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Testimonials
We got to meet Michael from MeteorOps through one of our employees. We needed DevOps help and guidance and Michael and the team provided all of it from the very beginning. They did everything from dev support to infrastructure design and configuration to helping during Production incidents like any one of our own employees. They actually became an integral part of our organization which says a lot about their personal attitude and dedication.
We were impressed with their commitment to the project.
Thanks to MeteorOps, infrastructure changes have been completed without any errors. They provide excellent ideas, manage tasks efficiently, and deliver on time. They communicate through virtual meetings, email, and a messaging app. Overall, their experience in Kubernetes and AWS is impressive.
Nguyen is a champ. He's fast and has great communication. Well done!
You guys are really a bunch of talented geniuses and it's a pleasure and a privilege to work with you.
Working with MeteorOps was exactly the solution we looked for. We met a professional, involved, problem solving DevOps team, that gave us an impact in a short term period.
I was impressed at how quickly they were able to handle new tasks at a high quality and value.
I was impressed with the amount of professionalism, communication, and speed of delivery.
Good consultants execute on task and deliver as planned. Better consultants overdeliver on their tasks. Great consultants become full technology partners and provide expertise beyond their scope.
I am happy to call MeteorOps my technology partners as they overdelivered, provide high-level expertise and I recommend their services as a very happy customer.
From my experience, working with MeteorOps brings high value to any company at almost any stage. They are uncompromising professionals, who achieve their goal no matter what.
They are very knowledgeable in their area of expertise.
They have been great at adjusting and improving as we have worked together.
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Free Project Planning: We dive into your goals and current state to prepare before a kickoff.
Pay-as-you-go: Use our capacity when you need it, none of that retainer nonsense.
Experts On-Demand: Get new experts from our team when you need specific knowledge or consultation.
We Don't Sleep: Just kidding we do sleep, but we can flexibly hop on calls when you need.
Ad-hoc Calls: When a video call works better than a chat, we hop on a call together.
How it works?
AWS ECS (Amazon Elastic Container Service) is a managed container orchestration service used to run, scale, and operate containerized applications on AWS. It is commonly adopted by platform and DevOps teams that want a consistent way to deploy microservices, APIs, and background workers with predictable updates and day-to-day operations.
ECS runs containers on Amazon EC2 or on AWS Fargate for serverless compute, and typically integrates with Amazon ECR for image storage, Elastic Load Balancing for traffic management, and CI/CD pipelines for automated releases. Related delivery practices are often covered in DevOps Engineering.
- Define workloads with task definitions and run them as long-lived services or scheduled tasks
- Support rolling deployments and service autoscaling based on demand
- Integrate with VPC networking and IAM for network isolation and access control
- Centralize logs, metrics, and events via Amazon CloudWatch
- Manage configuration and secrets through AWS-native integrations
Orchestration systems decide where and when workloads run on a cluster of machines (physical or virtual). On top of that, orchestration systems usually help manage the lifecycle of the workloads running on them. Nowadays, these systems are usually used to orchestrate containers, with the most popular one being Kubernetes.
There are many advantages to using Orchestration tools:
- Improve the utilization of CPU, memory, and storage usage by running many processes on a single machine
- Manage the entire lifecycle of the orchestrated workloads: pre & post initialization & termination
- Control the scale of workloads and the scale of their underlying infrastructure separately
- Centralized management of workloads and infrastructure
AWS ECS (Amazon Elastic Container Service) is a managed AWS-native container orchestrator used to run and scale containerized workloads with predictable operations and tight integration with core AWS services.
- Managed control plane handles service scheduling, task placement, and reconciliation without operating cluster masters.
- Flexible compute options support both EC2 for host-level control and AWS Fargate for per-task serverless compute.
- IAM task roles enable least-privilege access to AWS services without baking long-lived credentials into images.
- VPC-native networking assigns tasks ENIs and security groups, supporting private subnets, segmentation, and controlled ingress and egress.
- Load balancer integrations with ALB and NLB provide health checks, path-based routing, and stable service discovery patterns.
- Autoscaling integrates with CloudWatch metrics to scale task counts based on demand and protect availability during spikes.
