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A funnel icon represents the limitations of VMs. They are not as scalable or agile as containerized applications. Scaling a VM requires provisioning a whole new server, while scaling a containerized application simply involves spinning up more containers.

Journey of moving VM-based workloads to Kubernetes

Flip is a fintech company in Indonesia. We migrated their stateless services running on 25+ VMs in the Alibaba cloud to their managed Kubernetes offering (ACK). These application services served Flip's B2B and B2C traffic which often peaked at 25,000 requests/second. Problem Statement. Implement autoscaling of the infrastructure to handle peak traffic. Move to a Cloud-Native architecture to use modern tooling. Solve the problems related to configuration management and operational toil.

30%

Cost Saved

120

Pods at peak load

0sec

Downtime

Learn More

A funnel icon represents the limitations of VMs. They are not as scalable or agile as containerized applications. Scaling a VM requires provisioning a whole new server, while scaling a containerized application simply involves spinning up more containers.

Journey of moving VM-based workloads to Kubernetes

Flip is a fintech company in Indonesia. We migrated their stateless services running on 25+ VMs in the Alibaba cloud to their managed Kubernetes offering (ACK). These application services served Flip's B2B and B2C traffic which often peaked at 25,000 requests/second. Problem Statement. Implement autoscaling of the infrastructure to handle peak traffic. Move to a Cloud-Native architecture to use modern tooling. Solve the problems related to configuration management and operational toil.

30%

Cost Saved

120

Pods at peak load

0sec

Downtime

Learn More

A funnel icon represents the limitations of VMs. They are not as scalable or agile as containerized applications. Scaling a VM requires provisioning a whole new server, while scaling a containerized application simply involves spinning up more containers.

Journey of moving VM-based workloads to Kubernetes

Flip is a fintech company in Indonesia. We migrated their stateless services running on 25+ VMs in the Alibaba cloud to their managed Kubernetes offering (ACK). These application services served Flip's B2B and B2C traffic which often peaked at 25,000 requests/second. Problem Statement. Implement autoscaling of the infrastructure to handle peak traffic. Move to a Cloud-Native architecture to use modern tooling. Solve the problems related to configuration management and operational toil.

30%

Cost Saved

120

Pods at peak load

0sec

Downtime

Learn More

A funnel icon represents the limitations of VMs. They are not as scalable or agile as containerized applications. Scaling a VM requires provisioning a whole new server, while scaling a containerized application simply involves spinning up more containers.

Journey of moving VM-based workloads to Kubernetes

Flip is a fintech company in Indonesia. We migrated their stateless services running on 25+ VMs in the Alibaba cloud to their managed Kubernetes offering (ACK). These application services served Flip's B2B and B2C traffic which often peaked at 25,000 requests/second. Problem Statement. Implement autoscaling of the infrastructure to handle peak traffic. Move to a Cloud-Native architecture to use modern tooling. Solve the problems related to configuration management and operational toil.

30%

Cost Saved

120

Pods at peak load

0sec

Downtime

Learn More

A funnel icon represents the limitations of VMs. They are not as scalable or agile as containerized applications. Scaling a VM requires provisioning a whole new server, while scaling a containerized application simply involves spinning up more containers.

Journey of moving VM-based workloads to Kubernetes

Flip is a fintech company in Indonesia. We migrated their stateless services running on 25+ VMs in the Alibaba cloud to their managed Kubernetes offering (ACK). These application services served Flip's B2B and B2C traffic which often peaked at 25,000 requests/second. Problem Statement. Implement autoscaling of the infrastructure to handle peak traffic. Move to a Cloud-Native architecture to use modern tooling. Solve the problems related to configuration management and operational toil.

30%

Cost Saved

120

Pods at peak load

0sec

Downtime

Learn More

AutoScaling eKYC Machine Learning workloads to 2M+ req/day

Cloud monthly costs were reduced to a maximum of $10k per month (90% savings over predicted costs without the Autoscaler). The solution has been live and running successfully on production for 2+ years. SLA for uptime and response time are met during this period.

