SREs to focus on more critical tasks.
- Version control: Many configuration management tools include version control capabilities, allowing SREs to track and manage system and configuration changes. This can make it easier for SREs to collaborate on configuration changes and allow them to roll back to previous configurations if necessary.
- Compliance: Configuration management tools can ensure that systems comply with company policies and best practices. This can help to reduce the risk of security breaches and other compliance or legal issues.
Examples of configuration management tools include Ansible, Chef, and Puppet.
One of the most popular tools for infrastructure management is Terraform. Terraform is an infrastructure as code tool that lets you define cloud and on-prem resources in human-readable configuration files that you can version, reuse, and share. You can then use a consistent workflow to provision and manage your infrastructure throughout its lifecycle. Terraform can manage low-level components like compute, storage, and networking resources, as well as high-level components like DNS entries and SaaS features.
To summarize, the main objective of a configuration and infrastructure management system is to have a consistent and immutable infrastructure where all changes can be tracked. This helps in release planning and deployment.
Load testing tools allow SRE teams to understand the performance and scalability of their systems under various load volumes. These tools allow SREs to simulate high-traffic volume and measure their systems' response time and resource usage. This can help SREs identify bottlenecks and optimize the performance of their systems to handle expected levels of traffic. By performing load testing, SREs can ensure that their systems meet users' demands.
There are several benefits to using load testing tools:
- Performance optimization: Load testing tools allow SRE teams to identify bottlenecks and optimize the performance of their systems. This can help to ensure that systems can handle expected levels of traffic and can improve the user experience.
- Capacity planning: Load testing tools can help SRE teams understand their systems' capacity and plan for future growth. SREs can understand the resources required to support their systems and make informed decisions during capacity planning by simulating different traffic volumes.
- Stress testing: Load testing tools can stress test systems to identify vulnerabilities or weaknesses. This can help SRE teams improve their systems' reliability and resilience.
Examples of load testing tools include JMeter, Gatling, and LoadRunner.
Containerization tools allow SRE teams to manage the deployment and scaling of containers. Containers allow SREs to package and deploy applications and their dependencies in a portable and consistent manner. Containerization tools can be used to manage the deployment and scaling of containers, as well as to ensure that containers are consistently configured and compliant with company policies and best practices.
Some examples of containerization tools include Docker, Kubernetes, Containerd, and proprietary cloud containerization services such as AWS ECS (Elastic Container Service).
Testing tools are important for SRE teams, as they allow SREs to automate the testing of their systems and applications and identify and resolve issues. A wide range of testing tools is available, each designed to address specific testing needs. Some examples of testing tools commonly used by SRE teams include JUnit, Selenium, Pytest, and Postman.
In addition to the above tools, you could develop a custom solution to set up and strip down an ephemeral staging environment. You could create a Kubernetes deployment with all the necessary components and perform unit, functional, and end-to-end testing if you have multiple distributed software components.
Another idea for custom testing is to set up resources in a disjoint environment and send requests from this isolated environment to the UAT or testing environment. You could also use these requests routed across the platform to design an alerting system for which SREs might have a use case.
The above concept is shown in the diagram below. We set up an instance in a public cloud such as AWS. We develop an app to simulate user behavior and send requests downstream to the platform via the internet. Depending on the responses obtained back from the platform, different alerts can be configured using AWS Cloudwatch. Alerts from Cloudwatch can be integrated with the organization's central monitoring system, allowing an SRE to check the platform's health from the perspective of external users.
Incident response systems
Incident response systems are an essential part of any SRE practice, as they allow organizations to quickly and effectively respond to incidents that impact the availability, performance, or reliability of their systems.
Creating these systems requires establishing processes, tools, and people (SREs) responsible for identifying, triaging, and resolving incidents. These systems are crucial for meeting SLOs as they help properly organize and minimize MTTR (Mean Time to Repair).
One of the products that helps with this setup and integrates with other tenets of SRE is Squadcast’s Incident Response, while PagerDuty and OpsGenie offer alternative solutions.
