How mjunction cut AWS cloud costs by up to 25%
mjunction, one of India's largest B2B eCommerce companies, partnered with AppSquadz to bring visibility, discipline, and automation to its AWS environment, cutting spend without touching the performance of its business-critical platforms.
AWS Monthly Cloud Spend
25%
Reduction in AWS cloud costs
25%
Reduction in AWS cloud costs
87%
Spend on idle & orphaned resources
80%
Improved cost visibility
India's largest B2B eCommerce platform, running at scale on AWS
mjunction Services Limited delivers end-to-end digital commerce solutions across industries such as steel, coal, and logistics, running multiple critical workloads on AWS to support high-value transactions at scale. As its cloud footprint grew, so did its AWS spend, and workloads spread across multiple accounts and services made it hard to control costs without a structured approach.
Cloud spend growing faster than visibility could keep up
As mjunction's AWS environment expanded, five gaps stood between the business and a leaner, more predictable cloud bill.
Oversized & underutilized resources
EC2 instances and databases provisioned well beyond actual usage, with compute and storage spend that didn't match real demand.
Limited cost visibility
No consistent resource tagging or cost allocation, making it hard to attribute spend to teams, apps, or environments.
Idle & orphaned resources
Unattached EBS volumes, unused Elastic IPs, idle load balancers, and stale snapshots quietly accruing charges.
No reserved capacity strategy
Predictable, steady-state workloads running entirely on On-Demand pricing, missing out on Reserved Instance and Savings Plan discounts.
Inefficient storage tiering
Infrequently accessed data sitting on higher-cost storage tiers instead of being moved to cheaper options.
A structured cost optimization assessment across mjunction's AWS environment
AppSquadz combined visibility, cleanup, and commercial optimization into one engagement, reducing spend while preserving performance and reliability.
PHASE 01
Assess
- Compute Optimizer & Trusted Advisor review
- Usage pattern analysis
- Idle & orphaned resource audit
PHASE 02
Optimize
- Right-sizing EC2 & RDS
- Tagging & cost visibility rollout
- Reserved Instances & Savings Plans
- S3 lifecycle automation
PHASE 03
Sustain
- AWS Cost Explorer & Budgets
- Regular cleanup audits
- Ongoing cost governance
What AppSquadz implemented for mjunction
Compute & database
Right-sized EC2 instances and RDS databases using Compute Optimizer and Trusted Advisor recommendations
Cost visibility
Standardized tagging strategy plus Cost Explorer and Budgets configured to track spend by team, app, and environment
Resource cleanup
Decommissioned unattached EBS volumes, unused Elastic IPs, idle load balancers, and stale snapshots
Commercial strategy
Migrated steady-state workloads from On-Demand pricing to Reserved Instances and Savings Plans
Storage
Automated S3 Lifecycle Policies to shift infrequently accessed data to lower-cost tiers
Leaner AWS spend, without slowing the business down
25% overall AWS cost reduction
87% reduction in idle & orphaned resource spend
80% improved cost visibility across teams
60% lower storage costs via lifecycle automation
By aligning resource provisioning with actual workload demand and introducing consistent cost governance practices, the engagement let mjunction reduce AWS spend while maintaining the performance and scalability its business-critical platforms require.
Cost optimization works best as a system, not a single fix
mjunction's savings came from four things working together:
Right-sizing compute & database resources
Tagging & continuous cost visibility
Reserved capacity planning
Automated storage lifecycle management
Technologies used
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