Learn More

AutoScaling eKYC Machine Learning workloads to 2M+ req/day

Cloud monthly costs were reduced to a maximum of $10k per month (90% savings over predicted costs without the Autoscaler). The solution has been live and running successfully on production for 2+ years. SLA for uptime and response time are met during this period.

Learn More

AutoScaling eKYC Machine Learning workloads to 2M+ req/day

Cloud monthly costs were reduced to a maximum of $10k per month (90% savings over predicted costs without the Autoscaler). The solution has been live and running successfully on production for 2+ years. SLA for uptime and response time are met during this period.

Learn More

AutoScaling eKYC Machine Learning workloads to 2M+ req/day

Cloud monthly costs were reduced to a maximum of $10k per month (90% savings over predicted costs without the Autoscaler). The solution has been live and running successfully on production for 2+ years. SLA for uptime and response time are met during this period.

Learn More

AutoScaling eKYC Machine Learning workloads to 2M+ req/day

Cloud monthly costs were reduced to a maximum of $10k per month (90% savings over predicted costs without the Autoscaler). The solution has been live and running successfully on production for 2+ years. SLA for uptime and response time are met during this period.

Learn More

How we saved more than 42% on AWS Infrastructure Costs

The client a no-code platform to build mobile apps for a Shopify store. The platform is hosted on AWS and serves customers across the globe. Operational for 7+ years and have a 30+ member dev team with not much DevOps expertise in the team. Problem Statement. Reduce existing cloud infrastructure cost of $25k/month without affecting the business metrics and uptime. Implement cloud governance and infrastructure access policies for security. Continuous billing monitoring, alerts and deeper insights into cost allocations..

42%

Cost reduction for AWS Compute service

56%

Cost reduction for AWS RDS

90%

Cost reduction for AWS Data transfer

Learn More

How we saved more than 42% on AWS Infrastructure Costs

The client a no-code platform to build mobile apps for a Shopify store. The platform is hosted on AWS and serves customers across the globe. Operational for 7+ years and have a 30+ member dev team with not much DevOps expertise in the team. Problem Statement. Reduce existing cloud infrastructure cost of $25k/month without affecting the business metrics and uptime. Implement cloud governance and infrastructure access policies for security. Continuous billing monitoring, alerts and deeper insights into cost allocations..

42%

Cost reduction for AWS Compute service

56%

Cost reduction for AWS RDS

90%

Cost reduction for AWS Data transfer

Learn More

How we saved more than 42% on AWS Infrastructure Costs

The client a no-code platform to build mobile apps for a Shopify store. The platform is hosted on AWS and serves customers across the globe. Operational for 7+ years and have a 30+ member dev team with not much DevOps expertise in the team. Problem Statement. Reduce existing cloud infrastructure cost of $25k/month without affecting the business metrics and uptime. Implement cloud governance and infrastructure access policies for security. Continuous billing monitoring, alerts and deeper insights into cost allocations..

42%

Cost reduction for AWS Compute service

56%

Cost reduction for AWS RDS

90%

Cost reduction for AWS Data transfer

Learn More

How we saved more than 42% on AWS Infrastructure Costs

The client a no-code platform to build mobile apps for a Shopify store. The platform is hosted on AWS and serves customers across the globe. Operational for 7+ years and have a 30+ member dev team with not much DevOps expertise in the team. Problem Statement. Reduce existing cloud infrastructure cost of $25k/month without affecting the business metrics and uptime. Implement cloud governance and infrastructure access policies for security. Continuous billing monitoring, alerts and deeper insights into cost allocations..