A status page is a web-based platform that provides real-time information about the status of a company's services. It is often used to communicate the current state of a company's infrastructure, applications, and other systems to its customers and stakeholders. This page must show accurate and timely information.
Typically, support staff manually updates this page to display the system status to customers. A status page can be connected to SRE tools and health monitoring systems to automatically update when a critical component fails. Minimizing manual work as much as possible while maintaining high accuracy is imperative for maintaining the status page. Alerting systems must be accurate, and a careful selection of both private and public alerts that represent the health of the selected components of the system should be connected to the status page.
Historical trends regarding the health of these critical components should be provided so that customers can see the system's reliability. A few of the available tools for Status Page management are Squadcast, status.io, and Altassian Status Page.
A Service Level Objective (SLO) targets a service's availability and performance. It is a critical component of a Service Level Agreement (SLA), an agreement between a service provider and a customer outlining the terms and conditions of the provided service.
SLOs help organizations ensure that their services meet the needs of their customers and provide a way to measure the success of those services.
To effectively manage SLOs, organizations need tools and processes to monitor and track the performance of their services. This includes monitoring, incident management, and SLO reporting tools.
One such tool is Squadcast’s SLO tracking tool which helps with the following:
- Monitor Service Level Indicators (SLIs) like Availability, Latency, Response Times, Throughput, etc. Helps in setting custom thresholds and get notified when SLOs are breached.
- Keep Track of your SLOs in one centralized dashboard. Analyze breaches instantly with a quick snapshot of SLIs. Identify and mark ‘SLO breaching incidents’ and adjust Error Budget accordingly.
- Integrate with monitoring tools to automatically adjust Error Budget when an incident is reported. Or manually report incidents through the UI if your monitoring tool fails to catch a violation.
- Simplified Error Budget restoration; Simply mark incidents as false positives on the SLO Tracker dashboard and automatically restore valuable minutes.
In addition to Squadcast’s SLO tracking tool, a other notable mentions are Blameless and Nobl9.
A runbook is a set of procedures for operating and maintaining a system. It is a critical tool for ensuring the reliability and availability of a system, as it provides a step-by-step guide for performing tasks such as troubleshooting, incident response, and maintenance.
Runbook automation is using software to automate the execution of runbook procedures. Several tools and platforms are available for automating runbooks, including Rundeck and StackStorm.
The need for CI/CD tools arises from the increasing complexity of modern software development. As software applications become more complex, with larger codebases and multiple contributors, the risk of bugs and conflicts increases. Manual testing and deployment can be time-consuming and error-prone, leading to delays and potential errors in production.
CI/CD tools help to solve these problems by automating the process of building, testing, and deploying code changes. By integrating code changes frequently and automatically testing them, developers can catch errors early, reducing the risk of bugs and conflicts. By automating deployment, developers can ensure that code changes are deployed consistently and reliably, reducing the risk of errors in production.
How do CI/CD tools work?
CI/CD tools typically involve several components, including:
- Source control management: a system for managing code changes and version control, such as Git or Subversion
- Build automation: a tool for automatically building the code changes, such as Jenkins, Travis CI, or CircleCI
- Test automation: a tool for automatically testing the code changes, such as Selenium, JUnit, pytest
- Deployment automation: a tool for automatically deploying the code changes, such as Ansible or Puppet
In a typical CI/CD workflow, developers make changes to the codebase and push them to the source control management system. The CI/CD tool then detects the changes and automatically triggers a build, which compiles the code and generates an executable package or a binary package depending on your configuration. The tool then runs automated tests on the package to ensure that the changes have not introduced any bugs or conflicts.
If the tests pass, the tool then deploys the package to a staging environment for further testing and validation. Once the changes have been validated, the tool can automatically deploy the package to production, making the changes available to users.
The discipline of SRE focuses on ensuring software systems' reliability, performance, and availability. While site reliability engineering isn’t solely about tools, the right SRE tools can vastly improve observability, uptime, and performance.
With the information we have reviewed in this article, you can identify which SRE tools will best help you address business objectives and maintain highly-available systems.