Monday, September 8, 2025

Amazon Apache Flink | Overview & Hands-On.

Amazon Apache Flink - Overview & Hands-On.

Scope:

Intro,
Usesful link to documentation,
The Concept: Amazon Apache Flink
Key Features,
How It Works (Flow),
Architecture Overview,
Security & Permissions,
Operational Deep Dive,
Sample Use Cases,
Best Practices,
Insights,
Project: Hands-On.

Intro:

Amazon Managed Service for Apache Flink is a fully managed, serverless service from Amazon Web Services (AWS).
Amazon Managed Service for Apache Flink allows twtech to build and run applications using the Apache Flink framework.
Amazon Managed Service for Apache Flink service simplifies the processing of real-time streaming data with low latency, without requiring twtech to manage the underlying infrastructure or clusters.
Amazon Managed Service for Apache Flink was formerly known as Kinesis Data Analytics for Apache Flink.

Usesful link to documentation

https://aws.amazon.com/blogs/aws/announcing-amazon-managed-service-for-apache-flink-renamed-from-amazon-kinesis-data-analytics/

The Concept: Amazon Apache Flink

Amazon Managed Service for Apache Flink lets twtech build and run real-time stream processing applications using Apache Flink, an open-source distributed stream processing framework.
It’s fully managed, meaning AWS handles provisioning, scaling, patching, and fault-tolerance, so twtech can focus on building event-driven pipelines instead of managing infrastructure.

Key Features

1. Streaming ETL(extract transform load)

Transform, enrich, and aggregate streaming data in real time.
Example: Join a Kinesis data stream with reference data from S3 or DynamoDB.

2. Event-time Processing

Supports out-of-order and late-arriving events using Flink’s watermarks.

3. Stateful Applications

Manages application state (windows, aggregations, joins) with checkpointing and savepoints.
State is stored in Amazon S3 (durable, highly available).

4. Integrations

Sources: Kinesis Data Streams, Managed Kafka (MSK), self-managed Kafka, Amazon S3.
Sinks: Kinesis Data Streams, Kinesis Data Firehose, Amazon S3, OpenSearch, DynamoDB, Redshift, custom sinks.

5. Elastic Scaling

Automatically adjusts parallelism for throughput.
twtech can scale Flink applications up/down without downtime.

6. Monitoring

Amazon CloudWatch for logs and metrics.
AWS CloudTrail for auditing.
Managed Prometheus/Grafana for detailed Flink metrics.

How Apache Flink Works (Flow)

1. Data Sources (Kinesis Data Streams, MSK, Kafka, S3)
⬇

2. Amazon Managed Service for Apache Flink

o Runs Flink applications with managed runtime

o Provides windowing, filtering, joins, aggregations

o Maintains application state in S3
⬇

3. Data Sinks (Kinesis Firehose, S3, DynamoDB, OpenSearch, Redshift, custom apps)

Architecture Overview

Producers→ Kinesis Data Streams / MSK / Kafka / IoT Core

Amazon Managed Service for Apache Flink (Core Layer)

Job Manager (coordinates tasks)
Task Managers (execute stream tasks)
State backend on S3 (durable checkpoints)
Auto scaling + high availability

Consumers→ Firehose, Redshift, DynamoDB, OpenSearch, S3

Security & Permissions

IAM: Fine-grained permissions for reading/writing streams, S3, DynamoDB, etc.
Encryption:

o At rest (KMS) for S3 state, streams, and sinks.
o In transit with TLS.

VPC integration: Run Flink apps in private subnets, connect to MSK, RDS, etc.

Operational Deep Dive

Checkpointing

Automatic, periodic snapshots of state written to S3.
Used for fault tolerance → jobs can restart from latest checkpoint.

Savepoints

Manual snapshots for version upgrades or app migration.
Ensures state continuity across deployments.

Scaling

Horizontal scaling: add more Task Managers.
Vertical scaling: increase parallelism per task.
Elastic scaling: AWS-managed auto-scaling policies.

Failure Recovery

If a Task Manager fails, Flink restarts it using latest checkpoint.
If Job Manager fails, service launches a new one automatically.

Sample Use Cases

1. Real-Time Analytics

Process clickstreams, IoT sensor data, log events, or financial transactions.

2. Fraud Detection

Detect anomalies in payments in real time using event-time joins & ML inference.

3. Streaming ETL

Cleanse, normalize, and enrich IoT or log data before storing in Redshift/S3.

4. Monitoring & Alerting

Feed processed data into OpenSearch/Grafana dashboards.

Best Practices

Use event-time semantics (with watermarks) to handle late data.
Enable checkpoints frequently (every 30–60s).
Store state in S3 for durability.
Use RocksDB state backend for large stateful apps.
Leverage savepoints when upgrading apps.
Deploy via CI/CD (CloudFormation, CDK, Terraform) to ensure reproducibility.
Monitor backpressure & checkpoint durations to fine-tune parallelism.
Keep state size manageable (avoid unbounded windows).

Insights:

Apache Flink can read from kinesis Data Streams (KDS)
But Apache Flink it doesn't read from Amazon Data Firehose

Project: Hands-On

How twtech creates and use Amazon Apache Flink to Stream for real-time streaming data with low latency, without requiring it to manage the underlying infrastructure or clusters.

Search for service: kinesis (Real-Time Streaming)

Click on general menu tab: To expand and see all features

From Data Streams, Click on: Manage Apache Flink

How it works:

Youtube resource Link : https://youtu.be/vI1GiMSHuxM

Amazon Managed Service for Apache Flink makes it easy to build and run real-time streaming applications using Apache Flink.
Amazon Managed Service for Apache Flink takes care of everything required to run streaming applications.
There are no servers and clusters to manage, no compute and storage infrastructure to set up, and twtech only pay for the resources it uses.
twtech can easily setup and integrate data sources or destinations with minimal code, process data continuously with sub-second latencies, and respond to events in real-time.
Amazon Managed Service for Apache Flink takes care of the critical tasks of keeping twtech system secure, updated, compliant, and optimized, so twtech can focus on building applications.

Create streaming application:

Create streaming application

Managed Service for Apache Flink continuously reads and analyzes data from a connected streaming source in real time.
Managed Service for Apache Flink resources are not covered under the AWS Free Tier, and usage-based charges apply.