42%

Cost reduction for AWS Compute service

56%

Cost reduction for AWS RDS

90%

Cost reduction for AWS Data transfer

Learn More

How we saved more than 42% on AWS Infrastructure Costs

The client a no-code platform to build mobile apps for a Shopify store. The platform is hosted on AWS and serves customers across the globe. Operational for 7+ years and have a 30+ member dev team with not much DevOps expertise in the team. Problem Statement. Reduce existing cloud infrastructure cost of $25k/month without affecting the business metrics and uptime. Implement cloud governance and infrastructure access policies for security. Continuous billing monitoring, alerts and deeper insights into cost allocations..

42%

Cost reduction for AWS Compute service

56%

Cost reduction for AWS RDS

90%

Cost reduction for AWS Data transfer

Learn More

Migrating from Heroku PaaS to AWS

When ADPList approached us, they had an immediate problem at hand. The latency for the business critical APIs was high and caused poor user experience. Before anything else, we started focusing on solving that problem. The entire stack for ADPList was running on Heroku. To improve performance, the ADPList team already implemented vertical infrastructure scaling. However, this resulted in a massive increase in costs. Apart from the costs, we realized that Heroku isn’t particularly suited well for microservices deployments at ADPList due to:

300%

Application performance improvement

50%

Cost reduction

3x

Throughput improvement

Learn More

Migrating from Heroku PaaS to AWS

When ADPList approached us, they had an immediate problem at hand. The latency for the business critical APIs was high and caused poor user experience. Before anything else, we started focusing on solving that problem. The entire stack for ADPList was running on Heroku. To improve performance, the ADPList team already implemented vertical infrastructure scaling. However, this resulted in a massive increase in costs. Apart from the costs, we realized that Heroku isn’t particularly suited well for microservices deployments at ADPList due to:

300%

Application performance improvement

50%

Cost reduction

3x

Throughput improvement

Learn More

Migrating from Heroku PaaS to AWS

When ADPList approached us, they had an immediate problem at hand. The latency for the business critical APIs was high and caused poor user experience. Before anything else, we started focusing on solving that problem. The entire stack for ADPList was running on Heroku. To improve performance, the ADPList team already implemented vertical infrastructure scaling. However, this resulted in a massive increase in costs. Apart from the costs, we realized that Heroku isn’t particularly suited well for microservices deployments at ADPList due to:

300%

Application performance improvement

50%

Cost reduction

3x

Throughput improvement

Learn More

Migrating from Heroku PaaS to AWS

When ADPList approached us, they had an immediate problem at hand. The latency for the business critical APIs was high and caused poor user experience. Before anything else, we started focusing on solving that problem. The entire stack for ADPList was running on Heroku. To improve performance, the ADPList team already implemented vertical infrastructure scaling. However, this resulted in a massive increase in costs. Apart from the costs, we realized that Heroku isn’t particularly suited well for microservices deployments at ADPList due to:

300%

Application performance improvement

50%

Cost reduction

3x

Throughput improvement

Learn More

Migrating from Heroku PaaS to AWS

When ADPList approached us, they had an immediate problem at hand. The latency for the business critical APIs was high and caused poor user experience. Before anything else, we started focusing on solving that problem. The entire stack for ADPList was running on Heroku. To improve performance, the ADPList team already implemented vertical infrastructure scaling. However, this resulted in a massive increase in costs. Apart from the costs, we realized that Heroku isn’t particularly suited well for microservices deployments at ADPList due to:

300%

Application performance improvement

50%

Cost reduction

3x

Throughput improvement

Learn More

Pull Request Based Ephemeral Preview Environments on Kubernetes

Problem Statement. Set up Heroku PaaS style, ephemeral Preview environments for all frontend and backend services on Kubernetes Allow a Preview service to use another service in Preview mode as a dependency Configure the latest migrations and seed data in Preview environments, reducing the time to test a Pull Request Allow automated deletion of the Preview environment if it’s not actively used

Learn More

Pull Request Based Ephemeral Preview Environments on Kubernetes

Problem Statement. Set up Heroku PaaS style, ephemeral Preview environments for all frontend and backend services on Kubernetes Allow a Preview service to use another service in Preview mode as a dependency Configure the latest migrations and seed data in Preview environments, reducing the time to test a Pull Request Allow automated deletion of the Preview environment if it’s not actively used

