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The DevOps software market is full of options. CI/CD platforms, container orchestration tools, monitoring solutions, infrastructure automation—the choices seem endless.
You could easily spend months trying to compare every single tool, checking out features and getting lost in vendor demos.
That’s why we’ve put together our go-to set of tools, based on years of working on real projects. These are the solutions we’ve seen work time and time again for our clients.
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Request demoInfrastructure as Code (IaC)
Managing infrastructure manually is kind of like building a house without blueprints. It works fine until something goes wrong. Then you’re left guessing what caused the issue and where it happened. IaC tools address this problem by making everything clear, repeatable, and easy to manage with version control.
We mainly use Terraform. It lets you define your infrastructure using configuration files so you don’t have to click through web consoles. Whether you need to scale up or troubleshoot, you can see what’s deployed and what will change before you make any adjustments.
Terraform’s alternative is Pulumi. We turn to it when we describe projects with more complex needs or those that require much custom logic, as Pulumi brings more flexibility to the table.
Overall, we use the tool that best fits each project’s goals, but most of the time, though, Terraform’s reliability and versatility make it our go-to choice.
Cloud-Native Services
Some teams still choose the self-managed route. They run their own servers and handle all the maintenance themselves. It all sounds logical—if you take care of the infrastructure yourself, it should be more cost-effective.
Yet, what often gets overlooked is that the real costs aren’t just the server bills. It’s all the hours spent on setup, late nights fixing issues yourself, and manually applying security patches. Not to mention the hidden cost of downtime.
Cloud providers, like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure Cloud, have already thought through these problems and now offer their native tools for almost every DevOps task imaginable. Database management, container orchestration, monitoring, security, networking—you name it, they’ve built it.
Cloud providers designed these tools taking into account all the tricky edge cases you might not even know about yet and stress-tested their systems under huge workloads so you don’t have to.
We’ll walk through specific examples of these handy cloud-native tools in each category below.
Container Orchestration
Kubernetes doesn’t need an introduction. It’s the leader in container orchestration, and honestly, nothing else matches what it can do at scale.
Of course, AWS has its own service called ECS (Elastic Container Service). It handles some similar tasks and works great with other Amazon tools.
There’s also Docker Swarm, which is somewhat similar, too, but, again, like ECS, it doesn’t have the same level of management power as Kubernetes.
Kubernetes, in contrast, offers detailed control over every part of your containerized apps. Features like auto-scaling, rolling updates, service discovery, and load balancing are built in.
Yet, this advantage comes with a learning curve. Kubernetes isn’t the easiest to master, but once your team understands it, you’ll gain abilities that simpler tools can’t provide. So, if your project calls for features and flexibility, Kubernetes is in a league of its own.
When it comes to Kubernetes resource management, our team relies on Helm, a package manager for Kubernetes apps. We use it to set up monitoring, deploy complex apps, and keep configurations consistent across different environments. Helm charts help make deployments repeatable and cut down on configuration errors.
And kubectl is how we actually interact with Kubernetes clusters. Every command, update, or troubleshooting step runs through kubectl. It’s the main way we control and manage Kubernetes from the command line.
Databases
Databases are the backbone of your apps’ excellent performance. They store your user data, handle transactions, manage sessions, and more. Without a solid database setup, nothing else matters.
We usually rely on MySQL and PostgreSQL for relational data. MySQL is great for busy sites with lots of traffic, while PostgreSQL offers advanced features for more complex queries or when you need to keep your data extra accurate. Both are trusted by millions of users in real-world scenarios.
RabbitMQ plays a different role, but it’s still about managing data. It’s mainly used for message queuing and letting different parts of your system communicate with each other. If your app must process tasks in the background or coordinate between multiple services, then RabbitMQ should be your choice.
Running these databases on your own means you have to handle backups, security updates, and scaling issues, and monitor performance. That’s where mentioned above native cloud services come in handy.
Amazon RDS handles all the database maintenance work for you: backups run automatically, security patches get applied, and scaling happens when needed. Your team essentially gets MySQL or PostgreSQL without having to manage any of the behind-the-scenes tasks.
We also frequently use ElastiCache to speed up applications by caching frequently accessed data in memory. As a result, your main database isn’t hit by every single request since ElastiCache serves data lightning-fast.
DynamoDB is ideal for NoSQL workloads that need to be lightning-fast. If your app has huge traffic spikes or unpredictable usage patterns, DynamoDB scales automatically and charges you based on what you actually use.
CI/CD Automation
Since we personalize our CI/CD tools to align with each client’s specific infrastructure and team setup, the best choice depends on where their code is stored and what they’re deploying to.
If clients already use GitHub for their repositories, then GitHub Actions is a great fit, as it integrates smoothly and can handle most deployment tasks.
The same goes for teams using GitLab, where GitLab CI/CD covers automated testing, basic security checks, and simple deployments and has solid community support.
For clients heavily relying on AWS, we use tools like CodeBuild and CodeDeploy to help make the deployment process easier. Since they work with ECS or other AWS services, this saves a lot of time when it comes to integration.
Jenkins becomes useful when simpler tools aren’t enough. If you need to connect with external services via APIs, automate complex manual steps, or handle special deployment scenarios like clearing caches beforehand, Jenkins makes all that happen.
Of course, there’s a tradeoff: Jenkins needs its own server and more setup time, but it can do things that other tools may not be able to handle, or they can, but not in such a convenient way.
Monitoring
Monitoring tools are often split into two main camps. Both options can help you work with metrics, logs, and visualization, and both can send alerts. Basically, they address the same core needs, just in different ways.
