AWS Essentials for Financial Services

Why AWS Dominates in Finance

Amazon Web Services has the largest market share in cloud computing, and that share is even more pronounced in financial services. The reasons: AWS was first to market (launched in 2006), has the broadest service portfolio, and has invested heavily in compliance certifications and financial-sector specific features.

Major exchanges, hedge funds, and banks run on AWS. Capital markets firms use it for everything from risk computation to market data distribution. Understanding the core services is increasingly a job requirement rather than a nice-to-have.

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The Core Services

EC2: Virtual Servers

EC2 (Elastic Compute Cloud) gives you virtual machines in the cloud. You choose the instance type based on your workload:

The g suffix indicates Graviton (ARM) processors, which are typically 20-40% more cost-effective than equivalent Intel instances for most workloads.

# Launch an instance (CLI)
aws ec2 run-instances \
  --image-id ami-0c55b159cbfafe1f0 \
  --instance-type c7g.xlarge \
  --key-name my-key \
  --security-group-ids sg-12345678

# Or use infrastructure-as-code (Terraform)
resource "aws_instance" "risk_engine" {
  ami           = "ami-0c55b159cbfafe1f0"
  instance_type = "c7g.xlarge"
  tags = {
    Name = "risk-calculation-engine"
  }
}

S3: Object Storage

S3 (Simple Storage Service) is the backbone of data storage on AWS. Virtually unlimited capacity, 99.999999999% durability (eleven nines), and remarkably cheap at scale.

In finance, S3 is used for:

• Market data archives — years of tick data, cheaply stored and queryable
• Data lake — raw data from multiple sources before processing
• Backups — database snapshots, configuration backups
• Reports — generated documents, regulatory filings

import boto3

s3 = boto3.client('s3')

# Upload a file
s3.upload_file('daily_trades.parquet', 'trading-data-bucket', 'trades/2024/01/15.parquet')

# Download
s3.download_file('trading-data-bucket', 'trades/2024/01/15.parquet', 'local_trades.parquet')

# List files with a prefix
response = s3.list_objects_v2(Bucket='trading-data-bucket', Prefix='trades/2024/01/')
for obj in response.get('Contents', []):
    print(f"{obj['Key']}: {obj['Size']} bytes")

S3 storage classes let you optimise costs: Standard for frequently accessed data, Infrequent Access for monthly reports, Glacier for long-term archives that are rarely read.

RDS: Managed Databases

RDS runs PostgreSQL, MySQL, or other databases with AWS handling backups, patching, replication, and failover. For database design in the cloud, it is the most common starting point.

Aurora is AWS's enhanced version — compatible with PostgreSQL or MySQL but with better performance, automatic scaling, and cross-region replication. Many finance teams use Aurora for their primary transactional databases.

Lambda: Serverless Compute

Lambda runs code in response to events without any server management. You pay only when your code executes, billed per millisecond.

# lambda_function.py
def handler(event, context):
    """Process new trade files as they arrive in S3."""
    for record in event['Records']:
        bucket = record['s3']['bucket']['name']
        key = record['s3']['object']['key']

        # Download and process the trade file
        trades = load_trades_from_s3(bucket, key)
        validated = validate_trades(trades)
        insert_to_database(validated)

        return {
            'statusCode': 200,
            'body': f'Processed {len(validated)} trades from {key}'
        }

Common finance use cases: processing data files on arrival, scheduled report generation, alert notifications, and lightweight API endpoints.

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Networking on AWS

VPC: Your Private Network

A VPC (Virtual Private Cloud) is an isolated network within AWS. You control the IP ranges, subnets, routing, and access rules.

Typical architecture:

• Public subnets — load balancers, bastion hosts (things that face the internet)
• Private subnets — application servers, databases (no direct internet access)
• Security groups — firewall rules controlling inbound/outbound traffic per service

For networking fundamentals, see our dedicated guide.

Direct Connect

For latency-sensitive trading workloads, AWS Direct Connect provides a dedicated network connection from your data centre to AWS — bypassing the public internet entirely. Many trading firms use this for market data feeds and order routing.

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Security on AWS

IAM (Identity and Access Management) — controls who can do what. The principle of least privilege: each service gets exactly the permissions it needs and nothing more.

KMS (Key Management Service) — manages encryption keys. Financial data should be encrypted at rest (in S3, RDS, EBS) and in transit (TLS everywhere).

CloudTrail — logs every API call made in your account. Critical for auditing and compliance. If a regulator asks "who accessed this data and when?", CloudTrail has the answer.

GuardDuty — automated threat detection. Analyses CloudTrail logs, VPC flow logs, and DNS logs for suspicious activity.

For more on building secure financial applications, see our security and authentication guide.

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Cost Optimisation

AWS bills can grow rapidly. Key strategies:

• Right-size instances — monitor CPU and memory usage; downsize over-provisioned resources
• Reserved Instances — 30-60% savings for predictable workloads
• Spot Instances — 60-90% savings for interruptible batch processing
• S3 lifecycle policies — automatically move old data to cheaper storage classes
• Auto Scaling — scale up during market hours, scale down overnight

Set up AWS Cost Explorer and billing alarms from day one. The biggest cloud cost mistakes are things running when they should not be.