Learn More

Pull Request Based Ephemeral Preview Environments on Kubernetes

Problem Statement. Set up Heroku PaaS style, ephemeral Preview environments for all frontend and backend services on Kubernetes Allow a Preview service to use another service in Preview mode as a dependency Configure the latest migrations and seed data in Preview environments, reducing the time to test a Pull Request Allow automated deletion of the Preview environment if it’s not actively used

Learn More

Pull Request Based Ephemeral Preview Environments on Kubernetes

Problem Statement. Set up Heroku PaaS style, ephemeral Preview environments for all frontend and backend services on Kubernetes Allow a Preview service to use another service in Preview mode as a dependency Configure the latest migrations and seed data in Preview environments, reducing the time to test a Pull Request Allow automated deletion of the Preview environment if it’s not actively used

Learn More

Pull Request Based Ephemeral Preview Environments on Kubernetes

Problem Statement. Set up Heroku PaaS style, ephemeral Preview environments for all frontend and backend services on Kubernetes Allow a Preview service to use another service in Preview mode as a dependency Configure the latest migrations and seed data in Preview environments, reducing the time to test a Pull Request Allow automated deletion of the Preview environment if it’s not actively used

Learn More

Backup and recovery solution for SIEM data at Terabyte scale

Problem Statement. Build an automated backup and recovery process for the SIEM data Provide administrative controls for customizing the backup and restore options Implement tenant-wise customizations for data retention, data locality, and other parameters

1.5TB

Dataset handeled daily

100+

tenents using backup restore solution

$200

Running cost per month

Learn More

Backup and recovery solution for SIEM data at Terabyte scale

Problem Statement. Build an automated backup and recovery process for the SIEM data Provide administrative controls for customizing the backup and restore options Implement tenant-wise customizations for data retention, data locality, and other parameters

1.5TB

Dataset handeled daily

100+

tenents using backup restore solution

$200

Running cost per month

Learn More

Backup and recovery solution for SIEM data at Terabyte scale

Problem Statement. Build an automated backup and recovery process for the SIEM data Provide administrative controls for customizing the backup and restore options Implement tenant-wise customizations for data retention, data locality, and other parameters

1.5TB

Dataset handeled daily

100+

tenents using backup restore solution

$200

Running cost per month

Learn More

Backup and recovery solution for SIEM data at Terabyte scale

Problem Statement. Build an automated backup and recovery process for the SIEM data Provide administrative controls for customizing the backup and restore options Implement tenant-wise customizations for data retention, data locality, and other parameters

1.5TB

Dataset handeled daily

100+

tenents using backup restore solution

$200

Running cost per month

Learn More

Backup and recovery solution for SIEM data at Terabyte scale

Problem Statement. Build an automated backup and recovery process for the SIEM data Provide administrative controls for customizing the backup and restore options Implement tenant-wise customizations for data retention, data locality, and other parameters

1.5TB

Dataset handeled daily

100+

tenents using backup restore solution

$200

Running cost per month

Learn More

Homogeneous Monitoring across Cloud and On-premise

Monitor CPU, Memory, and Disk Utilization of the host systems and application containers. We needed a uniform solution to fetch metrics across AWS, GCP and on-premise data centers. All metrics should be stored and served from a single storage backend for uniformity, visualization and alerting.

Learn More

Homogeneous Monitoring across Cloud and On-premise

Monitor CPU, Memory, and Disk Utilization of the host systems and application containers. We needed a uniform solution to fetch metrics across AWS, GCP and on-premise data centers. All metrics should be stored and served from a single storage backend for uniformity, visualization and alerting.