So, on one side, we have Prometheus, Grafana, and Loki. They’re easier to deploy and manage, and they cover most monitoring tasks. However, Prometheus, Grafana, and Loki don’t handle heavy log parsing and processing
On the other side, there’s the Elasticsearch, Kibana & Logstash (ELK) stack, which is more powerful, as it offers deeper real-time log analysis, but it also has a steeper learning curve and, thus, is more complex to configure. But luckily, there’s a big community to assist you with core issues.
We also use Uptime Robot, a platform that checks if your website is actually up and running. It’s simple but effective, as it gives you clear uptime percentages and easy-to-read SLO/SLA metrics. You can monitor your main site or go deeper into individual services. DataDog offers similar features, but Uptime Robot tends to be simpler and has a more user-friendly interface.
When it comes to managing incidents, our team relies on PagerDuty. It creates alert workflows that escalate issues if they aren’t addressed quickly. For instance, the primary DevOps team gets notified first, and if they don’t respond, the alert moves up the chain.
Security
Security is made up of various layers working together to protect you from threats. The first line of defense, however, is often a web application firewall (WAF). It must be located between your website and the internet, screening incoming requests so that malicious traffic doesn’t reach your servers. Such tools help block common hacking methods like SQL injections and suspicious request patterns.
Cloudflare is a popular option that offers strong firewall features along with other security services. They handle DDoS attacks, bot filtering, and blocking malicious scripts.
Overall, most domain registrars and hosting providers come with security measures. It’s just necessary to figure out the right combination of protections that suits each client’s specific setup.
So, we don’t have favorites here, as the choice is broad, and we mainly implement the solution, depending on our clients’ needs. If a client already uses Cloudflare for their domain and doesn’t want to switch to Amazon, we work with their existing cloud firewall tools. On the other hand, if moving to AWS makes more sense for their overall system, that’s the route we’ll go.
Secret Management
Using hardcoded passwords in your code is a risky decision that can lead to serious security issues. That’s where secret management tools come in—they secure your sensitive data and make sure it’s only delivered to your applications when needed.
One of the solutions our team prefers is AWS Secrets Manager. It’s a cloud-based service that keeps your API keys, database passwords, and other secrets encrypted both when stored and during transfer. It also allows you to easily rotate secrets, thanks to its versioning feature. Plus, AWS Secrets Manager has protections to prevent accidental deletion of important credentials.
Yet, storing secrets is just part of the story. Getting them safely to your applications also matters. For this, we often use External Secret Operator. This tool connects AWS Secrets Manager to Kubernetes. It automatically fetches secrets from the cloud and creates Kubernetes secrets for your apps. This means your applications get the credentials they need without you having to manually move or copy sensitive data.
And to make sure everything runs smoothly, we add Reloader. When secrets update in Secrets Manager, External Secret Operator updates the corresponding Kubernetes secrets. Reloader then picks up on these changes and automatically restarts your containers and pods with the latest credentials.
The end result of this toolset is a fully automated system that keeps your secrets rotated and your applications up to date. Change a database password in AWS Secrets Manager, and your entire app setup updates itself seamlessly.
Documentation
Clear, well-maintained documents help new team members onboard quickly, while poor documentation can turn even simple tasks into a frustrating detective mission. At IT Outposts, we value good documentation because we’ve seen how much time it can save in the long run.
Google Docs, just like Kubernetes, doesn’t need an introduction. It’s simple to use, great for collaboration, and everyone knows how to use it.
Confluence offers a more structured way to organize information. It’s great for technical teams that need detailed, searchable knowledge bases.
Notion is a flexible tool that combines docs, project management, and databases. Also, we like its modern interface.
From our experience, the best documentation platform is simply the one our clients use every day. Therefore, here, we don’t favor one tool over another since what matters most is that our documentation solution can easily integrate with our clients’ workflows.
Maintenance
Our approach to maintenance is built around three main tools.
We use Jira to track all our tasks, whether it’s a simple security patch or a major server fix, because if it’s not logged, it doesn’t get done.
Confluence is where we store all our maintenance knowledge, like runbooks, troubleshooting tips, and step-by-step guides, so that our engineers can easily find what they need.
Slack is our go-to alert system, as monitoring tools send notifications straight to specific channels when servers go down or metrics spike, and clients often reach out there if they notice issues.
Conclusion
The tools we’ve discussed are just the core of our DevOps toolkit, but we’re not set on using only these specific ones. After all, every client’s needs are different.
Sometimes, a newer tool fits better than what we usually use. Other times, legacy systems require a more customized approach. We stay flexible because rigid plans don’t solve real-world problems. Therefore, our choices are guided by what will actually help each client the most.
If you want to skip the long setup process, our AMICSS package provides a ready-made infrastructure with over 20 expertly configured tools. It’s a fixed price, saving you more than 160 hours of engineering work, and it gets your setup done in just a week.
If you’re ready to make your DevOps setup more efficient, check out AMICSS and see how it can speed up your infrastructure deployment.
I am an IT professional with over 10 years of experience. My career trajectory is closely tied to strategic business development, sales expansion, and the structuring of marketing strategies.
Throughout my journey, I have successfully executed and applied numerous strategic approaches that have driven business growth and fortified competitive positions. An integral part of my experience lies in effective business process management, which, in turn, facilitated the adept coordination of cross-functional teams and the attainment of remarkable outcomes.
I take pride in my contributions to the IT sector’s advancement and look forward to exchanging experiences and ideas with professionals who share my passion for innovation and success.