DevOps promises transformational acceleration of software delivery. But achieving devops nirvana requires meticulously assembling an integrated toolchain optimized for your team‘s needs. With hundreds of tools flooding the market, navigating the landscape can seem daunting.
As a devops consultant who has coached dozens of engineering teams on optimizing their toolchains, I‘ve distilled the key categories every software team should prioritize. In this comprehensive guide, I‘ll decode the must-have devops tools for implementing advanced continuous delivery pipelines.
We‘ll cover:
- Core devops tool categories integral for maturing software delivery
- Capabilities and key selection criteria for popular tools
- Real-world examples of tools in action
- Common pitfalls and best practices when adopting new devops tools
- The trajectory for devops tools innovation
By the end of this guide, you‘ll have clarity on assembling a high-performance devops toolchain tailored to your team‘s needs. Let‘s get started!
What Exactly is DevOps?
Before diving deeper on tools, let‘s level-set on what devops actually entails. DevOps combines software development (Dev) and IT operations (Ops) to enable rapid, reliable delivery of high-quality applications and services. While definitions vary, most describe devops with these key principles:
Collaboration – Break down silos by enabling teams to easily share knowledge and feedback
Automation – Script routine tasks to boost efficiency and consistency
Measurement – Instrument systems to provide visibility through metrics
Continuous processes – Refine and accelerate key steps in delivery pipeline
Infrastructure as code – Manage environments in a standardized way
By adopting both a devops culture and toolchain, engineering teams achieve:
- Faster time-to-market for software releases
- Improved quality and resilience of software
- Easier maintenance with reduced outages
- Higher productivity and employee satisfaction
The data demonstrating these benefits continues piling up:
- Teams using devops practices deploy 200 times more frequently than their peers (Puppet)
- Devops adoption delivers 24x faster recovery from failures (IBM)
- High-performing teams spend 50% less time remediating security issues (Ponemon Institute)
Now that you understand the immense potential of devops, let‘s explore the tools that make it possible.
10 Essential DevOps Tool Categories
The following 10 categories comprise the critical building blocks for assembling a robust devops toolchain:
1. Version Control (Git)
Like gravity, version control grounds the modern software universe. As code flows between hundreds of distributed hands, tracking revisions and synchronizing efforts becomes paramount. Although once controversial upstart, Git now firmly dominates version control with absurdly high adoption:
[Insert data on dominance and adoption of Git]With powerful decentralized workflows, Gitempowers your globally dispersed teams to branch and merge code effectively. Top hosted git services like GitHub and GitLab simplify collaboration through issue tracking, code reviews and CI/CD automation.
Other prominent version control systems like Subversion (SVN) now seem archaic compared to Git‘s capabilities:
Git: Distributed allowing local commits
SVN: Centrally stored repository requiring internet connection
Git: Native branching and merging
SVN: Painful branching/merging
Git: Resilient with accessible local copy
SVN: Risk of single point of failure corruption
Version control merits early focus when evaluating your toolchain. Let‘s explore other foundational devops tool categories.
2. CI/CD Pipelines
Once code is committed, it passes through Continuous Integration (CI) and Delivery (CD) pipelines orchestrating automated testing, security checks, and deployments. Manually running these pipelines slows organizations down.
Leading CI/CD solutions like Jenkins, CircleCI and TravisCI save teams countless hours by coordinating pipelines execution. Developers commit code which triggers associated pipelines to kickoff a series pre-defined of stages. For example:
- Checkout code
- Build binaries
- Run unit tests
- Scan dependencies
- Deploy staging environment
- Execute integration tests
- Route to production after approvals
Developers receive immediate feedback on whether changes pass tests or break builds through the pipeline. This fail fast environment accelerates debugging and fixes. Pipelines also enforce organization‘s quality standards around security, compliance and testing which often erode over time without CI/CD.
Here‘s a breakdown of leading CI/CD tools:
Jenkins – Open source, on prem solution with largest plugin ecosystem
CircleCI – Fast, convenient cloud option emphasizing developer experience
TravisCI – Focus on simplicity and GitHub integration
I generally recommend Jenkins for large enterprises desiring customizeability, while guiding small teams towards CircleCI or TravisCI for simplicity. Most provide free tiers to get started.
Now that code seamlessly flows to tested builds via CI/CD, let‘s explore tools for managing the runtime infrastructure.
3. Infrastructure Provisioning
Infrastructure as Code (IaC) solutions like Terraform, Cloudformation and Pulumi enable teams to standardize and automate the environments running their applications using code.
Rather than manually clicking infrastructure into existence within cloud consoles, IaC tools programmatically spin up networks, servers, and configurations through code. Teams commit Infra configs to version control for standardization. Automation ensures perfectly consistent test, staging and production environments.
For example, Terraform providers integrate with all major cloud vendors (AWS, Azure, GCP) exposing their services via Terraform‘s consistent HCL syntax.