Learn More

Homogeneous Monitoring across Cloud and On-premise

Monitor CPU, Memory, and Disk Utilization of the host systems and application containers. We needed a uniform solution to fetch metrics across AWS, GCP and on-premise data centers. All metrics should be stored and served from a single storage backend for uniformity, visualization and alerting.

Learn More

Homogeneous Monitoring across Cloud and On-premise

Monitor CPU, Memory, and Disk Utilization of the host systems and application containers. We needed a uniform solution to fetch metrics across AWS, GCP and on-premise data centers. All metrics should be stored and served from a single storage backend for uniformity, visualization and alerting.

Learn More

Homogeneous Monitoring across Cloud and On-premise

Monitor CPU, Memory, and Disk Utilization of the host systems and application containers. We needed a uniform solution to fetch metrics across AWS, GCP and on-premise data centers. All metrics should be stored and served from a single storage backend for uniformity, visualization and alerting.

Learn More

Migrating 1.3TB of Primary Data from Self-Hosted MySQL to GCP CloudSQL

Problem Statement. Build an automated backup and recovery process for the SIEM data Provide administrative controls for customizing the backup and restore options Implement tenant-wise customizations for data retention, data locality, and other parameters

Learn More

Migrating 1.3TB of Primary Data from Self-Hosted MySQL to GCP CloudSQL

Problem Statement. Build an automated backup and recovery process for the SIEM data Provide administrative controls for customizing the backup and restore options Implement tenant-wise customizations for data retention, data locality, and other parameters

Learn More

Migrating 1.3TB of Primary Data from Self-Hosted MySQL to GCP CloudSQL

Problem Statement. Build an automated backup and recovery process for the SIEM data Provide administrative controls for customizing the backup and restore options Implement tenant-wise customizations for data retention, data locality, and other parameters

Learn More

Migrating 1.3TB of Primary Data from Self-Hosted MySQL to GCP CloudSQL

Problem Statement. Build an automated backup and recovery process for the SIEM data Provide administrative controls for customizing the backup and restore options Implement tenant-wise customizations for data retention, data locality, and other parameters

Learn More

Zero downtime MySQL schema migrations for 400M row table

Problem Statement. DB schema migrations on large tables (400+ million rows or 150+ GB in size for a single table) caused replication lag and impacted latencies. Adding indexes on large tables also resulted in replication lag and degraded query performance. Developers had to wait months to roll out their features which needed schema changes.

400 M

Biggest table migrated

7

migrations per month

0

Downtime due to schema migrations

Learn More

Zero downtime MySQL schema migrations for 400M row table

Problem Statement. DB schema migrations on large tables (400+ million rows or 150+ GB in size for a single table) caused replication lag and impacted latencies. Adding indexes on large tables also resulted in replication lag and degraded query performance. Developers had to wait months to roll out their features which needed schema changes.

400 M

Biggest table migrated

7

migrations per month

0

Downtime due to schema migrations

Learn More

Zero downtime MySQL schema migrations for 400M row table

Problem Statement. DB schema migrations on large tables (400+ million rows or 150+ GB in size for a single table) caused replication lag and impacted latencies. Adding indexes on large tables also resulted in replication lag and degraded query performance. Developers had to wait months to roll out their features which needed schema changes.

400 M

Biggest table migrated

7

migrations per month

0

Downtime due to schema migrations

Learn More

Zero downtime MySQL schema migrations for 400M row table

Problem Statement. DB schema migrations on large tables (400+ million rows or 150+ GB in size for a single table) caused replication lag and impacted latencies. Adding indexes on large tables also resulted in replication lag and degraded query performance. Developers had to wait months to roll out their features which needed schema changes.

400 M

Biggest table migrated

7

migrations per month

0

Downtime due to schema migrations

Learn More

Zero downtime MySQL schema migrations for 400M row table

Problem Statement. DB schema migrations on large tables (400+ million rows or 150+ GB in size for a single table) caused replication lag and impacted latencies. Adding indexes on large tables also resulted in replication lag and degraded query performance. Developers had to wait months to roll out their features which needed schema changes.

