Merge pull request #44 from openobserve/dynamodb-blog

dynamodb-monitoring-blog

content/blog/posts/how-to-monitor-dynamodb-table.md

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+---
+title: "How to Monitor Amazon DynamoDB Table via Kinesis Data Streams and Firehose Stream"
+seoTitle: "Monitor Amazon DynamoDB Table | Kinesis Data Streams & Firehose Stream"
+description: Learn effective ways to monitor DynamoDB tables using AWS Kinesis Data Streams and Firehose. Enhance your data management strategies today!
+img: /img/blog/dynamodb/image5.png
+alt: OpenObserve
+slug: how-to-monitor-dynamodb-table
+authors: 
+  - manas
+publishDate: 2024-12-11
+tags:
+  - dynamodb
+  - aws
+  - monitoring
+  - logs
+---
+
+## Introduction
+
+Many applications, especially those that rely on Amazon DynamoDB, benefit significantly from monitoring item-level changes as they occur. For instance, a popular mobile app might update its data thousands of times per second, while another service captures these updates to provide near-instantaneous usage metrics. Similarly, financial applications that modify stock market data in DynamoDB can have parallel systems that track these changes in real time, compute value-at-risk metrics, and automatically rebalance investment portfolios based on stock price movements.
+
+To achieve such capabilities, developers can leverage Amazon Kinesis Data Streams. This service captures **item-level** modifications in DynamoDB tables and replicates them to a Kinesis data stream. By doing so, devs can access these streams and monitor changes almost immediately, enabling them to continuously capture and store vast amounts of data efficiently. This blog will guide you through the entire process, from setting up your DynamoDB table to analyzing your data in OpenObserve. Let’s get started!
+
+## What is Amazon DynamoDB?
+
+**Amazon DynamoDB** is a fully managed NoSQL database service that excels in providing fast and predictable performance at scale. It’s designed for applications that require low-latency responses, making it ideal for scenarios like gaming, IoT, and mobile applications. With features like auto-scaling, built-in security, and backup options.
+
+## What are Amazon Kinesis Data Firehose and Data Streams?
+
+### Kinesis Data Streams
+
+Amazon **Kinesis Data Streams** is a robust service that allows you to collect and process real-time data streams. It captures **item-level changes in your DynamoDB table** and replicates them to a Kinesis data stream. This means you can access and analyze these changes almost instantly!
+
+### Kinesis Data Firehose
+
+Kinesis Data Firehose complements Data Streams by making it easy to load streaming data into various AWS services like Amazon S3, Redshift, or OpenObserve. With Firehose, you can transform and deliver your data in real time, enabling you to create dashboards, generate alerts, and implement dynamic analytics without any complex coding.
+
+## Prerequisites
+
+Before we jump into the setup, make sure you have the following:
+
+- An **AWS account**.
+- A **basic understanding of AWS services**, particularly Kinesis Firehose and DynamoDB.
+- **OpenObserve** set up and running.
+
+## Step 1: Create a Table in DynamoDB
+
+To create a new `Music` table using the DynamoDB console:
+
+1. Sign in to the AWS Management Console and open the DynamoDB console at [DynamoDB Console](https://console.aws.amazon.com/dynamodb/).
+2. In the left navigation pane, choose **Tables**.
+3. Choose **Create table**.
+4. Enter the table details as follows:
+   - For **Table name**, enter `Music`.
+   - For **Partition key**, enter `Artist`.
+   - For **Sort key**, enter `SongTitle`.
+5. For **Table settings**, keep the default selection of **Default settings**.
+6. Choose **Create table** to create the table.
+
+- ![image1](/img/blog/dynamodb/image8.png)
+
+## Step 2: Write Data to a DynamoDB Table
+
+Now that your table is ready, let's add some data:
+
+1. Open the DynamoDB console at [DynamoDB Console](https://console.aws.amazon.com/dynamodb/).
+2. In the left navigation pane, choose **Tables**.
+3. On the **Tables** page, choose the **Music** table.
+4. Choose **Explore table items**.