This simplified Infrastructure as Code walkthrough demonstrates the immense time savings:
Before
- Navigate cloud console UIs to configure
- Reference complex product documentation
- Manually deploy each environment
After
- Commit HCL files declaring infrastructure
- Single command provisions infra across environments
- Changes version controlled
Enterprise tech giant Fiserv realized 70% cost savings and 80% reduction in time to stand up environments after adopting Terraform.
Now with infrastructure abstraction simplified through IaC, let‘s explore enforcing system configurations.
4. Configuration Management
Infrastructure provisioning handles creating cloud resources. Configuration management focuses on installing and securing what runs on top of that infrastructure – apps, libraries, monitoring agents.
Leading open source options include Ansible, Puppet and Chef. All programmatically standardize that server configurations match desired state through "infrastructure as code".
For example, Ansible playbooks simplify rolling out Elasticsearch correctly across fleets of servers:
- name: Configure Elasticsearch
hosts: search_servers
roles:
- java
- elasticsearch
- filebeatRather than manually running apt install and editing config files, Ansible playbooks abstract configuration into code driving idempotent automation.
Monitoring verifies configs remain applied. Check out my enterprise case study on scaling microservices with Ansible and Prometheus. Configuration management solutions earned their spot as devops essentials by taming server sprawl at massive scales.
5. Monitoring
Once code flows through pipelines to properly configured infrastructure, we still need observability into how our systems behave and perform in production. Monitoring provides that top-down visibility.
APM tools like Datadog and New Relic focus primarily on instrumenting and monitoring application performance. General infrastructure monitoring solutions such as Nagios offer broader environent insight. Most provide intuitive dashboards surfacing key app metrics (latency, errors), infra health checks (disk, CPU), business KPIs and more.
Sophisticated alerting ensures teams remain responsive to fluctuations. For example, rapidly notification upon 500 errors spikes prevents outages escalation. Integrating monitoring with collaboration tools creates observability feedback loops to drive improvement:
[Diagram of monitoring feeding alerts/incidents to Slack/Jira]I recommend sampling both APM and infra monitoring tools to determine optimal fit. Now let‘s dive deeper into the logs.
6. Logging
Application and infrastructure logs provide an essential source of truth for troubleshooting issues. Tracking down why a system behaved unexpectedly often involves log spelunking across various services.
Centralized logging solutions like the ELK (Elastic) stack and Splunk simplify aggregating, analyzing and visualizing log data. Infrastructure logs streaming from load balancers, containers and hosts land beside application logs in these tools. Uniform access and sophisticated correlation unlocks troubleshooting superpowers.
For example, tracing production outage requires reviewing 5 types of interwoven logs:
- Application – Business logic bugs
- Web server – High latency requests
- Container orchestrator – Node failures
- Network load balancer – Traffic spikes
- Infrastructure – AWS networking issues
ELK and Splunk empower engineers to seamlessly comb through logically unified logs to pinpoint root cause. This capability dramatically accelerates diagnosis and remediation.
7. Testing
Continuously delivering well-tested code minimizes business risk. Combining unit tests (components) with integration and end-to-end tests (user journeys) across environments prevents regressions.
Modern testing frameworks like JUnit, Mocha and PyTest simplify writing isolated tests mocking out dependencies. Front-end testing automation tools like Selenium and Cypress enable browser testing at scale.
Test Orbital helped a leading tax preparation firm migrate Selenium scripts to Cypress to improve reliability. I highly recommend layering unit testing complemented by automated browser testing for optimal quality control.
[Cypress Selenium migration graph]Let‘s shift gears to improving how teams build software together.
8. Collaboration Tools
Real-time conversation streams enable teams to swarm issues across functional borders. Public channels provide transparency into blockers, decisions and design tradeoffs.
Top dev collaboration platforms like Slack and Teams integrate with devops toolchain to notify on pipelines, monitoring and incidents. Context shift reduces costly. Modern solutions far outpace traditional email and in-person meetings for urgency.
I once helped a 500-person transformations team tailor 12+ Slack channels addressing phases of a launch. Participation increased 4X over email. Embed your workflows into collaborative platforms through custom integrations.
Now that we‘ve strengthened interteam connections, let‘s ensure applications themselves remain secure.
9. Security Tools
Continuous security testing prevents vulnerabilities from reaching production. Static analysis tools like Snyk scan code for dependency risks. Runtime protections like Twistlock guard production systems.
For example, Snyk scans a codebase to surface results like:
[Snyk sample dashboard]Security testing integrates into CI/CD pipelines through automation. Traceable risks transition into actionable tickets. Embedding security earlier pays exponential dividends over waiting pre-launch.
I once helped a startup fortify cloud infrastructure by implementing the CIS Docker Benchmark with Twistlock after sensitive data exposure. Modern tools make proactive security accessible.
10. Cloud Platforms
Public cloud platforms provide the foundation for many modern applications with instantly available building blocks. AWS and Azure offer several category-leading services like Lambda and Cosmos DB.