400 M

Biggest table migrated

7

migrations per month

0

Downtime due to schema migrations

Learn More

Migrating Monolith Application to Cloud Native Stack

The client provides cloud and on-premise based Hospital Management Services (HMS) SaaS platform. This HMS serves 800+ B2B customers (tenants), including large hospital chains across the Middle East, Africa, and APAC region. The tech stack for the application is a Java-based backend, JSP-based server rendered UI, Redis, and MySQL as datastores. The HMS platform is deployed as a SaaS and in customers' cloud environments and on-premise data centers.

Learn More

Migrating Monolith Application to Cloud Native Stack

The client provides cloud and on-premise based Hospital Management Services (HMS) SaaS platform. This HMS serves 800+ B2B customers (tenants), including large hospital chains across the Middle East, Africa, and APAC region. The tech stack for the application is a Java-based backend, JSP-based server rendered UI, Redis, and MySQL as datastores. The HMS platform is deployed as a SaaS and in customers' cloud environments and on-premise data centers.

Learn More

Migrating Monolith Application to Cloud Native Stack

The client provides cloud and on-premise based Hospital Management Services (HMS) SaaS platform. This HMS serves 800+ B2B customers (tenants), including large hospital chains across the Middle East, Africa, and APAC region. The tech stack for the application is a Java-based backend, JSP-based server rendered UI, Redis, and MySQL as datastores. The HMS platform is deployed as a SaaS and in customers' cloud environments and on-premise data centers.

Learn More

Checkout our latest posts.

March 25, 2025 | 5 min read

Best Practices For Upgrading EKS Clusters.

Aashi Rathore

SRE @One2N

In this post, We will discuss why upgrading is essential and the cost implications of control plane operations. What are the essential steps to prepare your EKS cluster for an upgrade, including backup strategies, compatibility checks, and automation tools to make the process efficient, as well as best practices to ensure a smooth upgrade

March 10, 2025 | 5 min read

How to port-forward from EC2 instances without the need for opening any SSH Ports or creating Bastion hosts

Harsh Mishra

SRE @One2N

Learn how to port-forward from EC2 instances in private subnets without opening SSH ports or setting up bastion hosts. This AWS SSM Session Manager guide provides a secure, cost-effective, and simple solution for EC2 access and port forwarding.

February 24, 2025 | 4 min read

Gotchas to avoid when using spot instances in production

Aashi Rathore

SRE @One2N

In this post, we’ll explore the fundamentals of spot instances, the risks associated with their use in production, and key strategies to ensure seamless operations. We’ll also dive into a real-world incident where a spot instance termination caused service downtime and share the lessons learned to prevent similar issues in the future.

December 3, 2024 | 7 min read

Accessing Private EC2 Instances without Keys or Passwords

Adarsh Raj

SRE

Traditional methods of accessing Amazon EC2 instances, such as SSH keys and passwords, while effective can be cumbersome especially in large-scale environments, managing them is complex and prone to errors. In this blog, we explore how to use AWS Systems Manager Session Manager to securely access your private EC2 instances without the need for SSH keys or passwords.

December 2, 2024 | 5 min read

Using UTM and Vagrant to Spin Up Dev Environments on Apple Silicon Macs

Srivatsa RV

SRE @One2N

Learn how to set up a local development environment on M-series Macs using Vagrant and UTM, overcoming VirtualBox limitations and enabling seamless virtualization, containerization, and internetworking. This guide provides a step-by-step approach to integrating UTM with Vagrant for a production-like setup.

November 8, 2024 | 7 min read

Karpenter vs Cluster Autoscaler: A Comprehensive Guide to Kubernetes Node Scaling

Rahul H Bhatia

SRE

Discover the key differences between Karpenter and Cluster Autoscaler for Kubernetes node scaling. Learn how each tool handles dynamic workloads, node provisioning, and cost optimization to choose the best solution for your cloud-native environment.

Blog