5 min readAs a company in the field of technology and life sciences, we recognize the value of efficiency, but with hundreds of cloud-based tools, it can be difficult to understand which will best optimize your workflow. That’s why we recently asked some of our engineer experts to highlight their favorite Amazon Web Services tools. Read below to learn how certain AWS tools can enhance your day-to-day work.
Tool 1: Amazon Elastic Container Service (ECS) with Fargate
Madhu Kanigicherla
Project Manager, AWS Certified Solution Architect, AWS Certified Cloud Practitioner
What is your favorite AWS tool/workflow to use to increase efficiency?
Madhu:
My favorite AWS tool is Amazon Elastic Container Service (ECS) with Fargate. As a technical manager overseeing about 40 applications, ECS Fargate has become an indispensable part of our cloud strategy. It allows us to run containers without managing servers, which drastically reduces operational overhead. By running containers only when needed and paying for exact CPU and memory usage, we’ve significantly optimized our cloud spend. Auto scaling is another major benefit—it allows containers to scale dynamically based on load, ensuring performance during peak traffic without manual adjustments. This has been crucial for handling variable workloads efficiently.
When should someone use this tool?
Madhu:
ECS Fargate works best with containerized applications that require flexible scaling, high availability, and minimal infrastructure management. It’s ideal for microservices architectures, RESTful APIs, backend services, cron jobs, and event-driven workers. Fargate is especially effective for teams looking to adopt DevOps and CI/CD practices, as it integrates well with AWS Code Pipeline and other deployment tools.
What does this tool do well?
Madhu:
- No need to patch servers or scale clusters manually
- Deployment pipelines are easier to manage, and versioned task definitions make rollback and tracking more predictable
- Load balancing is straightforward with Application Load Balancer (ALB) support
Fargate enables us to run leaner, deploy faster, and scale smarter and simplifies DevOps significantly. For example, we recently needed to migrate an operating system that was near its end of life. Having half our applications on Fargate saved us the time and effort to migrate the OS on all instances.
Do you have any tips for other engineers wanting to use this tool?
Madhu:
- Start small: containerize one application and learn how task definitions, service scaling, and networking work.
- Be deliberate about setting up CPU and memory reservations to control costs.
- Use CloudWatch for logs and metrics, and define alerts early.
- Treat your task definitions like code: version them, review changes, and store them in source control.
- Invest early in logging, monitoring, and altering. That’s an important lesson I’ve learned, while Fargate abstracts infrastructure, observability is still your responsibility.
Tool 2: AWS Cloud Development Kit (CDK)
Charles Ngu
DevOps Engineer, AWS Certified DevOps Engineer
What is your favorite AWS tool/workflow to use to increase efficiency?
Charles:
AWS Cloud Development Kit (CDK) is my favorite. I use AWS CDK (with Python) to define cloud infrastructure as code. Instead of writing JSON or YAML manually in CloudFormation, I can write clean, reusable, and testable code using familiar programming languages. It significantly increases efficiency by reducing boilerplate, enabling code reuse (via constructs), and integrating well into Continuous Integration/Continuous Deployment pipelines. It also helps catch configuration errors earlier via “cdk synth” and “cdk diff” before deploying.
When should someone use this tool?
Charles:
While CDK itself doesn’t handle data, it’s excellent for provisioning infrastructure that supports all kinds of data—whether that’s object data in S3, structured data in RDS, time-series logs in CloudWatch, or streaming data via Kinesis. Its strength is in setting up the right AWS services that manage and process these data types.
What does this tool do well?
Charles:
- Strong abstraction with constructs that simplify complex infrastructure patterns
- Easy integration with other AWS services (e.g., Lambda, ECS, API Gateway)
- Built-in support for parameterization, context variables, and environment targeting (dev/stage/prod)
- Clear diffing and synthesis tools to preview changes before applying
Do you have any tips for other engineers wanting to use this tool?
Charles:
- Modularize early. Break your CDK code into reusable constructs to keep things organized and DRY (“don’t repeat yourself”).
- Use context and environment-aware settings to make your stacks easily portable across dev/test/prod.
- Run “cdk dif” before every deployment: it’s a lifesaver and avoids surprises
- Tag everything. Tags are easy to forget but crucial for cost management and organization.
- Use “cdk-aspects” to enforce security or cost controls across all resources.
Tool 3: Amazon CloudWatch
Xiaozheng (Judy) Yao
Senior Software Engineer, AWS Certified Developer
What is your favorite AWS tool/workflow to use to increase efficiency?
Judy:
I’d say Amazon CloudWatch is my favorite tool. I use it to monitor AWS resources and applications in real time. It helps me stay on top of system health, performance metrics, and logs without having to jump between multiple services. It’s efficient because it centralizes all observability data, and I can set up alarms and automated responses when something goes out of bounds, saving time and preventing bigger issues.
When should someone use this tool?
Judy:
CloudWatch works best with system-level and application-level metrics, like CPU utilization, memory usage, API call rates, error counts, and custom business logic, metrics. It also handles structured and unstructured logs from EC2, Lambda, ECS, and more.
What does this tool do well?
Judy:
- Real-time monitoring and dashboards for metrics across services
- Centralized logging with CloudWatch Logs
- Easy integration with alarms, auto-scaling, and automation
- Custom metric tracing and insights from logs
- Visualizing trends over time and troubleshooting incidents
Do you have any tips for other engineers wanting to use this tool?
Judy:
- Use metric filters and custom dashboards to surface the data that matters most to your app or service.
- Set up alarms with SNS notifications early—it’s better to catch issues before users do.
- Keep an eye on log retention setting to avoid surprise cost.
Are you ready to leverage these and other cloud tools for your work? As a certified AWS Advanced Tier Partner, we can help you find the right tool and approach for your needs.