+- ![image1](/img/blog/dynamodb/image6.png)
+
+5. In the **Items returned** section, choose **Create item**.
+
+#### On the **Create item** page, do the following to add your first item:
+
+1. Choose **Add new attribute**, and then choose **Number**.
+2. For **Attribute name**, enter `Awards`.
+3. Repeat this process to create an **AlbumTitle** of type **String**.
+4. Enter the following values for your item:
+   - For **Artist**, enter `No One You Know`.
+   - For **SongTitle**, enter `Call Me Today`.
+   - For **AlbumTitle**, enter `Somewhat Famous`.
+   - For **Awards**, enter `1`.
+5. Choose **Create item**.
+- ![image1](/img/blog/dynamodb/image4.png)
+
+#### Now, let's add another item:
+
+1. Repeat the process to create another item with the following values:
+   - For **Artist**, enter `Acme Band`.
+   - For **SongTitle**, enter `Happy Day`.
+   - For **AlbumTitle**, enter `Songs About Life`.
+   - For **Awards**, enter `10`.
+2. Choose **Create item**.
+
+#### Finally, add one more item with the same artist but different values:
+
+1. Repeat the process to create another item with the following values:
+   - For **Artist**, enter `Acme Band`.
+   - For **SongTitle**, enter `PartiQL Rocks`.
+   - For **AlbumTitle**, enter `Another Album Title`.
+   - For **Awards**, enter `8`.
+2. Choose **Create item**.
+
+## Step 3: Creating an Active Amazon Kinesis Data Stream
+
+Now, let’s create a Kinesis Data Stream and connect it to your DynamoDB table:
+
+1. Sign in to the AWS Management Console and open the Kinesis console at [Kinesis Console](https://console.aws.amazon.com/kinesis/).
+2. Choose **Create data stream**.
+3. Follow the instructions to create a stream called `dynamodbdemo`.
+4. Open the DynamoDB console at [DynamoDB Console](https://console.aws.amazon.com/dynamodb/).
+5. In the navigation pane on the left side of the console, choose **Tables**.
+6. Choose the **Music** table.
+7. Choose the **Exports and streams** tab.
+8. Choose the **Turn On** button.
+9. (Optional) Under Amazon Kinesis data stream details, you can change the record timestamp precision from microsecond (default) to millisecond.
+10. Choose `dynamodbdemo` from the dropdown list.
+- ![image1](/img/blog/dynamodb/image2.png)
+
+
+## Step 4: Create an Amazon Kinesis Data Firehose
+
+### Navigate to Kinesis Console
+1. In the AWS services menu, search for **Kinesis** and select it.
+
+### Create a Delivery Stream
+1. Click on **Create Firehose Stream**.
+2. For the **Source**, select **Kinesis Data Stream**, and choose your stream (`dynamodbdemo`).
+3. Click **Next**.
+
+- ![image1](/img/blog/dynamodb/image9.png)
+
+### Configure Destination
+1. Select **HTTP Endpoint** as the destination.
+2. **Endpoint URL:** Enter your OpenObserve Kinesis Firehose endpoint (obtain this from **OpenObserve -> Ingestions -> Custom -> Amazon Kinesis Firehose**.
+
+- ![image1](/img/blog/dynamodb/image3.gif)
+3. **Authentication Type:** Choose **Use access key** and enter your OpenObserve access key.
+4. Click **Next**.
+
+### Configure Backup Settings
+1. Choose whether to back up all data or only failed data. For this example, select **Failed data only**.
+2. Choose an existing S3 bucket or create a new one for backups (e.g. `dynamodbdemostream`).
+3. Click **Next**.
+
+- ![image1](/img/blog/dynamodb/image1.gif)
+
+### Finalize Firehose Stream Setup
+1. Click **Next**, configure buffer size and interval as needed (default values will suffice for this example), then click **Next** again.
+2. Review all settings and click on **Create Firehose stream**.