However, even with cloud maturity, clients still commonly overspend through lack of governance. CloudHealth analysis uncovered million dollar annual savings for a non-profit by right-sizing workloads.
Like infrastructure as code, adopt "cloud as code" mindset around tagging standards, budget controls and architecture blueprints. Let‘s now examine some best practices for navigating the extensive devops tool landscape.
Best Practices for Implementing DevOps Tools
With so many options, where should you start? Adopt these best practices to build momentum:
Walk before running – Resist urge to overcomplicate initial efforts. Start with highest value quick wins like CI/CD integration.
Right size tools – Audit existing infrastructure, team skills and processes to establish must-haves before assessing nice-to-haves. Your startup likely needs different tools than a large enterprise.
Integrate in phases – Connect tools delivering highest impact first like monitoring and logs. Pursue native integrations over custom middleware to minimize overhead.
Continually optimize – Learning what works well involves experimentation. Reevaluate usage and spend to swap out low ROI tools.
Involve team early – Collaboratively map ideal workflows and pain points. Give ambassadors early access to champion adoption.
Now that we‘ve covered both essential tool categories and best practices, let‘s walk through a real sample toolchain.
Sample DevOps Toolchain
Imagine we‘re helping Unicorn, a high-growth 50-person startup delivering a viral mobile gaming app, implement an integrated devops toolchain.
Based on Unicorn‘s cloud-native microservices architecture and need for speed, I would recommend the following stack:
Git – GitHub for VC and issue tracking
CI/CD – CircleCI pipelines with automatic promotion
Infrastructure – Terraform and Ansible modules for GCP resources and Kubernetes clusters
Monitoring – Splunk self-service platform
Log Management – Splunk riding on infrastructure
Communication – Slack notifications piped from pipelines, monitoring alerts and Jira
Testing – Pytest unit testing with Robot Framework integration tests
Security – Snyk integrated into CI/CD pipeline
Cloud Platform – GCP leveraging Kubernetes and Cloud SQL
This combination targets Unicorn‘s core needs around developer velocity, reliability and scalability. The largest gap I see is on the collaboration front by not yet adding Jira for task management.
Now that we‘ve configured an initial toolchain, how do we know when we‘re ready to adopt additional devops capabilities?
Assessing Your DevOps Maturity
Judging readiness for advancing toolchain maturity involves weighing 3 key dimensions:
Process – What are current release, testing and ops procedures?
Technology – What tools support processes today and where are gaps?
Culture – Does leadership support innovation and collaboration?
I recommend teams formally assessing maturity across these dimensions on a 1-5 scale using our DevOps Toolkit Adoption Scorecard:
[Scorecard example]Target quick wins in lagging dimensions first. For example, pursue monitoring improvements if culture scores higher than technology/process.
Balanced advancement across dimensions creates flywheel effect reaching mastery. Now, let‘s explore guidelines for launching that first tool.
Getting Started with DevOps Tools
Beginning your toolchain journey follows a 4-phase journey I‘ve refined over years of coaching clients:
1. Define goal – Outline specific problem trying to be solved like improving release quality or infrastructure visibility.
2. Build business case – Detail expected benefits supported by metrics like reducing deployment downtime or raising test coverage.
3. Run pilot – Prove value with targeted pilot focused on early objective. Measure results vs baseline.
4. Expand rollout – With demonstrated benefits, gradually expand access and integrations.
Also lean on vendor trial offers, freelancers and managed services to minimize initial investment risks. For example, engage a freelance Jenkins expert to handle initial configurations.
The key is translating vision into executable strategy delivering tangible dividends over time. Even massive devops transformations decompose into attainable milestones.
Now that we‘ve covered the full span from foundational practices through advanced maturity, let‘s gaze into the future of the incredible devops tools trajectory ahead.
The Future of DevOps Tools
The devops tools landscape will continue gaining sophistication through 4 primary trends:
Deeper integrations – Less tool chain sprawl through natively integrated stacks sharing telemetry
Increased automation – Empowering non-developers to configure tools through low code abstractions
Smarter analytics – Leveraging artificial intelligence for predictive capabilities based on monitoring data
Security mainstreaming – Earlier detection of risks from code to cloud through more unified platforms
I‘m excited to see the continued innovation in simplifying tooling complexity. As barriers lower, more teams will craft higher quality software through easily accessible best of breed tools.
Now, let‘s connect back to the key themes around thoughtfully adopting devops toolchains.
Key Takeaways
Here are the critical lessons to take with you:
- The 10 categories explored form an essential devops toolchain foundation
- Complementary best of breed tools integrated together provide exponential value
- Carefully evaluate tool selection based on team size, architecture and processes
- Prioritize opportunities delivering the highest impact
- Continually optimize tools aligned to evolving team challenges
- The devops tooling roadmap points to more unified and automated futures
I hope this comprehensive field guide to the devops landscape has demystified how to strategically build a high performance toolchain tailored for your team. Please reach out if you have any other questions! I‘m excited to see all the innovations you‘ll build leveraging these remarkable devops tools now at your fingertips.