- Task definitions provide a versioned deployment unit for images, CPU and memory, environment variables, secrets, and runtime settings.
- Deployment controls such as rolling updates, health-based deployments, and deployment circuit breakers reduce release risk.
- Observability integrates with CloudWatch Logs, Container Insights, and OpenTelemetry-compatible tooling for metrics and tracing.
- Cost optimization options such as Fargate Spot and EC2 Spot support lower-cost capacity for interruption-tolerant services and batch workloads.
ECS is a strong fit for microservices, internal APIs, background workers, and scheduled tasks where AWS integration and simpler day-2 operations are prioritized. Trade-offs can include less portability and a smaller ecosystem of third-party extensions compared to Kubernetes, which may matter for multi-cloud or highly customized platform requirements.
Common alternatives include Amazon EKS, HashiCorp Nomad, and managed Kubernetes platforms such as Google Kubernetes Engine (GKE) and Azure Kubernetes Service (AKS). For core concepts and service limits, see Amazon ECS documentation.
Our experience with AWS ECS helped us build repeatable delivery patterns, infrastructure modules, and operational runbooks that we use to help clients run containerized workloads reliably on AWS with clear security and cost controls.
Some of the things we did include:
- Designed and implemented ECS clusters on both EC2 and Fargate, selecting capacity strategies, task placement, and scaling policies based on workload characteristics.
- Built end-to-end CI/CD pipelines to build, scan, and deploy container images to ECS with safe rollout strategies (blue/green and canary) and automated rollback.
- Standardized service networking with ALB/NLB, private subnets, and service discovery, including cross-environment routing patterns for dev/stage/prod.
- Implemented secure IAM task roles, least-privilege policies, and secret handling via AWS Secrets Manager and Parameter Store, including rotation and audit-friendly access patterns.
- Set up observability for ECS services using CloudWatch metrics/logs, distributed tracing, and actionable alerting tied to SLOs and on-call workflows.
- Delivered infrastructure-as-code for ECS environments using Terraform modules, enabling consistent provisioning, drift detection, and controlled changes across accounts.
- Migrated container workloads from self-managed Docker hosts and AWS EKS to ECS where simpler operations and managed control planes were a better fit.
- Integrated ECS services with event-driven components (SQS/SNS/EventBridge) and data services, tuning task concurrency and retries for predictable throughput.
- Hardened deployments with image vulnerability scanning, runtime guardrails, and policy checks in pipelines, aligned to compliance requirements and internal standards.
- Optimized performance and cost by right-sizing CPU/memory, tuning autoscaling, using Spot where appropriate, and validating changes with load tests and real traffic patterns.
This experience helped us accumulate significant knowledge across multiple ECS use-cases—from greenfield platforms to migrations and cost optimization—and enables us to deliver high-quality AWS ECS setups that teams can operate confidently at scale.
Some of the things we can help you do with AWS ECS include:
- Review your current container platform (VPC/networking, IAM, registry, and delivery workflow) and deliver an ECS readiness report with prioritized fixes.
- Define an adoption roadmap for ECS on EC2 vs. Fargate, including cluster strategy, deployment patterns, environment promotion, and a pragmatic day-2 operating model.
- Design and implement production ECS services and task definitions with load balancers, service discovery, health checks, autoscaling, and safe rollout strategies.
- Standardize multi-account and multi-environment deployments using Infrastructure as Code (Terraform/CloudFormation) with reusable modules and controlled change management.
- Build secure CI/CD pipelines for container workloads (build, test, scan, deploy) with automated promotion, policy checks, and rollback-ready releases.
- Implement security and compliance guardrails such as least-privilege IAM, secrets management, image scanning, encryption, and network segmentation.
- Establish observability for ECS workloads with logs, metrics, tracing, dashboards, and actionable alerting to reduce MTTR and improve reliability.
- Optimize cost and performance through right-sizing, autoscaling tuning, capacity providers, and scheduling strategies aligned to workload profiles.
- Enable your team with pairing, runbooks, and focused training so engineers can ship and operate ECS confidently.
Learn more on the AWS ECS product page.