+
+
+## Step 5: Monitoring Changes in OpenObserve
+
+Now that your data is flowing through Kinesis Firehose, let’s explore how to monitor changes made to your DynamoDB table using OpenObserve.
+
+### Understanding the Log Records
+
+As changes occur in your DynamoDB table, they are captured and sent to OpenObserve in JSON format. Each log record contains several fields that provide valuable information about the changes. 
+
+- ![image1](/img/blog/dynamodb/image10.png)
+Here’s a breakdown of the key fields:
+- **_timestamp**: The precise time the event occurred.
+- **awsregion**: The AWS region where your DynamoDB table is located.
+- **dynamodb_approximatecreationdatetime**: The timestamp when the record was created.
+- **dynamodb_keys_artist** and **dynamodb_keys_songtitle**: The keys identifying the item that was modified.
+- **dynamodb_newimage**: Contains the new values for the attributes (e.g., `albumtitle`, `artist`, `awards`, `songtitle`).
+- **dynamodb_oldimage**: Contains the previous values for the attributes before the modification.
+- **eventid**: A unique identifier for the event.
+- **eventname**: Indicates the type of change (e.g., `MODIFY`, `INSERT`).
+- **tablename**: The name of the DynamoDB table.
+
+
+With the `eventname` field, you can create a real-time monitoring dashboard in OpenObserve that groups changes by event type, such as `MODIFY`, `INSERT`, etc. This allows you to quickly identify the nature of changes occurring in your DynamoDB table.
+
+You can download the dashboards [here](https://github.com/openobserve/dashboards).
+   - Create time series charts to visualize how frequently changes occur over time.
+   - Set up alerts for specific events, such as high-frequency modifications, to proactively monitor your application’s behavior.
+
+
+- ![image1](/img/blog/dynamodb/image7.png)
+
+By leveraging the real-time data captured from DynamoDB, you can gain insights into how your application is performing and respond promptly to any issues.
+
+## Best Practices for Monitoring DynamoDB Changes
+
+### Optimize Performance
+
+- **Shard Management**: Regularly monitor and adjust the number of shards in your Kinesis Data Stream to ensure it can handle your data volume and processing requirements. More shards can improve throughput but also increase costs. For more understanding on this refer [this](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/kds_using-shards-and-metrics.html)
+- **Data Throughput**: Ensure that your Firehose delivery stream is configured to handle the expected data load efficiently.
+
+### Ensure Data Consistency
+
+- **Data Validation**: Implement checks within OpenObserve to validate the incoming data and ensure that it accurately reflects the changes made in DynamoDB.
+
+### Monitor and Manage
+
+- **CloudWatch**: Utilize Amazon CloudWatch to monitor the metrics of your Kinesis Data Stream and Firehose. Set up alarms to alert you about throughput issues, errors, or processing latencies.
+- **Logging**: Implement logging within OpenObserve to capture detailed information about data processing and any errors that may occur.
+
+### Security and Access Control
+
+- **IAM Policies**: Configure IAM policies to restrict access to DynamoDB Streams and Kinesis Data Streams. Ensure that only authorized users and services have access to these resources to maintain security.
+
+## Use Cases for Monitoring DynamoDB Changes
+
+### Real-Time Analytics
+
+- **Stream Processing**: Use real-time data processing to generate insights, dashboards, and reports based on the changes captured from your DynamoDB tables.
+
+### Data Synchronization
+
+- **System Integration**: Keep different data stores and systems synchronized by capturing and replicating changes across databases and services.
+
+### Event-Driven Applications
+
+- **Trigger Actions**: Use changes in DynamoDB tables to trigger application workflows, notifications, or other actions, enhancing the responsiveness of your applications.
+
+## Conclusion
+
+Implementing a system for monitoring changes in DynamoDB with Amazon Kinesis and OpenObserve enables real-time data processing, synchronization, and analytics. By leveraging these AWS services, you can efficiently capture and respond to data changes, enhancing your ability to build dynamic and responsive data-driven applications. With the insights gained from monitoring your DynamoDB table directly in OpenObserve, you can make informed decisions that drive your application's success.
+